01: /*
02: * Copyright 2003-2004 The Apache Software Foundation.
03: *
04: * Licensed under the Apache License, Version 2.0 (the "License");
05: * you may not use this file except in compliance with the License.
06: * You may obtain a copy of the License at
07: *
08: * http://www.apache.org/licenses/LICENSE-2.0
09: *
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
29: 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: /* (non-Javadoc)
47: * @see org.apache.commons.math.stat.descriptive.UnivariateStatisticAbstractTest#getUnivariateStatistic()
48: */
49: public UnivariateStatistic getUnivariateStatistic() {
50: return new GeometricMean();
51: }
52:
53: /* (non-Javadoc)
54: * @see org.apache.commons.math.stat.descriptive.UnivariateStatisticAbstractTest#expectedValue()
55: */
56: public double expectedValue() {
57: return this .geoMean;
58: }
59:
60: public void testSpecialValues() {
61: GeometricMean mean = new GeometricMean();
62: // empty
63: assertTrue(Double.isNaN(mean.getResult()));
64:
65: // finite data
66: mean.increment(1d);
67: assertFalse(Double.isNaN(mean.getResult()));
68:
69: // add 0 -- makes log sum blow to minus infinity, should make 0
70: mean.increment(0d);
71: assertEquals(0d, mean.getResult(), 0);
72:
73: // add positive infinity - note the minus infinity above
74: mean.increment(Double.POSITIVE_INFINITY);
75: assertTrue(Double.isNaN(mean.getResult()));
76:
77: // clear
78: mean.clear();
79: assertTrue(Double.isNaN(mean.getResult()));
80:
81: // positive infinity by itself
82: mean.increment(Double.POSITIVE_INFINITY);
83: assertEquals(Double.POSITIVE_INFINITY, mean.getResult(), 0);
84:
85: // negative value -- should make NaN
86: mean.increment(-2d);
87: assertTrue(Double.isNaN(mean.getResult()));
88: }
89:
90: }
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