npm package: @stdlib/stats-base-ndarray-dmskmin
Description: Calculate the minimum value of a one-dimensional double-precision floating-point ndarray according to a mask.
Author: The Stdlib Authors
Latest version: 0.1.1

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# dmskmin

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

> Calculate the minimum value of a one-dimensional double-precision floating-point ndarray according to a mask.

<section class="intro">

</section>

<!-- /.intro -->

<section class="installation">

## Installation

```bash
npm install @stdlib/stats-base-ndarray-dmskmin
```

</section>

<section class="usage">

## Usage

```javascript
var dmskmin = require( '@stdlib/stats-base-ndarray-dmskmin' );
```

#### dmskmin( arrays )

Computes the minimum value of a one-dimensional double-precision floating-point ndarray according to a mask.

```javascript
var Float64Array = require( '@stdlib/array-float64' );
var Uint8Array = require( '@stdlib/array-uint8' );
var ndarray = require( '@stdlib/ndarray-base-ctor' );

var xbuf = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );
var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );

var maskbuf = new Uint8Array( [ 0, 0, 1, 0 ] );
var mask = new ndarray( 'uint8', maskbuf, [ 4 ], [ 1 ], 0, 'row-major' );

var v = dmskmin( [ x, mask ] );
// returns -2.0
```

The function has the following parameters:

-   **arrays**: array-like object containing a one-dimensional input ndarray and a one-dimensional mask ndarray.

</section>

<!-- /.usage -->

<section class="notes">

## Notes

-   If a mask array element is `0`, the corresponding element in the input ndarray is considered valid and **included** in computation. If a mask array element is `1`, the corresponding element in the input ndarray is considered invalid/missing and **excluded** from computation.
-   If provided an empty ndarray or a mask with all elements set to `1`, the function returns `NaN`.

</section>

<!-- /.notes -->

<section class="examples">

## Examples

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

```javascript
var Float64Array = require( '@stdlib/array-float64' );
var Uint8Array = require( '@stdlib/array-uint8' );
var uniform = require( '@stdlib/random-array-uniform' );
var bernoulli = require( '@stdlib/random-array-bernoulli' );
var ndarray = require( '@stdlib/ndarray-base-ctor' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var dmskmin = require( '@stdlib/stats-base-ndarray-dmskmin' );

var xbuf = uniform( 10, -50.0, 50.0, {
    'dtype': 'float64'
});
var x = new ndarray( 'float64', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
console.log( ndarray2array( x ) );

var maskbuf = bernoulli( xbuf.length, 0.2, {
    'dtype': 'uint8'
});
var mask = new ndarray( 'uint8', maskbuf, [ maskbuf.length ], [ 1 ], 0, 'row-major' );
console.log( ndarray2array( mask ) );

var v = dmskmin( [ x, mask ] );
console.log( v );
```

</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].

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---

## License

See [LICENSE][stdlib-license].


## Copyright

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

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