slacpy

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

Usage

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

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

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

var Float32Array = require( '@stdlib/array/float32' );

var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );
var B = new Float32Array( 4 );

slacpy( 'row-major', 'all', 2, 2, A, 2, B, 2 );
// B => <Float32Array>[ 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 Float32Array.
LDA: stride of the first dimension of A (a.k.a., leading dimension of the matrix A).
B: output Float32Array.
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 Float32Array = require( '@stdlib/array/float32' );

// Initial arrays...
var A0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
var B0 = new Float32Array( 5 );

// Create offset views...
var A1 = new Float32Array( A0.buffer, A0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var B1 = new Float32Array( B0.buffer, B0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

slacpy( 'row-major', 'all', 2, 2, A1, 2, B1, 2 );
// B0 => <Float32Array>[ 0.0, 2.0, 3.0, 4.0, 5.0 ]

slacpy.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 Float32Array = require( '@stdlib/array/float32' );

var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );
var B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );

slacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, 0 );
// B => <Float32Array>[ 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 Float32Array.
sa1: stride of the first dimension of A.
sa2: stride of the second dimension of A.
oa: starting index for A.
B: output Float32Array.
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 Float32Array = require( '@stdlib/array/float32' );

var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
var B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

slacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 );
// B => <Float32Array>[ 0.0, 0.0, 2.0, 3.0, 4.0, 5.0 ]

Notes

slacpy() corresponds to the LAPACK routine slacpy.

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 slacpy = require( '@stdlib/lapack/base/slacpy' );

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

var N = numel( shape );

var A = uniform( N, -10, 10, {
    'dtype': 'float32'
});
console.log( ndarray2array( A, shape, strides, 0, order ) );

var B = uniform( N, -10, 10, {
    'dtype': 'float32'
});
console.log( ndarray2array( B, shape, strides, 0, order ) );

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

C APIs

Usage

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Examples

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