@stdlib/lapack-base-iladlr
v0.1.1
Published
LAPACK routine to find the index of the last non-zero row in an input matrix.
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iladlr
Find the index of the last non-zero row in a matrix
A.
Installation
npm install @stdlib/lapack-base-iladlrUsage
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 1The 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 matrixA).
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 1iladlr.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 1The 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 1Notes
- 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 routineiladlr.
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 );C APIs
Usage
TODOTODO
TODO.
TODOTODO
TODOExamples
TODONotice
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
Copyright © 2016-2026. The Stdlib Authors.
