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A fast and easy to use dense and sparse matrix linear algebra library written in Java.
/*
* Copyright (c) 2022, 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.block;
import javax.annotation.Generated;
import org.ejml.data.FMatrixRBlock;
import org.ejml.data.FSubmatrixD1;
import static org.ejml.dense.block.InnerMultiplication_FDRB.*;
import static org.ejml.dense.block.MatrixOps_FDRB.checkShapeMult;
import org.ejml.concurrency.EjmlConcurrency;
/**
*
* Matrix multiplication for {@link FMatrixRBlock}. All sub-matrices must be block aligned.
*
*
* @author Peter Abeles
*/
@Generated("org.ejml.dense.block.MatrixMult_FDRB")
public class MatrixMult_MT_FDRB {
/**
*
* Performs a matrix multiplication on {@link FMatrixRBlock} submatrices.
*
* c = a * b
*
*
*
*
* It is assumed that all submatrices start at the beginning of a block and end at the end of a block.
*
*
* @param blockLength Size of the blocks in the submatrix.
* @param A A submatrix. Not modified.
* @param B A submatrix. Not modified.
* @param C Result of the operation. Modified,
*/
public static void mult( int blockLength,
FSubmatrixD1 A, FSubmatrixD1 B,
FSubmatrixD1 C ) {
checkShapeMult(blockLength, A, B, C);
EjmlConcurrency.loopFor(A.row0,A.row1,blockLength,i->{
int heightA = Math.min(blockLength, A.row1 - i);
for (int j = B.col0; j < B.col1; j += blockLength) {
int widthB = Math.min(blockLength, B.col1 - j);
int indexC = (i - A.row0 + C.row0)*C.original.numCols + (j - B.col0 + C.col0)*heightA;
for (int k = A.col0; k < A.col1; k += blockLength) {
int widthA = Math.min(blockLength, A.col1 - k);
int indexA = i*A.original.numCols + k*heightA;
int indexB = (k - A.col0 + B.row0)*B.original.numCols + j*widthA;
if (k == A.col0)
blockMultSet(A.original.data, B.original.data, C.original.data,
indexA, indexB, indexC, heightA, widthA, widthB);
else
blockMultPlus(A.original.data, B.original.data, C.original.data,
indexA, indexB, indexC, heightA, widthA, widthB);
}
}
});
}
/**
*
* Performs a matrix multiplication on {@link FMatrixRBlock} submatrices.
*
* c = c + a * b
*
*
*
*
* It is assumed that all submatrices start at the beginning of a block and end at the end of a block.
*
*
* @param blockLength Size of the blocks in the submatrix.
* @param A A submatrix. Not modified.
* @param B A submatrix. Not modified.
* @param C Result of the operation. Modified,
*/
public static void multPlus( int blockLength,
FSubmatrixD1 A, FSubmatrixD1 B,
FSubmatrixD1 C ) {
// checkShapeMult( blockLength,A,B,C);
EjmlConcurrency.loopFor(A.row0,A.row1,blockLength,i->{
int heightA = Math.min(blockLength, A.row1 - i);
for (int j = B.col0; j < B.col1; j += blockLength) {
int widthB = Math.min(blockLength, B.col1 - j);
int indexC = (i - A.row0 + C.row0)*C.original.numCols + (j - B.col0 + C.col0)*heightA;
for (int k = A.col0; k < A.col1; k += blockLength) {
int widthA = Math.min(blockLength, A.col1 - k);
int indexA = i*A.original.numCols + k*heightA;
int indexB = (k - A.col0 + B.row0)*B.original.numCols + j*widthA;
blockMultPlus(A.original.data, B.original.data, C.original.data,
indexA, indexB, indexC, heightA, widthA, widthB);
}
}
});
}
/**
*
* Performs a matrix multiplication on {@link FMatrixRBlock} submatrices.
*
* c = c - a * b
*
*
*
*
* It is assumed that all submatrices start at the beginning of a block and end at the end of a block.
*
*
* @param blockLength Size of the blocks in the submatrix.
* @param A A submatrix. Not modified.
* @param B A submatrix. Not modified.
* @param C Result of the operation. Modified,
*/
public static void multMinus( int blockLength,
FSubmatrixD1 A, FSubmatrixD1 B,
FSubmatrixD1 C ) {
// checkShapeMult( blockLength,A,B,C);
EjmlConcurrency.loopFor(A.row0,A.row1,blockLength,i->{
int heightA = Math.min(blockLength, A.row1 - i);
for (int j = B.col0; j < B.col1; j += blockLength) {
int widthB = Math.min(blockLength, B.col1 - j);
int indexC = (i - A.row0 + C.row0)*C.original.numCols + (j - B.col0 + C.col0)*heightA;
for (int k = A.col0; k < A.col1; k += blockLength) {
int widthA = Math.min(blockLength, A.col1 - k);
int indexA = i*A.original.numCols + k*heightA;
int indexB = (k - A.col0 + B.row0)*B.original.numCols + j*widthA;
blockMultMinus(A.original.data, B.original.data, C.original.data,
indexA, indexB, indexC, heightA, widthA, widthB);
}
}
});
}
/**
*
* Performs a matrix multiplication with a transpose on {@link FMatrixRBlock} submatrices.
