npm package: @stdlib/stats-base-dnanmskmin
Description: Calculate the minimum value of a double-precision floating-point strided array according to a mask, ignoring NaN values.
Author: The Stdlib Authors
Latest version: 0.2.2

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<details>
  <summary>
    About stdlib...
  </summary>
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# dnanmskmin

[![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 double-precision floating-point strided array according to a mask, ignoring `NaN` values.

<section class="intro">

</section>

<!-- /.intro -->

<section class="installation">

## Installation

```bash
npm install @stdlib/stats-base-dnanmskmin
```

</section>

<section class="usage">

## Usage

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

#### dnanmskmin( N, x, strideX, mask, strideMask )

Computes the minimum value of a double-precision floating-point strided array `x` according to a `mask`, ignoring `NaN` values.

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

var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );
var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );

var v = dnanmskmin( x.length, x, 1, mask, 1 );
// returns -2.0
```

The function has the following parameters:

-   **N**: number of indexed elements.
-   **x**: input [`Float64Array`][@stdlib/array/float64].
-   **strideX**: index increment for `x`.
-   **mask**: mask [`Uint8Array`][@stdlib/array/uint8]. If a `mask` array element is `0`, the corresponding element in `x` is considered valid and **included** in computation. If a `mask` array element is `1`, the corresponding element in `x` is considered invalid/missing and **excluded** from computation.
-   **strideMask**: index increment for `mask`.

The `N` and `stride` parameters determine which elements are accessed at runtime. For example, to compute the minimum value of every other element in `x`,

```javascript
var Float64Array = require( '@stdlib/array-float64' );
var Uint8Array = require( '@stdlib/array-uint8' );
var floor = require( '@stdlib/math-base-special-floor' );

var x = new Float64Array( [ 1.0, 2.0, 7.0, -2.0, -4.0, 3.0, -5.0, -6.0 ] );
var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
var N = floor( x.length / 2 );

var v = dnanmskmin( N, x, 2, mask, 2 );
// returns -4.0
```

Note that indexing is relative to the first index. To introduce offsets, use [`typed array`][mdn-typed-array] views.

<!-- eslint-disable stdlib/capitalized-comments -->

```javascript
var Float64Array = require( '@stdlib/array-float64' );
var Uint8Array = require( '@stdlib/array-uint8' );
var floor = require( '@stdlib/math-base-special-floor' );

var x0 = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, -5.0, -6.0 ] );
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

var N = floor( x0.length / 2 );

var v = dnanmskmin( N, x1, 2, mask1, 2 );
// returns -2.0
```

#### dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )

Computes the minimum value of a double-precision floating-point strided array according to a `mask`, ignoring `NaN` values and using alternative indexing semantics.

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

var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );
var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );

var v = dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 );
// returns -2.0
```

The function has the following additional parameters:

-   **offsetX**: starting index for `x`.
-   **offsetMask**: starting index for `mask`.

While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the minimum value for every other value in `x` starting from the second value

```javascript
var Float64Array = require( '@stdlib/array-float64' );
var Uint8Array = require( '@stdlib/array-uint8' );
var floor = require( '@stdlib/math-base-special-floor' );

var x = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, -5.0, -6.0 ] );
var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
var N = floor( x.length / 2 );

var v = dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 );
// returns -2.0
```

</section>

<!-- /.usage -->

<section class="notes">

## Notes

-   If `N <= 0`, both functions return `NaN`.

</section>

<!-- /.notes -->

<section class="examples">

## Examples

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

```javascript
var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var Float64Array = require( '@stdlib/array-float64' );
var Uint8Array = require( '@stdlib/array-uint8' );
var dnanmskmin = require( '@stdlib/stats-base-dnanmskmin' );

var mask;
var x;
var i;

x = new Float64Array( 10 );
mask = new Uint8Array( x.length );
for ( i = 0; i < x.length; i++ ) {
    if ( randu() < 0.2 ) {
        mask[ i ] = 1;
    } else {
        mask[ i ] = 0;
    }
    if ( randu() < 0.1 ) {
        x[ i ] = NaN;
    } else {
        x[ i ] = round( (randu()*100.0) - 50.0 );
    }
}
console.log( x );
console.log( mask );

var v = dnanmskmin( x.length, x, 1, mask, 1 );
console.log( v );
```

</section>

<!-- /.examples -->

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

<section class="related">

* * *

## See Also

-   <span class="package-name">[`@stdlib/stats-base/dmskmin`][@stdlib/stats/base/dmskmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a double-precision floating-point strided array according to a mask.</span>
-   <span class="package-name">[`@stdlib/stats-base/dnanmin`][@stdlib/stats/base/dnanmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a double-precision floating-point strided array, ignoring NaN values.</span>
-   <span class="package-name">[`@stdlib/stats-base/dnanmskmax`][@stdlib/stats/base/dnanmskmax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a double-precision floating-point strided array according to a mask, ignoring NaN values.</span>
-   <span class="package-name">[`@stdlib/stats-base/nanmskmin`][@stdlib/stats/base/nanmskmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a strided array according to a mask, ignoring NaN values.</span>
-   <span class="package-name">[`@stdlib/stats-base/snanmskmin`][@stdlib/stats/base/snanmskmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a single-precision floating-point strided array according to a mask, ignoring NaN values.</span>

</section>

<!-- /.related -->

<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->


<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; 2016-2024. The Stdlib [Authors][stdlib-authors].

</section>

<!-- /.stdlib -->

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

[stdlib-authors]: https://github.com/stdlib-js/stdlib/graphs/contributors

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

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

[@stdlib/array/float64]: https://www.npmjs.com/package/@stdlib/array-float64

[@stdlib/array/uint8]: https://www.npmjs.com/package/@stdlib/array-uint8

[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray

<!-- <related-links> -->

[@stdlib/stats/base/dmskmin]: https://www.npmjs.com/package/@stdlib/stats-base-dmskmin

[@stdlib/stats/base/dnanmin]: https://www.npmjs.com/package/@stdlib/stats-base-dnanmin

[@stdlib/stats/base/dnanmskmax]: https://www.npmjs.com/package/@stdlib/stats-base-dnanmskmax

[@stdlib/stats/base/nanmskmin]: https://www.npmjs.com/package/@stdlib/stats-base-nanmskmin

[@stdlib/stats/base/snanmskmin]: https://www.npmjs.com/package/@stdlib/stats-base-snanmskmin

<!-- </related-links> -->

</section>

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