mskunary2d

Apply a unary callback to elements in a two-dimensional nested input array 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-mskunary2d

Usage

var mskunary2d = require( '@stdlib/array-base-mskunary2d' );

mskunary2d( arrays, shape, fcn )

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

var abs = require( '@stdlib/math-base-special-abs' );

var x = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];
var mask = [ [ 0, 1 ], [ 0, 0 ] ];

var shape = [ 2, 2 ];

// Compute the absolute values in-place:
mskunary2d( [ x, mask, x ], shape, abs );
// x => [ [ 1.0, -2.0 ], [ 3.0, 4.0 ] ]

The function accepts the following arguments:

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

Notes

• The function assumes that the input and output arrays have the same shape.
• An element in an input array is "masked" if the corresponding element in the mask array is non-zero.

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 abs = require( '@stdlib/math-base-special-abs' );
var mskunary2d = require( '@stdlib/array-base-mskunary2d' );

var shape = [ 3, 3 ];

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

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

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

mskunary2d( [ x, mask, y ], shape, abs );
console.log( y );

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.