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Set the off-diagonal elements and the diagonal elements of a single-precision complex floating-point matrix to specified values.

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stdlib-js/lapack-base-claset

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claset

NPM version Build Status Coverage Status

Set the off-diagonal elements and the diagonal elements of a single-precision complex floating-point matrix to specified values.

Installation

npm install @stdlib/lapack-base-claset

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 claset = require( '@stdlib/lapack-base-claset' );

claset( order, uplo, M, N, alpha, beta, A, LDA )

Sets the off-diagonal elements and the diagonal elements of a single-precision complex floating-point matrix to specified values.

var Complex64Array = require( '@stdlib/array-complex64' );
var Complex64 = require( '@stdlib/complex-float32-ctor' );
var realf = require( '@stdlib/complex-float32-real' );
var imagf = require( '@stdlib/complex-float32-imag' );

var A = new Complex64Array( 4 );

var alpha = new Complex64( 1.0, 2.0 );
var beta = new Complex64( 3.0, 4.0 );

claset( 'row-major', 'all', 2, 2, alpha, beta, A, 2 );

var z = A.get( 0 );
// returns <Complex64>

var re = realf( z );
// returns 3.0

var im = imagf( z );
// returns 4.0

z = A.get( 1 );
// returns <Complex64>

re = realf( z );
// returns 1.0

im = imagf( z );
// returns 2.0

The function has the following parameters:

  • order: storage layout.
  • uplo: specifies whether to set the upper or lower triangular/trapezoidal part of a matrix A.
  • M: number of rows in A.
  • N: number of columns in A.
  • alpha: value assigned to off-diagonal elements.
  • beta: value assigned to diagonal elements.
  • A: input Complex64Array.
  • LDA: stride of the first dimension of A (a.k.a., leading dimension of the matrix A).

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

var Complex64Array = require( '@stdlib/array-complex64' );
var Complex64 = require( '@stdlib/complex-float32-ctor' );
var realf = require( '@stdlib/complex-float32-real' );
var imagf = require( '@stdlib/complex-float32-imag' );

// Initial array:
var A0 = new Complex64Array( 5 );

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

var alpha = new Complex64( 1.0, 2.0 );
var beta = new Complex64( 3.0, 4.0 );

claset( 'row-major', 'all', 2, 2, alpha, beta, A1, 2 );

var z = A0.get( 1 );
// returns <Complex64>

var re = realf( z );
// returns 3.0

var im = imagf( z );
// returns 4.0

claset.ndarray( uplo, M, N, alpha, beta, A, sa1, sa2, oa )

Sets the off-diagonal elements and the diagonal elements of a single-precision complex floating-point matrix to specified values using alternative indexing semantics.

var Complex64Array = require( '@stdlib/array-complex64' );
var Complex64 = require( '@stdlib/complex-float32-ctor' );
var realf = require( '@stdlib/complex-float32-real' );
var imagf = require( '@stdlib/complex-float32-imag' );

var A = new Complex64Array( 4 );

var alpha = new Complex64( 1.0, 2.0 );
var beta = new Complex64( 3.0, 4.0 );

claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, 0 );

var z = A.get( 0 );
// returns <Complex64>

var re = realf( z );
// returns 3.0

var im = imagf( z );
// returns 4.0

z = A.get( 1 );
// returns <Complex64>

re = realf( z );
// returns 1.0

im = imagf( z );
// returns 2.0

The function has the following parameters:

  • uplo: specifies whether to set the upper or lower triangular/trapezoidal part of a matrix A.
  • M: number of rows in A.
  • N: number of columns in A.
  • alpha: value assigned to off-diagonal elements.
  • beta: value assigned to diagonal elements.
  • A: input Complex64Array.
  • sa1: stride of the first dimension of A.
  • sa2: stride of the second dimension of A.
  • oa: starting index for A.

While typed array views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example,

var Complex64Array = require( '@stdlib/array-complex64' );
var Complex64 = require( '@stdlib/complex-float32-ctor' );
var realf = require( '@stdlib/complex-float32-real' );
var imagf = require( '@stdlib/complex-float32-imag' );

var A = new Complex64Array( 5 );

var alpha = new Complex64( 1.0, 2.0 );
var beta = new Complex64( 3.0, 4.0 );

claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, 1 );

var z = A.get( 0 );
// returns <Complex64>

var re = realf( z );
// returns 0.0

var im = imagf( z );
// returns 0.0

z = A.get( 1 );
// returns <Complex64>

re = realf( z );
// returns 3.0

im = imagf( z );
// returns 4.0

Notes

Examples

var Complex64Array = require( '@stdlib/array-complex64' );
var Complex64 = require( '@stdlib/complex-float32-ctor' );
var ndarray2array = require( '@stdlib/ndarray-base-to-array' );
var numel = require( '@stdlib/ndarray-base-numel' );
var shape2strides = require( '@stdlib/ndarray-base-shape2strides' );
var claset = require( '@stdlib/lapack-base-claset' );

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

var N = numel( shape );

var A = new Complex64Array( N );
console.log( ndarray2array( A, shape, strides, 0, order ) );

var alpha = new Complex64( 1.0, 2.0 );
var beta = new Complex64( 3.0, 4.0 );

claset( order, 'all', shape[ 0 ], shape[ 1 ], alpha, beta, A, strides[ 0 ] );
console.log( ndarray2array( A, shape, strides, 0, order ) );

C APIs

Usage

TODO

TODO

TODO.

TODO

TODO

TODO

Examples

TODO

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.

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License

See LICENSE.

Copyright

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