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 * @version $Revision: 155427 $ $Date: 2005-02-26 06:11:52 -0700 (Sat, 26 Feb 2005) $
27 */
28 public class GeometricMeanTest extends StorelessUnivariateStatisticAbstractTest{
29
30 protected GeometricMean stat;
31
32 /**
33 * @param name
34 */
35 public GeometricMeanTest(String name) {
36 super(name);
37 }
38
39 public static Test suite() {
40 TestSuite suite = new TestSuite(GeometricMeanTest.class);
41 suite.setName("Mean Tests");
42 return suite;
43 }
44
45 /* (non-Javadoc)
46 * @see org.apache.commons.math.stat.descriptive.UnivariateStatisticAbstractTest#getUnivariateStatistic()
47 */
48 public UnivariateStatistic getUnivariateStatistic() {
49 return new GeometricMean();
50 }
51
52 /* (non-Javadoc)
53 * @see org.apache.commons.math.stat.descriptive.UnivariateStatisticAbstractTest#expectedValue()
54 */
55 public double expectedValue() {
56 return this.geoMean;
57 }
58
59 public void testSpecialValues() {
60 GeometricMean mean = new GeometricMean();
61 // empty
62 assertTrue(Double.isNaN(mean.getResult()));
63
64 // finite data
65 mean.increment(1d);
66 assertFalse(Double.isNaN(mean.getResult()));
67
68 // add 0 -- makes log sum blow to minus infinity, should make 0
69 mean.increment(0d);
70 assertEquals(0d, mean.getResult(), 0);
71
72 // add positive infinity - note the minus infinity above
73 mean.increment(Double.POSITIVE_INFINITY);
74 assertTrue(Double.isNaN(mean.getResult()));
75
76 // clear
77 mean.clear();
78 assertTrue(Double.isNaN(mean.getResult()));
79
80 // positive infinity by itself
81 mean.increment(Double.POSITIVE_INFINITY);
82 assertEquals(Double.POSITIVE_INFINITY, mean.getResult(), 0);
83
84 // negative value -- should make NaN
85 mean.increment(-2d);
86 assertTrue(Double.isNaN(mean.getResult()));
87 }
88
89 }