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feat: add lapack/base/dorg2r
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‎lib/node_modules/@stdlib/lapack/base/dorg2r/lib/base.js

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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2024 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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// MODULES //
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var dscal = require( '@stdlib/blas/base/dscal' ).ndarray;
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var dlarf1f = require( './dlarf1f.js' );
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// MAIN //
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/**
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* Generates an M-by-N real matrix Q with orthonormal columns. The matrix Q is defined as the first N columns of a product of K elementary reflectors of order M. `Q = H(1) H(2) . . . H(K)` as returned by `dgeqrf`.
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*
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* @private
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* @param {PositiveInteger} M - number of rows in matrix `A`
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* @param {PositiveInteger} N - number of columns in matrix `A`
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* @param {NonNegativeInteger} K - number of elementary reflectors whose product defines the matrix Q
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* @param {Float64Array} A - input matrix (overwritten by Householder vectors from `dgeqrf`
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* @param {integer} strideA1 - stride of the first dimension of `A`
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* @param {integer} strideA2 - stride of the second dimension of `A`
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* @param {NonNegativeInteger} offsetA - index offset for `A`
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* @param {Float64Array} tau - vector of K scalar factors of the elementary reflectors
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* @param {integer} strideTau - stride length for `tau`
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* @param {NonNegativeInteger} offsetTau - index offset for `tau`
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* @param {Float64Array} work - workspace array
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* @param {integer} strideWork - stride length for `work`
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* @param {NonNegativeInteger} offsetWork - index offset for `work`
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*
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* @example
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* var Float64Array = require( '@stdlib/array/float64' );
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*
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* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
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* var tau = new Float64Array( [ 0.0, 0.0 ] );
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* var work = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
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*
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* dorg2r( 3, 2, 2, A, 1, 3, 0, tau, 1, 0, work, 1, 0 );
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* // A => <Float64Array>[ 1.0, 0.0, 0.0, 0.0, 1.0, 0.0 ]
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*/
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function dorg2r( M, N, K, A, strideA1, strideA2, offsetA, tau, strideTau, offsetTau, work, strideWork, offsetWork ) { // eslint-disable-line max-len, max-params
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var i;
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var j;
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var l;
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if ( N <= 0 ) {
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return;
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}
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// Initialize columns k+1:n to columns of the unit matrix
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for ( j = K; j < N; j++ ) {
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for ( l = 0; l < M; l++ ) {
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A[ offsetA + (l*strideA1) + (j*strideA2) ] = 0.0;
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}
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A[ offsetA + (j*strideA1) + (j*strideA2) ] = 1.0;
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}
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// Apply H(i) to A(i:m,i:n) from the left
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for ( i = K-1; i >= 0; i-- ) {
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if ( i < N ) {
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// Apply H(i) to A(i:m,i+1:n) from the left
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dlarf1f( 'left', M-i, N-i-1, A, strideA1, offsetA + (i*strideA1) + (i*strideA2), tau[ offsetTau + (i*strideTau) ], A, strideA1, strideA2, offsetA + (i*strideA1) + ((i+1)*strideA2), work, strideWork, offsetWork );
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}
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if ( i < M ) {
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// Scale A(i+1:m,i) by -tau(i)
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dscal( M-i-1, -tau[ offsetTau + (i*strideTau) ], A, strideA1, offsetA + ((i+1)*strideA1) + (i*strideA2) ); // eslint-disable-line max-len
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}
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// Set A(i,i) = 1 - tau(i)
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A[ offsetA + (i*strideA1) + (i*strideA2) ] = 1.0 - tau[ offsetTau + (i*strideTau) ]; // eslint-disable-line max-len
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// Set A(0:i-1,i) to zero
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for ( l = 0; l < i; l++ ) {
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A[ offsetA + (l*strideA1) + (i*strideA2) ] = 0.0;
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}
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}
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}
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// EXPORTS //
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module.exports = dorg2r;

