npm package: @stdlib/stats-strided-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: 0.1.1

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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-strided-dnanmskmin
```

</section>

<section class="usage">

## Usage

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

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

Computes the minimum value of a double-precision floating-point strided array 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**: stride length 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**: stride length for `mask`.

The `N` and stride parameters determine which elements in the strided array 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 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 v = dnanmskmin( 4, 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 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 v = dnanmskmin( 4, 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, offset parameters support indexing semantics based on starting indices. For example, to calculate the minimum value for every other element in `x` starting from the second element

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

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 v = dnanmskmin.ndarray( 4, 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 uniform = require( '@stdlib/random-base-uniform' );
var bernoulli = require( '@stdlib/random-base-bernoulli' );
var filledarrayBy = require( '@stdlib/array-filled-by' );
var dnanmskmin = require( '@stdlib/stats-strided-dnanmskmin' );

function rand() {
    if ( bernoulli( 0.8 ) < 1 ) {
        return NaN;
    }
    return uniform( -50.0, 50.0 );
}

var x = filledarrayBy( 10, 'float64', rand );
console.log( x );

var mask = filledarrayBy( x.length, 'uint8', bernoulli.factory( 0.2 ) );
console.log( mask );

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

</section>

<!-- /.examples -->

<!-- C interface documentation. -->

* * *

<section class="c">

## C APIs

<!-- 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 -->

<!-- C usage documentation. -->

<section class="usage">

### Usage

```c
#include "stdlib/stats/strided/dnanmskmin.h"
```

#### stdlib_strided_dnanmskmin( N, \*X, strideX, \*Mask, strideMask )

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

```c
#include <stdint.h>

const double x[] = { 1.0, -2.0, 4.0, 2.0, 0.0/0.0 };
const uint8_t mask[] = { 0, 0, 1, 0, 0 };

double v = stdlib_strided_dnanmskmin( 5, x, 1, mask, 1 );
// returns -2.0
```

The function accepts the following arguments:

-   **N**: `[in] CBLAS_INT` number of indexed elements.
-   **X**: `[in] double*` input array.
-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
-   **Mask**: `[in] uint8_t*` mask array. 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**: `[in] CBLAS_INT` stride length for `Mask`.

```c
double stdlib_strided_dnanmskmin( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask );
```

#### stdlib_strided_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.

```c
#include <stdint.h>

const double x[] = { 1.0, -2.0, 4.0, 2.0, 0.0/0.0 };
const uint8_t mask[] = { 0, 0, 1, 0, 0 };

double v = stdlib_strided_dnanmskmin_ndarray( 5, x, 1, 0, mask, 1, 0 );
// returns -2.0
```

The function accepts the following arguments:

-   **N**: `[in] CBLAS_INT` number of indexed elements.
-   **X**: `[in] double*` input array.
-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
-   **Mask**: `[in] uint8_t*` mask array. 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**: `[in] CBLAS_INT` stride length for `Mask`.
-   **offsetMask**: `[in] CBLAS_INT` starting index for `Mask`.

```c
double stdlib_strided_dnanmskmin_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask );
```

</section>

<!-- /.usage -->

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

<section class="notes">

</section>

<!-- /.notes -->

<!-- C API usage examples. -->

<section class="examples">

### Examples

```c
#include "stdlib/stats/strided/dnanmskmin.h"
#include <stdint.h>
#include <stdio.h>

int main( void ) {
    // Create a strided array:
    const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 0.0/0.0, 0.0/0.0 };

    // Create a mask array:
    const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 };

    // Specify the number of elements:
    const int N = 5;

    // Specify the stride lengths:
    const int strideX = 2;
    const int strideMask = 2;

    // Compute the minimum value:
    double v = stdlib_strided_dnanmskmin( N, x, strideX, mask, strideMask );

    // Print the result:
    printf( "min: %lf\n", v );
}
```

</section>

<!-- /.examples -->

</section>

<!-- /.c -->

<section class="references">

</section>

<!-- /.references -->

<!-- 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-strided/dmskmin`][@stdlib/stats/strided/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-strided/dnanmin`][@stdlib/stats/strided/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-strided/dnanmskmax`][@stdlib/stats/strided/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-strided/nanmskmin`][@stdlib/stats/strided/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-strided/snanmskmin`][@stdlib/stats/strided/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 -->

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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

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---

## License

See [LICENSE][stdlib-license].


## Copyright

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

</section>

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

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

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

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