1   /*
2    * Copyright 2003-2004 The Apache Software Foundation.
3    * 
4    * Licensed under the Apache License, Version 2.0 (the "License");
5    * you may not use this file except in compliance with the License.
6    * You may obtain a copy of the License at
7    * 
8    *      http://www.apache.org/licenses/LICENSE-2.0
9    * 
10   * Unless required by applicable law or agreed to in writing, software
11   * distributed under the License is distributed on an "AS IS" BASIS,
12   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13   * See the License for the specific language governing permissions and
14   * limitations under the License.
15   */
16  package org.apache.commons.math.stat.descriptive.moment;
17  
18  import junit.framework.Test;
19  import junit.framework.TestSuite;
20  
21  import org.apache.commons.math.stat.descriptive.StorelessUnivariateStatisticAbstractTest;
22  import org.apache.commons.math.stat.descriptive.UnivariateStatistic;
23  
24  /**
25   * Test cases for the {@link UnivariateStatistic} class.
26   * 
27   * @version $Revision: 155427 $ $Date: 2005-02-26 06:11:52 -0700 (Sat, 26 Feb 2005) $
28   */
29  public class VarianceTest extends StorelessUnivariateStatisticAbstractTest{
30  
31      protected Variance stat;
32      
33      /**
34       * @param name
35       */
36      public VarianceTest(String name) {
37          super(name);
38      }
39  
40      /* (non-Javadoc)
41       * @see org.apache.commons.math.stat.descriptive.UnivariateStatisticAbstractTest#getUnivariateStatistic()
42       */
43      public UnivariateStatistic getUnivariateStatistic() {
44          return new Variance();
45      }
46  
47      public static Test suite() {
48          TestSuite suite = new TestSuite(VarianceTest.class);
49          suite.setName("Variance Tests");
50          return suite;
51      }
52      
53      /* (non-Javadoc)
54       * @see org.apache.commons.math.stat.descriptive.UnivariateStatisticAbstractTest#expectedValue()
55       */
56      public double expectedValue() {
57          return this.var;
58      }
59      
60      /**
61       * Make sure Double.NaN is returned iff n = 0
62       *
63       */
64      public void testNaN() {
65          StandardDeviation std = new StandardDeviation();
66          assertTrue(Double.isNaN(std.getResult()));
67          std.increment(1d);
68          assertEquals(0d, std.getResult(), 0);
69      }
70      
71      /**
72       * Test population version of variance
73       */ 
74      public void testPopulation() {
75          double[] values = {-1.0d, 3.1d, 4.0d, -2.1d, 22d, 11.7d, 3d, 14d};
76          SecondMoment m = new SecondMoment();
77          m.evaluate(values);  // side effect is to add values
78          Variance v1 = new Variance();
79          v1.setBiasCorrected(false);
80          assertEquals(populationVariance(values), v1.evaluate(values), 1E-14);
81          v1.incrementAll(values);
82          assertEquals(populationVariance(values), v1.getResult(), 1E-14);
83          v1 = new Variance(false, m);
84          assertEquals(populationVariance(values), v1.getResult(), 1E-14);     
85          v1 = new Variance(false);
86          assertEquals(populationVariance(values), v1.evaluate(values), 1E-14);
87          v1.incrementAll(values);
88          assertEquals(populationVariance(values), v1.getResult(), 1E-14);     
89      }
90      
91      /**
92       * Definitional formula for population variance
93       */
94      protected double populationVariance(double[] v) {
95          double mean = new Mean().evaluate(v);
96          double sum = 0;
97          for (int i = 0; i < v.length; i++) {
98             sum += (v[i] - mean) * (v[i] - mean); 
99          }
100         return sum / (double) v.length;
101     }
102 
103 }