Removed old Univariate tests
git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@140869 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Tim O'Brien
parent
e9488d7cf6
commit
429a652114
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@ -1,199 +0,0 @@
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/* ====================================================================
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* The Apache Software License, Version 1.1
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*
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* Copyright (c) 2003 The Apache Software Foundation. All rights
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* reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* 1. Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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*
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* 2. Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in
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* the documentation and/or other materials provided with the
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* distribution.
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*
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* 3. The end-user documentation included with the redistribution, if
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* any, must include the following acknowlegement:
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* "This product includes software developed by the
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* Apache Software Foundation (http://www.apache.org/)."
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* Alternately, this acknowlegement may appear in the software itself,
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* if and wherever such third-party acknowlegements normally appear.
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*
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* 4. The names "The Jakarta Project", "Commons", and "Apache Software
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* Foundation" must not be used to endorse or promote products derived
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* from this software without prior written permission. For written
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* permission, please contact apache@apache.org.
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*
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* 5. Products derived from this software may not be called "Apache"
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* nor may "Apache" appear in their names without prior written
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* permission of the Apache Software Foundation.
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*
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* THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED
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* WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
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* OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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* DISCLAIMED. IN NO EVENT SHALL THE APACHE SOFTWARE FOUNDATION OR
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* ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
|
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* SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
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* LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
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* USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
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* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
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* OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
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* SUCH DAMAGE.
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* ====================================================================
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*
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* This software consists of voluntary contributions made by many
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* individuals on behalf of the Apache Software Foundation. For more
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* information on the Apache Software Foundation, please see
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* <http://www.apache.org/>.
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*/
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package org.apache.commons.math;
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import java.util.ArrayList;
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import java.util.List;
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import junit.framework.Test;
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import junit.framework.TestCase;
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import junit.framework.TestSuite;
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import org.apache.commons.math.beans.*;
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/**
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* Test cases for the {@link BeanListUnivariateImpl} class.
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*
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* @author <a href="mailto:tobrien@apache.org">Tim O'Brien</a>
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* @version $Revision: 1.1 $ $Date: 2003/05/29 19:41:31 $
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*/
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public final class BeanListUnivariateImplTest extends TestCase {
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private List patientList = null;
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private double tolerance = Double.MIN_VALUE;
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public BeanListUnivariateImplTest(String name) {
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super(name);
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}
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public void setUp() {
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patientList = new ArrayList();
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// Create and add patient bean 1
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VitalStats vs1 = new VitalStats( new Double(120.0),
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new Double(96.4) );
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Patient p1 = new Patient( vs1, new Integer( 35 ) );
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patientList.add( p1 );
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// Create and add patient bean 2
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VitalStats vs2 = new VitalStats( new Double(70.0),
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new Double(97.4) );
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Patient p2 = new Patient( vs2, new Integer( 23 ) );
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patientList.add( p2 );
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// Create and add patient bean 3
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VitalStats vs3 = new VitalStats( new Double(90.0),
