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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.decomposition.qr.QRDecompositionHouseholderTran_DDRM;
import org.ejml.interfaces.SolveNullSpace;

/**
 * 

Uses QR decomposition to find the null-space for a matrix of any shape if the number of * singular values is known. WARNING: This only uses the first several rows in the input matrix. The rest are * ignored.

* * Solves for AT=QR and the last column in Q is the null space. * * @author Peter Abeles */ public class SolveNullSpaceQR_DDRM implements SolveNullSpace { CustomizedQR decomposition = new CustomizedQR(); // Storage for Q matrix DMatrixRMaj Q = new DMatrixRMaj(1,1); /** * Finds the null space of A * @param A (Input) Matrix. Modified * @param numSingularValues Number of singular values * @param nullspace Storage for null-space * @return true if successful or false if it failed */ @Override public boolean process(DMatrixRMaj A , int numSingularValues, DMatrixRMaj nullspace ) { decomposition.decompose(A); if( A.numRows > A.numCols ) { Q.reshape(A.numCols,Math.min(A.numRows,A.numCols)); decomposition.getQ(Q, true); } else { Q.reshape(A.numCols, A.numCols); decomposition.getQ(Q, false); } nullspace.reshape(Q.numRows,numSingularValues); CommonOps_DDRM.extract(Q,0,Q.numRows,Q.numCols-numSingularValues,Q.numCols,nullspace,0,0); return true; } @Override public boolean inputModified() { return true; } /** * Special/Hack version of QR decomposition to avoid copying memory and pointless transposes */ private static class CustomizedQR extends QRDecompositionHouseholderTran_DDRM { @Override public void setExpectedMaxSize( int numRows , int numCols ) { this.numCols = numCols; this.numRows = numRows; minLength = Math.min(numCols,numRows); int maxLength = Math.max(numCols,numRows); // Don't delcare QR. It will use the input matrix for worspace if( v == null ) { v = new double[ maxLength ]; gammas = new double[ minLength ]; } if( v.length < maxLength ) { v = new double[ maxLength ]; } if( gammas.length < minLength ) { gammas = new double[ minLength ]; } } /** * Modified decomposition which assumes the input is a transpose of the matrix */ @Override public boolean decompose( DMatrixRMaj A_tran ) { // There is a "subtle" hack in the line below. Instead of passing in (cols,rows) I'm passing in // (cols,cols) that's because we don't care about updating everything past the cols setExpectedMaxSize(A_tran.numCols, Math.min(A_tran.numRows,A_tran.numCols)); // use the input matrix for its workspace this.QR = A_tran; error = false; for( int j = 0; j < minLength; j++ ) { householder(j); updateA(j); } return !error; } } public DMatrixRMaj getQ() { return Q; } }




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