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Create a plain object describing how to interpret a data buffer as an n-dimensional array.
npm install @stdlib/ndarray-base-descriptorAlternatively,
- To load the package in a website via a
scripttag without installation and bundlers, use the ES Module available on theesmbranch (see README). - If you are using Deno, visit the
denobranch (see README for usage intructions). - For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the
umdbranch (see README).
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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.
var descriptor = require( '@stdlib/ndarray-base-descriptor' );Returns a plain object describing how to interpret a data buffer as an n-dimensional array.
var buffer = [ 1, 2, 3, 4, 5, 6 ];
var shape = [ 3, 2 ];
var strides = [ 2, 1 ];
var offset = 0;
var out = descriptor( 'generic', buffer, shape, strides, offset, 'row-major' );
// returns {...}The function accepts the following arguments:
- dtype: data type.
- buffer: data buffer.
- shape: array shape (dimensions).
- strides: array strides which are index offsets specifying how to access along corresponding dimensions.
- offset: index offset specifying the location of the first indexed element in the data buffer.
- order: array order. Must be either
row-major(C-style) orcolumn-major(Fortran-style).
-
The returned object has the following properties:
-
This function is intended as a potential performance optimization. In V8, for example, even if two objects share common properties, if those properties were added in different orders or if one object has additional properties not shared by the other object, then those objects will have different "hidden" classes. If a function is provided many objects having different "shapes", some JavaScript VMs (e.g., V8) will consider the function "megamorphic" and fail to perform various runtime optimizations. Accordingly, the intent of this function is to create an object containing the minimal amount of meta data necessary to interpret a linear data buffer as an n-dimensional array and to ensure that internal functions operating on ndarrays are provided consistent argument "shapes".
var discreteUniform = require( '@stdlib/random-discrete-uniform' );
var getDType = require( '@stdlib/ndarray-dtype' );
var getData = require( '@stdlib/ndarray-data-buffer' );
var getShape = require( '@stdlib/ndarray-shape' );
var getStrides = require( '@stdlib/ndarray-strides' );
var getOffset = require( '@stdlib/ndarray-offset' );
var getOrder = require( '@stdlib/ndarray-order' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var descriptor = require( '@stdlib/ndarray-base-descriptor' );
var x = discreteUniform( [ 3, 3 ], 0, 10, {
'dtype': 'generic'
});
console.log( ndarray2array( x ) );
var obj = descriptor( getDType( x ), getData( x ), getShape( x ), getStrides( x ), getOffset( x ), getOrder( x ) );
console.log( obj );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.
See LICENSE.
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