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

Java example source code file (IntegerDistributionAbstractTest.java)

This example Java source code file (IntegerDistributionAbstractTest.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

abstractintegerdistribution, after, before, cumulative, expecting, incorrect, integerdistribution, integerdistributionabstracttest, inverse, mathillegalargumentexception, test, use

The IntegerDistributionAbstractTest.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.distribution;

import org.apache.commons.math3.TestUtils;
import org.apache.commons.math3.exception.MathIllegalArgumentException;
import org.apache.commons.math3.util.FastMath;
import org.junit.After;
import org.junit.Assert;
import org.junit.Before;
import org.junit.Test;

/**
 * Abstract base class for {@link IntegerDistribution} tests.
 * <p>
 * To create a concrete test class for an integer distribution implementation,
 *  implement makeDistribution() to return a distribution instance to use in
 *  tests and each of the test data generation methods below.  In each case, the
 *  test points and test values arrays returned represent parallel arrays of
 *  inputs and expected values for the distribution returned by makeDistribution().
 *  <p>
 *  makeDensityTestPoints() -- arguments used to test probability density calculation
 *  makeDensityTestValues() -- expected probability densities
 *  makeCumulativeTestPoints() -- arguments used to test cumulative probabilities
 *  makeCumulativeTestValues() -- expected cumulative probabilites
 *  makeInverseCumulativeTestPoints() -- arguments used to test inverse cdf evaluation
 *  makeInverseCumulativeTestValues() -- expected inverse cdf values
 * <p>
 *  To implement additional test cases with different distribution instances and test data,
 *  use the setXxx methods for the instance data in test cases and call the verifyXxx methods
 *  to verify results.
 *
 */
public abstract class IntegerDistributionAbstractTest {

//-------------------- Private test instance data -------------------------
    /** Discrete distribution instance used to perform tests */
    private IntegerDistribution distribution;

    /** Tolerance used in comparing expected and returned values */
    private double tolerance = 1E-12;

    /** Arguments used to test probability density calculations */
    private int[] densityTestPoints;

    /** Values used to test probability density calculations */
    private double[] densityTestValues;

    /** Values used to test logarithmic probability density calculations */
    private double[] logDensityTestValues;

    /** Arguments used to test cumulative probability density calculations */
    private int[] cumulativeTestPoints;

    /** Values used to test cumulative probability density calculations */
    private double[] cumulativeTestValues;

    /** Arguments used to test inverse cumulative probability density calculations */
    private double[] inverseCumulativeTestPoints;

    /** Values used to test inverse cumulative probability density calculations */
    private int[] inverseCumulativeTestValues;

    //-------------------- Abstract methods -----------------------------------

    /** Creates the default discrete distribution instance to use in tests. */
    public abstract IntegerDistribution makeDistribution();

    /** Creates the default probability density test input values */
    public abstract int[] makeDensityTestPoints();

    /** Creates the default probability density test expected values */
    public abstract double[] makeDensityTestValues();

    /** Creates the default logarithmic probability density test expected values.
     *
     * The default implementation simply computes the logarithm of all the values in
     * {@link #makeDensityTestValues()}.
     *
     * @return double[] the default logarithmic probability density test expected values.
     */
    public double[] makeLogDensityTestValues() {
        final double[] densityTestValues = makeDensityTestValues();
        final double[] logDensityTestValues = new double[densityTestValues.length];
        for (int i = 0; i < densityTestValues.length; i++) {
            logDensityTestValues[i] = FastMath.log(densityTestValues[i]);
        }
        return logDensityTestValues;
    }

    /** Creates the default cumulative probability density test input values */
    public abstract int[] makeCumulativeTestPoints();

    /** Creates the default cumulative probability density test expected values */
    public abstract double[] makeCumulativeTestValues();

    /** Creates the default inverse cumulative probability test input values */
    public abstract double[] makeInverseCumulativeTestPoints();

    /** Creates the default inverse cumulative probability density test expected values */
    public abstract int[] makeInverseCumulativeTestValues();

    //-------------------- Setup / tear down ----------------------------------

    /**
     * Setup sets all test instance data to default values
     */
    @Before
    public void setUp() {
        distribution = makeDistribution();
        densityTestPoints = makeDensityTestPoints();
        densityTestValues = makeDensityTestValues();
        logDensityTestValues = makeLogDensityTestValues();
        cumulativeTestPoints = makeCumulativeTestPoints();
        cumulativeTestValues = makeCumulativeTestValues();
        inverseCumulativeTestPoints = makeInverseCumulativeTestPoints();
        inverseCumulativeTestValues = makeInverseCumulativeTestValues();
    }

