/*
 * Copyright (c) 2009-2014, 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.alg.dense.mult;

import org.ejml.data.RowD1Matrix64F;

/**
 * 

* Specialized operations for performing inner and outer products for matrices. *

* *

* inner product: B=AT*A
* outer product: B=A*AT *

* * @author Peter Abeles */ public class MatrixMultProduct { public static void outer(RowD1Matrix64F a, RowD1Matrix64F c) { for( int i = 0; i < a.numRows; i++ ) { int indexC1 = i*c.numCols+i; int indexC2 = indexC1; for( int j = i; j < a.numRows; j++ , indexC2 += c.numCols) { int indexA = i*a.numCols; int indexB = j*a.numCols; double sum = 0; int end = indexA + a.numCols; for( ; indexA < end; indexA++,indexB++ ) { sum += a.data[indexA]*a.data[indexB]; } c.data[indexC2] = c.data[indexC1++] = sum; } } // for( int i = 0; i < a.numRows; i++ ) { // for( int j = 0; j < a.numRows; j++ ) { // double sum = 0; // for( int k = 0; k < a.numCols; k++ ) { // sum += a.get(i,k)*a.get(j,k); // } // c.set(i,j,sum); // } // } } public static void inner_small(RowD1Matrix64F a, RowD1Matrix64F c) { for( int i = 0; i < a.numCols; i++ ) { for( int j = i; j < a.numCols; j++ ) { int indexC1 = i*c.numCols+j; int indexC2 = j*c.numCols+i; int indexA = i; int indexB = j; double sum = 0; int end = indexA + a.numRows*a.numCols; for( ; indexA < end; indexA += a.numCols, indexB += a.numCols ) { sum += a.data[indexA]*a.data[indexB]; } c.data[indexC1] = c.data[indexC2] = sum; } } // for( int i = 0; i < a.numCols; i++ ) { // for( int j = i; j < a.numCols; j++ ) { // double sum = 0; // for( int k = 0; k < a.numRows; k++ ) { // sum += a.get(k,i)*a.get(k,j); // } // c.set(i,j,sum); // c.set(j,i,sum); // } // } } public static void inner_reorder(RowD1Matrix64F a, RowD1Matrix64F c) { for( int i = 0; i < a.numCols; i++ ) { int indexC = i*c.numCols+i; double valAi = a.data[i]; for( int j = i; j < a.numCols; j++ ) { c.data[indexC++] = valAi*a.data[j]; } for( int k = 1; k < a.numRows; k++ ) { indexC = i*c.numCols+i; int indexB = k*a.numCols+i; valAi = a.data[indexB]; for( int j = i; j < a.numCols; j++ ) { c.data[indexC++] += valAi*a.data[indexB++]; } } indexC = i*c.numCols+i; int indexC2 = indexC; for( int j = i; j < a.numCols; j++ , indexC2 += c.numCols) { c.data[indexC2] = c.data[indexC++]; } } // for( int i = 0; i < a.numCols; i++ ) { // for( int j = i; j < a.numCols; j++ ) { // c.set(i,j,a.get(0,i)*a.get(0,j)); // } // // for( int k = 1; k < a.numRows; k++ ) { // for( int j = i; j < a.numCols; j++ ) { // c.set(i,j, c.get(i,j)+ a.get(k,i)*a.get(k,j)); // } // } // for( int j = i; j < a.numCols; j++ ) { // c.set(j,i,c.get(i,j)); // } // } } public static void inner_reorder_upper(RowD1Matrix64F a, RowD1Matrix64F c) { for( int i = 0; i < a.numCols; i++ ) { int indexC = i*c.numCols+i; double valAi = a.data[i]; for( int j = i; j < a.numCols; j++ ) { c.data[indexC++] = valAi*a.data[j]; } for( int k = 1; k < a.numRows; k++ ) { indexC = i*c.numCols+i; int indexB = k*a.numCols+i; valAi = a.data[indexB]; for( int j = i; j < a.numCols; j++ ) { c.data[indexC++] += valAi*a.data[indexB++]; } } } } }

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