‎lib/node_modules/@stdlib/lapack/base/dorg2r/lib/dlarf1f.js

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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2025 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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/* eslint-disable max-len */
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// MODULES //
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var iladlc = require( '@stdlib/lapack/base/iladlc' ).ndarray;
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var iladlr = require( '@stdlib/lapack/base/iladlr' ).ndarray;
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var dgemv = require( '@stdlib/blas/base/dgemv' ).ndarray;
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var dger = require( '@stdlib/blas/base/dger' ).ndarray;
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var daxpy = require( '@stdlib/blas/base/daxpy' ).ndarray;
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var dscal = require( '@stdlib/blas/base/dscal' ).ndarray;
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// MAIN //
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/**
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* Applies a real elementary reflector `H = I - tau * v * v ^ T` to a real M by N matrix `C`.
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*
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* ## Notes
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*
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* - `work` should have `N` indexed elements if side = `left` and `M` indexed elements if side = `right`.
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* - `V` should have `1 + (M-1) * abs(strideV)` indexed elements if side = `left` and `1 + (N-1) * abs(strideV)` indexed elements if side = `right`.
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* - `C` is overwritten by `H * C` if side = `left` and `C * H` if side = `right`.
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*
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* @private
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* @param {string} side - specifies the side of multiplication with `C`. Use `left` to form `H * C` and `right` to from `C * H`.
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* @param {NonNegativeInteger} M - number of rows in `C`
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* @param {NonNegativeInteger} N - number of columns in `C`
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* @param {Float64Array} V - the vector `v` in the representation of `H`
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* @param {integer} strideV - stride length for `V`
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* @param {NonNegativeInteger} offsetV - starting index for `V`
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* @param {number} tau - the value of `tau` in representation of `H`
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* @param {Float64Array} C - input matrix
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* @param {integer} strideC1 - stride of the first dimension of `C`
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* @param {integer} strideC2 - stride of the second dimension of `C`
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* @param {NonNegativeInteger} offsetC - starting index for `C`
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* @param {Float64Array} work - workspace array
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* @param {integer} strideWork - stride length for `work`
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* @param {NonNegativeInteger} offsetWork - starting index for `work`
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* @returns {Float64Array} `C * H` or `H * C`
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*
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* @example
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* var Float64Array = require( '@stdlib/array/float64' );
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*
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* var C = new Float64Array( [ 1.0, 5.0, 9.0, 2.0, 6.0, 10.0, 3.0, 7.0, 11.0, 4.0, 8.0, 12.0 ] );
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* var V = new Float64Array( [ 0.5, 0.5, 0.5, 0.5 ] );
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* var work = new Float64Array( 3 );
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*
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* var out = dlarf1f( 'left', 4, 3, V, 1, 0, 1.0, C, 3, 1, 0, work, 1, 0 );
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* // returns <Float64Array>[ -4.5, -10.5, -16.5, -0.75, -1.75, -2.75, 0.25, -0.75, -1.75, 1.25, 0.25, -0.75 ]
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*/
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function dlarf1f( side, M, N, V, strideV, offsetV, tau, C, strideC1, strideC2, offsetC, work, strideWork, offsetWork ) { // eslint-disable-line max-params
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var lastv;
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var lastc;
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var i;
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lastv = 1;
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lastc = 0;
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if ( tau !== 0.0 ) {
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if ( side === 'left' ) {
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lastv = M;
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} else {
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lastv = N;
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}
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// i points to the last element in V
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i = offsetV + ( ( lastv - 1 ) * strideV );
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// Move i to the last non-zero element in V
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while ( lastv > 0 && V[ i ] === 0.0 ) {
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lastv -= 1;
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i -= strideV;
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}
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if ( side === 'left' ) {
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lastc = iladlc( lastv + 1, N, C, strideC1, strideC2, offsetC ) + 1; // to account for the difference between zero-based and one-based indexing
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} else {
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lastc = iladlr( M, lastv + 1, C, strideC1, strideC2, offsetC ) + 1; // to account for the difference between zero-based and one-based indexing
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}
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// lastc is zero if a matrix is filled with zeros
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}
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if ( lastc === 0 ) {
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// Returns C unchanged if tau is zero or all elements in C are zero
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return C;
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}
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if ( side === 'left' ) {
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if ( lastv === 0 ) {
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dscal( lastc, 1.0 - tau, C, strideC2, offsetC ); // scale the first row
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} else {
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dgemv( 'transpose', lastv-1, lastc, 1.0, C, strideC1, strideC2, offsetC + strideC1, V, strideV, offsetV + strideV, 0.0, work, strideWork, offsetWork ); // C( 1, 0 ) is accessed here
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daxpy( lastc, 1.0, C, strideC2, offsetC, work, strideWork, offsetWork ); // operates on the first row of C
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daxpy( lastc, -tau, work, strideWork, offsetWork, C, strideC2, offsetC ); // operates on the first row of C
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dger( lastv-1, lastc, -tau, V, strideV, offsetV + strideV, work, strideWork, offsetWork, C, strideC1, strideC2, offsetC + strideC1 ); // C( 1, 0 ) is accessed here
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}
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} else if ( lastv === 0 ) {
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dscal( lastc, 1.0 - tau, C, strideC1, offsetC ); // scale the first column
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} else {
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dgemv( 'no-transpose', lastc, lastv-1, 1.0, C, strideC1, strideC2, offsetC + strideC2, V, strideV, offsetV + strideV, 0.0, work, strideWork, offsetWork ); // C( 0, 1 ) is accessed here
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daxpy( lastc, 1.0, C, strideC1, offsetC, work, strideWork, offsetWork ); // operates on the first column of C
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daxpy( lastc, -tau, work, strideWork, offsetWork, C, strideC1, offsetC ); // operates on the first column of C
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dger( lastc, lastv-1, -tau, work, strideWork, offsetWork, V, strideV, offsetV + strideV, C, strideC1, strideC2, offsetC + strideC2 ); // C( 0, 1 ) is accessed here
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}
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return C;
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}
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// EXPORTS //
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module.exports = dlarf1f;