    /**
     * Cleans up test instance data
     */
    @After
    public void tearDown() {
        distribution = null;
        densityTestPoints = null;
        densityTestValues = null;
        logDensityTestValues = null;
        cumulativeTestPoints = null;
        cumulativeTestValues = null;
        inverseCumulativeTestPoints = null;
        inverseCumulativeTestValues = null;
    }

    //-------------------- Verification methods -------------------------------

    /**
     * Verifies that probability density calculations match expected values
     * using current test instance data
     */
    protected void verifyDensities() {
        for (int i = 0; i < densityTestPoints.length; i++) {
            Assert.assertEquals("Incorrect density value returned for " + densityTestPoints[i],
                    densityTestValues[i],
                    distribution.probability(densityTestPoints[i]), getTolerance());
        }
    }

    /**
     * Verifies that logarithmic probability density calculations match expected values
     * using current test instance data.
     */
    protected void verifyLogDensities() {
        for (int i = 0; i < densityTestPoints.length; i++) {
            // FIXME: when logProbability methods are added to IntegerDistribution in 4.0, remove cast below
            Assert.assertEquals("Incorrect log density value returned for " + densityTestPoints[i],
                    logDensityTestValues[i],
                    ((AbstractIntegerDistribution) distribution).logProbability(densityTestPoints[i]), tolerance);
        }
    }

    /**
     * Verifies that cumulative probability density calculations match expected values
     * using current test instance data
     */
    protected void verifyCumulativeProbabilities() {
        for (int i = 0; i < cumulativeTestPoints.length; i++) {
            Assert.assertEquals("Incorrect cumulative probability value returned for " + cumulativeTestPoints[i],
                    cumulativeTestValues[i],
                    distribution.cumulativeProbability(cumulativeTestPoints[i]), getTolerance());
        }
    }


    /**
     * Verifies that inverse cumulative probability density calculations match expected values
     * using current test instance data
     */
    protected void verifyInverseCumulativeProbabilities() {
        for (int i = 0; i < inverseCumulativeTestPoints.length; i++) {
            Assert.assertEquals("Incorrect inverse cumulative probability value returned for "
                    + inverseCumulativeTestPoints[i], inverseCumulativeTestValues[i],
                    distribution.inverseCumulativeProbability(inverseCumulativeTestPoints[i]));
        }
    }

    //------------------------ Default test cases -----------------------------

    /**
     * Verifies that probability density calculations match expected values
     * using default test instance data
     */
    @Test
    public void testDensities() {
        verifyDensities();
    }

    /**
     * Verifies that logarithmic probability density calculations match expected values
     * using default test instance data
     */
    @Test
    public void testLogDensities() {
        verifyLogDensities();
    }

    /**
     * Verifies that cumulative probability density calculations match expected values
     * using default test instance data
     */
    @Test
    public void testCumulativeProbabilities() {
        verifyCumulativeProbabilities();
    }

    /**
     * Verifies that inverse cumulative probability density calculations match expected values
     * using default test instance data
     */
    @Test
    public void testInverseCumulativeProbabilities() {
        verifyInverseCumulativeProbabilities();
    }

    @Test
    public void testConsistencyAtSupportBounds() {
        final int lower = distribution.getSupportLowerBound();
        Assert.assertEquals("Cumulative probability mmust be 0 below support lower bound.",
                0.0, distribution.cumulativeProbability(lower - 1), 0.0);
        Assert.assertEquals("Cumulative probability of support lower bound must be equal to probability mass at this point.",
                distribution.probability(lower), distribution.cumulativeProbability(lower), getTolerance());
        Assert.assertEquals("Inverse cumulative probability of 0 must be equal to support lower bound.",
                lower, distribution.inverseCumulativeProbability(0.0));

        final int upper = distribution.getSupportUpperBound();
        if (upper != Integer.MAX_VALUE)
            Assert.assertEquals("Cumulative probability of support upper bound must be equal to 1.",
                    1.0, distribution.cumulativeProbability(upper), 0.0);
        Assert.assertEquals("Inverse cumulative probability of 1 must be equal to support upper bound.",
                upper, distribution.inverseCumulativeProbability(1.0));
    }

