npm package: @stdlib/array-base-broadcasted-unary4d
Description: Apply a unary callback to elements in a broadcasted nested input array and assign results to elements in a four-dimensional nested output array.
Author: The Stdlib Authors
Latest version: 0.2.3

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# bunary4d

[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url] <!-- [![dependencies][dependencies-image]][dependencies-url] -->

> Apply a unary callback to elements in a [broadcasted][@stdlib/array/base/broadcast-array] nested input array and assign results to elements in a four-dimensional nested output array.

<section class="intro">

</section>

<!-- /.intro -->

<section class="installation">

## Installation

```bash
npm install @stdlib/array-base-broadcasted-unary4d
```

</section>

<section class="usage">

## Usage

```javascript
var bunary4d = require( '@stdlib/array-base-broadcasted-unary4d' );
```

#### bunary4d( arrays, shapes, fcn )

Applies a unary callback to elements in a [broadcasted][@stdlib/array/base/broadcast-array] nested input array and assigns results to elements in a four-dimensional nested output array.

```javascript
var zeros4d = require( '@stdlib/array-base-zeros4d' );
var abs = require( '@stdlib/math-base-special-abs' );

var x = [ [ [ [ -1.0, -2.0 ] ] ] ];
var y = zeros4d( [ 1, 1, 2, 2 ] );

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

// Compute the absolute values:
bunary4d( [ x, y ], shapes, abs );
// y => [ [ [ [ 1.0, 2.0 ], [ 1.0, 2.0 ] ] ] ]
```

The function accepts the following arguments:

-   **arrays**: array-like object containing one input nested array and one output nested array.
-   **shapes**: array shapes.
-   **fcn**: unary function to apply.

</section>

<!-- /.usage -->

<section class="notes">

## Notes

-   The input and output array shapes must be broadcast [compatible][@stdlib/ndarray/base/broadcast-shapes].

</section>

<!-- /.notes -->

<section class="examples">

## Examples

<!-- eslint no-undef: "error" -->

```javascript
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 abs = require( '@stdlib/math-base-special-abs' );
var bunary4d = require( '@stdlib/array-base-broadcasted-unary4d' );

var shapes = [
    [ 1, 1, 1, 3 ],
    [ 2, 3, 1, 3 ]
];

var x = filled4dBy( shapes[ 0 ], discreteUniform( -100, 100 ) );
console.log( x );

var y = zeros4d( shapes[ 1 ] );
console.log( y );

bunary4d( [ x, y ], shapes, abs );
console.log( y );
```

</section>

<!-- /.examples -->

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<section class="related">

</section>

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<section class="main-repo" >

* * *

## Notice

This package is part of [stdlib][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][stdlib], see the main project [repository][stdlib].

#### Community

[![Chat][chat-image]][chat-url]

---

## License

See [LICENSE][stdlib-license].


## Copyright

Copyright &copy; 2016-2026. The Stdlib [Authors][stdlib-authors].

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[umd]: https://github.com/umdjs/umd
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[deno-url]: https://github.com/stdlib-js/array-base-broadcasted-unary4d/tree/deno
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[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/array-base-broadcasted-unary4d/main/LICENSE

[@stdlib/array/base/broadcast-array]: https://www.npmjs.com/package/@stdlib/array-base-broadcast-array

[@stdlib/ndarray/base/broadcast-shapes]: https://www.npmjs.com/package/@stdlib/ndarray-base-broadcast-shapes

</section>

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