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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!

Unary

NPM version Build Status Coverage Status

Apply a unary callback to elements in a strided input array and assign results to elements in a strided output array.

Usage

To use in Observable,

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

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

var unary = require( 'path/to/vendor/umd/strided-base-unary/index.js' )

To include the bundle in a webpage,

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

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

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

unary( arrays, shape, strides, fcn )

Applies a unary callback to elements in a strided input array and assigns results to elements in a strided output array.

var Float64Array = require( '@stdlib/array-float64' );
var abs = require( '@stdlib/math-base-special-abs' );

var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );

// Compute the absolute values in-place:
unary( [ x, x ], [ x.length ], [ 1, 1 ], abs );
// x => <Float64Array>[ 2.0, 1.0, 3.0, 5.0, 4.0, 0.0, 1.0, 3.0 ]

The function accepts the following arguments:

  • arrays: array-like object containing one strided input array and one strided output array.
  • shape: array-like object containing a single element, the number of indexed elements.
  • strides: array-like object containing the stride lengths for the strided input and output arrays.
  • fcn: unary function to apply.

The shape and strides parameters determine which elements in the strided input and output arrays are accessed at runtime. For example, to index every other value in the strided input array and to index the first N elements of the strided output array in reverse order,

var Float64Array = require( '@stdlib/array-float64' );
var abs = require( '@stdlib/math-base-special-abs' );

var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ] );
var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

var N = 3;

unary( [ x, y ], [ N ], [ 2, -1 ], abs );
// y => <Float64Array>[ 5.0, 3.0, 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 Float64Array = require( '@stdlib/array-float64' );
var abs = require( '@stdlib/math-base-special-abs' );

// Initial arrays...
var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ] );
var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

// 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

var N = 3;

unary( [ x1, y1 ], [ N ], [ -2, 1 ], abs );
// y0 => <Float64Array>[ 0.0, 0.0, 0.0, 6.0, 4.0, 2.0 ]

unary.ndarray( arrays, shape, strides, offsets, fcn )

Applies a unary callback to elements in a strided input array and assigns results to elements in a strided output array using alternative indexing semantics.

var Float64Array = require( '@stdlib/array-float64' );
var abs = require( '@stdlib/math-base-special-abs' );

var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0, -5.0 ] );
var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );

unary.ndarray( [ x, y ], [ x.length ], [ 1, 1 ], [ 0, 0 ], abs );
// y => <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]

The function accepts the following additional arguments:

  • offsets: array-like object containing the starting indices (i.e., index offsets) for the strided input and output arrays.

While typed array views mandate a view offset based on the underlying buffer, the offsets parameter supports indexing semantics based on starting indices. For example, to index every other value in the strided input array starting from the second value and to index the last N elements in the strided output array,

var Float64Array = require( '@stdlib/array-float64' );
var abs = require( '@stdlib/math-base-special-abs' );

var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ] );
var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

var N = 3;

unary.ndarray( [ x, y ], [ N ], [ 2, -1 ], [ 1, y.length-1 ], abs );
// y => <Float64Array>[ 0.0, 0.0, 0.0, 6.0, 4.0, 2.0 ]

Examples

<!DOCTYPE html>
<html lang="en">
<body>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/random-base-discrete-uniform@umd/browser.js"></script>
<script type="text/javascript">
(function () {.factory;
var filledarray = require( '@stdlib/array-filled' );
var filledarrayBy = require( '@stdlib/array-filled-by' );
var unary = require( '@stdlib/strided-base-unary' );

function add10( x ) {
    return x + 10;
}

var N = 10;

var x = filledarrayBy( N, 'generic', discreteUniform( -100, 100 ) );
console.log( x );

var y = filledarray( 0.0, N, 'generic' );
console.log( y );

var shape = [ N ];
var strides = [ 1, -1 ];
var offsets = [ 0, N-1 ];

unary.ndarray( [ x, y ], shape, strides, offsets, add10 );
console.log( y );

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

See Also

  • @stdlib/strided-base/unary: apply a unary callback to elements in a strided input array and assign results to elements in a strided output array.
  • @stdlib/strided-base/dmap: apply a unary function to a double-precision floating-point strided input array and assign results to a double-precision floating-point strided output array.
  • @stdlib/strided-base/nullary: apply a nullary callback and assign results to elements in a strided output array.
  • @stdlib/strided-base/quaternary: apply a quaternary callback to strided input array elements and assign results to elements in a strided output array.
  • @stdlib/strided-base/quinary: apply a quinary callback to strided input array elements and assign results to elements in a strided output array.
  • @stdlib/strided-base/smap: apply a unary function to a single-precision floating-point strided input array and assign results to a single-precision floating-point strided output array.
  • @stdlib/strided-base/ternary: apply a ternary callback to strided input array elements and assign results to elements in a strided output array.

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.

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License

See LICENSE.

Copyright

Copyright © 2016-2025. The Stdlib Authors.