# @stdlib/stats-base-scuminabs

0.1.1 • Public • Published

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# scuminabs

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

## Installation

npm install @stdlib/stats-base-scuminabs

## Usage

var scuminabs = require( '@stdlib/stats-base-scuminabs' );

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

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

var Float32Array = require( '@stdlib/array-float32' );

var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
var y = new Float32Array( x.length );

scuminabs( x.length, x, 1, y, 1 );
// y => <Float32Array>[ 1.0, 1.0, 1.0 ]

The function has the following parameters:

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

var Float32Array = require( '@stdlib/array-float32' );

var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
var y = new Float32Array( x.length );

var v = scuminabs( 4, x, 2, y, 1 );
// y => <Float32Array>[ 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 views.

var Float32Array = require( '@stdlib/array-float32' );

// Initial arrays...
var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var y0 = new Float32Array( x0.length );

// Create offset views...
var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element

scuminabs( 4, x1, -2, y1, 1 );
// y0 => <Float32Array>[ 0.0, 0.0, 0.0, 4.0, 2.0, 2.0, 1.0, 0.0 ]

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

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

var Float32Array = require( '@stdlib/array-float32' );

var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
var y = new Float32Array( x.length );

scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 );
// y => <Float32Array>[ 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 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 absolute value 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

var Float32Array = require( '@stdlib/array-float32' );

var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var y = new Float32Array( x.length );

scuminabs.ndarray( 4, x, 2, 1, y, -1, y.length-1 );
// y => <Float32Array>[ 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0 ]

## Notes

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

## Examples

var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var Float32Array = require( '@stdlib/array-float32' );
var scuminabs = require( '@stdlib/stats-base-scuminabs' );

var y;
var x;
var i;

x = new Float32Array( 10 );
y = new Float32Array( x.length );
for ( i = 0; i < x.length; i++ ) {
x[ i ] = round( (randu()*100.0) - 50.0 );
}
console.log( x );
console.log( y );

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

## Notice

This package is part of 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, see the main project repository.

## Package Sidebar

### Install

npm i @stdlib/stats-base-scuminabs

### Repository

github.com/stdlib-js/stats-base-scuminabs

stdlib.io

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0.1.1

Apache-2.0

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