quinary4d

Apply a quinary callback to elements in five four-dimensional nested input arrays and assign results to elements in a four-dimensional nested output array.

Installation

npm install @stdlib/array-base-quinary4d

Usage

var quinary4d = require( '@stdlib/array-base-quinary4d' );

quinary4d( arrays, shape, fcn )

Applies a quinary callback to elements in five four-dimensional nested input arrays and assigns results to elements in a four-dimensional nested output array.

var add = require( '@stdlib/math-base-ops-add5' );
var zeros4d = require( '@stdlib/array-base-zeros4d' );

var x = [ [ [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ] ];
var out = zeros4d( [ 1, 1, 2, 2 ] );

var shape = [ 1, 1, 2, 2 ];

quinary4d( [ x, x, x, x, x, out ], shape, add );
// out => [ [ [ [ 5.0, 10.0 ], [ 15.0, 20.0 ] ] ] ]

The function accepts the following arguments:

• arrays: array-like object containing five input nested arrays and one output nested array.
• shape: array shape.
• fcn: quinary 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 filled4dBy = require( '@stdlib/array-base-filled4d-by' );
var zeros4d = require( '@stdlib/array-base-zeros4d' );
var add = require( '@stdlib/math-base-ops-add5' );
var quinary4d = require( '@stdlib/array-base-quinary4d' );

var shape = [ 1, 3, 3, 3 ];

var x = filled4dBy( shape, discreteUniform( -100, 100 ) );
console.log( x );

var y = filled4dBy( shape, discreteUniform( -100, 100 ) );
console.log( y );

var z = filled4dBy( shape, discreteUniform( -100, 100 ) );
console.log( z );

var w = filled4dBy( shape, discreteUniform( -100, 100 ) );
console.log( w );

var v = filled4dBy( shape, discreteUniform( -100, 100 ) );
console.log( v );

var out = zeros4d( shape );
console.log( out );

quinary4d( [ x, y, z, w, v, out ], shape, add );
console.log( out );

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.