001 /*
002 * Licensed to the Apache Software Foundation (ASF) under one or more
003 * contributor license agreements. See the NOTICE file distributed with
004 * this work for additional information regarding copyright ownership.
005 * The ASF licenses this file to You under the Apache License, Version 2.0
006 * (the "License"); you may not use this file except in compliance with
007 * the License. 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 package org.apache.commons.math.random;
018
019 import org.apache.commons.math.exception.NotStrictlyPositiveException;
020 import org.apache.commons.math.util.FastMath;
021
022 /**
023 * Abstract class implementing the {@link RandomGenerator} interface.
024 * Default implementations for all methods other than {@link #nextDouble()} and
025 * {@link #setSeed(long)} are provided.
026 * <p>
027 * All data generation methods are based on {@code code nextDouble()}.
028 * Concrete implementations <strong>must</strong> override
029 * this method and <strong>should</strong> provide better / more
030 * performant implementations of the other methods if the underlying PRNG
031 * supplies them.</p>
032 *
033 * @since 1.1
034 * @version $Revision: 990655 $ $Date: 2010-08-29 23:49:40 +0200 (dim. 29 ao??t 2010) $
035 */
036 public abstract class AbstractRandomGenerator implements RandomGenerator {
037
038 /**
039 * Cached random normal value. The default implementation for
040 * {@link #nextGaussian} generates pairs of values and this field caches the
041 * second value so that the full algorithm is not executed for every
042 * activation. The value {@code Double.NaN} signals that there is
043 * no cached value. Use {@link #clear} to clear the cached value.
044 */
045 private double cachedNormalDeviate = Double.NaN;
046
047 /**
048 * Construct a RandomGenerator.
049 */
050 public AbstractRandomGenerator() {
051 super();
052
053 }
054
055 /**
056 * Clears the cache used by the default implementation of
057 * {@link #nextGaussian}. Implemementations that do not override the
058 * default implementation of {@code nextGaussian} should call this
059 * method in the implementation of {@link #setSeed(long)}
060 */
061 public void clear() {
062 cachedNormalDeviate = Double.NaN;
063 }
064
065 /** {@inheritDoc} */
066 public void setSeed(int seed) {
067 setSeed((long) seed);
068 }
069
070 /** {@inheritDoc} */
071 public void setSeed(int[] seed) {
072 // the following number is the largest prime that fits in 32 bits (it is 2^32 - 5)
073 final long prime = 4294967291l;
074
075 long combined = 0l;
076 for (int s : seed) {
077 combined = combined * prime + s;
078 }
079 setSeed(combined);
080 }
081
082 /**
083 * Sets the seed of the underyling random number generator using a
084 * {@code long} seed. Sequences of values generated starting with the
085 * same seeds should be identical.
086 * <p>
087 * Implementations that do not override the default implementation of
088 * {@code nextGaussian} should include a call to {@link #clear} in the
089 * implementation of this method.</p>
090 *
091 * @param seed the seed value
092 */
093 public abstract void setSeed(long seed);
094
095 /**
096 * Generates random bytes and places them into a user-supplied
097 * byte array. The number of random bytes produced is equal to
098 * the length of the byte array.
099 * <p>
100 * The default implementation fills the array with bytes extracted from
101 * random integers generated using {@link #nextInt}.</p>
102 *
103 * @param bytes the non-null byte array in which to put the
104 * random bytes
105 */
106 public void nextBytes(byte[] bytes) {
107 int bytesOut = 0;
108 while (bytesOut < bytes.length) {
109 int randInt = nextInt();
110 for (int i = 0; i < 3; i++) {
111 if ( i > 0) {
112 randInt = randInt >> 8;
113 }
114 bytes[bytesOut++] = (byte) randInt;
115 if (bytesOut == bytes.length) {
116 return;
117 }
118 }
119 }
120 }
121
122 /**
123 * Returns the next pseudorandom, uniformly distributed {@code int}
124 * value from this random number generator's sequence.
125 * All 2<font size="-1"><sup>32</sup></font> possible {@code int} values
126 * should be produced with (approximately) equal probability.
127 * <p>
128 * The default implementation provided here returns
129 * <pre>
130 * <code>(int) (nextDouble() * Integer.MAX_VALUE)</code>
131 * </pre></p>
132 *
133 * @return the next pseudorandom, uniformly distributed {@code int}
134 * value from this random number generator's sequence
135 */
136 public int nextInt() {
137 return (int) (nextDouble() * Integer.MAX_VALUE);
138 }
139
140 /**
141 * Returns a pseudorandom, uniformly distributed {@code int} value
142 * between 0 (inclusive) and the specified value (exclusive), drawn from
143 * this random number generator's sequence.
