001 /*
002 * Licensed to the Apache Software Foundation (ASF) under one or more
003 * contributor license agreements. See the NOTICE file distributed with
004 * this work for additional information regarding copyright ownership.
005 * The ASF licenses this file to You under the Apache License, Version 2.0
006 * (the "License"); you may not use this file except in compliance with
007 * the License. You may obtain a copy of the License at
008 *
009 * http://www.apache.org/licenses/LICENSE-2.0
010 *
011 * Unless required by applicable law or agreed to in writing, software
012 * distributed under the License is distributed on an "AS IS" BASIS,
013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
014 * See the License for the specific language governing permissions and
015 * limitations under the License.
016 */
017 package org.apache.commons.math.stat.descriptive;
018
019 import java.util.ArrayList;
020 import java.util.List;
021
022 import org.apache.commons.math.TestUtils;
023
024 import junit.framework.Test;
025 import junit.framework.TestCase;
026 import junit.framework.TestSuite;
027
028 /**
029 * Test cases for the {@link ListUnivariateImpl} class.
030 *
031 * @version $Revision: 762087 $ $Date: 2009-04-05 10:20:18 -0400 (Sun, 05 Apr 2009) $
032 */
033
034 public final class ListUnivariateImplTest extends TestCase {
035
036 private double one = 1;
037 private float two = 2;
038 private int three = 3;
039
040 private double mean = 2;
041 private double sumSq = 18;
042 private double sum = 8;
043 private double var = 0.666666666666666666667;
044 private double std = Math.sqrt(var);
045 private double n = 4;
046 private double min = 1;
047 private double max = 3;
048 private double tolerance = 10E-15;
049
050 public ListUnivariateImplTest(String name) {
051 super(name);
052 }
053
054 public static Test suite() {
055 TestSuite suite = new TestSuite(ListUnivariateImplTest.class);
056 suite.setName("Frequency Tests");
057 return suite;
058 }
059
060 /** test stats */
061 public void testStats() {
062 List<Object> externalList = new ArrayList<Object>();
063
064 DescriptiveStatistics u = new ListUnivariateImpl( externalList );
065
066 assertEquals("total count",0,u.getN(),tolerance);
067 u.addValue(one);
068 u.addValue(two);
069 u.addValue(two);
070 u.addValue(three);
071 assertEquals("N",n,u.getN(),tolerance);
072 assertEquals("sum",sum,u.getSum(),tolerance);
073 assertEquals("sumsq",sumSq,u.getSumsq(),tolerance);
074 assertEquals("var",var,u.getVariance(),tolerance);
075 assertEquals("std",std,u.getStandardDeviation(),tolerance);
076 assertEquals("mean",mean,u.getMean(),tolerance);
077 assertEquals("min",min,u.getMin(),tolerance);
078 assertEquals("max",max,u.getMax(),tolerance);
079 u.clear();
080 assertEquals("total count",0,u.getN(),tolerance);
081 }
082
083 public void testN0andN1Conditions() throws Exception {
084 List<Object> list = new ArrayList<Object>();
085
086 DescriptiveStatistics u = new ListUnivariateImpl( list );
087
088 assertTrue("Mean of n = 0 set should be NaN", Double.isNaN( u.getMean() ) );
089 assertTrue("Standard Deviation of n = 0 set should be NaN", Double.isNaN( u.getStandardDeviation() ) );
090 assertTrue("Variance of n = 0 set should be NaN", Double.isNaN(u.getVariance() ) );
091
092 list.add( Double.valueOf(one));
093
094 assertTrue( "Mean of n = 1 set should be value of single item n1", u.getMean() == one);
095 assertTrue( "StdDev of n = 1 set should be zero, instead it is: " + u.getStandardDeviation(), u.getStandardDeviation() == 0);
096 assertTrue( "Variance of n = 1 set should be zero", u.getVariance() == 0);
097 }
098
099 public void testSkewAndKurtosis() {
100 DescriptiveStatistics u = new DescriptiveStatistics();
101
102 double[] testArray = { 12.5, 12, 11.8, 14.2, 14.9, 14.5, 21, 8.2, 10.3, 11.3, 14.1,
103 9.9, 12.2, 12, 12.1, 11, 19.8, 11, 10, 8.8, 9, 12.3 };
104 for( int i = 0; i < testArray.length; i++) {
105 u.addValue( testArray[i]);
106 }
107
108 assertEquals("mean", 12.40455, u.getMean(), 0.0001);
109 assertEquals("variance", 10.00236, u.getVariance(), 0.0001);
110 assertEquals("skewness", 1.437424, u.getSkewness(), 0.0001);
111 assertEquals("kurtosis", 2.37719, u.getKurtosis(), 0.0001);
112 }
113
114 public void testProductAndGeometricMean() throws Exception {
115 ListUnivariateImpl u = new ListUnivariateImpl(new ArrayList<Object>());
116 u.setWindowSize(10);
117
118 u.addValue( 1.0 );
119 u.addValue( 2.0 );
120 u.addValue( 3.0 );
121 u.addValue( 4.0 );
122
123 assertEquals( "Geometric mean not expected", 2.213364, u.getGeometricMean(), 0.00001 );
124
125 // Now test rolling - StorelessDescriptiveStatistics should discount the contribution
126 // of a discarded element
127 for( int i = 0; i < 10; i++ ) {
128 u.addValue( i + 2 );
129 }
130 // Values should be (2,3,4,5,6,7,8,9,10,11)
131
132 assertEquals( "Geometric mean not expected", 5.755931, u.getGeometricMean(), 0.00001 );
133
134
135 }
136
137 /** test stats */
138 public void testSerialization() {
139
140 DescriptiveStatistics u = new ListUnivariateImpl();
141
142 assertEquals("total count",0,u.getN(),tolerance);
143 u.addValue(one);
144 u.addValue(two);
145
146 DescriptiveStatistics u2 = (DescriptiveStatistics)TestUtils.serializeAndRecover(u);
147
148 u2.addValue(two);
149 u2.addValue(three);
150
151 assertEquals("N",n,u2.getN(),tolerance);
152 assertEquals("sum",sum,u2.getSum(),tolerance);
153 assertEquals("sumsq",sumSq,u2.getSumsq(),tolerance);
154 assertEquals("var",var,u2.getVariance(),tolerance);
155 assertEquals("std",std,u2.getStandardDeviation(),tolerance);
156 assertEquals("mean",mean,u2.getMean(),tolerance);
157 assertEquals("min",min,u2.getMin(),tolerance);
158 assertEquals("max",max,u2.getMax(),tolerance);
159
160 u2.clear();
161 assertEquals("total count",0,u2.getN(),tolerance);
162 }
163 }
164