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new Double(98.6) );
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Patient p3 = new Patient( vs3, new Integer( 42 ) );
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patientList.add( p3 );
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}
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public static Test suite() {
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TestSuite suite = new TestSuite(BeanListUnivariateImplTest.class);
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suite.setName("Freq Tests");
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return suite;
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}
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/** test stats */
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public void testStats() {
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StoreUnivariate u = new BeanListUnivariateImpl( patientList );
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assertEquals("total count",3,u.getN(),tolerance);
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u.clear();
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assertEquals("total count",0,u.getN(),tolerance);
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}
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public void testPropStats() {
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StoreUnivariate heartU = new BeanListUnivariateImpl( patientList,
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"vitalStats.heartRate" );
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assertEquals( "Mean heart rate unexpected", 93.333,
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heartU.getMean(), 0.001 );
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assertEquals( "Max heart rate unexpected", 120.0,
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heartU.getMax(), 0.001 );
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StoreUnivariate ageU = new BeanListUnivariateImpl( patientList,
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"age" );
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assertEquals( "Mean age unexpected", 33.333,
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ageU.getMean(), 0.001 );
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assertEquals( "Max age unexpected", 42.0,
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ageU.getMax(), 0.001 );
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}
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/* public void testN0andN1Conditions() throws Exception {
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List list = new ArrayList();
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StoreUnivariate u = new ListUnivariateImpl( list );
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assertTrue("Mean of n = 0 set should be NaN", Double.isNaN( u.getMean() ) );
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assertTrue("Standard Deviation of n = 0 set should be NaN", Double.isNaN( u.getStandardDeviation() ) );
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assertTrue("Variance of n = 0 set should be NaN", Double.isNaN(u.getVariance() ) );
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list.add( new Double(one));
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assertTrue( "Mean of n = 1 set should be value of single item n1", u.getMean() == one);
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assertTrue( "StdDev of n = 1 set should be zero, instead it is: " + u.getStandardDeviation(), u.getStandardDeviation() == 0);
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assertTrue( "Variance of n = 1 set should be zero", u.getVariance() == 0);
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}
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public void testSkewAndKurtosis() {
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StoreUnivariate u = new StoreUnivariateImpl();
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double[] testArray = { 12.5, 12, 11.8, 14.2, 14.9, 14.5, 21, 8.2, 10.3, 11.3, 14.1,
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9.9, 12.2, 12, 12.1, 11, 19.8, 11, 10, 8.8, 9, 12.3 };
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for( int i = 0; i < testArray.length; i++) {
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u.addValue( testArray[i]);
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}
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assertEquals("mean", 12.40455, u.getMean(), 0.0001);
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assertEquals("variance", 10.00236, u.getVariance(), 0.0001);
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assertEquals("skewness", 1.437424, u.getSkewness(), 0.0001);
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assertEquals("kurtosis", 2.37719, u.getKurtosis(), 0.0001);
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}
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public void testProductAndGeometricMean() throws Exception {
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ListUnivariateImpl u = new ListUnivariateImpl(new ArrayList());
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u.setWindowSize(10);
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u.addValue( 1.0 );
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u.addValue( 2.0 );
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u.addValue( 3.0 );
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u.addValue( 4.0 );
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assertEquals( "Product not expected", 24.0, u.getProduct(), Double.MIN_VALUE );
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assertEquals( "Geometric mean not expected", 2.213364, u.getGeometricMean(), 0.00001 );
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// Now test rolling - UnivariateImpl should discount the contribution
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// of a discarded element
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for( int i = 0; i < 10; i++ ) {
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u.addValue( i + 2 );
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}
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// Values should be (2,3,4,5,6,7,8,9,10,11)
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assertEquals( "Product not expected", 39916800.0, u.getProduct(), 0.00001 );
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assertEquals( "Geometric mean not expected", 5.755931, u.getGeometricMean(), 0.00001 );
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} */
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}
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@ -1,226 +0,0 @@
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/* ====================================================================
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* The Apache Software License, Version 1.1
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*
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* Copyright (c) 2003 The Apache Software Foundation. All rights
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* reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* 1. Redistributions of source code must retain the above copyright
|
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* notice, this list of conditions and the following disclaimer.
