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/*
 * Copyright (c) 2009-2018, 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.linsol.qr;

import org.ejml.data.DMatrixRMaj;
import org.ejml.dense.row.CommonOps_DDRM;
import org.ejml.dense.row.SpecializedOps_DDRM;
import org.ejml.dense.row.decomposition.TriangularSolver_DDRM;
import org.ejml.dense.row.linsol.LinearSolverAbstract_DDRM;
import org.ejml.interfaces.decomposition.QRDecomposition;


/**
 * 

* A solver for a generic QR decomposition algorithm. This will in general be a bit slower than the * specialized once since the full Q and R matrices need to be extracted. *

*

* It solve for x by first multiplying b by the transpose of Q then solving for the result. *
* QRx=b
* Rx=Q^T b
*

* * @author Peter Abeles */ public class LinearSolverQr_DDRM extends LinearSolverAbstract_DDRM { private QRDecomposition decomposer; protected int maxRows = -1; protected int maxCols = -1; protected DMatrixRMaj Q; protected DMatrixRMaj R; private DMatrixRMaj Y,Z; /** * Creates a linear solver that uses QR decomposition. * */ public LinearSolverQr_DDRM(QRDecomposition decomposer) { this.decomposer = decomposer; } /** * Changes the size of the matrix it can solve for * * @param maxRows Maximum number of rows in the matrix it will decompose. * @param maxCols Maximum number of columns in the matrix it will decompose. */ public void setMaxSize( int maxRows , int maxCols ) { this.maxRows = maxRows; this.maxCols = maxCols; Q = new DMatrixRMaj(maxRows,maxRows); R = new DMatrixRMaj(maxRows,maxCols); Y = new DMatrixRMaj(maxRows,1); Z = new DMatrixRMaj(maxRows,1); } /** * Performs QR decomposition on A * * @param A not modified. */ @Override public boolean setA(DMatrixRMaj A) { if( A.numRows > maxRows || A.numCols > maxCols ) { setMaxSize(A.numRows,A.numCols); } _setA(A); if( !decomposer.decompose(A) ) return false; Q.reshape(numRows,numRows, false); R.reshape(numRows,numCols, false); decomposer.getQ(Q,false); decomposer.getR(R,false); return true; } @Override public /**/double quality() { return SpecializedOps_DDRM.qualityTriangular(R); } /** * Solves for X using the QR decomposition. * * @param B A matrix that is n by m. Not modified. * @param X An n by m matrix where the solution is written to. Modified. */ @Override public void solve(DMatrixRMaj B, DMatrixRMaj X) { if( B.numRows != numRows ) throw new IllegalArgumentException("Unexpected dimensions for X: X rows = "+X.numRows+" expected = "+numCols); X.reshape(numCols,B.numCols); int BnumCols = B.numCols; Y.reshape(numRows,1, false); Z.reshape(numRows,1, false); // solve each column one by one for( int colB = 0; colB < BnumCols; colB++ ) { // make a copy of this column in the vector for( int i = 0; i < numRows; i++ ) { Y.data[i] = B.get(i,colB); } // Solve Qa=b // a = Q'b CommonOps_DDRM.multTransA(Q,Y,Z); // solve for Rx = b using the standard upper triangular solver TriangularSolver_DDRM.solveU(R.data,Z.data,numCols); // save the results for( int i = 0; i < numCols; i++ ) { X.set(i,colB,Z.data[i]); } } } @Override public boolean modifiesA() { return decomposer.inputModified(); } @Override public boolean modifiesB() { return false; } @Override public QRDecomposition getDecomposition() { return decomposer; } public QRDecomposition getDecomposer() { return decomposer; } public DMatrixRMaj getQ() { return Q; } public DMatrixRMaj getR() { return R; } }




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