singularvaluetest.java

另一个功能更强大的矩阵运算软件开源代码

/*
 * Copyright (C) 2003-2006 Bjørn-Ove Heimsund
 * 
 * This file is part of MTJ.
 * 
 * This library is free software; you can redistribute it and/or modify it
 * under the terms of the GNU Lesser General Public License as published by the
 * Free Software Foundation; either version 2.1 of the License, or (at your
 * option) any later version.
 * 
 * This library is distributed in the hope that it will be useful, but WITHOUT
 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
 * FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License
 * for more details.
 * 
 * You should have received a copy of the GNU Lesser General Public License
 * along with this library; if not, write to the Free Software Foundation,
 * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
 */

package no.uib.cipr.matrix;

import no.uib.cipr.matrix.DenseMatrix;
import no.uib.cipr.matrix.Matrix;
import no.uib.cipr.matrix.NotConvergedException;
import no.uib.cipr.matrix.SVD;
import no.uib.cipr.matrix.TridiagMatrix;
import junit.framework.TestCase;

/**
 * Test the singular value solver
 */
public class SingularvalueTest extends TestCase {

    /**
     * Matrix to decompose
     */
    private DenseMatrix A;

    /**
     * Maximum matrix size, to avoid too slow tests
     */
    private final int max = 100;

    public SingularvalueTest(String arg0) {
        super(arg0);
    }

    @Override
    protected void setUp() throws Exception {
        int n = Utilities.getInt(1, max);
        A = new DenseMatrix(n, n);
    }

    @Override
    protected void tearDown() throws Exception {
        A = null;
    }

    public void testStaticFactorize() throws NotConvergedException {
        assertEquals(A, SVD.factorize(A));
    }

    public void testFactor() throws NotConvergedException {
        SVD svd = new SVD(A.numRows(), A.numColumns());
        assertEquals(A, svd.factor(A.copy()));
    }

    private void assertEquals(Matrix A, SVD svd) {
        TridiagMatrix S = new TridiagMatrix(svd.getS().length);
        System.arraycopy(svd.getS(), 0, S.getDiagonal(), 0, svd.getS().length);
        DenseMatrix U = svd.getU();
        DenseMatrix Vt = svd.getVt();

        // Compute U*S*Vt
        Matrix s = U.mult(S.mult(Vt, new DenseMatrix(S.numRows(), Vt
                .numColumns())), new DenseMatrix(A.numRows(), A.numColumns()));

        // Check that A=U*S*Vt
        for (int i = 0; i < A.numRows(); ++i)
            for (int j = 0; j < A.numColumns(); ++j)
                assertEquals(A.get(i, j), s.get(i, j), 1e-12);
    }

}