@stdlib/lapack-base-dge-trans
v0.1.1
Published
Convert a matrix from row-major layout to column-major layout or vice versa.
Readme
dgetrans
Convert a matrix from row-major layout to column-major layout or vice versa.
Installation
npm install @stdlib/lapack-base-dge-transUsage
var dgetrans = require( '@stdlib/lapack-base-dge-trans' );dgetrans( order, M, N, A, LDA, out, LDO )
Converts a matrix from row-major layout to column-major layout or vice versa.
var Float64Array = require( '@stdlib/array-float64' );
var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
var out = new Float64Array( 6 );
out = dgetrans( 'row-major', 2, 3, A, 3, out, 2 );
// returns <Float64Array>[ 1.0, 4.0, 2.0, 5.0, 3.0, 6.0 ]The function has the following parameters:
- order: storage layout.
- 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 matrixA). - out: output
Float64Array. - LDO: stride of the first dimension of
out(a.k.a., leading dimension of the matrixout).
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( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] );
var out0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] );
// Create offset views...
var A1 = new Float64Array( A0.buffer, A0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var out1 = new Float64Array( out0.buffer, out0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
dgetrans( 'row-major', 2, 2, A1, 2, out1, 2 );
// out0 => <Float64Array>[ 0.0, 1.0, 3.0, 2.0, 4.0 ]dgetrans.ndarray( M, N, A, sa1, sa2, oa, out, so1, so2, oo )
Converts a matrix from row-major layout to column-major layout or vice versa using alternative indexing semantics.
var Float64Array = require( '@stdlib/array-float64' );
var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
var out = new Float64Array( 6 );
out = dgetrans.ndarray( 2, 3, A, 3, 1, 0, out, 2, 1, 0 );
// returns <Float64Array>[ 1.0, 4.0, 2.0, 5.0, 3.0, 6.0 ]The function has the following parameters:
- 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. - out: output
Float64Array. - so1: stride of the first dimension of
out. - so2: stride of the second dimension of
out. - oo: starting index for
out.
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 out = new Float64Array( [ 0.0, 0.0, 11.0, 312.0, 53.0, 412.0 ] );
dgetrans.ndarray( 2, 2, A, 2, 1, 1, out, 2, 1, 2 );
// out => <Float64Array>[ 0.0, 0.0, 1.0, 3.0, 2.0, 4.0 ]Notes
Examples
var ndarray2array = require( '@stdlib/ndarray-base-to-array' );
var shape2strides = require( '@stdlib/ndarray-base-shape2strides' );
var numel = require( '@stdlib/ndarray-base-numel' );
var Float64Array = require( '@stdlib/array-float64' );
var dgetrans = require( '@stdlib/lapack-base-dge-trans' );
var shapeA = [ 2, 3 ];
var shapeOut = [ 3, 2 ];
// Row-major layout...
var order = 'row-major';
var stridesA = shape2strides( shapeA, order );
var stridesOut = shape2strides( shapeOut, order );
var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
console.log( ndarray2array( A, shapeA, stridesA, 0, order ) );
var out = new Float64Array( numel( shapeA ) );
out = dgetrans( order, shapeA[0], shapeA[1], A, stridesA[0], out, stridesOut[0] );
console.log( ndarray2array( out, shapeOut, stridesOut, 0, order ) );
// Column-major layout...
order = 'column-major';
stridesA = shape2strides( shapeA, order );
stridesOut = shape2strides( shapeOut, order );
A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
console.log( ndarray2array( A, shapeA, stridesA, 0, order ) );
out = new Float64Array( numel( shapeA ) );
out = dgetrans( order, shapeA[0], shapeA[1], A, stridesA[1], out, stridesOut[1] );
console.log( ndarray2array( out, shapeOut, stridesOut, 0, order ) );
// Input and output arrays have different layouts...
stridesA = shape2strides( shapeA, 'row-major' );
stridesOut = shape2strides( shapeOut, 'column-major' );
A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
console.log( ndarray2array( A, shapeA, stridesA, 0, 'row-major' ) );
out = new Float64Array( numel( shapeA ) );
out = dgetrans.ndarray( shapeA[0], shapeA[1], A, stridesA[0], stridesA[1], 0, out, stridesOut[0], stridesOut[1], 0 );
console.log( ndarray2array( out, shapeOut, stridesOut, 0, 'column-major' ) );
// Input and output arrays have different layouts...
stridesA = shape2strides( shapeA, 'column-major' );
stridesOut = shape2strides( shapeOut, 'row-major' );
A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
console.log( ndarray2array( A, shapeA, stridesA, 0, 'column-major' ) );
out = new Float64Array( numel( shapeA ) );
out = dgetrans.ndarray( shapeA[0], shapeA[1], A, stridesA[0], stridesA[1], 0, out, stridesOut[0], stridesOut[1], 0 );
console.log( ndarray2array( out, shapeOut, stridesOut, 0, 'row-major' ) );C APIs
Usage
TODOTODO
TODO.
TODOTODO
TODOExamples
TODONotice
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.
