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iladlr

Find the index of the last non-zero row in a matrix A.

Installation

npm install @stdlib/lapack-base-iladlr

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

iladlr( order, M, N, A, LDA )

Returns the index of the last non-zero row in a matrix A.

var Float64Array = require( '@stdlib/array-float64' );

var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 0.0, 0.0 ] );

/*
    A = [
        [ 1.0, 2.0 ],
        [ 3.0, 4.0 ],
        [ 0.0, 0.0 ]
    ]
*/

var out = iladlr( 'row-major', 3, 2, A, 2 );
// returns 1

The function has the following parameters:

• order: storage layout.
• M: number of rows in A.
• N: number of columns in A.
• A: input Float64Array.
• 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 Float64Array = require( '@stdlib/array-float64' );

// Initial array:
var A0 = new Float64Array( [ 9999.0, 1.0, 2.0, 3.0, 4.0, 0.0, 0.0 ] );

// Create an offset view:
var A1 = new Float64Array( A0.buffer, A0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

var out = iladlr( 'row-major', 3, 2, A1, 2 );
// returns 1

iladlr.ndarray( M, N, A, strideA1, strideA2, offsetA )

Returns the index of the last non-zero row in a matrix A using alternative indexing semantics.

var Float64Array = require( '@stdlib/array-float64' );

var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 0.0, 0.0 ] );

/*
    A = [
        [ 1.0, 2.0 ],
        [ 3.0, 4.0 ],
        [ 0.0, 0.0 ]
    ]
*/

var out = iladlr.ndarray( 3, 2, A, 2, 1, 0 );
// returns 1

The function has the following parameters:

• M: number of rows in A.
• N: number of columns in A.
• A: input Float64Array.
• strideA1: stride of the first dimension of A.
• strideA2: stride of the second dimension of A.
• offsetA: 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 Float64Array = require( '@stdlib/array-float64' );

var A = new Float64Array( [ 9999.0, 1.0, 2.0, 3.0, 4.0, 0.0, 0.0 ] );

/*
    A = [
        [ 1.0, 2.0 ],
        [ 3.0, 4.0 ],
        [ 0.0, 0.0 ]
    ]
*/

var out = iladlr.ndarray( 3, 2, A, 2, 1, 1 );
// returns 1

Notes

• This routine is commonly used throughout LAPACK to shrink work domains (e.g., before bulge-chasing, deflation, or when trimming Householder panels), thus ensuring that higher-level routines operate only on numerically relevant sub-matrices.
• iladlr() corresponds to the LAPACK routine iladlr.

Examples

var ndarray2array = require( '@stdlib/ndarray-base-to-array' );
var Float64Array = require( '@stdlib/array-float64' );
var shape2strides = require( '@stdlib/ndarray-base-shape2strides' );
var iladlr = require( '@stdlib/lapack-base-iladlr' );

var shape = [ 3, 3 ];
var order = 'row-major';
var strides = shape2strides( shape, order );

var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 0.0, 0.0, 0.0 ] );
console.log( ndarray2array( A, shape, strides, 0, order ) );

var out = iladlr( order, shape[ 0 ], shape[ 1 ], A, strides[ 0 ] );
console.log( out );

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C APIs

Usage

TODO

TODO

TODO.

TODO

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Examples

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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

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License

See LICENSE.

Copyright

Copyright © 2016-2025. The Stdlib Authors.