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oj! Algorithms - ojAlgo - is Open Source Java code that has to do with mathematics, linear algebra and optimisation.
/*
* Copyright 1997-2022 Optimatika
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
package org.ojalgo.array.operation;
import org.ojalgo.scalar.Scalar;
/**
* [A] -= ([a][b]c+[b][a]c)
* [A] is assumed to be hermitian (square symmetric) [A] = [A]C.
* C == conjugate transpose
*
* @author apete
*/
public final class HermitianRank2Update implements ArrayOperation {
public static int THRESHOLD = 256;
// public static void invoke(final ComplexNumber[] data, final int firstColumn, final int columnLimit, final ComplexNumber[] vector1,
// final ComplexNumber[] vector2) {
//
// final int structure = vector1.length;
//
// ComplexNumber tmpVal1j;
// ComplexNumber tmpVal2j;
//
// int tmpIndex;
// for (int j = firstColumn; j < columnLimit; j++) {
//
// tmpVal1j = vector1[j].conjugate();
// tmpVal2j = vector2[j].conjugate();
//
// tmpIndex = j + (j * structure);
// for (int i = j; i < structure; i++) {
// data[tmpIndex] = data[tmpIndex].subtract(vector2[i].multiply(tmpVal1j).add(vector1[i].multiply(tmpVal2j)));
// tmpIndex++;
// }
// }
// }
public static void invoke(final double[] data, final int firstColumn, final int columnLimit, final double[] vector1, final double[] vector2) {
final int structure = vector1.length;
double tmpVal1j;
double tmpVal2j;
int tmpIndex;
for (int j = firstColumn; j < columnLimit; j++) {
tmpVal1j = vector1[j];
tmpVal2j = vector2[j];
tmpIndex = j + j * structure;
for (int i = j; i < structure; i++) {
data[tmpIndex++] -= vector2[i] * tmpVal1j + vector1[i] * tmpVal2j;
}
}
}
public static > void invoke(final N[] data, final int firstColumn, final int columnLimit, final N[] vector1, final N[] vector2) {
final int structure = vector1.length;
Scalar tmpVal1j;
Scalar tmpVal2j;
int tmpIndex;
for (int j = firstColumn; j < columnLimit; j++) {
tmpVal1j = vector1[j].conjugate();
tmpVal2j = vector2[j].conjugate();
tmpIndex = j + j * structure;
for (int i = j; i < structure; i++) {
data[tmpIndex] = data[tmpIndex].subtract(vector2[i].multiply(tmpVal1j).add(vector1[i].multiply(tmpVal2j))).get();
tmpIndex++;
}
}
}
}