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*
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* 2. Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in
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* the documentation and/or other materials provided with the
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* distribution.
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*
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* 3. The end-user documentation included with the redistribution, if
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* any, must include the following acknowlegement:
|
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||||||
* "This product includes software developed by the
|
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||||||
* Apache Software Foundation (http://www.apache.org/)."
|
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||||||
* Alternately, this acknowlegement may appear in the software itself,
|
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* if and wherever such third-party acknowlegements normally appear.
|
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||||||
*
|
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* 4. The names "The Jakarta Project", "Commons", and "Apache Software
|
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* Foundation" must not be used to endorse or promote products derived
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* from this software without prior written permission. For written
|
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* permission, please contact apache@apache.org.
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*
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* 5. Products derived from this software may not be called "Apache"
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* nor may "Apache" appear in their names without prior written
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* permission of the Apache Software Foundation.
|
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*
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* THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED
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* WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
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* OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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* DISCLAIMED. IN NO EVENT SHALL THE APACHE SOFTWARE FOUNDATION OR
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* ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
|
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* SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
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* LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
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* USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
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* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
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* OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
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* SUCH DAMAGE.
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* ====================================================================
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*
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* This software consists of voluntary contributions made by many
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* individuals on behalf of the Apache Software Foundation. For more
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* information on the Apache Software Foundation, please see
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* <http://www.apache.org/>.
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*/
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package org.apache.commons.math;
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import junit.framework.Test;
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import junit.framework.TestCase;
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import junit.framework.TestSuite;
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/**
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* Test cases for the TestStatistic class.
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*
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* @author Phil Steitz
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* @version $Revision: 1.1 $ $Date: 2003/05/26 02:11:50 $
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*/
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public final class BivariateRegressionTest extends TestCase {
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/*
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* NIST "Norris" refernce data set from
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* http://www.itl.nist.gov/div898/strd/lls/data/LINKS/DATA/Norris.dat
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* Strangely, order is {y,x}
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*/
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private double[][] data = {{0.1,0.2},{338.8,337.4},{118.1,118.2},
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{888.0,884.6},{9.2,10.1},{228.1,226.5},{668.5,666.3},{998.5,996.3},
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{449.1,448.6},{778.9,777.0},{559.2,558.2},{0.3,0.4},{0.1,0.6},
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{778.1,775.5},{668.8,666.9},{339.3,338.0},{448.9,447.5},{10.8,11.6},
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{557.7,556.0},{228.3,228.1},{998.0,995.8},{888.8,887.6},{119.6,120.2},
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{0.3,0.3},{0.6,0.3},{557.6,556.8},{339.3,339.1},{888.0,887.2},
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{998.5,999.0},{778.9,779.0},{10.2,11.1},{117.6,118.3},{228.9,229.2},
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{668.4,669.1},{449.2,448.9},{0.2,0.5}};
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/*
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* Correlation example from
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* http://www.xycoon.com/correlation.htm
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*/
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private double[][] corrData = {{101.0,99.2},{100.1,99.0},{100.0,100.0},
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{90.6,111.6},{86.5,122.2},{89.7,117.6},{90.6,121.1},{82.8,136.0},
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{70.1,154.2},{65.4,153.6},{61.3,158.5},{62.5,140.6},{63.6,136.2},
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{52.6,168.0},{59.7,154.3},{59.5,149.0},{61.3,165.5}};
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public BivariateRegressionTest(String name) {
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super(name);
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}
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public void setUp() {
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}
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public static Test suite() {
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TestSuite suite = new TestSuite(BivariateRegressionTest.class);
