npm package: @stdlib/ndarray-base-unary-addon-dispatch
Description: Dispatch to a native add-on applying a unary function to an input ndarray.
Author: The Stdlib Authors
Latest version: 0.1.1

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# dispatch

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> Dispatch to a native add-on applying a unary function to an input ndarray.

<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->

<section class="intro">

</section>

<!-- /.intro -->

<!-- Package usage documentation. -->

<section class="installation">

## Installation

```bash
npm install @stdlib/ndarray-base-unary-addon-dispatch
```

</section>

<section class="usage">

## Usage

```javascript
var dispatch = require( '@stdlib/ndarray-base-unary-addon-dispatch' );
```

#### dispatch( addon, fallback )

Returns a function which dispatches to a native add-on applying a unary function to an input ndarray.

```javascript
var array = require( '@stdlib/ndarray-array' );
var zeros = require( '@stdlib/ndarray-zeros' );
var dispatch = require( '@stdlib/ndarray-base-unary-addon-dispatch' );

function addon( x, metaX, y, metaY ) {
    // Call into native add-on...
}

function fallback( x, y ) {
    // Fallback JavaScript implementation...
}

// Create a dispatch function:
var f = dispatch( addon, fallback );

// ...

// Invoke the dispatch function with ndarray arguments:
var x = array( [ [ 1, 2], [ 3, 4 ] ] );
var y = zeros( [ 2, 2 ] );
f( x, y );
```

The returned function has the following signature:

```text
f( x, y )
```

where

-   **x**: input ndarray.
-   **y**: output ndarray.

The `addon` function should have the following signature:

```text
f( xbuf, metaX, ybuf, metaY )
```

where

-   **xbuf**: input ndarray data buffer.
-   **metaX**: [serialized][@stdlib/ndarray/base/serialize-meta-data] input ndarray meta data.
-   **ybuf**: output ndarray data buffer.
-   **metaY**: [serialized][@stdlib/ndarray/base/serialize-meta-data] output ndarray meta data.

The `fallback` function should have the following signature:

```text
f( x, y )
```

where

-   **x**: input ndarray.
-   **y**: output ndarray.

</section>

<!-- /.usage -->

<!-- Package usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->

<section class="notes">

## Notes

-   To determine whether to dispatch to the `addon` function, the returned dispatch function checks whether the underlying ndarray data buffers are typed arrays. If the data buffers are typed arrays, the dispatch function invokes the `addon` function; otherwise, the dispatch function invokes the `fallback` function.

</section>

<!-- /.notes -->

<!-- Package usage examples. -->

<section class="examples">

## Examples

<!-- eslint-disable max-len -->

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

```javascript
var array = require( '@stdlib/ndarray-array' );
var zeros = require( '@stdlib/ndarray-zeros' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var dispatch = require( '@stdlib/ndarray-base-unary-addon-dispatch' );

function addon( xbuf, metaX, ybuf, metaY ) {
    console.log( xbuf );
    // => <Float64Array>[ 1, 2, 3, 4 ]

    console.log( ybuf );
    // => <Float64Array>[ 0, 0, 0, 0 ]
}

function fallback( x, y ) {
    console.log( ndarray2array( x ) );
    // => [ [ 1, 2 ], [ 3, 4 ] ]

    console.log( ndarray2array( y ) );
    // => [ [ 0, 0 ], [ 0, 0 ] ]
}

// Create a dispatch function:
var f = dispatch( addon, fallback );

// Create ndarrays:
var opts = {
    'dtype': 'float64',
    'casting': 'unsafe'
};
var x = array( [ [ 1, 2 ], [ 3, 4 ] ], opts );
var y = zeros( [ 2, 2 ], opts );

// Dispatch to the add-on function:
f( x, y );

// Define new ndarrays:
opts = {
    'dtype': 'generic'
};
x = array( [ [ 1, 2 ], [ 3, 4 ] ], opts );
y = zeros( [ 2, 2 ], opts );

// Dispatch to the fallback function:
f( x, y );
```

</section>

<!-- /.examples -->

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</section>

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<section class="related">

</section>

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* * *

## 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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[@stdlib/ndarray/base/serialize-meta-data]: https://www.npmjs.com/package/@stdlib/ndarray-base-serialize-meta-data

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