1   /*
2    * Licensed to the Apache Software Foundation (ASF) under one or more
3    * contributor license agreements.  See the NOTICE file distributed with
4    * this work for additional information regarding copyright ownership.
5    * The ASF licenses this file to You under the Apache License, Version 2.0
6    * (the "License"); you may not use this file except in compliance with
7    * the License.  You may obtain a copy of the License at
8    * 
9    *      http://www.apache.org/licenses/LICENSE-2.0
10   * 
11   * Unless required by applicable law or agreed to in writing, software
12   * distributed under the License is distributed on an "AS IS" BASIS,
13   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14   * See the License for the specific language governing permissions and
15   * limitations under the License.
16   */
17  package org.apache.commons.math.stat.descriptive.moment;
18  
19  import junit.framework.Test;
20  import junit.framework.TestSuite;
21  
22  import org.apache.commons.math.stat.descriptive.StorelessUnivariateStatisticAbstractTest;
23  import org.apache.commons.math.stat.descriptive.UnivariateStatistic;
24  
25  /**
26   * Test cases for the {@link UnivariateStatistic} class.
27   * 
28   * @version $Revision: 480442 $ $Date: 2006-11-29 00:21:22 -0700 (Wed, 29 Nov 2006) $
29   */
30  public class VarianceTest extends StorelessUnivariateStatisticAbstractTest{
31  
32      protected Variance stat;
33      
34      /**
35       * @param name
36       */
37      public VarianceTest(String name) {
38          super(name);
39      }
40  
41      /* (non-Javadoc)
42       * @see org.apache.commons.math.stat.descriptive.UnivariateStatisticAbstractTest#getUnivariateStatistic()
43       */
44      public UnivariateStatistic getUnivariateStatistic() {
45          return new Variance();
46      }
47  
48      public static Test suite() {
49          TestSuite suite = new TestSuite(VarianceTest.class);
50          suite.setName("Variance Tests");
51          return suite;
52      }
53      
54      /* (non-Javadoc)
55       * @see org.apache.commons.math.stat.descriptive.UnivariateStatisticAbstractTest#expectedValue()
56       */
57      public double expectedValue() {
58          return this.var;
59      }
60      
61      /**
62       * Make sure Double.NaN is returned iff n = 0
63       *
64       */
65      public void testNaN() {
66          StandardDeviation std = new StandardDeviation();
67          assertTrue(Double.isNaN(std.getResult()));
68          std.increment(1d);
69          assertEquals(0d, std.getResult(), 0);
70      }
71      
72      /**
73       * Test population version of variance
74       */ 
75      public void testPopulation() {
76          double[] values = {-1.0d, 3.1d, 4.0d, -2.1d, 22d, 11.7d, 3d, 14d};
77          SecondMoment m = new SecondMoment();
78          m.evaluate(values);  // side effect is to add values
79          Variance v1 = new Variance();
80          v1.setBiasCorrected(false);
81          assertEquals(populationVariance(values), v1.evaluate(values), 1E-14);
82          v1.incrementAll(values);
83          assertEquals(populationVariance(values), v1.getResult(), 1E-14);
84          v1 = new Variance(false, m);
85          assertEquals(populationVariance(values), v1.getResult(), 1E-14);     
86          v1 = new Variance(false);
87          assertEquals(populationVariance(values), v1.evaluate(values), 1E-14);
88          v1.incrementAll(values);
89          assertEquals(populationVariance(values), v1.getResult(), 1E-14);     
90      }
91      
92      /**
93       * Definitional formula for population variance
94       */
95      protected double populationVariance(double[] v) {
96          double mean = new Mean().evaluate(v);
97          double sum = 0;
98          for (int i = 0; i < v.length; i++) {
99             sum += (v[i] - mean) * (v[i] - mean); 
100         }
101         return sum / (double) v.length;
102     }
103 
104 }