All Downloads are FREE. Search and download functionalities are using the official Maven repository.

org.ejml.dense.row.mult.MatrixMatrixMult_CDRM Maven / Gradle / Ivy

Go to download

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

There is a newer version: 0.43.1
Show newest version
/*
 * Copyright (c) 2009-2020, 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.mult;

import org.ejml.MatrixDimensionException;
import org.ejml.data.CMatrixRMaj;
import org.ejml.dense.row.CommonOps_CDRM;
import org.jetbrains.annotations.Nullable;

import javax.annotation.Generated;

/**
 * 

Matrix multiplication routines for complex row matrices in a row-major format.

* * *

DO NOT MODIFY. Automatically generated code created by GeneratorMatrixMatrixMult_CDRM

* * @author Peter Abeles */ @Generated("org.ejml.dense.row.mult.GeneratorMatrixMatrixMult_CDRM") @SuppressWarnings("Duplicates") public class MatrixMatrixMult_CDRM { public static void mult_reorder(CMatrixRMaj a , CMatrixRMaj b , CMatrixRMaj c) { if( a == c || b == c ) throw new IllegalArgumentException("Neither 'a' or 'b' can be the same matrix as 'c'"); else if( a.numCols != b.numRows ) { throw new MatrixDimensionException("The 'a' and 'b' matrices do not have compatible dimensions"); } else if( a.numRows != c.numRows || b.numCols != c.numCols ) { throw new MatrixDimensionException("The results matrix does not have the desired dimensions"); } if( a.numCols == 0 || a.numRows == 0 ) { CommonOps_CDRM.fill(c,0,0); return; } float realA,imagA; int indexCbase= 0; int strideA = a.getRowStride(); int strideB = b.getRowStride(); int strideC = c.getRowStride(); int endOfKLoop = b.numRows*strideB; for( int i = 0; i < a.numRows; i++ ) { int indexA = i*strideA; // need to assign c.data to a value initially int indexB = 0; int indexC = indexCbase; int end = indexB + strideB; realA = a.data[indexA++]; imagA = a.data[indexA++]; while( indexB < end ) { float realB = b.data[indexB++]; float imgB = b.data[indexB++]; c.data[indexC++] = realA*realB - imagA*imgB; c.data[indexC++] = realA*imgB + imagA*realB; } // now add to it while( indexB != endOfKLoop ) { // k loop indexC = indexCbase; end = indexB + strideB; realA = a.data[indexA++]; imagA = a.data[indexA++]; while( indexB < end ) { // j loop float realB = b.data[indexB++]; float imgB = b.data[indexB++]; c.data[indexC++] += realA*realB - imagA*imgB; c.data[indexC++] += realA*imgB + imagA*realB; } } indexCbase += strideC; } } public static void mult_small(CMatrixRMaj a , CMatrixRMaj b , CMatrixRMaj c) { if( a == c || b == c ) throw new IllegalArgumentException("Neither 'a' or 'b' can be the same matrix as 'c'"); else if( a.numCols != b.numRows ) { throw new MatrixDimensionException("The 'a' and 'b' matrices do not have compatible dimensions"); } else if( a.numRows != c.numRows || b.numCols != c.numCols ) { throw new MatrixDimensionException("The results matrix does not have the desired dimensions"); } int aIndexStart = 0; int indexC = 0; int strideA = a.getRowStride(); int strideB = b.getRowStride(); for( int i = 0; i < a.numRows; i++ ) { for( int j = 0; j < b.numCols; j++ ) { float realTotal = 0; float imgTotal = 0; int indexA = aIndexStart; int indexB = j*2; int end = indexA + strideA; while( indexA < end ) { float realA = a.data[indexA++]; float imagA = a.data[indexA++]; float realB = b.data[indexB]; float imgB = b.data[indexB+1]; realTotal += realA*realB - imagA*imgB; imgTotal += realA*imgB + imagA*realB; indexB += strideB; } c.data[indexC++] = realTotal; c.data[indexC++] = imgTotal; } aIndexStart += strideA; } } public static void multTransA_reorder(CMatrixRMaj a , CMatrixRMaj b , CMatrixRMaj c) { if( a == c || b == c ) throw new IllegalArgumentException("Neither 'a' or 'b' can be the same matrix as 'c'"); else if( a.numRows != b.numRows ) { throw new MatrixDimensionException("The 'a' and 'b' matrices do not have compatible dimensions"); } else if( a.numCols != c.numRows || b.numCols != c.numCols ) { throw new MatrixDimensionException("The results matrix does not have the desired dimensions"); } if( a.numCols == 0 || a.numRows == 0 ) { CommonOps_CDRM.fill(c,0,0); return; } float realA,imagA; for( int i = 0; i < a.numCols; i++ ) { int indexC_start = i*c.numCols*2; // first assign R realA = a.data[i*2]; imagA = a.data[i*2+1]; int indexB = 0; int end = indexB+b.numCols*2; int indexC = indexC_start; while( indexB




© 2015 - 2024 Weber Informatics LLC | Privacy Policy