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

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@license Apache-2.0
Copyright (c) 2020 The Stdlib Authors.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
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# dcumin
> Calculate the cumulative minimum of double-precision floating-point strided array elements.
<section class="intro">
</section>
<!-- /.intro -->
<section class="usage">
## Usage
```javascript
var dcumin = require( '@stdlib/stats/base/dcumin' );
```
#### dcumin( N, x, strideX, y, strideY )
Computes the cumulative minimum 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 );
dcumin( x.length, x, 1, y, 1 );
// y => <Float64Array>[ 1.0, -2.0, -2.0 ]
```
The function has the following parameters:
- **N**: number of indexed elements.
- **x**: input [`Float64Array`][@stdlib/array/float64].
- **strideX**: index increment for `x`.
- **y**: output [`Float64Array`][@stdlib/array/float64].
- **strideY**: index increment for `y`.
The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative minimum 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 = dcumin( 4, x, 2, y, 1 );
// y => <Float64Array>[ 1.0, 1.0, -2.0, -2.0, 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
dcumin( 4, x1, -2, y1, 1 );
// y0 => <Float64Array>[ 0.0, 0.0, 0.0, 4.0, 2.0, -2.0, -2.0, 0.0 ]
```
#### dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )
Computes the cumulative minimum 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 );
dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 );
// y => <Float64Array>[ 1.0, -2.0, -2.0 ]
```
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`, `offsetX` and `offsetY` parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative minimum of every other value in `x` starting from the second value 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 );
dcumin.ndarray( 4, x, 2, 1, y, -1, y.length-1 );
// y => <Float64Array>[ 0.0, 0.0, 0.0, 0.0, -2.0, -2.0, -2.0, 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 randu = require( '@stdlib/random/base/randu' );
var round = require( '@stdlib/math/base/special/round' );
var Float64Array = require( '@stdlib/array/float64' );
var dcumin = require( '@stdlib/stats/base/dcumin' );
var y;
var x;
var i;
x = new Float64Array( 10 );
y = new Float64Array( x.length );
for ( i = 0; i < x.length; i++ ) {
x[ i ] = round( randu()*100.0 );
}
console.log( x );
console.log( y );
dcumin( x.length, x, 1, y, -1 );
console.log( y );
```
</section>
<!-- /.examples -->
<section class="references">
</section>
<!-- /.references -->
<section class="links">
[@stdlib/array/float64]: https://www.npmjs.com/package/@stdlib/array-float64
[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
</section>
<!-- /.links -->