@stdlib/ndarray-base-unary-addon-dispatch
v0.1.1
Published
Dispatch to a native add-on applying a unary function to an input ndarray.
Readme
dispatch
Dispatch to a native add-on applying a unary function to an input ndarray.
Installation
npm install @stdlib/ndarray-base-unary-addon-dispatchUsage
var dispatch = require( '@stdlib/ndarray-base-unary-addon-dispatch' );dispatch( addon, fallback )
Returns a function which dispatches to a native add-on applying a unary function to an input ndarray.
var array = require( '@stdlib/ndarray-array' );
var zeros = require( '@stdlib/ndarray-zeros' );
var dispatch = require( '@stdlib/ndarray-base-unary-addon-dispatch' );
function addon( x, metaX, y, metaY ) {
// Call into native add-on...
}
function fallback( x, y ) {
// Fallback JavaScript implementation...
}
// Create a dispatch function:
var f = dispatch( addon, fallback );
// ...
// Invoke the dispatch function with ndarray arguments:
var x = array( [ [ 1, 2], [ 3, 4 ] ] );
var y = zeros( [ 2, 2 ] );
f( x, y );The returned function has the following signature:
f( x, y )where
- x: input ndarray.
- y: output ndarray.
The addon function should have the following signature:
f( xbuf, metaX, ybuf, metaY )where
- xbuf: input ndarray data buffer.
- metaX: serialized input ndarray meta data.
- ybuf: output ndarray data buffer.
- metaY: serialized output ndarray meta data.
The fallback function should have the following signature:
f( x, y )where
- x: input ndarray.
- y: output ndarray.
Notes
- To determine whether to dispatch to the
addonfunction, the returned dispatch function checks whether the underlying ndarray data buffers are typed arrays. If the data buffers are typed arrays, the dispatch function invokes theaddonfunction; otherwise, the dispatch function invokes thefallbackfunction.
Examples
var array = require( '@stdlib/ndarray-array' );
var zeros = require( '@stdlib/ndarray-zeros' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var dispatch = require( '@stdlib/ndarray-base-unary-addon-dispatch' );
function addon( xbuf, metaX, ybuf, metaY ) {
console.log( xbuf );
// => <Float64Array>[ 1, 2, 3, 4 ]
console.log( ybuf );
// => <Float64Array>[ 0, 0, 0, 0 ]
}
function fallback( x, y ) {
console.log( ndarray2array( x ) );
// => [ [ 1, 2 ], [ 3, 4 ] ]
console.log( ndarray2array( y ) );
// => [ [ 0, 0 ], [ 0, 0 ] ]
}
// Create a dispatch function:
var f = dispatch( addon, fallback );
// Create ndarrays:
var opts = {
'dtype': 'float64',
'casting': 'unsafe'
};
var x = array( [ [ 1, 2 ], [ 3, 4 ] ], opts );
var y = zeros( [ 2, 2 ], opts );
// Dispatch to the add-on function:
f( x, y );
// Define new ndarrays:
opts = {
'dtype': 'generic'
};
x = array( [ [ 1, 2 ], [ 3, 4 ] ], opts );
y = zeros( [ 2, 2 ], opts );
// Dispatch to the fallback function:
f( x, y );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
License
See LICENSE.
Copyright
Copyright © 2016-2026. The Stdlib Authors.
