Skip to content

Latest commit

 

History

History
376 lines (235 loc) · 11.8 KB

README.md

File metadata and controls

376 lines (235 loc) · 11.8 KB
About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

clacpy

NPM version Build Status Coverage Status

Copy all or part of a matrix A to another matrix B.

Installation

npm install @stdlib/lapack-base-clacpy

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 clacpy = require( '@stdlib/lapack-base-clacpy' );

clacpy( order, uplo, M, N, A, LDA, B, LDB )

Copies all or part of a matrix A to another matrix B.

var Complex64Array = require( '@stdlib/array-complex64' );
var reinterpret = require( '@stdlib/strided-base-reinterpret-complex64' );

var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
var B = new Complex64Array( 4 );

clacpy( 'row-major', 'all', 2, 2, A, 2, B, 2 );

var viewB = reinterpret( B, 0 );
// returns <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]

The function has the following parameters:

  • order: storage layout.
  • uplo: specifies whether to copy the upper or lower triangular/trapezoidal part of a matrix A.
  • M: number of rows in A.
  • N: number of columns in A.
  • A: input Complex64Array.
  • LDA: stride of the first dimension of A (a.k.a., leading dimension of the matrix A).
  • B: output Complex64Array.
  • LDB: stride of the first dimension of B (a.k.a., leading dimension of the matrix B).

Note that indexing is relative to the first index. To introduce an offset, use typed array views.

var Complex64Array = require( '@stdlib/array-complex64' );
var reinterpret = require( '@stdlib/strided-base-reinterpret-complex64' );

// Initial arrays...
var A0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] );
var B0 = new Complex64Array( 5 );

// Create offset views...
var A1 = new Complex64Array( A0.buffer, A0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var B1 = new Complex64Array( B0.buffer, B0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

clacpy( 'row-major', 'all', 2, 2, A1, 2, B1, 2 );

var viewB = reinterpret( B0, 0 );
// returns <Float32Array>[ 0.0, 0.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ]

clacpy.ndarray( uplo, M, N, A, sa1, sa2, oa, B, sb1, sb2, ob )

Copies all or part of a matrix A to another matrix B using alternative indexing semantics.

var Complex64Array = require( '@stdlib/array-complex64' );
var reinterpret = require( '@stdlib/strided-base-reinterpret-complex64' );

var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
var B = new Complex64Array( 4 );

clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, 0 );

var viewB = reinterpret( B, 0 );
// returns <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]

The function has the following parameters:

  • uplo: specifies whether to copy the upper or lower triangular/trapezoidal part of a matrix A.
  • M: number of rows in A.
  • N: number of columns in A.
  • A: input Complex64Array.
  • sa1: stride of the first dimension of A.
  • sa2: stride of the second dimension of A.
  • oa: starting index for A.
  • B: output Complex64Array.
  • sb1: stride of the first dimension of B.
  • sb2: stride of the second dimension of B.
  • ob: starting index for B.

While typed array views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example,

var Complex64Array = require( '@stdlib/array-complex64' );
var reinterpret = require( '@stdlib/strided-base-reinterpret-complex64' );

var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] );
var B = new Complex64Array( 6 );

clacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 );

var viewB = reinterpret( B, 0 );
// returns <Float32Array>[ 0.0, 0.0, 0.0, 0.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ]

Notes

Examples

var Complex64Array = require( '@stdlib/array-complex64' );
var ndarray2array = require( '@stdlib/ndarray-base-to-array' );
var uniform = require( '@stdlib/random-array-discrete-uniform' );
var numel = require( '@stdlib/ndarray-base-numel' );
var shape2strides = require( '@stdlib/ndarray-base-shape2strides' );
var clacpy = require( '@stdlib/lapack-base-clacpy' );

var shape = [ 5, 8 ];
var order = 'row-major';
var strides = shape2strides( shape, order );

var N = numel( shape );

var A = new Complex64Array( uniform( 2*N, -10, 10, {
    'dtype': 'generic'
}));
console.log( ndarray2array( A, shape, strides, 0, order ) );

var B = new Complex64Array( uniform( 2*N, -10, 10, {
    'dtype': 'generic'
}));
console.log( ndarray2array( B, shape, strides, 0, order ) );

clacpy( order, 'all', shape[ 0 ], shape[ 1 ], A, strides[ 0 ], B, strides[ 0 ] );
console.log( ndarray2array( B, shape, strides, 0, order ) );

C APIs

Usage

TODO

TODO

TODO.

TODO

TODO

TODO

Examples

TODO

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

Chat

License

See LICENSE.

Copyright

Copyright © 2016-2025. The Stdlib Authors.