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 * https://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
18 /*
19 * This is not the original file distributed by the Apache Software Foundation
20 * It has been modified by the Hipparchus project
21 */
22
23 package org.hipparchus.distribution.continuous;
24
25 import org.hipparchus.exception.MathIllegalArgumentException;
26 import org.junit.jupiter.api.BeforeEach;
27 import org.junit.jupiter.api.Test;
28
29 import static org.junit.jupiter.api.Assertions.assertEquals;
30 import static org.junit.jupiter.api.Assertions.assertThrows;
31
32 /**
33 * Test cases for {@link TriangularDistribution}.
34 */
35 public class TriangularDistributionTest extends RealDistributionAbstractTest {
36
37 // --- Override tolerance -------------------------------------------------
38
39 @BeforeEach
40 @Override
41 public void setUp() {
42 super.setUp();
43 setTolerance(1e-4);
44 }
45
46 //--- Implementations for abstract methods --------------------------------
47
48 /**
49 * Creates the default triangular distribution instance to use in tests.
50 */
51 @Override
52 public TriangularDistribution makeDistribution() {
53 // Left side 5 wide, right side 10 wide.
54 return new TriangularDistribution(-3, 2, 12);
55 }
56
57 /**
58 * Creates the default cumulative probability distribution test input
59 * values.
60 */
61 @Override
62 public double[] makeCumulativeTestPoints() {
63 return new double[] { -3.0001, // below lower limit
64 -3.0, // at lower limit
65 -2.0, -1.0, 0.0, 1.0, // on lower side
66 2.0, // at mode
67 3.0, 4.0, 10.0, 11.0, // on upper side
68 12.0, // at upper limit
69 12.0001 // above upper limit
70 };
71 }
72
73 /**
74 * Creates the default cumulative probability density test expected values.
75 */
76 @Override
77 public double[] makeCumulativeTestValues() {
78 // Top at 2 / (b - a) = 2 / (12 - -3) = 2 / 15 = 7.5
79 // Area left = 7.5 * 5 * 0.5 = 18.75 (1/3 of the total area)
80 // Area right = 7.5 * 10 * 0.5 = 37.5 (2/3 of the total area)
81 // Area total = 18.75 + 37.5 = 56.25
82 // Derivative left side = 7.5 / 5 = 1.5
83 // Derivative right side = -7.5 / 10 = -0.75
84 double third = 1 / 3.0;
85 double left = 18.75;
86 double area = 56.25;
87 return new double[] { 0.0,
88 0.0,
89 0.75 / area, 3 / area, 6.75 / area, 12 / area,
90 third,
91 (left + 7.125) / area, (left + 13.5) / area,
92 (left + 36) / area, (left + 37.125) / area,
93 1.0,
94 1.0
95 };
96 }
97
98 /**
99 * Creates the default inverse cumulative probability distribution test
100 * input values.
101 */
102 @Override
103 public double[] makeInverseCumulativeTestPoints() {
104 // Exclude the points outside the limits, as they have cumulative
105 // probability of zero and one, meaning the inverse returns the
106 // limits and not the points outside the limits.
107 double[] points = makeCumulativeTestValues();
108 double[] points2 = new double[points.length-2];
109 System.arraycopy(points, 1, points2, 0, points2.length);
110 return points2;
111 //return Arrays.copyOfRange(points, 1, points.length - 1);
112 }
113
114 /**
115 * Creates the default inverse cumulative probability density test expected
116 * values.
117 */
118 @Override
119 public double[] makeInverseCumulativeTestValues() {
120 // Exclude the points outside the limits, as they have cumulative
121 // probability of zero and one, meaning the inverse returns the
122 // limits and not the points outside the limits.
123 double[] points = makeCumulativeTestPoints();
124 double[] points2 = new double[points.length-2];
125 System.arraycopy(points, 1, points2, 0, points2.length);
126 return points2;
127 //return Arrays.copyOfRange(points, 1, points.length - 1);
128 }
129
130 /** Creates the default probability density test expected values. */
131 @Override
132 public double[] makeDensityTestValues() {
133 return new double[] { 0,
134 0,
135 2 / 75.0, 4 / 75.0, 6 / 75.0, 8 / 75.0,
136 10 / 75.0,
137 9 / 75.0, 8 / 75.0, 2 / 75.0, 1 / 75.0,
138 0,
139 0
140 };
141 }
142
143 //--- Additional test cases -----------------------------------------------
144
145 /** Test lower bound getter. */
146 @Test
147 void testGetLowerBound() {
148 TriangularDistribution distribution = makeDistribution();
149 assertEquals(-3.0, distribution.getSupportLowerBound(), 0);
150 }
151
152 /** Test upper bound getter. */
153 @Test
154 void testGetUpperBound() {
155 TriangularDistribution distribution = makeDistribution();
156 assertEquals(12.0, distribution.getSupportUpperBound(), 0);
157 }
158
159 /** Test pre-condition for equal lower/upper limit. */
160 @Test
161 void testPreconditions1() {
162 assertThrows(MathIllegalArgumentException.class, () -> {
163 new TriangularDistribution(0, 0, 0);
164 });
165 }
166
167 /** Test pre-condition for lower limit larger than upper limit. */
168 @Test
169 void testPreconditions2() {
170 assertThrows(MathIllegalArgumentException.class, () -> {
171 new TriangularDistribution(1, 1, 0);
172 });
173 }
174
175 /** Test pre-condition for mode larger than upper limit. */
176 @Test
177 void testPreconditions3() {
178 assertThrows(MathIllegalArgumentException.class, () -> {
179 new TriangularDistribution(0, 2, 1);
180 });
181 }
182
183 /** Test pre-condition for mode smaller than lower limit. */
184 @Test
185 void testPreconditions4() {
186 assertThrows(MathIllegalArgumentException.class, () -> {
187 new TriangularDistribution(2, 1, 3);
188 });
189 }
190
191 /** Test mean/variance. */
192 @Test
193 void testMeanVariance() {
194 TriangularDistribution dist;
195
196 dist = new TriangularDistribution(0, 0.5, 1.0);
197 assertEquals(0.5, dist.getNumericalMean(), 0);
198 assertEquals(dist.getNumericalVariance(), 1 / 24.0, 0);
199
200 dist = new TriangularDistribution(0, 1, 1);
201 assertEquals(dist.getNumericalMean(), 2 / 3.0, 0);
202 assertEquals(dist.getNumericalVariance(), 1 / 18.0, 0);
203
204 dist = new TriangularDistribution(-3, 2, 12);
205 assertEquals(dist.getNumericalMean(), 3 + (2 / 3.0), 0);
206 assertEquals(dist.getNumericalVariance(), 175 / 18.0, 0);
207 }
208 }