Press n or j to go to the next uncovered block, b, p or k for the previous block.
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* @license Apache-2.0
*
* Copyright (c) 2026 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
'use strict';
// MODULES //
var abs = require( '@stdlib/math/base/special/abs' );
// MAIN //
/**
* Computes an `LU` factorization of a general M-by-N matrix `A` using partial pivoting with row interchanges.
*
* @private
* @param {NonNegativeInteger} M - number of rows in `A`
* @param {NonNegativeInteger} N - number of columns in `A`
* @param {Float64Array} A - input matrix
* @param {integer} strideA1 - row stride of `A`
* @param {integer} strideA2 - column stride of `A`
* @param {NonNegativeInteger} offsetA - starting index of `A`
* @param {Int32Array} IPIV - vector of pivot indices
* @param {integer} strideIPIV - stride length for `IPIV`
* @param {NonNegativeInteger} offsetIPIV - starting index of `IPIV`
* @returns {integer} status code
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
* var Int32Array = require( '@stdlib/array/int32' );
*
* var A = new Float64Array( [ 2.0, 1.0, 4.0, 6.0 ] );
* var IPIV = new Int32Array( 2 );
*
* var info = dgetf2( 2, 2, A, 2, 1, 0, IPIV, 1, 0 );
* // info => 0
*/
function dgetf2( M, N, A, strideA1, strideA2, offsetA, IPIV, strideIPIV, offsetIPIV ) { // eslint-disable-line max-len
var maxVal;
var minMN;
var info;
var temp;
var val;
var jp;
var ip;
var r;
var c;
var j;
var o;
if ( M === 0 || N === 0 ) {
return 0;
}
minMN = ( M < N ) ? M : N;
info = 0;
for ( j = 0; j < minMN; j++ ) {
// Find pivot (maximum absolute value in column j from row j to M-1):
maxVal = -1.0;
jp = j;
for ( r = j; r < M; r++ ) {
val = abs( A[ offsetA + ( r * strideA1 ) + ( j * strideA2 ) ] );
if ( val > maxVal ) {
maxVal = val;
jp = r;
}
}
// Store pivot row index in IPIV (using custom indexing/offset/stride for IPIV):
ip = offsetIPIV + ( j * strideIPIV );
IPIV[ ip ] = jp;
// Check for singularity:
temp = A[ offsetA + ( jp * strideA1 ) + ( j * strideA2 ) ];
if ( temp !== 0.0 ) {
// Swap row j and row jp if they are not the same row:
if ( jp !== j ) {
for ( c = 0; c < N; c++ ) {
o = c * strideA2;
val = A[ offsetA + ( j * strideA1 ) + o ];
A[ offsetA + ( j * strideA1 ) + o ] =
A[ offsetA + ( jp * strideA1 ) + o ];
A[ offsetA + ( jp * strideA1 ) + o ] = val;
}
}
// Scale elements below the diagonal in column j:
if ( j < M - 1 ) {
// Divide A[r, j] by A[j, j] for r = j+1 to M-1
temp = A[ offsetA + ( j * strideA1 ) + ( j * strideA2 ) ];
for ( r = j + 1; r < M; r++ ) {
A[ offsetA + ( r * strideA1 ) + ( j * strideA2 ) ] /= temp;
}
}
} else if ( info === 0 ) {
info = j + 1; // 1-based index
}
// Update trailing submatrix (rows j+1 to M-1, columns j+1 to N-1):
if ( j < minMN - 1 ) {
for ( c = j + 1; c < N; c++ ) {
temp = A[ offsetA + ( j * strideA1 ) + ( c * strideA2 ) ];
if ( temp !== 0.0 ) {
for ( r = j + 1; r < M; r++ ) {
A[ offsetA + ( r * strideA1 ) + ( c * strideA2 ) ] -=
A[ offsetA + ( r * strideA1 ) + ( j * strideA2 ) ] *
temp;
}
}
}
}
}
return info;
}
// EXPORTS //
module.exports = dgetf2;
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