@stdlib/math-special-abs
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    0.0.5 • Public • Published

    abs

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    Compute the absolute value.

    The absolute value is defined as

    Absolute value

    Installation

    npm install @stdlib/math-special-abs

    Usage

    var abs = require( '@stdlib/math-special-abs' );

    abs( x[, options] )

    Computes the absolute value.

    var y = abs( -1.0 );
    // returns 1.0

    The function accepts the following arguments:

    • x: input ndarray, array-like object, or number. If provided an ndarray or array-like object, the function performs element-wise computation.
    • options: function options.

    If provided an ndarray, the function returns an ndarray having the same shape and data type as x.

    var array = require( '@stdlib/ndarray-array' );
    
    var x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] ); // 2x2
    var y = abs( x );
    // returns <ndarray>
    
    var v = y.get( 0, 1 );
    // returns 2.0

    If provided an array-like object, the function returns an array-like object having the same length and data type as x.

    var Float64Array = require( '@stdlib/array-float64' );
    
    var x = new Float64Array( [ -1.0, -2.0 ] );
    var y = abs( x );
    // returns <Float64Array>[ 1.0, 2.0 ]
    
    x = [ -1.0, -2.0 ];
    y = abs( x );
    // returns [ 1.0, 2.0 ]

    The function accepts the following options:

    • dtype: output array data type. Only applicable when x is either an ndarray or array-like object. By default, the output array data type is inferred from the input array.
    • order: output array order. Only applicable when x is an ndarray. By default, the output array order is inferred from the input array.

    By default, when provided either an ndarray or an array-like object, the function returns an object of the same "kind" (either an ndarray or array-like object, respectively) having the same underlying data type. To specify a different output array data type, set the dtype option.

    var Float32Array = require( '@stdlib/array-float32' );
    
    var x = new Float32Array( [ -1.0, -2.0 ] );
    var y = abs( x );
    // returns <Float32Array>[ 1.0, 2.0 ]
    
    x = new Float32Array( [ -1.0, -2.0 ] );
    y = abs( x, {
        'dtype': 'float64'
    });
    // returns <Float64Array>[ 1.0, 2.0 ]

    abs.assign( x, y )

    Computes the absolute value and assigns results to a provided output array.

    var array = require( '@stdlib/ndarray-array' );
    
    var x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] ); // 2x2
    var y = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] ); // 2x2
    var out = abs.assign( x, y );
    // returns <ndarray>
    
    var bool = ( out === y );
    // returns true
    
    var v = y.get( 0, 1 );
    // returns 2.0

    The output array must be the same data "kind" (i.e., ndarray or array-like object) as the input array. For example, if x is an ndarray, y must also be an ndarray. Similarly, if x is an array-like object, y must also be an array-like object.

    TODO: broadcasting discussion and example(s).

    Examples

    var Float64Array = require( '@stdlib/array-float64' );
    var array = require( '@stdlib/ndarray-array' );
    var ind2sub = require( '@stdlib/ndarray-ind2sub' );
    var abs = require( '@stdlib/math-special-abs' );
    
    // Provide a number...
    var v = abs( -1.0 );
    console.log( 'x = %d => abs(x) = %d', -1.0, v );
    
    // Provide an array-like object...
    var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );
    var y = abs( x );
    
    var i;
    for ( i = 0; i < x.length; i++ ) {
        console.log( 'x_%d = %d => abs(x_%d) = %d', i, x[ i ], i, y[ i ] );
    }
    
    // Provide an ndarray...
    x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );
    y = abs( x );
    
    var sh = x.shape;
    var sub;
    for ( i = 0; i < x.length; i++ ) {
        sub = ind2sub( sh, i );
        console.log( 'x_%d%d = %d => abs(x_%d%d) = %d', sub[ 0 ], sub[ 1 ], x.iget( i ), sub[ 0 ], sub[ 1 ], y.iget( i ) );
    }

    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 © 2016-2021. The Stdlib Authors.

    Install

    npm i @stdlib/math-special-abs

    Homepage

    stdlib.io

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    Version

    0.0.5

    License

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