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suite.setName("BivariateRegression Tests");
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return suite;
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}
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public void testNorris() {
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BivariateRegression regression = new BivariateRegression();
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for (int i = 0; i < data.length; i++) {
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regression.addData(data[i][1],data[i][0]);
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}
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assertEquals("slope",1.00211681802045,
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regression.getSlope(),10E-12);
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assertEquals("slope std err",0.429796848199937E-03,
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regression.getSlopeStdErr(),10E-12);
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assertEquals("number of observations",36,regression.getN());
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assertEquals("intercept", -0.262323073774029,
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regression.getIntercept(),10E-12);
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assertEquals("std err intercept", 0.232818234301152,
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regression.getInterceptStdErr(),10E-12);
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assertEquals("r-square",0.999993745883712,
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regression.getRSquare(),10E-12);
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assertEquals("SSR",4255954.13232369,
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regression.getRegressionSumSquares(),10E-8);
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assertEquals("MSE",0.782864662630069,
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regression.getMeanSquareError(),10E-8);
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assertEquals("SSE",26.6173985294224,
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regression.getSumSquaredErrors(),10E-8);
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assertEquals("predict(0)",-0.262323073774029,
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regression.predict(0),10E-12);
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assertEquals("predict(1)",1.00211681802045-0.262323073774029,
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regression.predict(1),10E-11);
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}
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public void testCorr() {
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BivariateRegression regression = new BivariateRegression();
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regression.addData(corrData);
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assertEquals("number of observations",17,regression.getN());
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assertEquals("r-square",.896123,
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regression.getRSquare(),10E-6);
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assertEquals("r",-.946638,
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regression.getR(),10E-6);
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}
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public void testNaNs() {
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BivariateRegression regression = new BivariateRegression();
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assertTrue("intercept not NaN",Double.isNaN(regression.getIntercept()));
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assertTrue("slope not NaN",Double.isNaN(regression.getSlope()));
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assertTrue("slope std err not NaN",
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Double.isNaN(regression.getSlopeStdErr()));
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assertTrue("intercept std err not NaN",
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Double.isNaN(regression.getInterceptStdErr()));
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assertTrue("MSE not NaN",Double.isNaN(regression.getMeanSquareError()));
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assertTrue("e not NaN",Double.isNaN(regression.getR()));
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|
||||||
assertTrue("r-square not NaN",Double.isNaN(regression.getRSquare()));
|
|
||||||
assertTrue("RSS not NaN",
|
|
||||||
Double.isNaN(regression.getRegressionSumSquares()));
|
|
||||||
assertTrue("SSE not NaN",Double.isNaN(regression.getSumSquaredErrors()));
|
|
||||||
assertTrue("SSTO not NaN",Double.isNaN(regression.getTotalSumSquares()));
|
|
||||||
assertTrue("predict not NaN",Double.isNaN(regression.predict(0)));
|
|
||||||
|
|
||||||
regression.addData(1,2);
|
|
||||||
regression.addData(1,3);
|
|
||||||
|
|
||||||
// No x variation, so these should still blow...
|
|
||||||
assertTrue("intercept not NaN",Double.isNaN(regression.getIntercept()));
|
|
||||||
assertTrue("slope not NaN",Double.isNaN(regression.getSlope()));
|
|
||||||
assertTrue("slope std err not NaN",
|
|
||||||
Double.isNaN(regression.getSlopeStdErr()));
|
|
||||||
assertTrue("intercept std err not NaN",
|
|
||||||
Double.isNaN(regression.getInterceptStdErr()));
|
|
||||||
assertTrue("MSE not NaN",Double.isNaN(regression.getMeanSquareError()));
|
|
||||||
assertTrue("e not NaN",Double.isNaN(regression.getR()));
|
|
||||||
assertTrue("r-square not NaN",Double.isNaN(regression.getRSquare()));
|
|
||||||
assertTrue("RSS not NaN",
|
|
||||||
Double.isNaN(regression.getRegressionSumSquares()));
|
|
||||||
assertTrue("SSE not NaN",Double.isNaN(regression.getSumSquaredErrors()));
|
|
||||||
assertTrue("predict not NaN",Double.isNaN(regression.predict(0)));
|
|
||||||
|
|
||||||
// but SSTO should be OK
|
|
||||||
assertTrue("SSTO NaN",!Double.isNaN(regression.getTotalSumSquares()));
|
|
||||||
|
|
||||||
regression = new BivariateRegression();
|
|
||||||
|
|
||||||
regression.addData(1,2);
|
|
||||||
regression.addData(3,3);
|
|
||||||
|
|
||||||
// All should be OK except MSE, s(b0), s(b1) which need one more df
|
|
||||||
assertTrue("interceptNaN",!Double.isNaN(regression.getIntercept()));
|
|
||||||
assertTrue("slope NaN",!Double.isNaN(regression.getSlope()));
|
|
||||||
assertTrue("slope std err not NaN",
|
|
||||||
Double.isNaN(regression.getSlopeStdErr()));
|
|
||||||
assertTrue("intercept std err not NaN",
|
|
||||||
Double.isNaN(regression.getInterceptStdErr()));
|
|
||||||
assertTrue("MSE not NaN",Double.isNaN(regression.getMeanSquareError()));
|
|
||||||
assertTrue("r NaN",!Double.isNaN(regression.getR()));
|
|
||||||
assertTrue("r-square NaN",!Double.isNaN(regression.getRSquare()));
|
|
||||||
assertTrue("RSS NaN",
|
|
||||||
!Double.isNaN(regression.getRegressionSumSquares()));
|
|
||||||
assertTrue("SSE NaN",!Double.isNaN(regression.getSumSquaredErrors()));
|
|
||||||
assertTrue("SSTO NaN",!Double.isNaN(regression.getTotalSumSquares()));
|
|
||||||
assertTrue("predict NaN",!Double.isNaN(regression.predict(0)));
|
|
||||||
|
|
||||||
regression.addData(1,4);
|
|
||||||
|
|
||||||
// MSE, MSE, s(b0), s(b1) should all be OK now
|
|
||||||
assertTrue("MSE NaN",!Double.isNaN(regression.getMeanSquareError()));
|
|
||||||
assertTrue("slope std err NaN",