    /**
     * Verifies that illegal arguments are correctly handled
     */
    @Test
    public void testIllegalArguments() {
        try {
            distribution.cumulativeProbability(1, 0);
            Assert.fail("Expecting MathIllegalArgumentException for bad cumulativeProbability interval");
        } catch (MathIllegalArgumentException ex) {
            // expected
        }
        try {
            distribution.inverseCumulativeProbability(-1);
            Assert.fail("Expecting MathIllegalArgumentException for p = -1");
        } catch (MathIllegalArgumentException ex) {
            // expected
        }
        try {
            distribution.inverseCumulativeProbability(2);
            Assert.fail("Expecting MathIllegalArgumentException for p = 2");
        } catch (MathIllegalArgumentException ex) {
            // expected
        }
    }

    /**
     * Test sampling
     */
    @Test
    public void testSampling() {
        int[] densityPoints = makeDensityTestPoints();
        double[] densityValues = makeDensityTestValues();
        int sampleSize = 1000;
        int length = TestUtils.eliminateZeroMassPoints(densityPoints, densityValues);
        AbstractIntegerDistribution distribution = (AbstractIntegerDistribution) makeDistribution();
        double[] expectedCounts = new double[length];
        long[] observedCounts = new long[length];
        for (int i = 0; i < length; i++) {
            expectedCounts[i] = sampleSize * densityValues[i];
        }
        distribution.reseedRandomGenerator(1000); // Use fixed seed
        int[] sample = distribution.sample(sampleSize);
        for (int i = 0; i < sampleSize; i++) {
          for (int j = 0; j < length; j++) {
              if (sample[i] == densityPoints[j]) {
                  observedCounts[j]++;
              }
          }
        }
        TestUtils.assertChiSquareAccept(densityPoints, expectedCounts, observedCounts, .001);
    }

    //------------------ Getters / Setters for test instance data -----------
    /**
     * @return Returns the cumulativeTestPoints.
     */
    protected int[] getCumulativeTestPoints() {
        return cumulativeTestPoints;
    }

    /**
     * @param cumulativeTestPoints The cumulativeTestPoints to set.
     */
    protected void setCumulativeTestPoints(int[] cumulativeTestPoints) {
        this.cumulativeTestPoints = cumulativeTestPoints;
    }

    /**
     * @return Returns the cumulativeTestValues.
     */
    protected double[] getCumulativeTestValues() {
        return cumulativeTestValues;
    }

    /**
     * @param cumulativeTestValues The cumulativeTestValues to set.
     */
    protected void setCumulativeTestValues(double[] cumulativeTestValues) {
        this.cumulativeTestValues = cumulativeTestValues;
    }

    /**
     * @return Returns the densityTestPoints.
     */
    protected int[] getDensityTestPoints() {
        return densityTestPoints;
    }

    /**
     * @param densityTestPoints The densityTestPoints to set.
     */
    protected void setDensityTestPoints(int[] densityTestPoints) {
        this.densityTestPoints = densityTestPoints;
    }

    /**
     * @return Returns the densityTestValues.
     */
    protected double[] getDensityTestValues() {
        return densityTestValues;
    }

    /**
     * @param densityTestValues The densityTestValues to set.
     */
    protected void setDensityTestValues(double[] densityTestValues) {
        this.densityTestValues = densityTestValues;
    }

    /**
     * @return Returns the distribution.
     */
    protected IntegerDistribution getDistribution() {
        return distribution;
    }

    /**
     * @param distribution The distribution to set.
     */
    protected void setDistribution(IntegerDistribution distribution) {
        this.distribution = distribution;
    }

    /**
     * @return Returns the inverseCumulativeTestPoints.
     */
    protected double[] getInverseCumulativeTestPoints() {
        return inverseCumulativeTestPoints;
    }

    /**
     * @param inverseCumulativeTestPoints The inverseCumulativeTestPoints to set.
     */
    protected void setInverseCumulativeTestPoints(double[] inverseCumulativeTestPoints) {
        this.inverseCumulativeTestPoints = inverseCumulativeTestPoints;
    }

    /**
     * @return Returns the inverseCumulativeTestValues.
     */
    protected int[] getInverseCumulativeTestValues() {
        return inverseCumulativeTestValues;
    }

    /**
     * @param inverseCumulativeTestValues The inverseCumulativeTestValues to set.
     */
    protected void setInverseCumulativeTestValues(int[] inverseCumulativeTestValues) {
        this.inverseCumulativeTestValues = inverseCumulativeTestValues;
    }

    /**
     * @return Returns the tolerance.
     */
    protected double getTolerance() {
        return tolerance;
    }

    /**
     * @param tolerance The tolerance to set.
     */
    protected void setTolerance(double tolerance) {
        this.tolerance = tolerance;
    }

}

Other Java examples (source code examples)

Here is a short list of links related to this Java IntegerDistributionAbstractTest.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.