gcartesianProduct

npm install @stdlib/blas-ext-base-gcartesian-product

Alternatively,

• To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
• If you are using Deno, visit the deno branch (see README for usage intructions).
• For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).

The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.

To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

var gcartesianProduct = require( '@stdlib/blas-ext-base-gcartesian-product' );

Computes the Cartesian product for two strided arrays.

var x = [ 1.0, 2.0 ];
var y = [ 3.0, 4.0 ];
var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];

gcartesianProduct( 'row-major', x.length, y.length, x, 1, y, 1, out, 2 );
// out => [ 1.0, 3.0, 1.0, 4.0, 2.0, 3.0, 2.0, 4.0 ]

The function has the following parameters:

• order: storage layout. Must be either 'row-major' or 'column-major'.
• M: number of indexed elements in x.
• N: number of indexed elements in y.
• x: first input Array or typed array.
• strideX: stride length for x.
• y: second input Array or typed array.
• strideY: stride length for y.
• out: output Array or typed array.
• LDO: stride length between successive contiguous vectors of the matrix out (a.k.a., leading dimension of out).

The M, N, and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the Cartesian product of every other element:

var x = [ 1.0, 0.0, 2.0, 0.0 ];
var y = [ 3.0, 0.0, 4.0, 0.0 ];
var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];

gcartesianProduct( 'row-major', 2, 2, x, 2, y, 2, out, 2 );
// out => [ 1.0, 3.0, 1.0, 4.0, 2.0, 3.0, 2.0, 4.0 ]

Note that indexing is relative to the first index. To introduce an offset, use typed array views.

var Float64Array = require( '@stdlib/array-float64' );

// Initial arrays:
var x0 = new Float64Array( [ 0.0, 1.0, 2.0 ] );
var y0 = new Float64Array( [ 0.0, 3.0, 4.0 ] );

// Create offset views:
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

// Output array:
var out = new Float64Array( 8 );

gcartesianProduct( 'row-major', 2, 2, x1, 1, y1, 1, out, 2 );
// out => <Float64Array>[ 1.0, 3.0, 1.0, 4.0, 2.0, 3.0, 2.0, 4.0 ]

Computes the Cartesian product for two strided arrays using alternative indexing semantics.

var x = [ 1.0, 2.0 ];
var y = [ 3.0, 4.0 ];
var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];

gcartesianProduct.ndarray( x.length, y.length, x, 1, 0, y, 1, 0, out, 2, 1, 0 );
// out => [ 1.0, 3.0, 1.0, 4.0, 2.0, 3.0, 2.0, 4.0 ]

The function has the following parameters:

• M: number of indexed elements in x.
• N: number of indexed elements in y.
• x: first input Array or typed array.
• strideX: stride length for x.
• offsetX: starting index for x.
• y: second input Array or typed array.
• strideY: stride length for y.
• offsetY: starting index for y.
• out: output Array or typed array.
• strideOut1: stride length for the first dimension of out.
• strideOut2: stride length for the second dimension of out.
• offsetOut: starting index for out.

While typed array views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to access only the last two elements of x:

var x = [ 0.0, 1.0, 2.0 ];
var y = [ 3.0, 4.0 ];
var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];

gcartesianProduct.ndarray( 2, y.length, x, 1, 1, y, 1, 0, out, 2, 1, 0 );
// out => [ 1.0, 3.0, 1.0, 4.0, 2.0, 3.0, 2.0, 4.0 ]

• Pairs are stored as rows in the output matrix, where the first column contains the first element of each pair and the second column contains the second element.
• For input arrays of lengths M and N, the output array must contain at least M * N * 2 indexed elements.
• For row-major order, the LDO parameter must be greater than or equal to 2. For column-major order, the LDO parameter must be greater than or equal to max(1,M*N).
• If M <= 0 or N <= 0, both functions return out unchanged.
• Both functions support array-like objects having getter and setter accessors for array element access (e.g., @stdlib/array-base/accessor).
• Depending on the environment, the typed versions (dcartesianProduct, etc.) are likely to be significantly more performant.

This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.

For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.

See LICENSE.

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