|
|
||||||
!Double.isNaN(regression.getSlopeStdErr()));
|
|
||||||
assertTrue("intercept std err NaN",
|
|
||||||
!Double.isNaN(regression.getInterceptStdErr()));
|
|
||||||
}
|
|
||||||
|
|
||||||
public void testClear() {
|
|
||||||
BivariateRegression regression = new BivariateRegression();
|
|
||||||
regression.addData(corrData);
|
|
||||||
assertEquals("number of observations",17,regression.getN());
|
|
||||||
regression.clear();
|
|
||||||
assertEquals("number of observations",0,regression.getN());
|
|
||||||
regression.addData(corrData);
|
|
||||||
assertEquals("r-square",.896123,regression.getRSquare(),10E-6);
|
|
||||||
regression.addData(data);
|
|
||||||
assertEquals("number of observations",53,regression.getN());
|
|
||||||
}
|
|
||||||
|
|
||||||
}
|
|
||||||
|
|
||||||
|
|
@ -1,181 +0,0 @@
|
||||||
/* ====================================================================
|
|
||||||
* The Apache Software License, Version 1.1
|
|
||||||
*
|
|
||||||
* Copyright (c) 2003 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 acknowlegement:
|
|
||||||
* "This product includes software developed by the
|
|
||||||
* Apache Software Foundation (http://www.apache.org/)."
|
|
||||||
* Alternately, this acknowlegement may appear in the software itself,
|
|
||||||
* if and wherever such third-party acknowlegements 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 names 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;
|
|
||||||
|
|
||||||
import java.util.ArrayList;
|
|
||||||
import java.util.List;
|
|
||||||
|
|
||||||
import junit.framework.Test;
|
|
||||||
import junit.framework.TestCase;
|
|
||||||
import junit.framework.TestSuite;
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Test cases for the {@link Univariate} class.
|
|
||||||
*
|
|
||||||
* @author <a href="mailto:phil@steitz.com">Phil Steitz</a>
|
|
||||||
* @version $Revision: 1.3 $ $Date: 2003/05/21 17:59:20 $
|
|
||||||
*/
|
|
||||||
|
|
||||||
public final class ListUnivariateImplTest extends TestCase {
|
|
||||||
private double one = 1;
|
|
||||||
private float two = 2;
|
|
||||||
private int three = 3;
|
|
||||||
|
|
||||||
private double mean = 2;
|
|
||||||
private double sumSq = 18;
|
|
||||||
private double sum = 8;
|
|
||||||
private double var = 0.666666666666666666667;
|
|
||||||
private double std = Math.sqrt(var);
|
|
||||||
private double n = 4;
|
|
||||||
private double min = 1;
|
|
||||||
private double max = 3;
|
|
||||||
private double skewness = 0;
|
|
||||||
private double kurtosis = 0.5;
|
|
||||||
private int kClass = StoreUnivariate.LEPTOKURTIC;
|
|
||||||
private double tolerance = 10E-15;
|
|
||||||
|
|
||||||
public ListUnivariateImplTest(String name) {
|
|
||||||
super(name);
|
|
||||||
}
|
|
||||||
|
|
||||||
public void setUp() {
|
|
||||||
}
|
|
||||||
|
|
||||||
public static Test suite() {
|
|
||||||
TestSuite suite = new TestSuite(ListUnivariateImplTest.class);
|
|
||||||
suite.setName("Freq Tests");
|
|
||||||
return suite;
|
|
||||||
}
|
|
||||||
|
|
||||||
/** test stats */
|
|
||||||
public void testStats() {
|
|
||||||
List externalList = new ArrayList();
|
|
||||||
|
|
||||||
StoreUnivariate u = new ListUnivariateImpl( externalList );
|
|
||||||
|
|
||||||
assertEquals("total count",0,u.getN(),tolerance);
|
|
||||||
u.addValue(one);
|
|
||||||
u.addValue(two);
|
|
||||||
u.addValue(two);
|
|
||||||
u.addValue(three);
|
|
||||||
assertEquals("N",n,u.getN(),tolerance);
|
|
||||||
assertEquals("sum",sum,u.getSum(),tolerance);
|
|
||||||
assertEquals("sumsq",sumSq,u.getSumsq(),tolerance);
|
|
||||||
assertEquals("var",var,u.getVariance(),tolerance);
|
|
||||||
assertEquals("std",std,u.getStandardDeviation(),tolerance);
|
|
||||||
assertEquals("mean",mean,u.getMean(),tolerance);
|
|
||||||
assertEquals("min",min,u.getMin(),tolerance);
|
|
||||||
assertEquals("max",max,u.getMax(),tolerance);
|
|
||||||
u.clear();
|
|
||||||
assertEquals("total count",0,u.getN(),tolerance);
|
|
||||||
}
|
|
||||||
|
|
||||||
public void testN0andN1Conditions() throws Exception {
|
|
||||||
List list = new ArrayList();
|
|
||||||
|
|
||||||
StoreUnivariate u = new ListUnivariateImpl( list );
|
|
||||||
|
|
||||||
assertTrue("Mean of n = 0 set should be NaN", Double.isNaN( u.getMean() ) );
|
|
||||||
assertTrue("Standard Deviation of n = 0 set should be NaN", Double.isNaN( u.getStandardDeviation() ) );
|
|
||||||
assertTrue("Variance of n = 0 set should be NaN", Double.isNaN(u.getVariance() ) );
|
|
||||||
|
|
||||||
list.add( new Double(one));
|
|
||||||
|
|
||||||
assertTrue( "Mean of n = 1 set should be value of single item n1", u.getMean() == one);
|
|
||||||
assertTrue( "StdDev of n = 1 set should be zero, instead it is: " + u.getStandardDeviation(), u.getStandardDeviation() == 0);
|
|
||||||
assertTrue( "Variance of n = 1 set should be zero", u.getVariance() == 0);
|
|
||||||
}
|
|
||||||
|
|
||||||
public void testSkewAndKurtosis() {
|
|
||||||
StoreUnivariate u = new StoreUnivariateImpl();
|
|
||||||
|
|
||||||
double[] testArray = { 12.5, 12, 11.8, 14.2, 14.9, 14.5, 21, 8.2, 10.3, 11.3, 14.1,
|
|
||||||
9.9, 12.2, 12, 12.1, 11, 19.8, 11, 10, 8.8, 9, 12.3 };
|
|
||||||
for( int i = 0; i < testArray.length; i++) {
|
|
||||||
u.addValue( testArray[i]);
|
|
||||||
}
|
|
||||||
|
|
||||||
assertEquals("mean", 12.40455, u.getMean(), 0.0001);
|
|
||||||
assertEquals("variance", 10.00236, u.getVariance(), 0.0001);
|
|
||||||
assertEquals("skewness", 1.437424, u.getSkewness(), 0.0001);
|
|
||||||
assertEquals("kurtosis", 2.37719, u.getKurtosis(), 0.0001);
|
|
||||||
}
|
|
||||||
|
|
||||||
public void testProductAndGeometricMean() throws Exception {
|
|
||||||
ListUnivariateImpl u = new ListUnivariateImpl(new ArrayList());
|
|
||||||
u.setWindowSize(10);
|
|
||||||
|
|
||||||
u.addValue( 1.0 );
|
|
||||||
u.addValue( 2.0 );
|
|
||||||
u.addValue( 3.0 );
|
|
||||||
u.addValue( 4.0 );
|
|
||||||
|
|
||||||
assertEquals( "Product not expected", 24.0, u.getProduct(), Double.MIN_VALUE );
|
|
||||||
assertEquals( "Geometric mean not expected", 2.213364, u.getGeometricMean(), 0.00001 );
|
|
||||||
|
|
||||||
// Now test rolling - UnivariateImpl should discount the contribution
|
|
||||||
// of a discarded element
|
|
||||||
for( int i = 0; i < 10; i++ ) {
|
|
||||||
u.addValue( i + 2 );
|
|
||||||
}
|
|
||||||
// Values should be (2,3,4,5,6,7,8,9,10,11)
|
|
||||||
|
|
||||||
assertEquals( "Product not expected", 39916800.0, u.getProduct(), 0.00001 );
|
|
||||||
assertEquals( "Geometric mean not expected", 5.755931, u.getGeometricMean(), 0.00001 );
|
|
||||||
|
|
||||||
|
|
||||||
}
|
|
||||||
|
|
||||||
}
|
|
||||||
|
|
||||||
|
|
@ -1,172 +0,0 @@
|
||||||
/* ====================================================================
|
|
||||||
* The Apache Software License, Version 1.1
|
|
||||||
*
|
|
||||||
* Copyright (c) 2003 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 acknowlegement:
|
|
||||||
* "This product includes software developed by the
|
|
||||||
* Apache Software Foundation (http://www.apache.org/)."
|
|
||||||
* Alternately, this acknowlegement may appear in the software itself,
|
|
||||||
* if and wherever such third-party acknowlegements 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 names 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;
|
|
||||||
|
|
||||||
import junit.framework.Test;
|
|
||||||
import junit.framework.TestCase;
|
|
||||||
import junit.framework.TestSuite;
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Test cases for the {@link Univariate} class.
