Copy all or part of a matrix A to another matrix B.
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> Copy all or part of a matrix A to another matrix B.
``bash`
npm install @stdlib/lapack-base-dlacpy
`javascript`
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.
`javascript
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 =>
`
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.A
- M: number of rows in .A
- N: number of columns in .Float64Array
- A: input [][mdn-float64array].A
- LDA: stride of the first dimension of (a.k.a., leading dimension of the matrix A).Float64Array
- B: output [][mdn-float64array].B
- LDB: stride of the first dimension of (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][mdn-typed-array] views.
`javascript
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 =>
`
#### 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.
`javascript
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 =>
`
The function has the following parameters:
- uplo: specifies whether to copy the upper or lower triangular/trapezoidal part of a matrix A.A
- M: number of rows in .A
- N: number of columns in .Float64Array
- A: input [][mdn-float64array].A
- sa1: stride of the first dimension of .A
- sa2: stride of the second dimension of .A
- oa: starting index for .Float64Array
- B: output [][mdn-float64array].B
- sb1: stride of the first dimension of .B
- sb2: stride of the second dimension of .B
- ob: starting index for .
While [typed array][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example,
`javascript
var Float64Array = require( '@stdlib/array-float64' );
var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
var B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
dlacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 );
// B =>
`
- dlacpy() corresponds to the [LAPACK][lapack] routine [dlacpy][lapack-dlacpy].
`javascript
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`
#include "stdlib/lapack/base/dlacpy.h"
#### c_dlacpy( layout, uplo, M, N, \A, LDA, \B, LDB )
Copies all or part of a matrix A to another matrix B.
`c
#include "stdlib/lapack/base/shared.h"
const double A[] = { 1.0, 2.0, 3.0, 4.0 };
double B[] = { 0.0, 0.0, 0.0, 0.0 };
c_dlacpy( LAPACK_ROW_MAJOR, LAPACK_UPPER_TRIANGLE, 2, 2, A, 2, B, 2 );
`
The function accepts the following arguments:
- order: [in] LAPACK_LAYOUT storage layout.[in] int
- uplo: specifies whether to copy the upper or lower triangular/trapezoidal part of a matrix A.[in] LAPACK_INT
- M: number of rows in A.[in] LAPACK_INT
- N: number of columns in A.[in] double*
- A: input matrix.[in] LAPACK_INT
- LDA: stride of the first dimension of A (a.k.a., leading dimension of the matrix A).[out] double*
- B: output matrix.[in] LAPACK_INT
- LDB: stride of the first dimension of B (a.k.a., leading dimension of the matrix B).
`c`
LAPACK_INT c_dlacpy( const LAPACK_LAYOUT layout, const int uplo, const LAPACK_INT M, const LAPACK_INT N, const double A, const LAPACK_INT LDA, double B, const LAPACK_INT LDB );
#### c_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.
`c
#include "stdlib/lapack/base/shared.h"
const double A[] = { 1.0, 2.0, 3.0, 4.0 };
double B[] = { 0.0, 0.0, 0.0, 0.0 };
c_dlacpy_ndarray( LAPACK_UPPER_TRIANGLE, 2, 2, A, 2, 1, 0, B, 2, 1, 0 );
`
The function accepts the following arguments:
- uplo: [in] int specifies whether to copy the upper or lower triangular/trapezoidal part of a matrix A.[in] LAPACK_INT
- M: number of rows in A.[in] LAPACK_INT
- N: number of columns in A.[in] double*
- A: input matrix.[in] LAPACK_INT
- sa1: stride of the first dimension of A.[in] LAPACK_INT
- sa2: stride of the second dimension of A.[in] LAPACK_INT
- oa: starting index for A.[out] double*
- B: output matrix.[in] LAPACK_INT
- sb1: stride of the first dimension of B.[in] LAPACK_INT
- sb2: stride of the second dimension of B.[in] LAPACK_INT
- ob: starting index for B.
`c`
LAPACK_INT c_dlacpy_ndarray( const int uplo, const LAPACK_INT M, const LAPACK_INT N, const double A, const LAPACK_INT strideA1, const LAPACK_INT strideA2, const LAPACK_INT offsetA, double B, const LAPACK_INT strideB1, const LAPACK_INT strideB2, const LAPACK_INT offsetB );
`c
#include "stdlib/lapack/base/dlacpy.h"
#include "stdlib/lapack/base/shared.h"
#include
int main( void ) {
// Define a 3x3 input matrix stored in row-major order:
const double A[ 3*3 ] = {
1.0, 2.0, 3.0,
4.0, 5.0, 6.0,
7.0, 8.0, 9.0
};
// Define a 3x3 output matrix:
double B[ 3*3 ] = {
0.0, 0.0, 0.0,
0.0, 0.0, 0.0,
0.0, 0.0, 0.0
};
// Specify the number of elements along each dimension of A:
const int M = 3;
const int N = 3;
// Copy elements from the upper triangle of A to B:
c_dlacpy( LAPACK_ROW_MAJOR, LAPACK_UPPER_TRIANGLE, M, N, A, N, B, N );
// Print the result:
for ( int i = 0; i < M; i++ ) {
for ( int j = 0; j < N; j++ ) {
printf( "B[ %i, %i ] = %lf\n", i, j, B[ (i*N)+j ] );
}
}
// Copy elements from the lower triangle of A to B using alternative indexing semantics:
c_dlacpy_ndarray( LAPACK_LOWER_TRIANGLE, M, N, A, N, 1, 0, B, N, 1, 0 );
// Print the result:
for ( int i = 0; i < M; i++ ) {
for ( int j = 0; j < N; j++ ) {
printf( "B[ %i, %i ] = %lf\n", i, j, B[ (i*N)+j ] );
}
}
}
`
*
This package is part of [stdlib][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][stdlib], see the main project [repository][stdlib].
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[mdn-float64array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Float64Array
[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray