Create a function which performs element-wise computation by applying a unary function to each element in an input ndarray.
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> 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.
``bash`
npm install @stdlib/math-tools-unary
`javascript`
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.
`javascript
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][@stdlib/ndarray/output-dtype-policies].
- casting: input ndarray casting [policy][@stdlib/ndarray/input-casting-policies].
#### ufunc( x\[, options] )
Performs element-wise computation.
`javascript
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
var y = ufunc( x );
// returns
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.
`javascript
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
var y = ufunc( x, {
'dtype': 'generic'
});
// returns
var dt = getDType( y );
// returns 'generic'
`
#### ufunc.assign( x, out )
Performs element-wise computation and assigns results to a provided output ndarray.
`javascript
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
var y = zerosLike( x );
// returns
var out = ufunc.assign( x, y );
// returns
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.
- A provided unary function should have the following signature:
`text`
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.
`javascript
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 ) );
`
*
This package is part of [stdlib][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][stdlib], see the main project [repository][stdlib].
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