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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.block;

import org.ejml.data.FMatrixRBlock;
import org.ejml.data.FSubmatrixD1;


/**
 * Performs rank-n update operations on the inner blocks of a {@link FMatrixRBlock}
 *
 * It is assumed and not checked that the submatrices are aligned along the matrix's blocks.
 *
 * @author Peter Abeles
 */
public class InnerRankUpdate_FDRB {

    /**
     * 

* Performs:
*
* A = A + α B TB *

* * @param blockLength Size of the block in the block matrix. * @param alpha scaling factor for right hand side. * @param A Block aligned submatrix. * @param B Block aligned submatrix. */ public static void rankNUpdate(int blockLength , float alpha , FSubmatrixD1 A , FSubmatrixD1 B ) { int heightB = B.row1-B.row0; if( heightB > blockLength ) throw new IllegalArgumentException("Height of B cannot be greater than the block length"); int N = B.col1-B.col0; if( A.col1-A.col0 != N ) throw new IllegalArgumentException("A does not have the expected number of columns based on B's width"); if( A.row1-A.row0 != N ) throw new IllegalArgumentException("A does not have the expected number of rows based on B's width"); for( int i = B.col0; i < B.col1; i += blockLength ) { int indexB_i = B.row0*B.original.numCols + i*heightB; int widthB_i = Math.min(blockLength,B.col1-i); int rowA = i-B.col0+A.row0; int heightA = Math.min( blockLength , A.row1 - rowA); for( int j = B.col0; j < B.col1; j += blockLength ) { int widthB_j = Math.min(blockLength,B.col1-j); int indexA = rowA * A.original.numCols + (j-B.col0+A.col0)*heightA; int indexB_j = B.row0*B.original.numCols + j*heightB; InnerMultiplication_FDRB.blockMultPlusTransA(alpha, B.original.data,B.original.data,A.original.data, indexB_i,indexB_j,indexA,heightB,widthB_i,widthB_j); } } } /** *

* Rank N update function for a symmetric inner submatrix and only operates on the upper * triangular portion of the submatrix.
*
* A = A - B TB *

*/ public static void symmRankNMinus_U(int blockLength , FSubmatrixD1 A , FSubmatrixD1 B ) { int heightB = B.row1-B.row0; if( heightB > blockLength ) throw new IllegalArgumentException("Height of B cannot be greater than the block length"); int N = B.col1-B.col0; if( A.col1-A.col0 != N ) throw new IllegalArgumentException("A does not have the expected number of columns based on B's width"); if( A.row1-A.row0 != N ) throw new IllegalArgumentException("A does not have the expected number of rows based on B's width"); for( int i = B.col0; i < B.col1; i += blockLength ) { int indexB_i = B.row0*B.original.numCols + i*heightB; int widthB_i = Math.min(blockLength,B.col1-i); int rowA = i-B.col0+A.row0; int heightA = Math.min( blockLength , A.row1 - rowA); for( int j = i; j < B.col1; j += blockLength ) { int widthB_j = Math.min(blockLength,B.col1-j); int indexA = rowA * A.original.numCols + (j-B.col0+A.col0)*heightA; int indexB_j = B.row0*B.original.numCols + j*heightB; if( i == j ) { // only the upper portion of this block needs to be modified since it is along a diagonal multTransABlockMinus_U( B.original.data,A.original.data, indexB_i,indexB_j,indexA,heightB,widthB_i,widthB_j); } else { multTransABlockMinus( B.original.data,A.original.data, indexB_i,indexB_j,indexA,heightB,widthB_i,widthB_j); } } } } /** *

* Rank N update function for a symmetric inner submatrix and only operates on the lower * triangular portion of the submatrix.
*
* A = A - B*BT
*

*/ public static void symmRankNMinus_L(int blockLength , FSubmatrixD1 A , FSubmatrixD1 B ) { int widthB = B.col1-B.col0; if( widthB > blockLength ) throw new IllegalArgumentException("Width of B cannot be greater than the block length"); int N = B.row1-B.row0; if( A.col1-A.col0 != N ) throw new IllegalArgumentException("A does not have the expected number of columns based on B's height"); if( A.row1-A.row0 != N ) throw new IllegalArgumentException("A does not have the expected number of rows based on B's height"); for( int i = B.row0; i < B.row1; i += blockLength ) { int heightB_i = Math.min(blockLength,B.row1-i); int indexB_i = i*B.original.numCols + heightB_i*B.col0; int rowA = i-B.row0+A.row0; int heightA = Math.min( blockLength , A.row1 - rowA); for( int j = B.row0; j <= i; j += blockLength ) { int widthB_j = Math.min(blockLength,B.row1-j); int indexA = rowA * A.original.numCols + (j-B.row0+A.col0)*heightA; int indexB_j = j*B.original.numCols + widthB_j*B.col0; if( i == j ) { multTransBBlockMinus_L( B.original.data,A.original.data, indexB_i,indexB_j,indexA,widthB,heightB_i,widthB_j); } else { multTransBBlockMinus( B.original.data,A.original.data, indexB_i,indexB_j,indexA,widthB,heightB_i,widthB_j); } } } } /** *

