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 * http://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 package org.apache.commons.math.random;
18
19 /**
20 * Abstract class implementing the {@link RandomGenerator} interface.
21 * Default implementations for all methods other than {@link #nextDouble()} and
22 * {@link #setSeed(long)} are provided.
23 * <p>
24 * All data generation methods are based on <code>nextDouble().</code>
25 * Concrete implementations <strong>must</strong> override
26 * this method and <strong>should</strong> provide better / more
27 * performant implementations of the other methods if the underlying PRNG
28 * supplies them.</p>
29 *
30 * @since 1.1
31 * @version $Revision: 615734 $ $Date: 2008-01-27 23:10:03 -0700 (Sun, 27 Jan 2008) $
32 */
33 public abstract class AbstractRandomGenerator implements RandomGenerator {
34
35 /**
36 * Cached random normal value. The default implementation for
37 * {@link #nextGaussian} generates pairs of values and this field caches the
38 * second value so that the full algorithm is not executed for every
39 * activation. The value <code>Double.NaN</code> signals that there is
40 * no cached value. Use {@link #clear} to clear the cached value.
41 */
42 private double cachedNormalDeviate = Double.NaN;
43
44 /**
45 * Construct a RandomGenerator.
46 */
47 public AbstractRandomGenerator() {
48 super();
49
50 }
51
52 /**
53 * Clears the cache used by the default implementation of
54 * {@link #nextGaussian}. Implemementations that do not override the
55 * default implementation of <code>nextGaussian</code> should call this
56 * method in the implementation of {@link #setSeed(long)}
57 */
58 public void clear() {
59 cachedNormalDeviate = Double.NaN;
60 }
61
62 /**
63 * Sets the seed of the underyling random number generator using a
64 * <code>long</code> seed. Sequences of values generated starting with the
65 * same seeds should be identical.
66 * <p>
67 * Implementations that do not override the default implementation of
68 * <code>nextGaussian</code> should include a call to {@link #clear} in the
69 * implementation of this method.</p>
70 *
71 * @param seed the seed value
72 */
73 public abstract void setSeed(long seed);
74
75 /**
76 * Generates random bytes and places them into a user-supplied
77 * byte array. The number of random bytes produced is equal to
78 * the length of the byte array.
79 * <p>
80 * The default implementation fills the array with bytes extracted from
81 * random integers generated using {@link #nextInt}.</p>
82 *
83 * @param bytes the non-null byte array in which to put the
84 * random bytes
85 */
86 public void nextBytes(byte[] bytes) {
87 int bytesOut = 0;
88 while (bytesOut < bytes.length) {
89 int randInt = nextInt();
90 for (int i = 0; i < 3; i++) {
91 if ( i > 0) {
92 randInt = randInt >> 8;
93 }
94 bytes[bytesOut++] = (byte) randInt;
95 if (bytesOut == bytes.length) {
96 return;
97 }
98 }
99 }
100 }
101
102 /**
103 * Returns the next pseudorandom, uniformly distributed <code>int</code>
104 * value from this random number generator's sequence.
105 * All 2<font size="-1"><sup>32</sup></font> possible <tt>int</tt> values
106 * should be produced with (approximately) equal probability.
107 * <p>
108 * The default implementation provided here returns
109 * <pre>
110 * <code>(int) (nextDouble() * Integer.MAX_VALUE)</code>
111 * </pre></p>
112 *
113 * @return the next pseudorandom, uniformly distributed <code>int</code>
114 * value from this random number generator's sequence
115 */
116 public int nextInt() {
117 return (int) (nextDouble() * Integer.MAX_VALUE);
118 }
119
120 /**
121 * Returns a pseudorandom, uniformly distributed <tt>int</tt> value
122 * between 0 (inclusive) and the specified value (exclusive), drawn from
123 * this random number generator's sequence.
124 * <p>
125 * The default implementation returns
126 * <pre>
127 * <code>(int) (nextDouble() * n</code>
128 * </pre></p>
129 *
130 * @param n the bound on the random number to be returned. Must be
131 * positive.
132 * @return a pseudorandom, uniformly distributed <tt>int</tt>
133 * value between 0 (inclusive) and n (exclusive).
134 * @throws IllegalArgumentException if n is not positive.
