Skip to content

Latest commit

 

History

History
327 lines (206 loc) · 11.7 KB

README.md

File metadata and controls

327 lines (206 loc) · 11.7 KB
Raw
About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

sabs2

NPM version Build Status Coverage Status

Compute the squared absolute value for each element in a single-precision floating-point strided array.

Usage

To use in Observable,

sabs2 = require( 'https://cdn.jsdelivr.net/gh/stdlib-js/math-strided-special-sabs2@umd/browser.js' )

To vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:

var sabs2 = require( 'path/to/vendor/umd/math-strided-special-sabs2/index.js' )

To include the bundle in a webpage,

<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/math-strided-special-sabs2@umd/browser.js"></script>

If no recognized module system is present, access bundle contents via the global scope:

<script type="text/javascript">
(function () {
    window.sabs2;
})();
</script>

sabs2( N, x, strideX, y, strideY )

Computes the squared absolute value for each element in a single-precision floating-point strided array x and assigns the results to elements in a single-precision floating-point strided array y.

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

var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );

// Compute the squared absolute values in-place:
sabs2( x.length, x, 1, x, 1 );
// x => <Float32Array>[ 4.0, 1.0, 9.0, 25.0, 16.0, 0.0, 1.0, 9.0 ]

The function accepts the following arguments:

  • N: number of indexed elements.
  • x: input Float32Array.
  • strideX: index increment for x.
  • y: output Float32Array.
  • strideY: index increment for y.

The N and stride parameters determine which elements in x and y are accessed at runtime. For example, to index every other value in x and to index the first N elements of y in reverse order,

var Float32Array = require( '@stdlib/array-float32' );
var floor = require( '@stdlib/math-base-special-floor' );

var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ] );
var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

var N = floor( x.length / 2 );

sabs2( N, x, 2, y, -1 );
// y => <Float32Array>[ 25.0, 9.0, 1.0, 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' );
var floor = require( '@stdlib/math-base-special-floor' );

// Initial arrays...
var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ] );
var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

// 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

var N = floor( x0.length / 2 );

sabs2( N, x1, -2, y1, 1 );
// y0 => <Float32Array>[ 0.0, 0.0, 0.0, 36.0, 16.0, 4.0 ]

sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )

Computes the squared absolute value for each element in a single-precision floating-point strided array x and assigns the results to elements in a single-precision floating-point strided array y using alternative indexing semantics.

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

var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0, -5.0 ] );
var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );

sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 );
// y => <Float32Array>[ 1.0, 4.0, 9.0, 16.0, 25.0 ]

The function accepts the following additional arguments:

  • offsetX: starting index for x.
  • offsetY: starting index for y.

While typed array views mandate a view offset based on the underlying buffer, the offsetX and offsetY parameters support indexing semantics based on starting indices. For example, to index every other value in x starting from the second value and to index the last N elements in y,

var Float32Array = require( '@stdlib/array-float32' );
var floor = require( '@stdlib/math-base-special-floor' );

var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ] );
var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

var N = floor( x.length / 2 );

sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 );
// y => <Float32Array>[ 0.0, 0.0, 0.0, 36.0, 16.0, 4.0 ]

Examples

<!DOCTYPE html>
<html lang="en">
<body>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/math-base-special-round@umd/browser.js"></script>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/random-base-randu@umd/browser.js"></script>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/array-float32@umd/browser.js"></script>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/math-strided-special-sabs2@umd/browser.js"></script>
<script type="text/javascript">
(function () {

var x = new Float32Array( 10 );
var y = new Float32Array( 10 );

var i;
for ( i = 0; i < x.length; i++ ) {
    x[ i ] = round( (randu()*200.0) - 100.0 );
}
console.log( x );
console.log( y );

sabs2.ndarray( x.length, x, 1, 0, y, -1, y.length-1 );
console.log( y );

})();
</script>
</body>
</html>

See Also

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.

Community

Chat

License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.