* Performs the following operation on a block:
*
* c = c - aTa
*

*/ protected static void multTransABlockMinus( float[] dataA, float []dataC, int indexA, int indexB, int indexC, final int heightA, final int widthA, final int widthC ) { // for( int i = 0; i < widthA; i++ ) { // for( int k = 0; k < heightA; k++ ) { // // float valA = dataA[k*widthA + i + indexA]; // for( int j = 0; j < widthC; j++ ) { // dataC[ i*widthC + j + indexC ] -= valA * dataA[k*widthC + j + indexB]; // } // } // } int rowB = indexB; int endLoopK = rowB + heightA*widthC; int startA = indexA; //for( int k = 0; k < heightA; k++ ) { for( ; rowB != endLoopK; rowB += widthC , startA += widthA ) { int a = startA; int c = indexC; int endA = a + widthA; int endB = rowB + widthC; while( a != endA ) { float valA = dataA[a++]; int b = rowB; while( b != endB ) { dataC[ c++ ] -= valA * dataA[b++]; } } } } /** *

* Performs the following operation on the upper triangular portion of a block:
*
* c = c - aTa
*

*/ protected static void multTransABlockMinus_U( float[] dataA, float []dataC, int indexA, int indexB, int indexC, final int heightA, final int widthA, final int widthC ) { // for( int i = 0; i < widthA; i++ ) { // for( int k = 0; k < heightA; k++ ) { // // float valA = dataA[k*widthA + i + indexA]; // for( int j = i; j < widthC; j++ ) { // dataC[ i*widthC + j + indexC ] -= valA * dataA[k*widthC + j + indexB]; // } // } // } for( int i = 0; i < widthA; i++ ) { for( int k = 0; k < heightA; k++ ) { float valA = dataA[k*widthA + i + indexA]; int b = k*widthC + indexB + i; int c = i*widthC + indexC + i; int endC = (c-i)+widthC; while( c != endC ) { // for( int j = i; j < widthC; j++ ) { dataC[ c++ ] -= valA * dataA[b++]; } } } } /** *

* Performs the following operation on a block:
*
* c = c - a*aT
*

*/ protected static void multTransBBlockMinus( final float[] dataA, final float []dataC, final int indexA, final int indexB, final int indexC, final int widthA, final int heightA, final int widthC ) { // for( int i = 0; i < heightA; i++ ) { // for( int j = 0; j < widthC; j++ ) { // float sum = 0; // for( int k = 0; k < widthA; k++ ) { // sum += dataA[i*widthA + k + indexA] * dataA[j*widthA + k + indexB]; // } // dataC[ i*widthC + j + indexC ] -= sum; // } // } int rowA = indexA; int c = indexC; for( int i = 0; i < heightA; i++ , rowA += widthA ) { final int endA = rowA + widthA; int rowB = indexB; final int endLoopJ = c + widthC; // for( int j = 0; j < widthC; j++ ) { while( c != endLoopJ ) { int a = rowA; int b = rowB; float sum = 0; while( a != endA ) { sum += dataA[a++] * dataA[b++]; } dataC[ c++ ] -= sum; rowB += widthA; } } } /** *

* Performs the following operation on the lower triangular portion of a block:
*
* c = c - a*aT
*

*/ protected static void multTransBBlockMinus_L( float[] dataA, float []dataC, int indexA, int indexB, int indexC, final int widthA, final int heightA, final int widthC ) { // for( int i = 0; i < heightA; i++ ) { // for( int j = 0; j <= i; j++ ) { // float sum = 0; // for( int k = 0; k < widthA; k++ ) { // sum += dataA[i*widthA + k + indexA] * dataA[j*widthA + k + indexB]; // } // dataC[ i*widthC + j + indexC ] -= sum; // } // } for( int i = 0; i < heightA; i++ ) { int rowA = i*widthA+indexA; int endA = rowA + widthA; int rowB = indexB; int rowC = i*widthC + indexC; for( int j = 0; j <= i; j++ , rowB += widthA) { float sum = 0; int a = rowA; int b = rowB; while( a != endA ) { sum += dataA[a++] * dataA[b++]; } dataC[ rowC + j ] -= sum; } } } }




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