npm package: @stdlib/stats-strided-dcuminabs
Description: Calculate the cumulative minimum absolute value of double-precision floating-point strided array elements.
Author: The Stdlib Authors
Latest version: 0.1.1

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# dcuminabs

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> Calculate the cumulative minimum absolute value of double-precision floating-point strided array elements.

<section class="intro">

</section>

<!-- /.intro -->

<section class="installation">

## Installation

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

</section>

<section class="usage">

## Usage

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

#### dcuminabs( N, x, strideX, y, strideY )

Computes the cumulative minimum absolute value of double-precision floating-point strided array elements.

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

var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
var y = new Float64Array( x.length );

dcuminabs( x.length, x, 1, y, 1 );
// y => <Float64Array>[ 1.0, 1.0, 1.0 ]
```

The function has the following parameters:

-   **N**: number of indexed elements.
-   **x**: input [`Float64Array`][@stdlib/array/float64].
-   **strideX**: stride length for `x`.
-   **y**: output [`Float64Array`][@stdlib/array/float64].
-   **strideY**: stride length for `y`.

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

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

var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
var y = new Float64Array( x.length );

var v = dcuminabs( 4, x, 2, y, 1 );
// y => <Float64Array>[ 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0 ]
```

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

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

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

// Initial arrays...
var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var y0 = new Float64Array( x0.length );

// Create offset views...
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element

dcuminabs( 4, x1, -2, y1, 1 );
// y0 => <Float64Array>[ 0.0, 0.0, 0.0, 4.0, 2.0, 2.0, 1.0, 0.0 ]
```

#### dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )

Computes the cumulative minimum absolute value of double-precision floating-point strided array elements using alternative indexing semantics.

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

var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
var y = new Float64Array( x.length );

dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 );
// y => <Float64Array>[ 1.0, 1.0, 1.0 ]
```

The function has the following additional parameters:

-   **offsetX**: starting index for `x`.
-   **offsetY**: starting index for `y`.

While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to calculate the cumulative minimum absolute value of every other element in `x` starting from the second element and to store in the last `N` elements of `y` starting from the last element

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

var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var y = new Float64Array( x.length );

dcuminabs.ndarray( 4, x, 2, 1, y, -1, y.length-1 );
// y => <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0 ]
```

</section>

<!-- /.usage -->

<section class="notes">

## Notes

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

</section>

<!-- /.notes -->

<section class="examples">

## Examples

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

```javascript
var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var Float64Array = require( '@stdlib/array-float64' );
var dcuminabs = require( '@stdlib/stats-strided-dcuminabs' );

var x = discreteUniform( 10, -50, 50, {
    'dtype': 'float64'
});
console.log( x );

var y = new Float64Array( x.length );
console.log( y );

dcuminabs( x.length, x, 1, y, -1 );
console.log( y );
```

</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/dcuminabs.h"
```

#### stdlib_strided_dcuminabs( N, \*X, strideX, \*Y, strideY )

Computes the cumulative minumum absolute value of double-precision floating-point strided array elements.

```c
const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 };
double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };

stdlib_strided_dcuminabs( 4, x, 2, y, -2 );
```

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`.
-   **Y**: `[out] double*` output array.
-   **strideY**: `[in] CBLAS_INT` stride length for `Y`.

```c
void stdlib_strided_dcuminabs( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY );
```

#### stdlib_strided_dcuminabs_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY )

Computes the cumulative minumum absolute value of double-precision floating-point strided array elements using alternative indexing semantics.

```c
const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 };
double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };

stdlib_strided_dcuminabs_ndarray( 4, x, 2, 0, y, -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`.
-   **Y**: `[out] double*` output array.
-   **strideY**: `[in] CBLAS_INT` stride length for `Y`.
-   **offsetY**: `[in] CBLAS_INT` starting index for `Y`.

```c
void stdlib_strided_dcuminabs_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY );
```

</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/dcuminabs.h"
#include <stdio.h>

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

    // Specify the number of elements:
    const int N = 4;

    // Specify stride lengths:
    const int strideX = 2;
    const int strideY = -2;

    // Compute the cumulative minumum absolute value:
    stdlib_strided_dcuminabs( N, x, strideX, y, strideY );

    // Print the result:
    for ( int i = 0; i < 8; i++ ) {
        printf( "y[ %d ] = %lf\n", i, y[ i ] );
    }
}
```

</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-base/cuminabs`][@stdlib/stats/base/cuminabs]</span><span class="delimiter">: </span><span class="description">calculate the cumulative minimum absolute value of a strided array.</span>
-   <span class="package-name">[`@stdlib/stats-strided/dcumaxabs`][@stdlib/stats/strided/dcumaxabs]</span><span class="delimiter">: </span><span class="description">calculate the cumulative maximum absolute value of double-precision floating-point strided array elements.</span>
-   <span class="package-name">[`@stdlib/stats-strided/dcumin`][@stdlib/stats/strided/dcumin]</span><span class="delimiter">: </span><span class="description">calculate the cumulative minimum of double-precision floating-point strided array elements.</span>
-   <span class="package-name">[`@stdlib/stats-strided/scuminabs`][@stdlib/stats/strided/scuminabs]</span><span class="delimiter">: </span><span class="description">calculate the cumulative minimum absolute value of single-precision floating-point strided array elements.</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].

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

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

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

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

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

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