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@stdlib/lapack-base-dlacpy

v0.1.0

Published

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

Downloads

16

Readme

dlacpy

NPM version Build Status Coverage Status

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

Usage

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

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

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

var Float64Array = require( '@stdlib/array-float64' );

var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
var B = new Float64Array( 4 );

dlacpy( 'row-major', 'all', 2, 2, A, 2, B, 2 );
// B => <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]

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 Float64Array.
  • LDA: stride of the first dimension of A (a.k.a., leading dimension of the matrix A).
  • B: output Float64Array.
  • 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 Float64Array = require( '@stdlib/array-float64' );

// Initial arrays...
var A0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
var B0 = new Float64Array( 5 );

// Create offset views...
var A1 = new Float64Array( A0.buffer, A0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var B1 = new Float64Array( B0.buffer, B0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

dlacpy( 'row-major', 'all', 2, 2, A1, 2, B1, 2 );
// B0 => <Float64Array>[ 0.0, 2.0, 3.0, 4.0, 5.0 ]

dlacpy.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 Float64Array = require( '@stdlib/array-float64' );

var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
var B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );

dlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, 0 );
// B => <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]

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 Float64Array.
  • sa1: stride of the first dimension of A.
  • sa2: stride of the second dimension of A.
  • oa: starting index for A.
  • B: output Float64Array.
  • 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 Float64Array = require( '@stdlib/array-float64' );

var A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] );
var B = new Float64Array( [ 0.0, 0.0, 11.0, 312.0, 53.0, 412.0 ] );

dlacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 );
// B => <Float64Array>[ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ]

Notes

Examples

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

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

var N = numel( shape );

var A = uniform( N, -10, 10, {
    'dtype': 'float64'
});
console.log( ndarray2array( A, shape, strides, 0, order ) );

var B = uniform( N, -10, 10, {
    'dtype': 'float64'
});
console.log( ndarray2array( B, shape, strides, 0, order ) );

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

C APIs

Installation

npm install @stdlib/lapack-base-dlacpy

Usage

TODO

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TODO

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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.

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License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.