001    /*
002     * Copyright (C) 2008-2010 by Holger Arndt
003     *
004     * This file is part of the Universal Java Matrix Package (UJMP).
005     * See the NOTICE file distributed with this work for additional
006     * information regarding copyright ownership and licensing.
007     *
008     * UJMP is free software; you can redistribute it and/or modify
009     * it under the terms of the GNU Lesser General Public License as
010     * published by the Free Software Foundation; either version 2
011     * of the License, or (at your option) any later version.
012     *
013     * UJMP is distributed in the hope that it will be useful,
014     * but WITHOUT ANY WARRANTY; without even the implied warranty of
015     * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
016     * GNU Lesser General Public License for more details.
017     *
018     * You should have received a copy of the GNU Lesser General Public
019     * License along with UJMP; if not, write to the
020     * Free Software Foundation, Inc., 51 Franklin St, Fifth Floor,
021     * Boston, MA  02110-1301  USA
022     */
023    
024    package org.ujmp.ejml.calculation;
025    
026    import org.ejml.alg.dense.decomposition.DecompositionFactory;
027    import org.ejml.alg.dense.decomposition.QRDecomposition;
028    import org.ejml.alg.dense.linsol.LinearSolver;
029    import org.ejml.alg.dense.linsol.qr.LinearSolverQrHouseCol;
030    import org.ejml.data.DenseMatrix64F;
031    import org.ujmp.core.Matrix;
032    import org.ujmp.ejml.EJMLDenseDoubleMatrix2D;
033    
034    public class QR implements
035                    org.ujmp.core.doublematrix.calculation.general.decomposition.QR<Matrix> {
036    
037            public static QR INSTANCE = new QR();
038    
039            public Matrix[] calc(Matrix source) {
040                    QRDecomposition qr = DecompositionFactory.qr();
041                    DenseMatrix64F matrix = null;
042                    if (source instanceof EJMLDenseDoubleMatrix2D) {
043                            matrix = ((EJMLDenseDoubleMatrix2D) source).getWrappedObject();
044                    } else {
045                            matrix = new EJMLDenseDoubleMatrix2D(source).getWrappedObject();
046                    }
047                    qr.decompose(matrix);
048                    DenseMatrix64F qm = qr.getQ(null, true);
049                    DenseMatrix64F rm = qr.getR(null, true);
050                    Matrix q = new EJMLDenseDoubleMatrix2D(qm);
051                    Matrix r = new EJMLDenseDoubleMatrix2D(rm);
052                    return new Matrix[] { q, r };
053            }
054    
055            public Matrix solve(Matrix a, Matrix b) {
056                    LinearSolver solver = new LinearSolverQrHouseCol();
057                    DenseMatrix64F a2 = null;
058                    DenseMatrix64F b2 = null;
059                    if (a instanceof EJMLDenseDoubleMatrix2D) {
060                            a2 = ((EJMLDenseDoubleMatrix2D) a).getWrappedObject();
061                    } else {
062                            a2 = new EJMLDenseDoubleMatrix2D(a).getWrappedObject();
063                    }
064                    if (b instanceof EJMLDenseDoubleMatrix2D) {
065                            b2 = ((EJMLDenseDoubleMatrix2D) b).getWrappedObject();
066                    } else {
067                            b2 = new EJMLDenseDoubleMatrix2D(b).getWrappedObject();
068                    }
069                    solver.setA(a2);
070                    DenseMatrix64F x = new DenseMatrix64F(a2.numCols, b2.numCols);
071                    solver.solve(b2, x);
072                    return new EJMLDenseDoubleMatrix2D(x);
073            }
074    
075    }