Commons Math example source code file (EigenSolverTest.java)

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

Java - Commons Math tags/keywords

decompositionsolver, decompositionsolver, eigendecompositionimpl, eigendecompositionimpl, eigensolvertest, exception, illegalargumentexception, invalidmatrixexception, override, random, random, realmatrix, realmatrix, testcase, util

The Commons Math EigenSolverTest.java 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.math.linear;

import java.util.Random;

import junit.framework.TestCase;

import org.apache.commons.math.util.MathUtils;

public class EigenSolverTest extends TestCase {

    private double[] refValues;
    private RealMatrix matrix;

    public EigenSolverTest(String name) {
        super(name);
    }

    /** test non invertible matrix */
    public void testNonInvertible() {
        Random r = new Random(9994100315209l);
        RealMatrix m =
            EigenDecompositionImplTest.createTestMatrix(r, new double[] { 1.0, 0.0, -1.0, -2.0, -3.0 });
        DecompositionSolver es = new EigenDecompositionImpl(m, MathUtils.SAFE_MIN).getSolver();
        assertFalse(es.isNonSingular());
        try {
            es.getInverse();
            fail("an exception should have been thrown");
        } catch (InvalidMatrixException ime) {
            // expected behavior
        } catch (Exception e) {
            fail("wrong exception caught");
        }
    }

    /** test invertible matrix */
    public void testInvertible() {
        Random r = new Random(9994100315209l);
        RealMatrix m =
            EigenDecompositionImplTest.createTestMatrix(r, new double[] { 1.0, 0.5, -1.0, -2.0, -3.0 });
        DecompositionSolver es = new EigenDecompositionImpl(m, MathUtils.SAFE_MIN).getSolver();
        assertTrue(es.isNonSingular());
        RealMatrix inverse = es.getInverse();
        RealMatrix error =
            m.multiply(inverse).subtract(MatrixUtils.createRealIdentityMatrix(m.getRowDimension()));
        assertEquals(0, error.getNorm(), 4.0e-15);
    }

    /** test solve dimension errors */
    public void testSolveDimensionErrors() {
        DecompositionSolver es = new EigenDecompositionImpl(matrix, MathUtils.SAFE_MIN).getSolver();
        RealMatrix b = MatrixUtils.createRealMatrix(new double[2][2]);
        try {
            es.solve(b);
            fail("an exception should have been thrown");
        } catch (IllegalArgumentException iae) {
            // expected behavior
        } catch (Exception e) {
            fail("wrong exception caught");
        }
        try {
            es.solve(b.getColumn(0));
            fail("an exception should have been thrown");
        } catch (IllegalArgumentException iae) {
            // expected behavior
        } catch (Exception e) {
            fail("wrong exception caught");
        }
        try {
            es.solve(new ArrayRealVectorTest.RealVectorTestImpl(b.getColumn(0)));
            fail("an exception should have been thrown");
        } catch (IllegalArgumentException iae) {
            // expected behavior
        } catch (Exception e) {
            fail("wrong exception caught");
        }
    }

    /** test solve */
    public void testSolve() {
        RealMatrix m = MatrixUtils.createRealMatrix(new double[][] {
                { 91,  5, 29, 32, 40, 14 },
                {  5, 34, -1,  0,  2, -1 },
                { 29, -1, 12,  9, 21,  8 },
                { 32,  0,  9, 14,  9,  0 },
                { 40,  2, 21,  9, 51, 19 },
                { 14, -1,  8,  0, 19, 14 }
        });
        DecompositionSolver es = new EigenDecompositionImpl(m, MathUtils.SAFE_MIN).getSolver();
        RealMatrix b = MatrixUtils.createRealMatrix(new double[][] {
                { 1561, 269, 188 },
                {   69, -21,  70 },
                {  739, 108,  63 },
                {  324,  86,  59 },
                { 1624, 194, 107 },
                {  796,  69,  36 }
        });
        RealMatrix xRef = MatrixUtils.createRealMatrix(new double[][] {
                { 1,   2, 1 },
                { 2,  -1, 2 },
                { 4,   2, 3 },
                { 8,  -1, 0 },
                { 16,  2, 0 },
                { 32, -1, 0 }
        });

        // using RealMatrix
        RealMatrix solution=es.solve(b);
        assertEquals(0, solution.subtract(xRef).getNorm(), 2.5e-12);

        // using double[]
        for (int i = 0; i < b.getColumnDimension(); ++i) {
            assertEquals(0,
                         new ArrayRealVector(es.solve(b.getColumn(i))).subtract(xRef.getColumnVector(i)).getNorm(),
                         2.0e-11);
        }

        // using Array2DRowRealMatrix
        for (int i = 0; i < b.getColumnDimension(); ++i) {
            assertEquals(0,
                         es.solve(b.getColumnVector(i)).subtract(xRef.getColumnVector(i)).getNorm(),
                         2.0e-11);
        }

        // using RealMatrix with an alternate implementation
        for (int i = 0; i < b.getColumnDimension(); ++i) {
            ArrayRealVectorTest.RealVectorTestImpl v =
                new ArrayRealVectorTest.RealVectorTestImpl(b.getColumn(i));
            assertEquals(0,
                         es.solve(v).subtract(xRef.getColumnVector(i)).getNorm(),
                         2.0e-11);
        }

    }

    @Override
    public void setUp() {
        refValues = new double[] {
                2.003, 2.002, 2.001, 1.001, 1.000, 0.001
        };
        matrix = EigenDecompositionImplTest.createTestMatrix(new Random(35992629946426l), refValues);
    }

    @Override
    public void tearDown() {
        refValues = null;
        matrix    = null;
    }

}