‎lib/node_modules/@stdlib/lapack/base/dorg2r/lib/dorg2r.js

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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2025 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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// MODULES //
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var isLayout = require( '@stdlib/blas/base/assert/is-layout' );
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var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major-string' );
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var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string' );
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var max = require( '@stdlib/math/base/special/max' );
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var format = require( '@stdlib/string/format' );
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var base = require( './base.js' );
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// MAIN //
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/**
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* Generates an M-by-N real matrix Q with orthonormal columns. The matrix Q is defined as the first N columns of a product of K elementary reflectors of order M. `Q = H(1) H(2) . . . H(K)` as returned by `dgeqrf`.
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*
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* @param {string} order - storage layout
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* @param {PositiveInteger} M - number of rows in matrix `A`
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* @param {PositiveInteger} N - number of columns in matrix `A`
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* @param {NonNegativeInteger} K - number of elementary reflectors whose product defines the matrix Q
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* @param {Float64Array} A - input matrix (overwritten by Householder vectors from `dgeqrf`
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* @param {PositiveInteger} LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`)
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* @param {Float64Array} tau - vector of K scalar factors of the elementary reflectors
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* @param {Float64Array} work - workspace array
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* @throws {TypeError} first argument must be a valid order
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* @throws {RangeError} sixth argument must be greater than or equal to max(1,M)
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* @returns {Float64Array} matrix `A` overwritten with the orthogonal matrix Q
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*
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* @example
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* var Float64Array = require( '@stdlib/array/float64' );
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*
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* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
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* var tau = new Float64Array( [ 0.0, 0.0 ] );
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* var work = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
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*
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* dorg2r( 'column-major', 3, 2, 2, A, 3, tau, work );
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* // A => <Float64Array>[ 1.0, 0.0, 0.0, 0.0, 1.0, 0.0 ]
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*/
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function dorg2r( order, M, N, K, A, LDA, tau, work ) {
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var sa1;
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var sa2;
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if ( !isLayout( order ) ) {
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throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) );
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}
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if ( isRowMajor( order ) && LDA < max( 1, M ) ) {
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throw new RangeError( format( 'invalid argument. Sixth argument must be greater than or equal to max(1,%d). Value: `%d`.', M, LDA ) );
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}
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if ( isColumnMajor( order ) ) {
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sa1 = 1;
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sa2 = LDA;
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} else { // order === 'row-major'
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sa1 = LDA;
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sa2 = 1;
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}
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return base( M, N, K, A, sa1, sa2, 0, tau, 1, 0, work, 1, 0 );
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}
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// EXPORTS //
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module.exports = dorg2r;

‎lib/node_modules/@stdlib/lapack/base/dorg2r/lib/index.js

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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2025 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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/**
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* Generate an M-by-N real matrix Q with orthonormal columns. The matrix Q is defined as the first N columns of a product of K elementary reflectors of order M. `Q = H(1) H(2) . . . H(K)` as returned by `dgeqrf`.
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*
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* @module @stdlib/lapack/base/dorg2r
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*
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* @example
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* var Float64Array = require( '@stdlib/array/float64' );
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* var dorg2r = require( '@stdlib/lapack/base/dorg2r' );
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*
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* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
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* var tau = new Float64Array( [ 0.0, 0.0 ] );
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* var work = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
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*
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* dorg2r( 'column-major', 3, 2, 2, A, 3, tau, work );
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* // A => <Float64Array>[ 1.0, 0.0, 0.0, 0.0, 1.0, 0.0 ]
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*
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* @example
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* var Float64Array = require( '@stdlib/array/float64' );
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* var dorg2r = require( '@stdlib/lapack/base/dorg2r' );
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*
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* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
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* var tau = new Float64Array( [ 0.0, 0.0 ] );
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* var work = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
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*
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* dorg2r.ndarray( 3, 2, 2, A, 1, 3, 0, tau, 1, 0, work, 1, 0 );
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* // A => <Float64Array>[ 1.0, 0.0, 0.0, 0.0, 1.0, 0.0 ]
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*/
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// MODULES //
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var join = require( 'path' ).join;
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var tryRequire = require( '@stdlib/utils/try-require' );
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var isError = require( '@stdlib/assert/is-error' );
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var main = require( './main.js' );
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// MAIN //
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var dorg2r;
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var tmp = tryRequire( join( __dirname, './native.js' ) );
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if ( isError( tmp ) ) {
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dorg2r = main;
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} else {
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dorg2r = tmp;
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}
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// EXPORTS //
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module.exports = dorg2r;

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