alvinalexander.com | career | drupal | java | mac | mysql | perl | scala | uml | unix  

Commons Math example source code file (ContinuousDistributionAbstractTest.java)

This example Commons Math source code file (ContinuousDistributionAbstractTest.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

abstractcontinuousdistribution, continuousdistribution, continuousdistribution, continuousdistributionabstracttest, exception, exception, expecting, expecting, illegalargumentexception, illegalargumentexception, inconsistent, incorrect, override, testcase

The Commons Math ContinuousDistributionAbstractTest.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.distribution;

import junit.framework.TestCase;

import org.apache.commons.math.TestUtils;

/**
 * Abstract base class for {@link ContinuousDistribution} tests.
 * <p>
 * To create a concrete test class for a continuous distribution
 * implementation, first implement makeDistribution() to return a distribution
 * instance to use in tests. Then implement 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().  Default implementations
 * are provided for the makeInverseXxx methods that just invert the mapping
 * defined by the arrays returned by the makeCumulativeXxx methods.
 * <p>
 * makeCumulativeTestPoints() -- arguments used to test cumulative probabilities
 * makeCumulativeTestValues() -- expected cumulative probabilites
 * makeDensityTestValues() -- expected density values at cumulativeTestPoints
 * makeInverseCumulativeTestPoints() -- arguments used to test inverse cdf
 * 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.
 * <p>
 * Error tolerance can be overriden by implementing getTolerance().
 * <p>
 * Test data should be validated against reference tables or other packages
 * where possible, and the source of the reference data and/or validation
 * should be documented in the test cases.  A framework for validating
 * distribution data against R is included in the /src/test/R source tree.
 * <p>
 * See {@link NormalDistributionTest} and {@link ChiSquareDistributionTest}
 * for examples.
 *
 * @version $Revision: 924362 $ $Date: 2010-03-17 12:45:31 -0400 (Wed, 17 Mar 2010) $
 */
public abstract class ContinuousDistributionAbstractTest extends TestCase {

//-------------------- Private test instance data -------------------------
    /**  Distribution instance used to perform tests */
    private ContinuousDistribution distribution;

    /** Tolerance used in comparing expected and returned values */
    private double tolerance = 1E-4;

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

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

    //-------------------------------------------------------------------------

    /**
     * Constructor for ContinuousDistributionAbstractTest.
     * @param name
     */
    public ContinuousDistributionAbstractTest(String name) {
        super(name);
    }

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

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

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

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

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

    //---- Default implementations of inverse test data generation methods ----

    /** Creates the default inverse cumulative probability test input values */
    public double[] makeInverseCumulativeTestPoints() {
        return makeCumulativeTestValues();
    }

    /** Creates the default inverse cumulative probability density test expected values */
    public double[] makeInverseCumulativeTestValues() {
        return makeCumulativeTestPoints();
    }

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

    /**
     * Setup sets all test instance data to default values
     */
    @Override
    protected void setUp() throws Exception {
        super.setUp();
        distribution = makeDistribution();
        cumulativeTestPoints = makeCumulativeTestPoints();
        cumulativeTestValues = makeCumulativeTestValues();
        inverseCumulativeTestPoints = makeInverseCumulativeTestPoints();
        inverseCumulativeTestValues = makeInverseCumulativeTestValues();
        densityTestValues = makeDensityTestValues();
    }

    /**
     * Cleans up test instance data
     */
    @Override
    protected void tearDown() throws Exception {
        super.tearDown();
        distribution = null;
        cumulativeTestPoints = null;
        cumulativeTestValues = null;
        inverseCumulativeTestPoints = null;
        inverseCumulativeTestValues = null;
        densityTestValues = null;
    }

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

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

    /**
     * Verifies that density calculations match expected values
     */
    protected void verifyDensities() throws Exception {
        for (int i = 0; i < cumulativeTestPoints.length; i++) {
            TestUtils.assertEquals("Incorrect probability density value returned for "
                + cumulativeTestPoints[i], densityTestValues[i],
                 //TODO: remove cast when density(double) is added to ContinuousDistribution
                 ((AbstractContinuousDistribution) distribution).density(cumulativeTestPoints[i]),
                 getTolerance());
        }
    }

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

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

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

    /**
     * Verifies that density calculations return expected values
     * for default test instance data
     */
    public void testDensities() throws Exception {
        verifyDensities();
    }

    /**
     * Verifies that probability computations are consistent
     */
    public void testConsistency() throws Exception {
        for (int i=1; i < cumulativeTestPoints.length; i++) {

            // check that cdf(x, x) = 0
            TestUtils.assertEquals(0d,
               distribution.cumulativeProbability
                 (cumulativeTestPoints[i], cumulativeTestPoints[i]), tolerance);

            // check that P(a < X < b) = P(X < b) - P(X < a)
            double upper = Math.max(cumulativeTestPoints[i], cumulativeTestPoints[i -1]);
            double lower = Math.min(cumulativeTestPoints[i], cumulativeTestPoints[i -1]);
            double diff = distribution.cumulativeProbability(upper) -
                distribution.cumulativeProbability(lower);
            double direct = distribution.cumulativeProbability(lower, upper);
            TestUtils.assertEquals("Inconsistent cumulative probabilities for ("
                    + lower + "," + upper + ")", diff, direct, tolerance);
        }
    }

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

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

    /**
     * @param cumulativeTestPoints The cumulativeTestPoints to set.
     */
    protected void setCumulativeTestPoints(double[] 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;
    }

    protected double[] getDensityTestValues() {
        return densityTestValues;
    }

    protected void setDensityTestValues(double[] densityTestValues) {
        this.densityTestValues = densityTestValues;
    }

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

    /**
     * @param distribution The distribution to set.
     */
    protected void setDistribution(AbstractContinuousDistribution 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 double[] getInverseCumulativeTestValues() {
        return inverseCumulativeTestValues;
    }

    /**
     * @param inverseCumulativeTestValues The inverseCumulativeTestValues to set.
     */
    protected void setInverseCumulativeTestValues(double[] 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 Commons Math examples (source code examples)

Here is a short list of links related to this Commons Math ContinuousDistributionAbstractTest.java source code file:

... this post is sponsored by my books ...

#1 New Release!

FP Best Seller

 

new blog posts

 

Copyright 1998-2021 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.