/* ====================================================================
* The Apache Software License, Version 1.1
*
* Copyright (c) 2003-2004 The Apache Software Foundation. All rights
* reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* 1. Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
*
* 2. Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in
* the documentation and/or other materials provided with the
* distribution.
*
* 3. The end-user documentation included with the redistribution, if
* any, must include the following acknowledgement:
* "This product includes software developed by the
* Apache Software Foundation (http://www.apache.org/)."
* Alternately, this acknowledgement may appear in the software itself,
* if and wherever such third-party acknowledgements normally appear.
*
* 4. The names "The Jakarta Project", "Commons", and "Apache Software
* Foundation" must not be used to endorse or promote products derived
* from this software without prior written permission. For written
* permission, please contact apache@apache.org.
*
* 5. Products derived from this software may not be called "Apache"
* nor may "Apache" appear in their name without prior written
* permission of the Apache Software Foundation.
*
* THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED
* WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
* OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE APACHE SOFTWARE FOUNDATION OR
* ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
* SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
* LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
* USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
* OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
* SUCH DAMAGE.
* ====================================================================
*
* This software consists of voluntary contributions made by many
* individuals on behalf of the Apache Software Foundation. For more
* information on the Apache Software Foundation, please see
* <http://www.apache.org/>.
*/
package org.apache.commons.math.random;
import junit.framework.Test;
import junit.framework.TestCase;
import junit.framework.TestSuite;
import java.io.File;
import java.net.URL;
import java.net.URLDecoder;
import org.apache.commons.math.stat.DescriptiveStatistics;
import org.apache.commons.math.stat.StorelessDescriptiveStatisticsImpl;
/**
* Test cases for the EmpiricalDistribution class
*
* @version $Revision: 1.10 $ $Date: 2004/01/15 05:22:08 $
*/
public final class EmpiricalDistributionTest extends TestCase {
protected EmpiricalDistribution empiricalDistribution = null;
protected File file = null;
protected URL url = null;
public EmpiricalDistributionTest(String name) {
super(name);
}
public void setUp() {
empiricalDistribution = new EmpiricalDistributionImpl(100);
url = getClass().getResource("testData.txt");
String fileName = URLDecoder.decode(url.getFile());
file = new File(fileName);
}
public static Test suite() {
TestSuite suite = new TestSuite(EmpiricalDistributionTest.class);
suite.setName("EmpiricalDistribution Tests");
return suite;
}
/**
* Test EmpiricalDistrbution.load() using sample data file.<br>
* Check that the sampleCount, mu and sigma match data in
* the sample data file.
*/
public void testLoad() throws Exception {
empiricalDistribution.load(url);
// testData File has 10000 values, with mean ~ 5.0, std dev ~ 1
// Make sure that loaded distribution matches this
assertEquals(empiricalDistribution.getSampleStats().getN(),1000,10E-7);
//TODO: replace with statistical tests
assertEquals
(empiricalDistribution.getSampleStats().getMean(),
5.069831575018909,10E-7);
assertEquals
(empiricalDistribution.getSampleStats().getStandardDeviation(),
1.0173699343977738,10E-7);
}
/**
* Generate 1000 random values and make sure they look OK.<br>
* Note that there is a non-zero (but very small) probability that
* these tests will fail even if the code is working as designed.
*/
public void testNext() throws Exception {
tstGen(0.1);
}
/**
* Make sure exception thrown if digest getNext is attempted
* before loading empiricalDistribution.
*/
public void testNexFail() {
try {
empiricalDistribution.getNextValue();
fail("Expecting IllegalStateException");
} catch (IllegalStateException ex) {;}
}
/**
* Make sure we can handle a grid size that is too fine
*/
public void testGridTooFine() throws Exception {
empiricalDistribution = new EmpiricalDistributionImpl(10000);
tstGen(0.1);
}
/**
* How about too fat?
*/
public void testGridTooFat() throws Exception {
empiricalDistribution = new EmpiricalDistributionImpl(1);
tstGen(5); // ridiculous tolerance; but ridiculous grid size
// really just checking to make sure we do not bomb
}
private void tstGen(double tolerance)throws Exception {
empiricalDistribution.load(file);
DescriptiveStatistics stats = new StorelessDescriptiveStatisticsImpl();
for (int i = 1; i < 1000; i++) {
stats.addValue(empiricalDistribution.getNextValue());
}
//TODO: replace these with statistical tests -- refactor as necessary
assertEquals("mean", stats.getMean(),5.069831575018909,tolerance);
assertEquals
("std dev", stats.getStandardDeviation(),1.0173699343977738,tolerance);
}
}