135 */
136 public int nextInt(int n) {
137 if (n <= 0 ) {
138 throw new IllegalArgumentException("upper bound must be positive");
139 }
140 int result = (int) (nextDouble() * n);
141 return result < n ? result : n - 1;
142 }
143
144 /**
145 * Returns the next pseudorandom, uniformly distributed <code>long</code>
146 * value from this random number generator's sequence. All
147 * 2<font size="-1"><sup>64</sup></font> possible <tt>long</tt> values
148 * should be produced with (approximately) equal probability.
149 * <p>
150 * The default implementation returns
151 * <pre>
152 * <code>(long) (nextDouble() * Long.MAX_VALUE)</code>
153 * </pre></p>
154 *
155 * @return the next pseudorandom, uniformly distributed <code>long</code>
156 *value from this random number generator's sequence
157 */
158 public long nextLong() {
159 return (long) (nextDouble() * Long.MAX_VALUE);
160 }
161
162 /**
163 * Returns the next pseudorandom, uniformly distributed
164 * <code>boolean</code> value from this random number generator's
165 * sequence.
166 * <p>
167 * The default implementation returns
168 * <pre>
169 * <code>nextDouble() <= 0.5</code>
170 * </pre></p>
171 *
172 * @return the next pseudorandom, uniformly distributed
173 * <code>boolean</code> value from this random number generator's
174 * sequence
175 */
176 public boolean nextBoolean() {
177 return nextDouble() <= 0.5;
178 }
179
180 /**
181 * Returns the next pseudorandom, uniformly distributed <code>float</code>
182 * value between <code>0.0</code> and <code>1.0</code> from this random
183 * number generator's sequence.
184 * <p>
185 * The default implementation returns
186 * <pre>
187 * <code>(float) nextDouble() </code>
188 * </pre></p>
189 *
190 * @return the next pseudorandom, uniformly distributed <code>float</code>
191 * value between <code>0.0</code> and <code>1.0</code> from this
192 * random number generator's sequence
193 */
194 public float nextFloat() {
195 return (float) nextDouble();
196 }
197
198 /**
199 * Returns the next pseudorandom, uniformly distributed
200 * <code>double</code> value between <code>0.0</code> and
201 * <code>1.0</code> from this random number generator's sequence.
202 * <p>
203 * This method provides the underlying source of random data used by the
204 * other methods.</p>
205 *
206 * @return the next pseudorandom, uniformly distributed
207 * <code>double</code> value between <code>0.0</code> and
208 * <code>1.0</code> from this random number generator's sequence
209 */
210 public abstract double nextDouble();
211
212 /**
213 * Returns the next pseudorandom, Gaussian ("normally") distributed
214 * <code>double</code> value with mean <code>0.0</code> and standard
215 * deviation <code>1.0</code> from this random number generator's sequence.
216 * <p>
217 * The default implementation uses the <em>Polar Method</em>
218 * due to G.E.P. Box, M.E. Muller and G. Marsaglia, as described in
219 * D. Knuth, <u>The Art of Computer Programming</u>, 3.4.1C.</p>
220 * <p>
221 * The algorithm generates a pair of independent random values. One of
222 * these is cached for reuse, so the full algorithm is not executed on each
223 * activation. Implementations that do not override this method should
224 * make sure to call {@link #clear} to clear the cached value in the
225 * implementation of {@link #setSeed(long)}.</p>
226 *
227 * @return the next pseudorandom, Gaussian ("normally") distributed
228 * <code>double</code> value with mean <code>0.0</code> and
229 * standard deviation <code>1.0</code> from this random number
230 * generator's sequence
231 */
232 public double nextGaussian() {
233 if (!Double.isNaN(cachedNormalDeviate)) {
234 double dev = cachedNormalDeviate;
235 cachedNormalDeviate = Double.NaN;
236 return dev;
237 }
238 double v1 = 0;
239 double v2 = 0;
240 double s = 1;
241 while (s >=1 ) {
242 v1 = 2 * nextDouble() - 1;
243 v2 = 2 * nextDouble() - 1;
244 s = v1 * v1 + v2 * v2;
245 }
246 if (s != 0) {
247 s = Math.sqrt(-2 * Math.log(s) / s);
248 }
249 cachedNormalDeviate = v2 * s;
250 return v1 * s;
251 }
252 }