org.moeaframework.util.statistics.MannWhitneyUTestTest.java Source code

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Here is the source code for org.moeaframework.util.statistics.MannWhitneyUTestTest.java

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/* Copyright 2009-2015 David Hadka
 *
 * This file is part of the MOEA Framework.
 *
 * The MOEA Framework 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 3 of the License, or (at your
 * option) any later version.
 *
 * The MOEA Framework 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 the MOEA Framework.  If not, see <http://www.gnu.org/licenses/>.
 */
package org.moeaframework.util.statistics;

import org.junit.Assert;
import org.junit.Test;
import org.moeaframework.TestThresholds;
import org.moeaframework.core.PRNG;
import org.moeaframework.core.Settings;

/**
 * Tests the {@link MannWhitneyUTest} class.
 */
public class MannWhitneyUTestTest {

    /**
     * Test from Sheskin (2004) in Chapter 12.
     */
    @Test
    public void testExample1() {
        MannWhitneyUTest test = new MannWhitneyUTest();
        test.add(11, 0);
        test.add(1, 0);
        test.add(0, 0);
        test.add(2, 0);
        test.add(0, 0);
        test.add(11, 1);
        test.add(11, 1);
        test.add(5, 1);
        test.add(8, 1);
        test.add(4, 1);

        Assert.assertFalse(test.test(0.05));
    }

    /**
     * This is the Tortoise vs. Hare example from
     * <a href="http://en.wikipedia.org/wiki/Mann%E2%80%93Whitney_U">
     * Wikipedia</a>
     */
    @Test
    public void testExample2() {
        MannWhitneyUTest test = new MannWhitneyUTest();

        for (int i = 0; i <= 8; i++) {
            test.add(i, 0);
        }

        for (int i = 9; i <= 18; i++) {
            test.add(i, 1);
        }

        for (int i = 19; i <= 28; i++) {
            test.add(i, 0);
        }

        for (int i = 29; i <= 37; i++) {
            test.add(i, 1);
        }

        Assert.assertTrue(test.test(0.05));
        Assert.assertEquals(100, test.lastU, TestThresholds.STATISTICS_EPS);
    }

    /**
     * Commons Math 3.0 introduced their own MannWhitneyUTest class.  The
     * Commons Math implementation only supports the normal approximation for
     * the U statistic, and will be inaccurate with small sample sizes.
     */
    @Test
    public void testCommonsMath() {
        double[] d1 = new double[100];
        double[] d2 = new double[100];

        for (int i = 0; i < 100; i++) {
            d1[i] = PRNG.nextGaussian(10.0, 5.0);
            d2[i] = PRNG.nextGaussian(11.0, 6.0);
        }

        MannWhitneyUTest test1 = new MannWhitneyUTest();
        test1.addAll(d1, 0);
        test1.addAll(d2, 1);
        test1.test(0.05);
        double u1 = test1.lastU;

        org.apache.commons.math3.stat.inference.MannWhitneyUTest test2 = new org.apache.commons.math3.stat.inference.MannWhitneyUTest();
        double u2 = test2.mannWhitneyU(d1, d2);

        Assert.assertEquals(100 * 100 - u2, u1, Settings.EPS);
    }

    @Test
    public void testAllEqual() {
        MannWhitneyUTest test = new MannWhitneyUTest();
        test.add(10, 0);
        test.add(10, 0);
        test.add(10, 0);
        test.add(10, 0);
        test.add(10, 0);
        test.add(10, 1);
        test.add(10, 1);
        test.add(10, 1);
        test.add(10, 1);
        test.add(10, 1);

        Assert.assertFalse(test.test(0.05));
        Assert.assertFalse(test.test(0.01));
    }

}