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A fast and easy to use dense and sparse matrix linear algebra library written in Java.
/*
* Copyright (c) 2009-2017, Peter Abeles. All Rights Reserved.
*
* This file is part of Efficient Java Matrix Library (EJML).
*
* 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.
*/
package org.ejml.dense.row.misc;
import org.ejml.data.CMatrixRMaj;
/**
* Algorithms for transposing row complex matrices
*
* @author Peter Abeles
*/
public class TransposeAlgs_CDRM {
/**
* In-place transpose for a square matrix. On most architectures it is faster than the standard transpose
* algorithm, but on most modern computers it's slower than block transpose.
*
* @param mat The matrix that is transposed in-place. Modified.
*/
public static void square( CMatrixRMaj mat )
{
int index = 2;
int rowStride = mat.getRowStride();
int indexEnd = rowStride;
for( int i = 0; i < mat.numRows;
i++ , index += (i+1)*2 , indexEnd += rowStride ) {
int indexOther = (i+1)*rowStride + i*2;
for( ; index < indexEnd; index += 2, indexOther += rowStride) {
float real = mat.data[ index ];
float img = mat.data[ index+1 ];
mat.data[ index ] = mat.data[ indexOther ];
mat.data[ index+1 ] = mat.data[ indexOther+1 ];
mat.data[indexOther] = real;
mat.data[indexOther+1] = img;
}
}
}
public static void squareConjugate( CMatrixRMaj mat )
{
int index = 2;
int rowStride = mat.getRowStride();
int indexEnd = rowStride;
for( int i = 0; i < mat.numRows;
i++ , index += (i+1)*2 , indexEnd += rowStride ) {
mat.data[ index-1 ] = -mat.data[ index-1 ];
int indexOther = (i+1)*rowStride + i*2;
for( ; index < indexEnd; index += 2, indexOther += rowStride) {
float real = mat.data[ index ];
float img = mat.data[ index+1 ];
mat.data[ index ] = mat.data[ indexOther ];
mat.data[ index+1 ] = -mat.data[ indexOther+1 ];
mat.data[indexOther] = real;
mat.data[indexOther+1] = -img;
}
}
}
/**
* A straight forward transpose. Good for small non-square matrices.
*
* @param A Original matrix. Not modified.
* @param A_tran Transposed matrix. Modified.
*/
public static void standard(CMatrixRMaj A, CMatrixRMaj A_tran)
{
int index = 0;
int rowStrideTran = A_tran.getRowStride();
int rowStride = A.getRowStride();
for( int i = 0; i < A_tran.numRows; i++ ) {
int index2 = i*2;
int end = index + rowStrideTran;
while( index < end ) {
A_tran.data[index++] = A.data[ index2 ];
A_tran.data[index++] = A.data[ index2+1 ];
index2 += rowStride;
}
}
}
/**
* A straight forward conjugate transpose. Good for small non-square matrices.
*
* @param A Original matrix. Not modified.
* @param A_tran Transposed matrix. Modified.
*/
public static void standardConjugate(CMatrixRMaj A, CMatrixRMaj A_tran)
{
int index = 0;
int rowStrideTran = A_tran.getRowStride();
int rowStride = A.getRowStride();
for( int i = 0; i < A_tran.numRows; i++ ) {
int index2 = i*2;
int end = index + rowStrideTran;
while( index < end ) {
A_tran.data[index++] = A.data[ index2 ];
A_tran.data[index++] = -A.data[ index2+1 ];
index2 += rowStride;
}
}
}
}