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NullaryStrided1dDispatch

Constructor for applying a strided function to an ndarray.

Installation

npm install @stdlib/ndarray-base-nullary-strided1d-dispatch

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 NullaryStrided1dDispatch = require( '@stdlib/ndarray-base-nullary-strided1d-dispatch' );

NullaryStrided1dDispatch( table, idtypes, odtypes[, options] )

Returns an interface for applying a strided function to an ndarray.

var base = require( '@stdlib/blas-ext-base-ndarray-gsorthp' );

var table = {
    'default': base
};

var dtypes = [ 'float64', 'float32', 'generic' ];

var nullary = new NullaryStrided1dDispatch( table, [ dtypes ], dtypes );

The constructor has the following parameters:

• table: strided function dispatch table. Must have the following properties:

  • default: default strided function which should be invoked when provided ndarrays have data types which do not have a corresponding specialized implementation.

  A dispatch table may have the following additional properties:

  • types: one-dimensional list of ndarray data types describing specialized output ndarray argument signatures. Only the output ndarray argument data types should be specified. Additional ndarray argument data types should be omitted and are not considered during dispatch. The length of types must equal the number of strided functions specified by fcns.
  • fcns: list of strided functions which are specific to specialized output ndarray argument signatures.

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

• odtypes: list of supported output data types.

• options: function options (optional).

The constructor supports the following options:

• strictTraversalOrder: boolean specifying whether the order of element traversal must match the memory layout order of an output ndarray. Default: false.

NullaryStrided1dDispatch.prototype.assign( out[, ...args][, options] )

Applies a strided function and assigns results to a provided output ndarray.

var base = require( '@stdlib/blas-ext-base-ndarray-gsorthp' );
var dtypes = require( '@stdlib/ndarray-dtypes' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var scalar2ndarray = require( '@stdlib/ndarray-from-scalar' );
var ndarray = require( '@stdlib/ndarray-base-ctor' );
var NullaryStrided1dDispatch = require( '@stdlib/ndarray-base-nullary-strided1d-dispatch' );

var idt = dtypes( 'real_and_generic' );
var odt = dtypes( 'all' );

var table = {
    'default': base
};
var nullary = new NullaryStrided1dDispatch( table, [ idt ], odt );

var xbuf = [ -1.0, 2.0, -3.0 ];
var x = new ndarray( 'generic', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );

var order = scalar2ndarray( 1.0, {
    'dtype': 'generic'
});

var out = nullary.assign( x, order, {
    'dims': [ 0 ]
});
// returns <ndarray>

var arr = ndarray2array( x );
// returns [ -3.0, -1.0, 2.0 ]

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

The method has the following parameters:

• out: output ndarray.
• args: additional input ndarray arguments (optional).
• options: function options (optional).

The method accepts the following options:

• dims: list of dimensions over which to perform an operation.

Notes

• A strided function should have the following signature:

  f( arrays )
  

  where

  • arrays: array containing an output ndarray, followed by any additional ndarray arguments.

Examples

var dsorthp = require( '@stdlib/blas-ext-base-ndarray-dsorthp' );
var ssorthp = require( '@stdlib/blas-ext-base-ndarray-ssorthp' );
var base = require( '@stdlib/blas-ext-base-ndarray-gsorthp' );
var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var dtypes = require( '@stdlib/ndarray-dtypes' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var scalar2ndarray = require( '@stdlib/ndarray-from-scalar' );
var ndarray = require( '@stdlib/ndarray-ctor' );
var NullaryStrided1dDispatch = require( '@stdlib/ndarray-base-nullary-strided1d-dispatch' );

// Define the supported input and output data types:
var idt = dtypes( 'real_and_generic' );
var odt = dtypes( 'all' );

// Define a dispatch table:
var table = {
    'types': [
        'float64', // input/output
        'float32'  // input/output
    ],
    'fcns': [
        dsorthp,
        ssorthp
    ],
    'default': base
};

// Create an interface for performing operation:
var sorthp = new NullaryStrided1dDispatch( table, [ idt ], odt );

// Generate an array of random numbers:
var xbuf = discreteUniform( 25, -10, 10, {
    'dtype': 'float64'
});

// Wrap in an ndarray:
var x = new ndarray( 'float64', xbuf, [ 5, 5 ], [ 5, 1 ], 0, 'row-major' );
console.log( ndarray2array( x ) );

// Specify the sort order:
var order = scalar2ndarray( 1.0, {
    'dtype': 'generic'
});

// Perform operation:
sorthp.assign( x, order, {
    'dims': [ 0, 1 ]
});

// Print the results:
console.log( ndarray2array( x ) );

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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

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