mskbinary2d

Apply a binary callback to elements in two two-dimensional nested input arrays according to elements in a two-dimensional nested mask array and assign results to elements in a two-dimensional nested output array.

Installation

npm install @stdlib/array-base-mskbinary2d

Usage

var mskbinary2d = require( '@stdlib/array-base-mskbinary2d' );

mskbinary2d( arrays, shape, fcn )

Applies a binary callback to elements in two two-dimensional nested input arrays according to elements in a two-dimensional nested mask array and assigns results to elements in a two-dimensional nested output array.

var add = require( '@stdlib/math-base-ops-add' );
var zeros2d = require( '@stdlib/array-base-zeros2d' );

var x = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ];
var z = zeros2d( [ 2, 2 ] );

var mask = [ [ 0, 1 ], [ 0, 0 ] ];

var shape = [ 2, 2 ];

mskbinary2d( [ x, x, mask, z ], shape, add );
// z => [ [ 2.0, 0.0 ], [ 6.0, 8.0 ] ]

The function accepts the following arguments:

• arrays: array-like object containing two input nested arrays, an input nested mask array, and one output nested array.
• shape: array shape.
• fcn: binary function to apply.

Notes

• The function assumes that the input and output arrays have the same shape.

Examples

var discreteUniform = require( '@stdlib/random-base-discrete-uniform' ).factory;
var bernoulli = require( '@stdlib/random-base-bernoulli' ).factory;
var filled2dBy = require( '@stdlib/array-base-filled2d-by' );
var zeros2d = require( '@stdlib/array-base-zeros2d' );
var add = require( '@stdlib/math-base-ops-add' );
var mskbinary2d = require( '@stdlib/array-base-mskbinary2d' );

var shape = [ 3, 3 ];

var x = filled2dBy( shape, discreteUniform( -100, 100 ) );
console.log( x );

var y = filled2dBy( shape, discreteUniform( -100, 100 ) );
console.log( y );

var mask = filled2dBy( shape, bernoulli( 0.5 ) );
console.log( mask );

var z = zeros2d( shape );
console.log( z );

mskbinary2d( [ x, y, mask, z ], shape, add );
console.log( z );

Notice

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.

Community

License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.