About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

ctriu

Copy the upper triangular part of a single-precision complex floating-point matrix A to another matrix B.

Installation

npm install @stdlib/blas-ext-base-ctriu

Alternatively,

• To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
• If you are using Deno, visit the deno branch (see README for usage intructions).
• For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (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.

Usage

var ctriu = require( '@stdlib/blas-ext-base-ctriu' );

ctriu( order, M, N, k, A, LDA, B, LDB )

Copies the upper triangular part of a single-precision complex floating-point matrix A to another matrix B.

var Complex64Array = require( '@stdlib/array-complex64' );

var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
var B = new Complex64Array( 4 );

ctriu( 'row-major', 2, 2, 0, A, 2, B, 2 );
// B => <Complex64Array>[ 1.0, 2.0, 3.0, 4.0, 0.0, 0.0, 7.0, 8.0 ]

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 = 0 refers to the main diagonal, k < 0 refers to a diagonal below the main diagonal, and k > 0 refers to a diagonal above the main diagonal. Accordingly, when k < 0, the function copies the upper triangle and one or more sub-diagonals (i.e., part of the lower triangle), and, when k > 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 matrix A).
• B: output matrix.
• LDB: stride of the first dimension of B (a.k.a., leading dimension of the matrix B).

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 Complex64Array = require( '@stdlib/array-complex64' );

var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
var B = new Complex64Array( 4 );

ctriu( 'row-major', 2, 2, -1, A, 2, B, 2 );
// B => <Complex64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]

Note that indexing is relative to the first index. To introduce an offset, use typed array views.

var Complex64Array = require( '@stdlib/array-complex64' );

// Initial arrays...
var A0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] );
var B0 = new Complex64Array( 5 );

// Create offset views...
var A1 = new Complex64Array( A0.buffer, A0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var B1 = new Complex64Array( B0.buffer, B0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

ctriu( 'row-major', 2, 2, 0, A1, 2, B1, 2 );
// B0 => <Complex64Array>[ 0.0, 0.0, 3.0, 4.0, 5.0, 6.0, 0.0, 0.0, 9.0, 10.0 ]

ctriu.ndarray( M, N, k, A, sa1, sa2, oa, B, sb1, sb2, ob )

Copies the upper triangular part of a single-precision complex floating-point matrix A to another matrix B using alternative indexing semantics.

var Complex64Array = require( '@stdlib/array-complex64' );

var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
var B = new Complex64Array( 4 );

ctriu.ndarray( 2, 2, 0, A, 2, 1, 0, B, 2, 1, 0 );
// B => <Complex64Array>[ 1.0, 2.0, 3.0, 4.0, 0.0, 0.0, 7.0, 8.0 ]

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 Complex64Array = require( '@stdlib/array-complex64' );

var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
var B = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

ctriu.ndarray( 2, 2, 0, A, 2, 1, 0, B, 2, 1, 2 );
// B => <Complex64Array>[ 0.0, 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 0.0, 0.0, 7.0, 8.0 ]

Notes

• Elements outside of the copied region are left unchanged.

Examples

var ndarray2array = require( '@stdlib/ndarray-base-to-array' );
var uniform = require( '@stdlib/random-array-discrete-uniform' );
var Complex64Array = require( '@stdlib/array-complex64' );
var numel = require( '@stdlib/ndarray-base-numel' );
var shape2strides = require( '@stdlib/ndarray-base-shape2strides' );
var ctriu = require( '@stdlib/blas-ext-base-ctriu' );

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

var N = numel( shape );

var opts = {
    'dtype': 'float32'
};
var A = new Complex64Array( uniform( N*2, -10, 10, opts ) );
console.log( ndarray2array( A, shape, strides, 0, order ) );

var B = new Complex64Array( uniform( N*2, -10, 10, opts ) );
console.log( ndarray2array( B, shape, strides, 0, order ) );

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

---

C APIs

Usage

#include "stdlib/blas/ext/base/ctriu.h"

stdlib_strided_ctriu( layout, M, N, k, *A, LDA, *B, LDB )

Copies the upper triangular part of a single-precision complex floating-point matrix A to another matrix B.