144 * <p>
145 * The default implementation returns
146 * <pre>
147 * <code>(int) (nextDouble() * n</code>
148 * </pre></p>
149 *
150 * @param n the bound on the random number to be returned. Must be
151 * positive.
152 * @return a pseudorandom, uniformly distributed {@code int}
153 * value between 0 (inclusive) and n (exclusive).
154 * @throws NotStrictlyPositiveException if {@code n <= 0}.
155 */
156 public int nextInt(int n) {
157 if (n <= 0 ) {
158 throw new NotStrictlyPositiveException(n);
159 }
160 int result = (int) (nextDouble() * n);
161 return result < n ? result : n - 1;
162 }
163
164 /**
165 * Returns the next pseudorandom, uniformly distributed {@code long}
166 * value from this random number generator's sequence. All
167 * 2<font size="-1"><sup>64</sup></font> possible {@code long} values
168 * should be produced with (approximately) equal probability.
169 * <p>
170 * The default implementation returns
171 * <pre>
172 * <code>(long) (nextDouble() * Long.MAX_VALUE)</code>
173 * </pre></p>
174 *
175 * @return the next pseudorandom, uniformly distributed {@code long}
176 *value from this random number generator's sequence
177 */
178 public long nextLong() {
179 return (long) (nextDouble() * Long.MAX_VALUE);
180 }
181
182 /**
183 * Returns the next pseudorandom, uniformly distributed
184 * {@code boolean} value from this random number generator's
185 * sequence.
186 * <p>
187 * The default implementation returns
188 * <pre>
189 * <code>nextDouble() <= 0.5</code>
190 * </pre></p>
191 *
192 * @return the next pseudorandom, uniformly distributed
193 * {@code boolean} value from this random number generator's
194 * sequence
195 */
196 public boolean nextBoolean() {
197 return nextDouble() <= 0.5;
198 }
199
200 /**
201 * Returns the next pseudorandom, uniformly distributed {@code float}
202 * value between {@code 0.0} and {@code 1.0} from this random
203 * number generator's sequence.
204 * <p>
205 * The default implementation returns
206 * <pre>
207 * <code>(float) nextDouble() </code>
208 * </pre></p>
209 *
210 * @return the next pseudorandom, uniformly distributed {@code float}
211 * value between {@code 0.0} and {@code 1.0} from this
212 * random number generator's sequence
213 */
214 public float nextFloat() {
215 return (float) nextDouble();
216 }
217
218 /**
219 * Returns the next pseudorandom, uniformly distributed
220 * {@code double} value between {@code 0.0} and
221 * {@code 1.0} from this random number generator's sequence.
222 * <p>
223 * This method provides the underlying source of random data used by the
224 * other methods.</p>
225 *
226 * @return the next pseudorandom, uniformly distributed
227 * {@code double} value between {@code 0.0} and
228 * {@code 1.0} from this random number generator's sequence
229 */
230 public abstract double nextDouble();
231
232 /**
233 * Returns the next pseudorandom, Gaussian ("normally") distributed
234 * {@code double} value with mean {@code 0.0} and standard
235 * deviation {@code 1.0} from this random number generator's sequence.
236 * <p>
237 * The default implementation uses the <em>Polar Method</em>
238 * due to G.E.P. Box, M.E. Muller and G. Marsaglia, as described in
239 * D. Knuth, <u>The Art of Computer Programming</u>, 3.4.1C.</p>
240 * <p>
241 * The algorithm generates a pair of independent random values. One of
242 * these is cached for reuse, so the full algorithm is not executed on each
243 * activation. Implementations that do not override this method should
244 * make sure to call {@link #clear} to clear the cached value in the
245 * implementation of {@link #setSeed(long)}.</p>
246 *
247 * @return the next pseudorandom, Gaussian ("normally") distributed
248 * {@code double} value with mean {@code 0.0} and
249 * standard deviation {@code 1.0} from this random number
250 * generator's sequence
251 */
252 public double nextGaussian() {
253 if (!Double.isNaN(cachedNormalDeviate)) {
254 double dev = cachedNormalDeviate;
255 cachedNormalDeviate = Double.NaN;
256 return dev;
257 }
258 double v1 = 0;
259 double v2 = 0;
260 double s = 1;
261 while (s >=1 ) {
262 v1 = 2 * nextDouble() - 1;
263 v2 = 2 * nextDouble() - 1;
264 s = v1 * v1 + v2 * v2;
265 }
266 if (s != 0) {
267 s = FastMath.sqrt(-2 * FastMath.log(s) / s);
268 }
269 cachedNormalDeviate = v2 * s;
270 return v1 * s;
271 }
272 }