|
|
||||||
*
|
|
||||||
* @author <a href="mailto:phil@steitz.com">Phil Steitz</a>
|
|
||||||
* @version $Revision: 1.2 $ $Date: 2003/05/21 17:59:20 $
|
|
||||||
*/
|
|
||||||
|
|
||||||
public final class StoreUnivariateImplTest extends TestCase {
|
|
||||||
private double one = 1;
|
|
||||||
private float two = 2;
|
|
||||||
private int three = 3;
|
|
||||||
private double mean = 2;
|
|
||||||
private double sumSq = 18;
|
|
||||||
private double sum = 8;
|
|
||||||
private double var = 0.666666666666666666667;
|
|
||||||
private double std = Math.sqrt(var);
|
|
||||||
private double n = 4;
|
|
||||||
private double min = 1;
|
|
||||||
private double max = 3;
|
|
||||||
private double skewness = 0;
|
|
||||||
private double kurtosis = 0.5;
|
|
||||||
private int kClass = StoreUnivariate.LEPTOKURTIC;
|
|
||||||
private double tolerance = 10E-15;
|
|
||||||
|
|
||||||
public StoreUnivariateImplTest(String name) {
|
|
||||||
super(name);
|
|
||||||
}
|
|
||||||
|
|
||||||
public void setUp() {
|
|
||||||
}
|
|
||||||
|
|
||||||
public static Test suite() {
|
|
||||||
TestSuite suite = new TestSuite(StoreUnivariateImplTest.class);
|
|
||||||
suite.setName("Freq Tests");
|
|
||||||
return suite;
|
|
||||||
}
|
|
||||||
|
|
||||||
/** test stats */
|
|
||||||
public void testStats() {
|
|
||||||
StoreUnivariate u = new StoreUnivariateImpl();
|
|
||||||
assertEquals("total count",0,u.getN(),tolerance);
|
|
||||||
u.addValue(one);
|
|
||||||
u.addValue(two);
|
|
||||||
u.addValue(two);
|
|
||||||
u.addValue(three);
|
|
||||||
assertEquals("N",n,u.getN(),tolerance);
|
|
||||||
assertEquals("sum",sum,u.getSum(),tolerance);
|
|
||||||
assertEquals("sumsq",sumSq,u.getSumsq(),tolerance);
|
|
||||||
assertEquals("var",var,u.getVariance(),tolerance);
|
|
||||||
assertEquals("std",std,u.getStandardDeviation(),tolerance);
|
|
||||||
assertEquals("mean",mean,u.getMean(),tolerance);
|
|
||||||
assertEquals("min",min,u.getMin(),tolerance);
|
|
||||||
assertEquals("max",max,u.getMax(),tolerance);
|
|
||||||
u.clear();
|
|
||||||
assertEquals("total count",0,u.getN(),tolerance);
|
|
||||||
}
|
|
||||||
|
|
||||||
public void testN0andN1Conditions() throws Exception {
|
|
||||||
StoreUnivariate u = new StoreUnivariateImpl();
|
|
||||||
|
|
||||||
assertTrue("Mean of n = 0 set should be NaN", Double.isNaN( u.getMean() ) );
|
|
||||||
assertTrue("Standard Deviation of n = 0 set should be NaN", Double.isNaN( u.getStandardDeviation() ) );
|
|
||||||
assertTrue("Variance of n = 0 set should be NaN", Double.isNaN(u.getVariance() ) );
|
|
||||||
|
|
||||||
u.addValue(one);
|
|
||||||
|
|
||||||
assertTrue( "Mean of n = 1 set should be value of single item n1", u.getMean() == one);
|
|
||||||
assertTrue( "StdDev of n = 1 set should be zero, instead it is: " + u.getStandardDeviation(), u.getStandardDeviation() == 0);
|
|
||||||
assertTrue( "Variance of n = 1 set should be zero", u.getVariance() == 0);
|
|
||||||
}
|
|
||||||
|
|
||||||
public void testSkewAndKurtosis() {
|
|
||||||
StoreUnivariate u = new StoreUnivariateImpl();
|
|
||||||
|
|
||||||
double[] testArray = { 12.5, 12, 11.8, 14.2, 14.9, 14.5, 21, 8.2, 10.3, 11.3, 14.1,
|
|
||||||
9.9, 12.2, 12, 12.1, 11, 19.8, 11, 10, 8.8, 9, 12.3 };
|
|
||||||
for( int i = 0; i < testArray.length; i++) {
|
|
||||||
u.addValue( testArray[i]);
|
|
||||||
}
|
|
||||||
|
|
||||||
assertEquals("mean", 12.40455, u.getMean(), 0.0001);
|
|
||||||
assertEquals("variance", 10.00236, u.getVariance(), 0.0001);
|
|
||||||
assertEquals("skewness", 1.437424, u.getSkewness(), 0.0001);
|
|
||||||
assertEquals("kurtosis", 2.37719, u.getKurtosis(), 0.0001);
|
|
||||||
}
|
|
||||||
|
|
||||||
public void testProductAndGeometricMean() throws Exception {
|
|
||||||
StoreUnivariateImpl u = new StoreUnivariateImpl();
|
|
||||||
u.setWindowSize(10);
|
|
||||||
|
|
||||||
u.addValue( 1.0 );
|
|
||||||
u.addValue( 2.0 );
|
|
||||||
u.addValue( 3.0 );
|
|
||||||
u.addValue( 4.0 );
|
|
||||||
|
|
||||||
assertEquals( "Product not expected", 24.0, u.getProduct(), Double.MIN_VALUE );
|
|
||||||
assertEquals( "Geometric mean not expected", 2.213364, u.getGeometricMean(), 0.00001 );
|
|
||||||
|
|
||||||
// Now test rolling - UnivariateImpl should discount the contribution
|
|
||||||
// of a discarded element
|
|
||||||
for( int i = 0; i < 10; i++ ) {
|
|
||||||
u.addValue( i + 2 );
|
|
||||||
}
|
|
||||||
// Values should be (2,3,4,5,6,7,8,9,10,11)
|
|
||||||
|
|
||||||
assertEquals( "Product not expected", 39916800.0, u.getProduct(), 0.00001 );
|
|
||||||
assertEquals( "Geometric mean not expected", 5.755931, u.getGeometricMean(), 0.00001 );
|
|
||||||
|
|
||||||
|
|
||||||
}
|
|
||||||
|
|
||||||
}
|
|
||||||
|
|
||||||
|
|
@ -1,238 +0,0 @@
|
||||||
/* ====================================================================
|
|
||||||
* The Apache Software License, Version 1.1
|
|
||||||
*
|
|
||||||
* Copyright (c) 2003 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 acknowlegement:
|
|
||||||
* "This product includes software developed by the
|
|
||||||
* Apache Software Foundation (http://www.apache.org/)."
