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16 package org.apache.commons.math.stat.descriptive;
17
18 import java.util.ArrayList  ;
19 import java.util.List ;
20
21 import org.apache.commons.math.util.NumberTransformer;
22 import org.apache.commons.math.util.TransformerMap;
23 import junit.framework.Test;
24 import junit.framework.TestCase;
25 import junit.framework.TestSuite;
26
27
32
33 public final class MixedListUnivariateImplTest extends TestCase {
34 private double one = 1;
35 private float two = 2;
36 private int three = 3;
37
38 private double mean = 2;
39 private double sumSq = 18;
40 private double sum = 8;
41 private double var = 0.666666666666666666667;
42 private double std = Math.sqrt(var);
43 private double n = 4;
44 private double min = 1;
45 private double max = 3;
46 private double skewness = 0;
47 private double kurtosis = 0.5;
48 private double tolerance = 10E-15;
49
50 private TransformerMap transformers = new TransformerMap();
51
52 public MixedListUnivariateImplTest(String name) {
53 super(name);
54 transformers = new TransformerMap();
55
56 transformers.putTransformer(Foo.class, new NumberTransformer() {
57 public double transform(Object o) {
58 return Double.parseDouble(((Foo) o).heresFoo());
59 }
60 });
61
62 transformers.putTransformer(Bar.class, new NumberTransformer() {
63 public double transform(Object o) {
64 return Double.parseDouble(((Bar) o).heresBar());
65 }
66
67 });
68
69 }
70
71 public void setUp() {
72 }
73
74 public static Test suite() {
75 TestSuite suite = new TestSuite(MixedListUnivariateImplTest.class);
76 suite.setName("Mixed List Tests");
77 return suite;
78 }
79
80
81 public void testStats() {
82 List externalList = new ArrayList ();
83
84 DescriptiveStatistics u = new ListUnivariateImpl(externalList,transformers);
85
86 assertEquals("total count", 0, u.getN(), tolerance);
87 u.addValue(one);
88 u.addValue(two);
89 u.addValue(two);
90 u.addValue(three);
91 assertEquals("N", n, u.getN(), tolerance);
92 assertEquals("sum", sum, u.getSum(), tolerance);
93 assertEquals("sumsq", sumSq, u.getSumsq(), tolerance);
94 assertEquals("var", var, u.getVariance(), tolerance);
95 assertEquals("std", std, u.getStandardDeviation(), tolerance);
96 assertEquals("mean", mean, u.getMean(), tolerance);
97 assertEquals("min", min, u.getMin(), tolerance);
98 assertEquals("max", max, u.getMax(), tolerance);
99 u.clear();
100 assertEquals("total count", 0, u.getN(), tolerance);
101 }
102
103 public void testN0andN1Conditions() throws Exception {
104 List list = new ArrayList ();
105
106 DescriptiveStatistics u = new ListUnivariateImpl(new ArrayList (),transformers);
107
108 assertTrue(
109 "Mean of n = 0 set should be NaN",
110 Double.isNaN(u.getMean()));
111 assertTrue(
112 "Standard Deviation of n = 0 set should be NaN",
113 Double.isNaN(u.getStandardDeviation()));
114 assertTrue(
115 "Variance of n = 0 set should be NaN",
116 Double.isNaN(u.getVariance()));
117
118 u.addValue(one);
119
120 assertTrue(
121 "Mean of n = 1 set should be value of single item n1, instead it is " + u.getMean() ,
122 u.getMean() == one);
123
124 assertTrue(
125 "StdDev of n = 1 set should be zero, instead it is: "
126 + u.getStandardDeviation(),
127 u.getStandardDeviation() == 0);
128 assertTrue(
129 "Variance of n = 1 set should be zero",
130 u.getVariance() == 0);
131 }
132
133 public void testSkewAndKurtosis() {
134 ListUnivariateImpl u =
135 new ListUnivariateImpl(new ArrayList (), transformers);
136
137 u.addObject("12.5");
138 u.addObject(new Integer (12));
139 u.addObject("11.8");
140 u.addObject("14.2");
141 u.addObject(new Foo());
142 u.addObject("14.5");
143 u.addObject(new Long (21));
144 u.addObject("8.2");
145 u.addObject("10.3");
146 u.addObject("11.3");
147 u.addObject(new Float (14.1));
148 u.addObject("9.9");
149 u.addObject("12.2");
150 u.addObject(new Bar());
151 u.addObject("12.1");
152 u.addObject("11");
153 u.addObject(new Double (19.8));
154 u.addObject("11");
155 u.addObject("10");
156 u.addObject("8.8");
157 u.addObject("9");
158 u.addObject("12.3");
159
160
161 assertEquals("mean", 12.40455, u.getMean(), 0.0001);
162 assertEquals("variance", 10.00236, u.getVariance(), 0.0001);
163 assertEquals("skewness", 1.437424, u.getSkewness(), 0.0001);
164 assertEquals("kurtosis", 2.37719, u.getKurtosis(), 0.0001);
165 }
166
167 public void testProductAndGeometricMean() throws Exception {
168 ListUnivariateImpl u = new ListUnivariateImpl(new ArrayList (),transformers);
169 u.setWindowSize(10);
170
171 u.addValue(1.0);
172 u.addValue(2.0);
173 u.addValue(3.0);
174 u.addValue(4.0);
175
176 assertEquals(
177 "Geometric mean not expected",
178 2.213364,
179 u.getGeometricMean(),
180 0.00001);
181
182 for (int i = 0; i < 10; i++) {
185 u.addValue(i + 2);
186 }
187 assertEquals(
189 "Geometric mean not expected",
190 5.755931,
191 u.getGeometricMean(),
192 0.00001);
193
194 }
195
196 public final class Foo {
197 public String heresFoo() {
198 return "14.9";
199 }
200 }
201
202 public final class Bar {
203 public String heresBar() {
204 return "12.0";
205 }
206 }
207 }
208 |
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