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 * @version $Revision: 762087 $ $Date: 2009-04-05 10:20:18 -0400 (Sun, 05 Apr 2009) $
28 */
29 public class GeometricMeanTest extends StorelessUnivariateStatisticAbstractTest{
30
31 protected GeometricMean stat;
32
33 /**
34 * @param name
35 */
36 public GeometricMeanTest(String name) {
37 super(name);
38 }
39
40 public static Test suite() {
41 TestSuite suite = new TestSuite(GeometricMeanTest.class);
42 suite.setName("Mean Tests");
43 return suite;
44 }
45
46 /**
47 * {@inheritDoc}
48 */
49 @Override
50 public UnivariateStatistic getUnivariateStatistic() {
51 return new GeometricMean();
52 }
53
54 /**
55 * {@inheritDoc}
56 */
57 @Override
58 public double expectedValue() {
59 return this.geoMean;
60 }
61
62 public void testSpecialValues() {
63 GeometricMean mean = new GeometricMean();
64 // empty
65 assertTrue(Double.isNaN(mean.getResult()));
66
67 // finite data
68 mean.increment(1d);
69 assertFalse(Double.isNaN(mean.getResult()));
70
71 // add 0 -- makes log sum blow to minus infinity, should make 0
72 mean.increment(0d);
73 assertEquals(0d, mean.getResult(), 0);
74
75 // add positive infinity - note the minus infinity above
76 mean.increment(Double.POSITIVE_INFINITY);
77 assertTrue(Double.isNaN(mean.getResult()));
78
79 // clear
80 mean.clear();
81 assertTrue(Double.isNaN(mean.getResult()));
82
83 // positive infinity by itself
84 mean.increment(Double.POSITIVE_INFINITY);
85 assertEquals(Double.POSITIVE_INFINITY, mean.getResult(), 0);
86
87 // negative value -- should make NaN
88 mean.increment(-2d);
89 assertTrue(Double.isNaN(mean.getResult()));
90 }
91
92 }