#include "stdlib/blas/base/shared.h"
#include "stdlib/complex/float32/ctor.h"

const float A[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };
float B[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f };

stdlib_strided_ctriu( CblasRowMajor, 2, 2, 0, (stdlib_complex64_t *)A, 2, (stdlib_complex64_t *)B, 2 );

The function accepts the following arguments:

• layout: [in] CBLAS_LAYOUT storage layout.
• M: [in] CBLAS_INT number of rows in A.
• N: [in] CBLAS_INT number of columns in A.
• k: [in] CBLAS_INT diagonal below which to ignore.
• A: [in] stdlib_complex64_t* input matrix.
• LDA: [in] CBLAS_INT stride of the first dimension of A (a.k.a., leading dimension of the matrix A).
• B: [out] stdlib_complex64_t* output matrix.
• LDB: [in] CBLAS_INT stride of the first dimension of B (a.k.a., leading dimension of the matrix B).

void API_SUFFIX(stdlib_strided_ctriu)( const CBLAS_LAYOUT layout, const CBLAS_INT M, const CBLAS_INT N, const CBLAS_INT k, const stdlib_complex64_t *A, const CBLAS_INT LDA, stdlib_complex64_t *B, const CBLAS_INT LDB );

stdlib_strided_ctriu_ndarray( M, N, k, *A, sa1, sa2, oa, *B, sb1, sb2, ob )

Copies the upper triangular part of a single-precision complex floating-point matrix A to another matrix B using alternative indexing semantics.

#include "stdlib/blas/base/shared.h"
#include "stdlib/complex/float32/ctor.h"

const float A[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };
float B[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f };

stdlib_strided_ctriu_ndarray( 2, 2, 0, (stdlib_complex64_t *)A, 2, 1, 0, (stdlib_complex64_t *)B, 2, 1, 0 );

The function accepts the following arguments:

• M: [in] CBLAS_INT number of rows in A.
• N: [in] CBLAS_INT number of columns in A.
• k: [in] CBLAS_INT diagonal below which to ignore.
• A: [in] stdlib_complex64_t* input matrix.
• sa1: [in] CBLAS_INT stride of the first dimension of A.
• sa2: [in] CBLAS_INT stride of the second dimension of A.
• oa: [in] CBLAS_INT starting index for A.
• B: [out] stdlib_complex64_t* output matrix.
• sb1: [in] CBLAS_INT stride of the first dimension of B.
• sb2: [in] CBLAS_INT stride of the second dimension of B.
• ob: [in] CBLAS_INT starting index for B.

void API_SUFFIX(stdlib_strided_ctriu_ndarray)( const CBLAS_INT M, const CBLAS_INT N, const CBLAS_INT k, const stdlib_complex64_t *A, const CBLAS_INT strideA1, const CBLAS_INT strideA2, const CBLAS_INT offsetA, stdlib_complex64_t *B, const CBLAS_INT strideB1, const CBLAS_INT strideB2, const CBLAS_INT offsetB );

Examples

#include "stdlib/blas/ext/base/ctriu.h"
#include "stdlib/blas/base/shared.h"
#include "stdlib/complex/float32/ctor.h"
#include <stdio.h>

int main( void ) {
    // Define a 3x3 input matrix stored in row-major order:
    const float A[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f };

    // Define a 3x3 output matrix:
    float B[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f };

    // Specify the number of elements along each dimension of `A`:
    const CBLAS_INT M = 3;
    const CBLAS_INT N = 3;

    // Copy the upper triangular part of `A` to `B`:
    stdlib_strided_ctriu( CblasRowMajor, M, N, 0, (stdlib_complex64_t *)A, N, (stdlib_complex64_t *)B, N );

    // Print the result:
    for ( int i = 0; i < M; i++ ) {
        for ( int j = 0; j < N; j++ ) {
            int idx = ( (i*N) + j ) * 2;
            printf( "B[ %i,%i ] = %f + %fi\n", i, j, B[ idx ], B[ idx+1 ] );
        }
    }

    // Copy the upper triangular part of `A`, including the first sub-diagonal, to `B` using alternative indexing semantics:
    stdlib_strided_ctriu_ndarray( M, N, -1, (stdlib_complex64_t *)A, N, 1, 0, (stdlib_complex64_t *)B, N, 1, 0 );

    // Print the result:
    for ( int i = 0; i < M; i++ ) {
        for ( int j = 0; j < N; j++ ) {
            int idx = ( (i*N) + j ) * 2;
            printf( "B[ %i,%i ] = %f + %fi\n", i, j, B[ idx ], B[ idx+1 ] );
        }
    }
}

---

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.

Community

---

License

See LICENSE.

Copyright

Copyright © 2016-2026. The Stdlib Authors.