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Unary

Create a function which performs element-wise computation by applying a unary function to each element in an input ndarray.

The purpose of this package is to provide a thin wrapper around a lower-level interface supporting multiple dispatch based on the data types of provided ndarray arguments. The wrapper performs the following tasks:

• validates input arguments.
• casts input ndarrays according to a casting policy.
• allocates an output ndarray according to an output data type policy.

Installation

npm install @stdlib/math-tools-unary

Alternatively,

• To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
• If you are using Deno, visit the deno branch (see README for usage intructions).
• For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).

The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.

To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

Usage

var factory = require( '@stdlib/math-tools-unary' );

factory( fcn, idtypes, odtypes, policies )

Returns a function which performs element-wise computation by applying a unary function to each element in an input ndarray.

var base = require( '@stdlib/math-base-special-abs' );
var dispatch = require( '@stdlib/ndarray-dispatch' );
var unary = require( '@stdlib/ndarray-base-unary' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var array = require( '@stdlib/ndarray-array' );

var types = [
    'float64', 'float64',
    'float64', 'generic',
    'generic', 'generic'
];
var data = [
    base,
    base,
    base
];
var dispatcher = dispatch( unary, types, data, 2, 1, 1 );

var idt = [ 'float64', 'generic' ];
var odt = idt;

var policies = {
    'output': 'real_and_generic',
    'casting': 'none'
};
var ufunc = factory( dispatcher, [ idt ], odt, policies );

The function has the following arguments:

• fcn: function which applies a unary function to each element in an ndarray and assigns results to an output ndarray.

• idtypes: list containing lists of supported input data types for each input ndarray argument.

• odtypes: list of supported output data types.

• policies: dispatch policies. Must have the following properties:

  • output: output data type policy.
  • casting: input ndarray casting policy.

ufunc( x[, options] )

Performs element-wise computation.

var base = require( '@stdlib/math-base-special-abs' );
var dispatch = require( '@stdlib/ndarray-dispatch' );
var unary = require( '@stdlib/ndarray-base-unary' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var array = require( '@stdlib/ndarray-array' );

var types = [
    'float64', 'float64',
    'float64', 'generic',
    'generic', 'generic'
];
var data = [
    base,
    base,
    base
];
var dispatcher = dispatch( unary, types, data, 2, 1, 1 );

var idt = [ 'float64', 'generic' ];
var odt = idt;

var policies = {
    'output': 'real_and_generic',
    'casting': 'none'
};
var ufunc = factory( dispatcher, [ idt ], odt, policies );

var x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );
// returns <ndarray>

var y = ufunc( x );
// returns <ndarray>

var arr = ndarray2array( y );
// returns [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]

The function has the following parameters:

• x: input ndarray.
• options: function options (optional).

The function accepts the following options:

• dtype: output ndarray data type. Setting this option, overrides the output data type policy.
• order: output ndarray order.

By default, the function returns an ndarray having a data type determined by the output data type policy. To override the default behavior, set the dtype option.

var base = require( '@stdlib/math-base-special-abs' );
var dispatch = require( '@stdlib/ndarray-dispatch' );
var unary = require( '@stdlib/ndarray-base-unary' );
var getDType = require( '@stdlib/ndarray-dtype' );
var array = require( '@stdlib/ndarray-array' );

var types = [
    'float64', 'float64',
    'float64', 'generic',
    'generic', 'generic'
];
var data = [
    base,
    base,
    base
];
var dispatcher = dispatch( unary, types, data, 2, 1, 1 );

var idt = [ 'float64', 'generic' ];
var odt = idt;

var policies = {
    'output': 'real_and_generic',
    'casting': 'none'
};
var ufunc = factory( dispatcher, [ idt ], odt, policies );

var x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );
// returns <ndarray>

var y = ufunc( x, {
    'dtype': 'generic'
});
// returns <ndarray>

var dt = getDType( y );
// returns 'generic'

ufunc.assign( x, out )

Performs element-wise computation and assigns results to a provided output ndarray.

var base = require( '@stdlib/math-base-special-abs' );
var dispatch = require( '@stdlib/ndarray-dispatch' );
var unary = require( '@stdlib/ndarray-base-unary' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var zerosLike = require( '@stdlib/ndarray-zeros-like' );
var array = require( '@stdlib/ndarray-array' );

var types = [
    'float64', 'float64',
    'float64', 'generic',
    'generic', 'generic'
];
var data = [
    base,
    base,
    base
];
var dispatcher = dispatch( unary, types, data, 2, 1, 1 );

var idt = [ 'float64', 'generic' ];
var odt = idt;

var policies = {
    'output': 'real_and_generic',
    'casting': 'none'
};
var ufunc = factory( dispatcher, [ idt ], odt, policies );

var x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );
// returns <ndarray>

var y = zerosLike( x );
// returns <ndarray>

var out = ufunc.assign( x, y );
// returns <ndarray>

var bool = ( out === y );
// returns true

var arr = ndarray2array( out );
// returns [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]

The method has the following parameters:

• x: input ndarray.
• out: output ndarray.

Notes

• A provided unary function should have the following signature:

  f( x, y )
  

  where

  • x: input ndarray.
  • y: output ndarray.

• The output data type policy only applies to the function returned by the main function. For the assign method, the output ndarray is allowed to have any supported output data type.

Examples

var base = require( '@stdlib/math-base-special-abs' );
var basef = require( '@stdlib/math-base-special-absf' );
var uniform = require( '@stdlib/random-uniform' );
var dispatch = require( '@stdlib/ndarray-dispatch' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var unary = require( '@stdlib/ndarray-base-unary' );
var ufunc = require( '@stdlib/math-tools-unary' );

// Create a function which dispatches based on argument data types:
var types = [
    'float64', 'float64',
    'float32', 'float32',
    'generic', 'generic'
];
var data = [
    base,
    basef,
    base
];
var dispatcher = dispatch( unary, types, data, 2, 1, 1 );

// Define the supported input and output data types:
var idt = [ 'float64', 'float32', 'generic' ];
var odt = [ 'float64', 'float32', 'generic' ];

// Define dispatch policies:
var policies = {
    'output': 'same',
    'casting': 'none'
};

// Create a function that performs element-wise computation:
var abs = ufunc( dispatcher, [ idt ], odt, policies );

// Generate an array of random numbers:
var x = uniform( [ 5, 5 ], -10.0, 10.0, {
    'dtype': 'float64'
});
console.log( ndarray2array( x ) );

// Perform element-wise computation:
var y = abs( x );
console.log( ndarray2array( y ) );

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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

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License

See LICENSE.

Copyright

Copyright © 2016-2025. The Stdlib Authors.