|
|
||||||
* Alternately, this acknowlegement may appear in the software itself,
|
|
||||||
* if and wherever such third-party acknowlegements 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 names 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;
|
|
||||||
|
|
||||||
import junit.framework.Test;
|
|
||||||
import junit.framework.TestCase;
|
|
||||||
import junit.framework.TestSuite;
|
|
||||||
|
|
||||||
/**
|
|
||||||
* Test cases for the {@link Univariate} class.
|
|
||||||
*
|
|
||||||
* @author Phil Steitz
|
|
||||||
* @author Tim Obrien
|
|
||||||
* @version $Revision: 1.4 $ $Date: 2003/05/29 19:49:18 $
|
|
||||||
*/
|
|
||||||
|
|
||||||
public final class UnivariateImplTest extends TestCase {
|
|
||||||
private double one = 1;
|
|
||||||
private float twoF = 2;
|
|
||||||
private long twoL = 2;
|
|
||||||
private int three = 3;
|
|
||||||
private double mean = 2;
|
|
||||||
private double sumSq = 18;
|
|
||||||
private double sum = 8;
|
|
||||||
private double var = 0.666666666666666666667;
|
|
||||||
private double std = Math.sqrt(var);
|
|
||||||
private double n = 4;
|
|
||||||
private double min = 1;
|
|
||||||
private double max = 3;
|
|
||||||
private double tolerance = 10E-15;
|
|
||||||
|
|
||||||
public UnivariateImplTest(String name) {
|
|
||||||
super(name);
|
|
||||||
}
|
|
||||||
|
|
||||||
public void setUp() {
|
|
||||||
}
|
|
||||||
|
|
||||||
public static Test suite() {
|
|
||||||
TestSuite suite = new TestSuite(UnivariateImplTest.class);
|
|
||||||
suite.setName("Freq Tests");
|
|
||||||
return suite;
|
|
||||||
}
|
|
||||||
|
|
||||||
/** test stats */
|
|
||||||
public void testStats() {
|
|
||||||
UnivariateImpl u = new UnivariateImpl();
|
|
||||||
assertEquals("total count",0,u.getN(),tolerance);
|
|
||||||
u.addValue(one);
|
|
||||||
u.addValue(twoF);
|
|
||||||
u.addValue(twoL);
|
|
||||||
u.addValue(three);
|
|
||||||
assertEquals("N",n,u.getN(),tolerance);
|
|
||||||
assertEquals("sum",sum,u.getSum(),tolerance);
|
|
||||||
assertEquals("sumsq",sumSq,u.getSumsq(),tolerance);
|
|
||||||
assertEquals("var",var,u.getVariance(),tolerance);
|
|
||||||
assertEquals("std",std,u.getStandardDeviation(),tolerance);
|
|
||||||
assertEquals("mean",mean,u.getMean(),tolerance);
|
|
||||||
assertEquals("min",min,u.getMin(),tolerance);
|
|
||||||
assertEquals("max",max,u.getMax(),tolerance);
|
|
||||||
u.clear();
|
|
||||||
assertEquals("total count",0,u.getN(),tolerance);
|
|
||||||
}
|
|
||||||
|
|
||||||
public void testN0andN1Conditions() throws Exception {
|
|
||||||
UnivariateImpl u = new UnivariateImpl();
|
|
||||||
assertTrue("Mean of n = 0 set should be NaN",
|
|
||||||
Double.isNaN( u.getMean() ) );
|
|
||||||
assertTrue("Standard Deviation of n = 0 set should be NaN",
|
|
||||||
Double.isNaN( u.getStandardDeviation() ) );
|
|
||||||
assertTrue("Variance of n = 0 set should be NaN",
|
|
||||||
Double.isNaN(u.getVariance() ) );
|
|
||||||
assertTrue("skew of n = 0 set should be NaN",
|
|
||||||
Double.isNaN(u.getSkewness() ) );
|
|
||||||
assertTrue("kurtosis of n = 0 set should be NaN",
|
|
||||||
Double.isNaN(u.getKurtosis() ) );
|
|
||||||
|
|
||||||
|
|
||||||
/* n=1 */
|
|
||||||
u.addValue(one);
|
|
||||||
assertTrue("mean should be one (n = 1)",
|
|
||||||
u.getMean() == one);
|
|
||||||
assertTrue("geometric should be one (n = 1)",
|
|
||||||
u.getGeometricMean() == one);
|
|
||||||
assertTrue("Std should be zero (n = 1)",
|
|
||||||
u.getStandardDeviation() == 0.0);
|
|
||||||
assertTrue("variance should be zero (n = 1)",
|
|
||||||
u.getVariance() == 0.0);
|
|
||||||
assertTrue("skew should be zero (n = 1)",
|
|
||||||
u.getSkewness() == 0.0);
|
|
||||||
