001 /*
002 * Java Genetic Algorithm Library (jenetics-1.5.0).
003 * Copyright (c) 2007-2013 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.util.object.eq;
025 import static org.jenetics.util.object.hashCodeOf;
026
027 import java.io.Serializable;
028 import java.util.Locale;
029
030 import org.jscience.mathematics.number.Float64;
031
032 import org.jenetics.util.Function;
033 import org.jenetics.util.Range;
034
035
036 /**
037 * <a href="http://en.wikipedia.org/wiki/Uniform_distribution_%28continuous%29">
038 * Uniform distribution</a> class.
039 *
040 * @see LinearDistribution
041 *
042 * @author <a href="mailto:franz.wilhelmstoetter@gmx.at">Franz Wilhelmstötter</a>
043 * @since 1.0
044 * @version 1.0 — <em>$Date: 2013-09-01 $</em>
045 */
046 public class UniformDistribution<
047 N extends Number & Comparable<? super N>
048 >
049 implements Distribution<N>
050 {
051
052 /**
053 * <p>
054 * <img
055 * src="doc-files/uniform-pdf.gif"
056 * alt="f(x)=\left\{\begin{matrix}
057 * \frac{1}{max-min} & for & x \in [min, max] \\
058 * 0 & & otherwise \\
059 * \end{matrix}\right."
060 * />
061 * </p>
062 *
063 * @author <a href="mailto:franz.wilhelmstoetter@gmx.at">Franz Wilhelmstötter</a>
064 * @since 1.0
065 * @version 1.0 — <em>$Date: 2013-09-01 $</em>
066 */
067 static final class PDF<N extends Number & Comparable<? super N>>
068 implements
069 Function<N, Float64>,
070 Serializable
071 {
072 private static final long serialVersionUID = 1L;
073
074 private final double _min;
075 private final double _max;
076 private final Float64 _probability;
077
078 public PDF(final Range<N> domain) {
079 _min = domain.getMin().doubleValue();
080 _max = domain.getMax().doubleValue();
081 _probability = Float64.valueOf(1.0/(_max - _min));
082 }
083
084 @Override
085 public Float64 apply(final N value) {
086 final double x = value.doubleValue();
087
088 Float64 result = Float64.ZERO;
089 if (x >= _min && x <= _max) {
090 result = _probability;
091 }
092
093 return result;
094 }
095
096 @Override
097 public String toString() {
098 return format(Locale.ENGLISH, "p(x) = %s", _probability);
099 }
100
101 }
102
103 /**
104 * <p>
105 * <img
106 * src="doc-files/uniform-cdf.gif"
107 * alt="f(x)=\left\{\begin{matrix}
108 * 0 & for & x < min \\
109 * \frac{x-min}{max-min} & for & x \in [min, max] \\
110 * 1 & for & x > max \\
111 * \end{matrix}\right."
112 * />
113 * </p>
114 *
115 * @author <a href="mailto:franz.wilhelmstoetter@gmx.at">Franz Wilhelmstötter</a>
116 * @since 1.0
117 * @version 1.0 — <em>$Date: 2013-09-01 $</em>
118 */
119 static final class CDF<N extends Number & Comparable<? super N>>
120 implements
121 Function<N, Float64>,
122 Serializable
123 {
124 private static final long serialVersionUID = 1L;
125
126
127 private final double _min;
128 private final double _max;
129 private final double _divisor;
130
131 public CDF(final Range<N> domain) {
132 _min = domain.getMin().doubleValue();
133 _max = domain.getMax().doubleValue();
134 _divisor = _max - _min;
135 assert (_divisor > 0);
136 }
137
138 @Override
139 public Float64 apply(final N value) {
140 final double x = value.doubleValue();
141
142 Float64 result = Float64.ZERO;
143 if (x < _min) {
144 result = Float64.ZERO;
145 } else if (x > _max) {
146 result = Float64.ONE;
147 } else {
148 result = Float64.valueOf((x - _min)/_divisor);
149 }
150
151 return result;
152 }
153
154 @Override
155 public String toString() {
156 return format(
157 Locale.ENGLISH,
158 "P(x) = (x - %1$s)/(%2$s - %1$s)", _min, _max
159 );
160 }
161
162 }
163
164
165 private final Range<N> _domain;
166 private final Function<N, Float64> _cdf;
167 private final Function<N, Float64> _pdf;
168
169 /**
170 * Create a new uniform distribution with the given {@code domain}.
171 *
172 * @param domain the domain of the distribution.
173 * @throws NullPointerException if the {@code domain} is {@code null}.
174 */
175 public UniformDistribution(final Range<N> domain) {
176 _domain = requireNonNull(domain, "Domain");
177 _cdf = new CDF<>(_domain);
178 _pdf = new PDF<>(_domain);
179 }
180
181 /**
182 * Create a new uniform distribution with the given min and max values.
183 *
184 * @param min the minimum value of the domain.
185 * @param max the maximum value of the domain.
186 * @throws IllegalArgumentException if {@code min >= max}
187 * @throws NullPointerException if one of the arguments is {@code null}.
188 */
189 public UniformDistribution(final N min, final N max) {
190 this(new Range<>(min, max));
191 }
192
193 @Override
194 public Range<N> getDomain() {
195 return _domain;
196 }
197
198 /**
199 * Return a new PDF object.
200 *
201 * <p>
202 * <img
203 * src="doc-files/uniform-pdf.gif"
204 * alt="f(x)=\left\{\begin{matrix}
205 * \frac{1}{max-min} & for & x \in [min, max] \\
206 * 0 & & otherwise \\
207 * \end{matrix}\right."
208 * />
209 * </p>
210 *
211 */
212 @Override
213 public Function<N, Float64> getPDF() {
214 return _pdf;
215 }
216
217 /**
218 * Return a new CDF object.
219 *
220 * <p>
221 * <img
222 * src="doc-files/uniform-cdf.gif"
223 * alt="f(x)=\left\{\begin{matrix}
224 * 0 & for & x < min \\
225 * \frac{x-min}{max-min} & for & x \in [min, max] \\
226 * 1 & for & x > max \\
227 * \end{matrix}\right."
228 * />
229 * </p>
230 *
231 */
232 @Override
233 public Function<N, Float64> getCDF() {
234 return _cdf;
235 }
236
237 @Override
238 public int hashCode() {
239 return hashCodeOf(getClass()).and(_domain).value();
240 }
241
242 @Override
243 public boolean equals(final Object obj) {
244 if (obj == this) {
245 return true;
246 }
247 if (obj == null || getClass() != obj.getClass()) {
248 return false;
249 }
250
251 final UniformDistribution<?> dist = (UniformDistribution<?>)obj;
252 return eq(_domain, dist._domain);
253 }
254
255 @Override
256 public String toString() {
257 return format("UniformDistribution[%s]", _domain);
258 }
259
260 }
261
262
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