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Merge branch 'develop' of https://github.com/stdlib-js/stdlib into develop
2 parents 34d7694 + 080456e commit fc0a168

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‎lib/node_modules/@stdlib/math/base/random/chi/benchmark/r/DESCRIPTION‎

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Package: rchi-benchmarks
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Title: Benchmarks
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Version: 0.0.0
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Authors@R: person("stdlib", "js", role = c("aut","cre"))
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Description: Benchmarks.
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Depends: R (>=3.3.3)
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Imports:
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microbenchmark
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chi
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LazyData: true

‎lib/node_modules/@stdlib/math/base/random/chi/benchmark/r/benchmark.R‎

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#!/usr/bin/env Rscript
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# Set the precision to 16 digits:
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options( digits = 16 );
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#' Run benchmarks.
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#'
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#' @examples
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#' main();
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main <- function() {
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# Define benchmark parameters:
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name <- "chi";
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iterations <- 1000000L;
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repeats <- 3;
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#' Print the TAP version.
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#'
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#' @examples
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#' print_version();
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print_version <- function() {
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cat( "TAP version 13\n" );
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}
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#' Print the TAP summary.
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#'
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#' @param total Total number of tests.
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#' @param passing Total number of passing tests.
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#'
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#' @examples
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#' print_summary( 3, 3 );
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print_summary <- function( total, passing ) {
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cat( "#\n" );
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cat( paste0( "1..", total, "\n" ) ); # TAP plan
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cat( paste0( "# total ", total, "\n" ) );
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cat( paste0( "# pass ", passing, "\n" ) );
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cat( "#\n" );
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cat( "# ok\n" );
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}
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#' Print benchmark results.
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#'
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#' @param iterations Number of iterations.
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#' @param elapsed Elapsed time in seconds.
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#'
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#' @examples
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#' print_results( 10000L, 0.131009101868 );
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print_results <- function( iterations, elapsed ) {
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rate <- iterations / elapsed;
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cat( " ---\n" );
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cat( paste0( " iterations: ", iterations, "\n" ) );
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cat( paste0( " elapsed: ", elapsed, "\n" ) );
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cat( paste0( " rate: ", rate, "\n" ) );
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cat( " ...\n" );
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}
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#' Run a benchmark.
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#'
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#' ## Notes
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#'
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#' * We compute and return a total "elapsed" time, rather than the minimum
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#' evaluation time, to match benchmark results in other languages (e.g.,
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#' Python).
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#'
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#'
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#' @param iterations Number of Iterations.
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#' @return Elapsed time in seconds.
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#'
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#' @examples
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#' elapsed <- benchmark( 10000L );
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benchmark <- function( iterations ) {
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# Run the benchmarks:
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results <- microbenchmark::microbenchmark( chi::rchi( 1, runif(1,min=1.0,max=101.0) ), times = iterations );
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# Sum all the raw timing results to get a total "elapsed" time:
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elapsed <- sum( results$time );
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# Convert the elapsed time from nanoseconds to seconds:
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elapsed <- elapsed / 1.0e9;
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return( elapsed );
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}
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print_version();
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for ( i in 1:repeats ) {
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cat( paste0( "# r::", name, "\n" ) );
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elapsed <- benchmark( iterations );
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print_results( iterations, elapsed );
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cat( paste0( "ok ", i, " benchmark finished", "\n" ) );
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}
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print_summary( repeats, repeats );
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}
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main();

‎lib/node_modules/@stdlib/math/base/random/chisquare/benchmark/r/DESCRIPTION‎

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Package: rchisq-benchmarks
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Title: Benchmarks
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Version: 0.0.0
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Authors@R: person("stdlib", "js", role = c("aut","cre"))
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Description: Benchmarks.
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Depends: R (>=3.3.3)
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Imports:
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microbenchmark
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LazyData: true

