home | career | drupal | java | mac | mysql | perl | scala | uml | unix  

Java example source code file (SingularValueSolverTest.java)

This example Java source code file (SingularValueSolverTest.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

array2drowrealmatrix, decompositionsolver, mathillegalargumentexception, realmatrix, realvector, singularvaluedecomposition, singularvaluesolvertest, test

The SingularValueSolverTest.java Java example source code

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You 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.apache.commons.math3.linear;

import org.apache.commons.math3.exception.MathIllegalArgumentException;

import org.junit.Assert;
import org.junit.Test;

public class SingularValueSolverTest {

    private double[][] testSquare = {
            { 24.0 / 25.0, 43.0 / 25.0 },
            { 57.0 / 25.0, 24.0 / 25.0 }
    };
    private double[][] bigSingular = {
        { 1.0, 2.0,   3.0,    4.0 },
        { 2.0, 5.0,   3.0,    4.0 },
        { 7.0, 3.0, 256.0, 1930.0 },
        { 3.0, 7.0,   6.0,    8.0 }
    }; // 4th row = 1st + 2nd

    private static final double normTolerance = 10e-14;

    /** test solve dimension errors */
    @Test
    public void testSolveDimensionErrors() {
        DecompositionSolver solver =
            new SingularValueDecomposition(MatrixUtils.createRealMatrix(testSquare)).getSolver();
        RealMatrix b = MatrixUtils.createRealMatrix(new double[3][2]);
        try {
            solver.solve(b);
            Assert.fail("an exception should have been thrown");
        } catch (MathIllegalArgumentException iae) {
            // expected behavior
        }
        try {
            solver.solve(b.getColumnVector(0));
            Assert.fail("an exception should have been thrown");
        } catch (MathIllegalArgumentException iae) {
            // expected behavior
        }
        try {
            solver.solve(new ArrayRealVectorTest.RealVectorTestImpl(b.getColumn(0)));
            Assert.fail("an exception should have been thrown");
        } catch (MathIllegalArgumentException iae) {
            // expected behavior
        }
    }

    /** test least square solve */
    @Test
    public void testLeastSquareSolve() {
        RealMatrix m =
            MatrixUtils.createRealMatrix(new double[][] {
                                   { 1.0, 0.0 },
                                   { 0.0, 0.0 }
                               });
        DecompositionSolver solver = new SingularValueDecomposition(m).getSolver();
        RealMatrix b = MatrixUtils.createRealMatrix(new double[][] {
            { 11, 12 }, { 21, 22 }
        });
        RealMatrix xMatrix = solver.solve(b);
        Assert.assertEquals(11, xMatrix.getEntry(0, 0), 1.0e-15);
        Assert.assertEquals(12, xMatrix.getEntry(0, 1), 1.0e-15);
        Assert.assertEquals(0, xMatrix.getEntry(1, 0), 1.0e-15);
        Assert.assertEquals(0, xMatrix.getEntry(1, 1), 1.0e-15);
        RealVector xColVec = solver.solve(b.getColumnVector(0));
        Assert.assertEquals(11, xColVec.getEntry(0), 1.0e-15);
        Assert.assertEquals(0, xColVec.getEntry(1), 1.0e-15);
        RealVector xColOtherVec = solver.solve(new ArrayRealVectorTest.RealVectorTestImpl(b.getColumn(0)));
        Assert.assertEquals(11, xColOtherVec.getEntry(0), 1.0e-15);
        Assert.assertEquals(0, xColOtherVec.getEntry(1), 1.0e-15);
    }

    /** test solve */
    @Test
    public void testSolve() {
        DecompositionSolver solver =
            new SingularValueDecomposition(MatrixUtils.createRealMatrix(testSquare)).getSolver();
        RealMatrix b = MatrixUtils.createRealMatrix(new double[][] {
                { 1, 2, 3 }, { 0, -5, 1 }
        });
        RealMatrix xRef = MatrixUtils.createRealMatrix(new double[][] {
                { -8.0 / 25.0, -263.0 / 75.0, -29.0 / 75.0 },
                { 19.0 / 25.0,   78.0 / 25.0,  49.0 / 25.0 }
        });

        // using RealMatrix
        Assert.assertEquals(0, solver.solve(b).subtract(xRef).getNorm(), normTolerance);

        // using ArrayRealVector
        for (int i = 0; i < b.getColumnDimension(); ++i) {
            Assert.assertEquals(0,
                         solver.solve(b.getColumnVector(i)).subtract(xRef.getColumnVector(i)).getNorm(),
                         1.0e-13);
        }

        // using RealVector with an alternate implementation
        for (int i = 0; i < b.getColumnDimension(); ++i) {
            ArrayRealVectorTest.RealVectorTestImpl v =
                new ArrayRealVectorTest.RealVectorTestImpl(b.getColumn(i));
            Assert.assertEquals(0,
                         solver.solve(v).subtract(xRef.getColumnVector(i)).getNorm(),
                         1.0e-13);
        }

    }

    /** test condition number */
    @Test
    public void testConditionNumber() {
        SingularValueDecomposition svd =
            new SingularValueDecomposition(MatrixUtils.createRealMatrix(testSquare));
        // replace 1.0e-15 with 1.5e-15
        Assert.assertEquals(3.0, svd.getConditionNumber(), 1.5e-15);
    }

    @Test
    public void testMath320B() {
        RealMatrix rm = new Array2DRowRealMatrix(new double[][] {
            { 1.0, 2.0 }, { 1.0, 2.0 }
        });
        SingularValueDecomposition svd =
            new SingularValueDecomposition(rm);
        RealMatrix recomposed = svd.getU().multiply(svd.getS()).multiply(svd.getVT());
        Assert.assertEquals(0.0, recomposed.subtract(rm).getNorm(), 2.0e-15);
    }

    @Test
    public void testSingular() {
      SingularValueDecomposition svd =
          new SingularValueDecomposition(MatrixUtils.createRealMatrix(bigSingular));
      RealMatrix pseudoInverse = svd.getSolver().getInverse();
      RealMatrix expected = new Array2DRowRealMatrix(new double[][] {
          {-0.0355022687,0.0512742236,-0.0001045523,0.0157719549},
          {-0.3214992438,0.3162419255,0.0000348508,-0.0052573183},
          {0.5437098346,-0.4107754586,-0.0008256918,0.132934376},
          {-0.0714905202,0.053808742,0.0006279816,-0.0176817782}
      });
      Assert.assertEquals(0, expected.subtract(pseudoInverse).getNorm(), 1.0e-9);
    }

}

Other Java examples (source code examples)

Here is a short list of links related to this Java SingularValueSolverTest.java source code file:



my book on functional programming

 

new blog posts

 

Copyright 1998-2019 Alvin Alexander, alvinalexander.com
All Rights Reserved.

A percentage of advertising revenue from
pages under the /java/jwarehouse URI on this website is
paid back to open source projects.