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Java > Open Source Codes > org > apache > commons > math > distribution > NormalDistributionTest


1 /*
2  * Copyright 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
17 package org.apache.commons.math.distribution;
18
19 /**
20  * Test cases for NormalDistribution.
21  * Extends ContinuousDistributionAbstractTest. See class javadoc for
22  * ContinuousDistributionAbstractTest for details.
23  *
24  * @version $Revision$ $Date: 2005-02-26 05:11:52 -0800 (Sat, 26 Feb 2005) $
25  */
26 public class NormalDistributionTest extends ContinuousDistributionAbstractTest {
27     
28     /**
29      * Constructor for NormalDistributionTest.
30      * @param arg0
31      */
32     public NormalDistributionTest(String JavaDoc arg0) {
33         super(arg0);
34     }
35     
36     public static void main(String JavaDoc[] args) {
37         junit.swingui.TestRunner.run(NormalDistributionTest.class);
38     }
39     
40     //-------------- Implementations for abstract methods -----------------------
41
42     /** Creates the default continuous distribution instance to use in tests. */
43     public ContinuousDistribution makeDistribution() {
44         return DistributionFactory.newInstance().createNormalDistribution(2.1, 1.4);
45     }
46     
47     /** Creates the default cumulative probability distribution test input values */
48     public double[] makeCumulativeTestPoints() {
49         // quantiles computed using R
50 return new double[] {-2.226325d, -1.156887d, -0.6439496d, -0.2027951d, 0.3058278d,
51                 6.426325d, 5.356887d, 4.84395d, 4.402795d, 3.894172d};
52     }
53     
54     /** Creates the default cumulative probability density test expected values */
55     public double[] makeCumulativeTestValues() {
56         return new double[] {0.001d, 0.01d, 0.025d, 0.05d, 0.1d, 0.999d,
57                 0.990d, 0.975d, 0.950d, 0.900d};
58     }
59     
60     // --------------------- Override tolerance --------------
61 protected void setup() throws Exception JavaDoc {
62         super.setUp();
63         setTolerance(1E-6);
64     }
65     
66     //---------------------------- Additional test cases -------------------------
67
68     private void verifyQuantiles() throws Exception JavaDoc {
69         NormalDistribution distribution = (NormalDistribution) getDistribution();
70         double mu = distribution.getMean();
71         double sigma = distribution.getStandardDeviation();
72         setCumulativeTestPoints( new double[] {mu - 2 *sigma, mu - sigma,
73                 mu, mu + sigma, mu +2 * sigma, mu +3 * sigma, mu + 4 * sigma,
74                 mu + 5 * sigma});
75         // Quantiles computed using R (same as Mathematica)
76 setCumulativeTestValues(new double[] {0.02275013, 0.1586553, 0.5, 0.8413447,
77                 0.9772499, 0.9986501, 0.9999683, 0.9999997});
78         verifyCumulativeProbabilities();
79     }
80     
81     public void testQuantiles() throws Exception JavaDoc {
82         verifyQuantiles();
83         setDistribution(DistributionFactory.newInstance().createNormalDistribution(0, 1));
84         verifyQuantiles();
85         setDistribution(DistributionFactory.newInstance().createNormalDistribution(0, 0.1));
86         verifyQuantiles();
87     }
88     
89     public void testInverseCumulativeProbabilityExtremes() throws Exception JavaDoc {
90         setInverseCumulativeTestPoints(new double[] {0, 1});
91         setInverseCumulativeTestValues(
92                 new double[] {Double.NEGATIVE_INFINITY, Double.POSITIVE_INFINITY});
93         verifyInverseCumulativeProbabilities();
94     }
95     
96     public void testGetMean() {
97         NormalDistribution distribution = (NormalDistribution) getDistribution();
98         assertEquals(2.1, distribution.getMean(), 0);
99     }
100     
101     public void testSetMean() throws Exception JavaDoc {
102         double mu = Math.random();
103         NormalDistribution distribution = (NormalDistribution) getDistribution();
104         distribution.setMean(mu);
105         verifyQuantiles();
106     }
107     
108     public void testGetStandardDeviation() {
109         NormalDistribution distribution = (NormalDistribution) getDistribution();
110         assertEquals(1.4, distribution.getStandardDeviation(), 0);
111     }
112     
113     public void testSetStandardDeviation() throws Exception JavaDoc {
114         double sigma = 0.1d + Math.random();
115         NormalDistribution distribution = (NormalDistribution) getDistribution();
116         distribution.setStandardDeviation(sigma);
117         assertEquals(sigma, distribution.getStandardDeviation(), 0);
118         verifyQuantiles();
119         try {
120             distribution.setStandardDeviation(0);
121             fail("Expecting IllegalArgumentException for sd = 0");
122         } catch (IllegalArgumentException JavaDoc ex) {
123             // Expected
124 }
125     }
126 }
127
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