assertTrue("kurtosis should be zero (n = 1)",
|
|
||||||
u.getKurtosis() == 0.0);
|
|
||||||
|
|
||||||
/* n=2 */
|
|
||||||
u.addValue(twoF);
|
|
||||||
assertTrue("Std should not be zero (n = 2)",
|
|
||||||
u.getStandardDeviation() != 0.0);
|
|
||||||
assertTrue("variance should not be zero (n = 2)",
|
|
||||||
u.getVariance() != 0.0);
|
|
||||||
assertTrue("skew should not be zero (n = 2)",
|
|
||||||
u.getSkewness() == 0.0);
|
|
||||||
assertTrue("kurtosis should be zero (n = 2)",
|
|
||||||
u.getKurtosis() == 0.0);
|
|
||||||
|
|
||||||
/* n=3 */
|
|
||||||
u.addValue(twoL);
|
|
||||||
assertTrue("skew should not be zero (n = 3)",
|
|
||||||
u.getSkewness() != 0.0);
|
|
||||||
assertTrue("kurtosis should be zero (n = 3)",
|
|
||||||
u.getKurtosis() == 0.0);
|
|
||||||
|
|
||||||
/* n=4 */
|
|
||||||
u.addValue(three);
|
|
||||||
assertTrue("kurtosis should not be zero (n = 4)",
|
|
||||||
u.getKurtosis() != 0.0);
|
|
||||||
|
|
||||||
}
|
|
||||||
|
|
||||||
public void testProductAndGeometricMean() throws Exception {
|
|
||||||
UnivariateImpl u = new UnivariateImpl(10);
|
|
||||||
|
|
||||||
u.addValue( 1.0 );
|
|
||||||
u.addValue( 2.0 );
|
|
||||||
u.addValue( 3.0 );
|
|
||||||
u.addValue( 4.0 );
|
|
||||||
|
|
||||||
assertEquals( "Product not expected", 24.0, u.getProduct(),
|
|
||||||
Double.MIN_VALUE );
|
|
||||||
assertEquals( "Geometric mean not expected", 2.213364,
|
|
||||||
u.getGeometricMean(), 0.00001 );
|
|
||||||
|
|
||||||
// Now test rolling - UnivariateImpl should discount the contribution
|
|
||||||
// of a discarded element
|
|
||||||
for( int i = 0; i < 10; i++ ) {
|
|
||||||
u.addValue( i + 2 );
|
|
||||||
}
|
|
||||||
// Values should be (2,3,4,5,6,7,8,9,10,11)
|
|
||||||
|
|
||||||
assertEquals( "Product not expected", 39916800.0,
|
|
||||||
u.getProduct(), 0.00001 );
|
|
||||||
assertEquals( "Geometric mean not expected", 5.755931,
|
|
||||||
u.getGeometricMean(), 0.00001 );
|
|
||||||
}
|
|
||||||
|
|
||||||
public void testRollingMinMax() {
|
|
||||||
UnivariateImpl u = new UnivariateImpl(3);
|
|
||||||
u.addValue( 1.0 );
|
|
||||||
u.addValue( 5.0 );
|
|
||||||
u.addValue( 3.0 );
|
|
||||||
u.addValue( 4.0 ); // discarding min
|
|
||||||
assertEquals( "min not expected", 3.0,
|
|
||||||
u.getMin(), Double.MIN_VALUE);
|
|
||||||
u.addValue(1.0); // discarding max
|
|
||||||
assertEquals( "max not expected", 4.0,
|
|
||||||
u.getMax(), Double.MIN_VALUE);
|
|
||||||
}
|
|
||||||
|
|
||||||
public void testNaNContracts() {
|
|
||||||
UnivariateImpl u = new UnivariateImpl();
|
|
||||||
double nan = Double.NaN;
|
|
||||||
assertTrue("mean not NaN",Double.isNaN(u.getMean()));
|
|
||||||
assertTrue("min not NaN",Double.isNaN(u.getMin()));
|
|
||||||
assertTrue("std dev not NaN",Double.isNaN(u.getStandardDeviation()));
|
|
||||||
assertTrue("var not NaN",Double.isNaN(u.getVariance()));
|
|
||||||
assertTrue("geom mean not NaN",Double.isNaN(u.getGeometricMean()));
|
|
||||||
|
|
||||||
u.addValue(1.0);
|
|
||||||
|
|
||||||
assertEquals( "mean not expected", 1.0,
|
|
||||||
u.getMean(), Double.MIN_VALUE);
|
|
||||||
assertEquals( "variance not expected", 0.0,
|
|
||||||
u.getVariance(), Double.MIN_VALUE);
|
|
||||||
assertEquals( "geometric mean not expected", 1.0,
|
|
||||||
u.getGeometricMean(), Double.MIN_VALUE);
|
|
||||||
|
|
||||||
u.addValue(-1.0);
|
|
||||||
|
|
||||||
assertTrue("geom mean not NaN",Double.isNaN(u.getGeometricMean()));
|
|
||||||
|
|
||||||
u.addValue(0.0);
|
|
||||||
|
|
||||||
assertTrue("geom mean not NaN",Double.isNaN(u.getGeometricMean()));
|
|
||||||
|
|
||||||
//FiXME: test all other NaN contract specs
|
|
||||||
}
|
|
||||||
|
|
||||||
}
|
|
||||||
Loading…
Reference in New Issue