npm package: @stdlib/stats-strided-distances
Description: Distance metrics for strided arrays.
Author: The Stdlib Authors
Latest version: 0.1.1

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<details>
  <summary>
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# Distance Metrics

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

> Distance metrics for strided arrays.

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</section>

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<section class="installation">

## Installation

```bash
npm install @stdlib/stats-strided-distances
```

</section>

<section class="usage">

## Usage

```javascript
var ns = require( '@stdlib/stats-strided-distances' );
```

#### ns

Namespace containing APIs for computing distance metrics on strided arrays.

```javascript
var o = ns;
// returns {...}
```

The namespace exports the following:

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<div class="namespace-toc">

-   <span class="signature">[`dchebychev( N, x, strideX, y, strideY )`][@stdlib/stats/strided/distances/dchebychev]</span><span class="delimiter">: </span><span class="description">compute the Chebychev distance between two double-precision floating-point strided arrays.</span>
-   <span class="signature">[`dcityblock( N, x, strideX, y, strideY )`][@stdlib/stats/strided/distances/dcityblock]</span><span class="delimiter">: </span><span class="description">compute the city block (Manhattan) distance between two double-precision floating-point strided arrays.</span>
-   <span class="signature">[`dcosineDistance( N, x, strideX, y, strideY )`][@stdlib/stats/strided/distances/dcosine-distance]</span><span class="delimiter">: </span><span class="description">compute the cosine distance between two double-precision floating-point strided arrays.</span>
-   <span class="signature">[`dcosineSimilarity( N, x, strideX, y, strideY )`][@stdlib/stats/strided/distances/dcosine-similarity]</span><span class="delimiter">: </span><span class="description">compute the cosine similarity of two double-precision floating-point strided arrays.</span>
-   <span class="signature">[`deuclidean( N, x, strideX, y, strideY )`][@stdlib/stats/strided/distances/deuclidean]</span><span class="delimiter">: </span><span class="description">compute the Euclidean distance between two double-precision floating-point strided arrays.</span>
-   <span class="signature">[`dsquaredEuclidean( N, x, strideX, y, strideY )`][@stdlib/stats/strided/distances/dsquared-euclidean]</span><span class="delimiter">: </span><span class="description">compute the squared Euclidean distance between two double-precision floating-point strided arrays.</span>

</div>

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</section>

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<section class="notes">

</section>

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<section class="examples">

## Examples

<!-- TODO: better examples -->

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

```javascript
var objectKeys = require( '@stdlib/utils-keys' );
var ns = require( '@stdlib/stats-strided-distances' );

console.log( objectKeys( ns ) );
```

</section>

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<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->

<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].

</section>

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[npm-image]: http://img.shields.io/npm/v/@stdlib/stats-strided-distances.svg
[npm-url]: https://npmjs.org/package/@stdlib/stats-strided-distances

[test-image]: https://github.com/stdlib-js/stats-strided-distances/actions/workflows/test.yml/badge.svg?branch=v0.1.1
[test-url]: https://github.com/stdlib-js/stats-strided-distances/actions/workflows/test.yml?query=branch:v0.1.1

[coverage-image]: https://img.shields.io/codecov/c/github/stdlib-js/stats-strided-distances/main.svg
[coverage-url]: https://codecov.io/github/stdlib-js/stats-strided-distances?branch=main

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[stdlib]: https://github.com/stdlib-js/stdlib

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[umd]: https://github.com/umdjs/umd
[es-module]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules

[deno-url]: https://github.com/stdlib-js/stats-strided-distances/tree/deno
[deno-readme]: https://github.com/stdlib-js/stats-strided-distances/blob/deno/README.md
[umd-url]: https://github.com/stdlib-js/stats-strided-distances/tree/umd
[umd-readme]: https://github.com/stdlib-js/stats-strided-distances/blob/umd/README.md
[esm-url]: https://github.com/stdlib-js/stats-strided-distances/tree/esm
[esm-readme]: https://github.com/stdlib-js/stats-strided-distances/blob/esm/README.md
[branches-url]: https://github.com/stdlib-js/stats-strided-distances/blob/main/branches.md

[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/stats-strided-distances/main/LICENSE

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[@stdlib/stats/strided/distances/dchebychev]: https://www.npmjs.com/package/@stdlib/stats-strided-distances-dchebychev

[@stdlib/stats/strided/distances/dcityblock]: https://www.npmjs.com/package/@stdlib/stats-strided-distances-dcityblock

[@stdlib/stats/strided/distances/dcosine-distance]: https://www.npmjs.com/package/@stdlib/stats-strided-distances-dcosine-distance

[@stdlib/stats/strided/distances/dcosine-similarity]: https://www.npmjs.com/package/@stdlib/stats-strided-distances-dcosine-similarity

[@stdlib/stats/strided/distances/deuclidean]: https://www.npmjs.com/package/@stdlib/stats-strided-distances-deuclidean

[@stdlib/stats/strided/distances/dsquared-euclidean]: https://www.npmjs.com/package/@stdlib/stats-strided-distances-dsquared-euclidean

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</section>

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