001 /*
002 * Java Genetic Algorithm Library (jenetics-2.0.2).
003 * Copyright (c) 2007-2014 Franz Wilhelmstötter
004 *
005 * Licensed under the Apache License, Version 2.0 (the "License");
006 * you may not use this file except in compliance with the License.
007 * You may obtain a copy of the License at
008 *
009 * http://www.apache.org/licenses/LICENSE-2.0
010 *
011 * Unless required by applicable law or agreed to in writing, software
012 * distributed under the License is distributed on an "AS IS" BASIS,
013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
014 * See the License for the specific language governing permissions and
015 * limitations under the License.
016 *
017 * Author:
018 * Franz Wilhelmstötter (franz.wilhelmstoetter@gmx.at)
019 */
020 package org.jenetics.stat;
021
022 import static java.lang.String.format;
023 import static java.util.Objects.requireNonNull;
024 import static org.jenetics.internal.util.object.eq;
025
026 import java.io.Serializable;
027 import java.util.Locale;
028
029 import org.jenetics.internal.util.HashBuilder;
030
031 import org.jenetics.util.Function;
032 import org.jenetics.util.Range;
033
034
035 /**
036 * <a href="http://en.wikipedia.org/wiki/Uniform_distribution_%28continuous%29">
037 * Uniform distribution</a> class.
038 *
039 * @see LinearDistribution
040 *
041 * @author <a href="mailto:franz.wilhelmstoetter@gmx.at">Franz Wilhelmstötter</a>
042 * @since 1.0
043 * @version 2.0 — <em>$Date: 2014-03-28 $</em>
044 */
045 public class UniformDistribution<
046 N extends Number & Comparable<? super N>
047 >
048 implements Distribution<N>
049 {
050
051 /**
052 * <p>
053 * <img
054 * src="doc-files/uniform-pdf.gif"
055 * alt="f(x)=\left\{\begin{matrix}
056 * \frac{1}{max-min} & for & x \in [min, max] \\
057 * 0 & & otherwise \\
058 * \end{matrix}\right."
059 * >
060 * </p>
061 *
062 * @author <a href="mailto:franz.wilhelmstoetter@gmx.at">Franz Wilhelmstötter</a>
063 * @since 1.0
064 * @version 2.0 — <em>$Date: 2014-03-28 $</em>
065 */
066 static final class PDF<N extends Number & Comparable<? super N>>
067 implements
068 Function<N, Double>,
069 Serializable
070 {
071 private static final long serialVersionUID = 2L;
072
073 private final double _min;
074 private final double _max;
075 private final Double _probability;
076
077 public PDF(final Range<N> domain) {
078 _min = domain.getMin().doubleValue();
079 _max = domain.getMax().doubleValue();
080 _probability = 1.0/(_max - _min);
081 }
082
083 @Override
084 public Double apply(final N value) {
085 final double x = value.doubleValue();
086
087 double result = 0.0;
088 if (x >= _min && x <= _max) {
089 result = _probability;
090 }
091
092 return result;
093 }
094
095 @Override
096 public String toString() {
097 return format(Locale.ENGLISH, "p(x) = %s", _probability);
098 }
099
100 }
101
102 /**
103 * <p>
104 * <img
105 * src="doc-files/uniform-cdf.gif"
106 * alt="f(x)=\left\{\begin{matrix}
107 * 0 & for & x < min \\
108 * \frac{x-min}{max-min} & for & x \in [min, max] \\
109 * 1 & for & x > max \\
110 * \end{matrix}\right."
111 * >
112 * </p>
113 *
114 * @author <a href="mailto:franz.wilhelmstoetter@gmx.at">Franz Wilhelmstötter</a>
115 * @since 1.0
116 * @version 2.0 — <em>$Date: 2014-03-28 $</em>
117 */
118 static final class CDF<N extends Number & Comparable<? super N>>
119 implements
120 Function<N, Double>,
121 Serializable
122 {
123 private static final long serialVersionUID = 2L;
124
125
126 private final double _min;
127 private final double _max;
128 private final double _divisor;
129
130 public CDF(final Range<N> domain) {
131 _min = domain.getMin().doubleValue();
132 _max = domain.getMax().doubleValue();
133 _divisor = _max - _min;
134 assert (_divisor > 0);
135 }
136
137 @Override
138 public Double apply(final N value) {
139 final double x = value.doubleValue();
140
141 double result = 0.0;
142 if (x < _min) {
143 result = 0.0;
144 } else if (x > _max) {
145 result = 1.0;
146 } else {
147 result = (x - _min)/_divisor;
148 }
149
150 return result;
151 }
152
153 @Override
154 public String toString() {
155 return format(
156 Locale.ENGLISH,
157 "P(x) = (x - %1$s)/(%2$s - %1$s)", _min, _max
158 );
159 }
160
161 }
162
163
164 private final Range<N> _domain;
165 private final Function<N, Double> _cdf;
166 private final Function<N, Double> _pdf;
167
168 /**
169 * Create a new uniform distribution with the given {@code domain}.
170 *
171 * @param domain the domain of the distribution.
172 * @throws NullPointerException if the {@code domain} is {@code null}.
173 */
174 public UniformDistribution(final Range<N> domain) {
175 _domain = requireNonNull(domain, "Domain");
176 _cdf = new CDF<>(_domain);
177 _pdf = new PDF<>(_domain);
178 }
179
180 /**
181 * Create a new uniform distribution with the given min and max values.
182 *
183 * @param min the minimum value of the domain.
184 * @param max the maximum value of the domain.
185 * @throws IllegalArgumentException if {@code min >= max}
186 * @throws NullPointerException if one of the arguments is {@code null}.
187 */
188 public UniformDistribution(final N min, final N max) {
189 this(new Range<>(min, max));
190 }
191
192 @Override
193 public Range<N> getDomain() {
194 return _domain;
195 }
196
197 /**
198 * Return a new PDF object.
199 *
200 * <p>
201 * <img
202 * src="doc-files/uniform-pdf.gif"
203 * alt="f(x)=\left\{\begin{matrix}
204 * \frac{1}{max-min} & for & x \in [min, max] \\
205 * 0 & & otherwise \\
206 * \end{matrix}\right."
207 * >
208 * </p>
209 *
210 */
211 @Override
212 public Function<N, Double> getPDF() {
213 return _pdf;
214 }
215
216 /**
217 * Return a new CDF object.
218 *
219 * <p>
220 * <img
221 * src="doc-files/uniform-cdf.gif"
222 * alt="f(x)=\left\{\begin{matrix}
223 * 0 & for & x < min \\
224 * \frac{x-min}{max-min} & for & x \in [min, max] \\
225 * 1 & for & x > max \\
226 * \end{matrix}\right."
227 * >
228 * </p>
229 *
230 */
231 @Override
232 public Function<N, Double> getCDF() {
233 return _cdf;
234 }
235
236 @Override
237 public int hashCode() {
238 return HashBuilder.of(getClass()).and(_domain).value();
239 }
240
241 @Override
242 public boolean equals(final Object obj) {
243 if (obj == this) {
244 return true;
245 }
246 if (obj == null || getClass() != obj.getClass()) {
247 return false;
248 }
249
250 final UniformDistribution<?> dist = (UniformDistribution<?>)obj;
251 return eq(_domain, dist._domain);
252 }
253
254 @Override
255 public String toString() {
256 return format("UniformDistribution[%s]", _domain);
257 }
258
259 }
|