time-to-botec/squiggle/node_modules/@stdlib/stats/base/nanmin-by/README.md

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# nanminBy

> Calculate the minimum value of a strided array via a callback function, ignoring `NaN` values.

<section class="usage">

## Usage

```javascript
var nanminBy = require( '@stdlib/stats/base/nanmin-by' );
```

#### nanminBy( N, x, stride, clbk\[, thisArg] )

Calculates the minimum value of strided array `x` via a callback function, ignoring `NaN` values.

```javascript
function accessor( v ) {
    return v * 2.0;
}

var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, 0.0, -1.0, -3.0, NaN ];

var v = nanminBy( x.length, x, 1, accessor );
// returns -10.0
```

The function has the following parameters:

-   **N**: number of indexed elements.
-   **x**: input [`Array`][mdn-array], [`typed array`][mdn-typed-array], or an array-like object (excluding strings and functions). 
-   **stride**: index increment.
-   **clbk**: callback function.
-   **thisArg**: execution context (_optional_).

The invoked callback is provided four arguments:

-   **value**: array element.
-   **aidx**: array index.
-   **sidx**: strided index (`offset + aidx*stride`).
-   **array**: input array/collection.

To set the callback execution context, provide a `thisArg`.

```javascript
function accessor( v ) {
    this.count += 1;
    return v * 2.0;
}

var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, 0.0, -1.0, -3.0, NaN ];

var context = {
    'count': 0
};

var v = nanminBy( x.length, x, 1, accessor, context );
// returns -10.0

var cnt = context.count;
// returns 10
```

The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to access every other element

```javascript
var floor = require( '@stdlib/math/base/special/floor' );

function accessor( v ) {
    return v * 2.0;
}

var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0, NaN, NaN ];
var N = floor( x.length / 2 );

var v = nanminBy( N, x, 2, accessor );
// returns -4.0
```

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

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

function accessor( v ) {
    return v * 2.0;
}

// Initial array...
var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );

// Create an offset view...
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var N = floor( x0.length/2 );

// Access every other element...
var v = nanminBy( N, x1, 2, accessor );
// returns -12.0
```

#### nanminBy.ndarray( N, x, stride, offset, clbk\[, thisArg] )

Calculates the minimum value of strided array `x` via a callback function, ignoring `NaN` values and using alternative indexing semantics.

```javascript
function accessor( v ) {
    return v * 2.0;
}

var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, 0.0, -1.0, -3.0, NaN ];

var v = nanminBy.ndarray( x.length, x, 1, 0, accessor );
// returns -10.0
```

The function has the following additional parameters:

-   **offset**: starting index.

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 access only the last three elements of `x`

```javascript
function accessor( v ) {
    return v * 2.0;
}

var x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];

var v = nanminBy.ndarray( 3, x, 1, x.length-3, accessor );
// returns -12.0
```

</section>

<!-- /.usage -->

<section class="notes">

## Notes

-   If `N <= 0`, both functions return `NaN`.
-   A provided callback function should return a numeric value.
-   If a provided callback function returns `NaN`, the value is ignored.
-   If a provided callback function does not return any value (or equivalently, explicitly returns `undefined`), the value is ignored.
-   When possible, prefer using [`dnanmin`][@stdlib/stats/base/dnanmin], [`snanmin`][@stdlib/stats/base/snanmin], and/or [`nanmin`][@stdlib/stats/base/nanmin], as, depending on the environment, these interfaces are likely to be significantly more performant.

</section>

<!-- /.notes -->

<section class="examples">

## Examples

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

```javascript
var round = require( '@stdlib/math/base/special/round' );
var randu = require( '@stdlib/random/base/randu' );
var Float64Array = require( '@stdlib/array/float64' );
var gfillBy = require( '@stdlib/blas/ext/base/gfill-by' );
var nanminBy = require( '@stdlib/stats/base/nanmin-by' );

function fill() {
    if ( randu() < 0.2 ) {
        return NaN;
    }
    return round( ( randu()*100.0 ) - 50.0 );
}

function accessor( v ) {
    return v * 2.0;
}

var x = new Float64Array( 10 );

gfillBy( x.length, x, 1, fill );
console.log( x );

var v = nanminBy( x.length, x, 1, accessor );
console.log( v );
```

</section>

<!-- /.examples -->

<section class="links">

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

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

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

[@stdlib/stats/base/nanmin]: https://www.npmjs.com/package/@stdlib/stats/tree/main/base/nanmin

[@stdlib/stats/base/snanmin]: https://www.npmjs.com/package/@stdlib/stats/tree/main/base/snanmin

</section>

<!-- /.links -->