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Copy the upper triangular part of a matrix
Ato another matrixB.
npm install @stdlib/blas-ext-base-gtriuAlternatively,
- To load the package in a website via a
scripttag without installation and bundlers, use the ES Module available on theesmbranch (see README). - If you are using Deno, visit the
denobranch (see README for usage intructions). - For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the
umdbranch (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.
var gtriu = require( '@stdlib/blas-ext-base-gtriu' );Copies the upper triangular part of a matrix A to another matrix B.
var A = [ 1.0, 2.0, 3.0, 4.0 ];
var B = [ 0.0, 0.0, 0.0, 0.0 ];
gtriu( 'row-major', 2, 2, 0, A, 2, B, 2 );
// B => [ 1.0, 2.0, 0.0, 4.0 ]The function has the following parameters:
- order: storage layout.
- M: number of rows in
A. - N: number of columns in
A. - k: diagonal below which to ignore. A value of
k = 0refers to the main diagonal,k < 0refers to a diagonal below the main diagonal, andk > 0refers to a diagonal above the main diagonal. Accordingly, whenk < 0, the function copies the upper triangle and one or more sub-diagonals (i.e., part of the lower triangle), and, whenk > 0, the function copies only part of the upper triangle. - A: input matrix.
- LDA: stride of the first dimension of
A(a.k.a., leading dimension of the matrixA). - B: output matrix.
- LDB: stride of the first dimension of
B(a.k.a., leading dimension of the matrixB).
Setting the k parameter to a value other than 0 allows including and excluding sub- and super-diagonals, respectively. For example, to copy the upper triangle and the first sub-diagonal,
var A = [ 1.0, 2.0, 3.0, 4.0 ];
var B = [ 0.0, 0.0, 0.0, 0.0 ];
gtriu( 'row-major', 2, 2, -1, A, 2, B, 2 );
// B => [ 1.0, 2.0, 3.0, 4.0 ]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
gtriu( 'row-major', 2, 2, 0, A1, 2, B1, 2 );
// B0 => <Float64Array>[ 0.0, 2.0, 3.0, 0.0, 5.0 ]Copies the upper triangular part of a matrix A to another matrix B using alternative indexing semantics.
var A = [ 1.0, 2.0, 3.0, 4.0 ];
var B = [ 0.0, 0.0, 0.0, 0.0 ];
gtriu.ndarray( 2, 2, 0, A, 2, 1, 0, B, 2, 1, 0 );
// B => [ 1.0, 2.0, 0.0, 4.0 ]The function has the following parameters:
- M: number of rows in
A. - N: number of columns in
A. - k: diagonal below which to ignore.
- A: input matrix.
- sa1: stride of the first dimension of
A. - sa2: stride of the second dimension of
A. - oa: starting index for
A. - B: output matrix.
- 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 A = [ 1.0, 2.0, 3.0, 4.0 ];
var B = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
gtriu.ndarray( 2, 2, 0, A, 2, 1, 0, B, 2, 1, 2 );
// B => [ 0.0, 0.0, 1.0, 2.0, 0.0, 4.0 ]- Both functions support array-like objects having getter and setter accessors for array element access (e.g.,
@stdlib/array-base/accessor). - Elements outside of the copied region are left unchanged.
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 gtriu = require( '@stdlib/blas-ext-base-gtriu' );
var shape = [ 5, 8 ];
var order = 'row-major';
var strides = shape2strides( shape, order );
var N = numel( shape );
var A = uniform( N, -10, 10, {
'dtype': 'generic'
});
console.log( ndarray2array( A, shape, strides, 0, order ) );
var B = uniform( N, -10, 10, {
'dtype': 'generic'
});
console.log( ndarray2array( B, shape, strides, 0, order ) );
gtriu( order, shape[ 0 ], shape[ 1 ], 0, A, strides[ 0 ], B, strides[ 0 ] );
console.log( ndarray2array( B, shape, strides, 0, order ) );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.
See LICENSE.
Copyright © 2016-2026. The Stdlib Authors.