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A fast and easy to use dense and sparse matrix linear algebra library written in Java.

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/*
 * 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.ZMatrixRMaj;

/**
 * Algorithms for transposing row complex matrices
 *
 * @author Peter Abeles
 */
public class TransposeAlgs_ZDRM {
    /**
     * 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( ZMatrixRMaj 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) {
                double real = mat.data[ index ];
                double 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( ZMatrixRMaj 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) {
                double real = mat.data[ index ];
                double 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(ZMatrixRMaj A, ZMatrixRMaj 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(ZMatrixRMaj A, ZMatrixRMaj 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;
            }
        }
    }
}




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