*
* c = aT * b
*
*
*
*
* It is assumed that all submatrices start at the beginning of a block and end at the end of a block.
*
*
* @param blockLength Size of the blocks in the submatrix.
* @param A A submatrix. Not modified.
* @param B A submatrix. Not modified.
* @param C Result of the operation. Modified,
*/
public static void multTransA( int blockLength,
FSubmatrixD1 A, FSubmatrixD1 B,
FSubmatrixD1 C ) {
EjmlConcurrency.loopFor(A.col0,A.col1,blockLength,i->{
int widthA = Math.min(blockLength, A.col1 - i);
for (int j = B.col0; j < B.col1; j += blockLength) {
int widthB = Math.min(blockLength, B.col1 - j);
int indexC = (i - A.col0 + C.row0)*C.original.numCols + (j - B.col0 + C.col0)*widthA;
for (int k = A.row0; k < A.row1; k += blockLength) {
int heightA = Math.min(blockLength, A.row1 - k);
int indexA = k*A.original.numCols + i*heightA;
int indexB = (k - A.row0 + B.row0)*B.original.numCols + j*heightA;
if (k == A.row0)
blockMultSetTransA(A.original.data, B.original.data, C.original.data,
indexA, indexB, indexC, heightA, widthA, widthB);
else
blockMultPlusTransA(A.original.data, B.original.data, C.original.data,
indexA, indexB, indexC, heightA, widthA, widthB);
}
}
});
}
public static void multPlusTransA( int blockLength,
FSubmatrixD1 A, FSubmatrixD1 B,
FSubmatrixD1 C ) {
EjmlConcurrency.loopFor(A.col0,A.col1,blockLength,i->{
int widthA = Math.min(blockLength, A.col1 - i);
for (int j = B.col0; j < B.col1; j += blockLength) {
int widthB = Math.min(blockLength, B.col1 - j);
int indexC = (i - A.col0 + C.row0)*C.original.numCols + (j - B.col0 + C.col0)*widthA;
for (int k = A.row0; k < A.row1; k += blockLength) {
int heightA = Math.min(blockLength, A.row1 - k);
int indexA = k*A.original.numCols + i*heightA;
int indexB = (k - A.row0 + B.row0)*B.original.numCols + j*heightA;
blockMultPlusTransA(A.original.data, B.original.data, C.original.data,
indexA, indexB, indexC, heightA, widthA, widthB);
}
}
});
}
public static void multMinusTransA( int blockLength,
FSubmatrixD1 A, FSubmatrixD1 B,
FSubmatrixD1 C ) {
EjmlConcurrency.loopFor(A.col0,A.col1,blockLength,i->{
int widthA = Math.min(blockLength, A.col1 - i);
for (int j = B.col0; j < B.col1; j += blockLength) {
int widthB = Math.min(blockLength, B.col1 - j);
int indexC = (i - A.col0 + C.row0)*C.original.numCols + (j - B.col0 + C.col0)*widthA;
for (int k = A.row0; k < A.row1; k += blockLength) {
int heightA = Math.min(blockLength, A.row1 - k);
int indexA = k*A.original.numCols + i*heightA;
int indexB = (k - A.row0 + B.row0)*B.original.numCols + j*heightA;
blockMultMinusTransA(A.original.data, B.original.data, C.original.data,
indexA, indexB, indexC, heightA, widthA, widthB);
}
}
});
}
/**
*
* Performs a matrix multiplication with a transpose on {@link FMatrixRBlock} submatrices.
*
* c = a * b T
*
*
*
*
* It is assumed that all submatrices start at the beginning of a block and end at the end of a block.
*
*
* @param blockLength Length of the blocks in the submatrix.
* @param A A submatrix. Not modified.
* @param B A submatrix. Not modified.
* @param C Result of the operation. Modified,
*/
public static void multTransB( int blockLength,
FSubmatrixD1 A, FSubmatrixD1 B,
FSubmatrixD1 C ) {
EjmlConcurrency.loopFor(A.row0,A.row1,blockLength,i->{
int heightA = Math.min(blockLength, A.row1 - i);
for (int j = B.row0; j < B.row1; j += blockLength) {
int widthC = Math.min(blockLength, B.row1 - j);
int indexC = (i - A.row0 + C.row0)*C.original.numCols + (j - B.row0 + C.col0)*heightA;
for (int k = A.col0; k < A.col1; k += blockLength) {
int widthA = Math.min(blockLength, A.col1 - k);
int indexA = i*A.original.numCols + k*heightA;
int indexB = j*B.original.numCols + (k - A.col0 + B.col0)*widthC;
if (k == A.col0)
blockMultSetTransB(A.original.data, B.original.data, C.original.data,
indexA, indexB, indexC, heightA, widthA, widthC);
else
blockMultPlusTransB(A.original.data, B.original.data, C.original.data,
indexA, indexB, indexC, heightA, widthA, widthC);
}
}
});
}
}