‎lib/node_modules/@stdlib/math/base/random/chisquare/benchmark/r/benchmark.R‎

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#!/usr/bin/env Rscript
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# Set the precision to 16 digits:
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options( digits = 16 );
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#' Run benchmarks.
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#'
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#' @examples
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#' main();
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main <- function() {
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# Define benchmark parameters:
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name <- "chisquare";
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iterations <- 1000000L;
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repeats <- 3;
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#' Print the TAP version.
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#'
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#' @examples
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#' print_version();
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print_version <- function() {
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cat( "TAP version 13\n" );
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}
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#' Print the TAP summary.
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#'
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#' @param total Total number of tests.
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#' @param passing Total number of passing tests.
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#'
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#' @examples
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#' print_summary( 3, 3 );
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print_summary <- function( total, passing ) {
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cat( "#\n" );
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cat( paste0( "1..", total, "\n" ) ); # TAP plan
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cat( paste0( "# total ", total, "\n" ) );
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cat( paste0( "# pass ", passing, "\n" ) );
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cat( "#\n" );
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cat( "# ok\n" );
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}
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#' Print benchmark results.
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#'
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#' @param iterations Number of iterations.
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#' @param elapsed Elapsed time in seconds.
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#'
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#' @examples
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#' print_results( 10000L, 0.131009101868 );
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print_results <- function( iterations, elapsed ) {
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rate <- iterations / elapsed;
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cat( " ---\n" );
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cat( paste0( " iterations: ", iterations, "\n" ) );
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cat( paste0( " elapsed: ", elapsed, "\n" ) );
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cat( paste0( " rate: ", rate, "\n" ) );
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cat( " ...\n" );
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}
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#' Run a benchmark.
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#'
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#' ## Notes
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#'
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#' * We compute and return a total "elapsed" time, rather than the minimum
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#' evaluation time, to match benchmark results in other languages (e.g.,
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#' Python).
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#'
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#'
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#' @param iterations Number of Iterations.
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#' @return Elapsed time in seconds.
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#'
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#' @examples
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#' elapsed <- benchmark( 10000L );
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benchmark <- function( iterations ) {
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# Run the benchmarks:
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results <- microbenchmark::microbenchmark( rchisq( 1, runif(1,min=1.0,max=101.0) ), times = iterations );
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# Sum all the raw timing results to get a total "elapsed" time:
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elapsed <- sum( results$time );
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# Convert the elapsed time from nanoseconds to seconds:
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elapsed <- elapsed / 1.0e9;
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return( elapsed );
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}
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print_version();
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for ( i in 1:repeats ) {
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cat( paste0( "# r::", name, "\n" ) );
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elapsed <- benchmark( iterations );
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print_results( iterations, elapsed );
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cat( paste0( "ok ", i, " benchmark finished", "\n" ) );
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}
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print_summary( repeats, repeats );
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}
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main();

‎lib/node_modules/@stdlib/math/base/random/exponential/benchmark/r/DESCRIPTION‎

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Package: rexp-benchmarks
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Title: Benchmarks
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Version: 0.0.0
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Authors@R: person("stdlib", "js", role = c("aut","cre"))
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Description: Benchmarks.
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Depends: R (>=3.3.3)
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Imports:
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microbenchmark
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LazyData: true

‎lib/node_modules/@stdlib/math/base/random/exponential/benchmark/r/benchmark.R‎

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#!/usr/bin/env Rscript
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# Set the precision to 16 digits:
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options( digits = 16 );
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#' Run benchmarks.
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#'
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#' @examples
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#' main();
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main <- function() {
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# Define benchmark parameters:
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name <- "exponential";
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iterations <- 1000000L;
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repeats <- 3;
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#' Print the TAP version.
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#'
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#' @examples
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#' print_version();
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print_version <- function() {
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cat( "TAP version 13\n" );
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}
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#' Print the TAP summary.
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#'
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#' @param total Total number of tests.
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#' @param passing Total number of passing tests.
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#'
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#' @examples
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#' print_summary( 3, 3 );
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print_summary <- function( total, passing ) {
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cat( "#\n" );
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cat( paste0( "1..", total, "\n" ) ); # TAP plan
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cat( paste0( "# total ", total, "\n" ) );
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cat( paste0( "# pass ", passing, "\n" ) );
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cat( "#\n" );
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cat( "# ok\n" );
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}
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#' Print benchmark results.
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#'
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#' @param iterations Number of iterations.
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#' @param elapsed Elapsed time in seconds.
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#'
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#' @examples
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#' print_results( 10000L, 0.131009101868 );
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print_results <- function( iterations, elapsed ) {
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rate <- iterations / elapsed;
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cat( " ---\n" );
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cat( paste0( " iterations: ", iterations, "\n" ) );
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cat( paste0( " elapsed: ", elapsed, "\n" ) );
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cat( paste0( " rate: ", rate, "\n" ) );
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cat( " ...\n" );
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}
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#' Run a benchmark.
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#'
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#' ## Notes
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#'
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#' * We compute and return a total "elapsed" time, rather than the minimum
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#' evaluation time, to match benchmark results in other languages (e.g.,
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#' Python).
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#'
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#'
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#' @param iterations Number of Iterations.
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#' @return Elapsed time in seconds.
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#'
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#' @examples
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#' elapsed <- benchmark( 10000L );
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benchmark <- function( iterations ) {
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# Run the benchmarks:
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results <- microbenchmark::microbenchmark( rexp( 1, runif(1,min=0.0,max=100.0)+.Machine$double.eps ), times = iterations );
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# Sum all the raw timing results to get a total "elapsed" time:
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elapsed <- sum( results$time );
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# Convert the elapsed time from nanoseconds to seconds:
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elapsed <- elapsed / 1.0e9;
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return( elapsed );
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}
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print_version();
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for ( i in 1:repeats ) {
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cat( paste0( "# r::", name, "\n" ) );
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elapsed <- benchmark( iterations );
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print_results( iterations, elapsed );
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cat( paste0( "ok ", i, " benchmark finished", "\n" ) );
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}
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print_summary( repeats, repeats );
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}
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main();

‎lib/node_modules/@stdlib/math/base/random/poisson/benchmark/r/DESCRIPTION‎

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Package: rpois-benchmarks
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Title: Benchmarks
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Version: 0.0.0
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Authors@R: person("stdlib", "js", role = c("aut","cre"))
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Description: Benchmarks.
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Depends: R (>=3.3.3)
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Imports:
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microbenchmark
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LazyData: true

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