1 /*
2 * Copyright 2005 The Apache Software Foundation.
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16 package org.apache.commons.math.random;
17
18 /**
19 * Abstract class implementing the {@link RandomGenerator} interface.
20 * Default implementations for all methods other than {@link #nextDouble()} and
21 * {@link #setSeed(long)} are provided.
22 * <p>
23 * All data generation methods are based on <code>nextDouble().</code>
24 * Concrete implementations <strong>must</strong> override
25 * this method and <strong>should</strong> provide better / more
26 * performant implementations of the other methods if the underlying PRNG
27 * supplies them.
28 *
29 * @since 1.1
30 * @version $Revision: 209144 $ $Date: 2005-07-04 16:30:05 -0700 (Mon, 04 Jul 2005) $
31 */
32 public abstract class AbstractRandomGenerator implements RandomGenerator {
33
34 /**
35 * Cached random normal value. The default implementation for
36 * {@link #nextGaussian} generates pairs of values and this field caches the
37 * second value so that the full algorithm is not executed for every
38 * activation. The value <code>Double.NaN</code> signals that there is
39 * no cached value. Use {@link #clear} to clear the cached value.
40 */
41 private double cachedNormalDeviate = Double.NaN;
42
43 /**
44 * Construct a RandomGenerator.
45 */
46 public AbstractRandomGenerator() {
47 super();
48
49 }
50
51 /**
52 * Clears the cache used by the default implementation of
53 * {@link #nextGaussian}. Implemementations that do not override the
54 * default implementation of <code>nextGaussian</code> should call this
55 * method in the implementation of {@link #setSeed(long)}
56 */
57 public void clear() {
58 cachedNormalDeviate = Double.NaN;
59 }
60
61 /**
62 * Sets the seed of the underyling random number generator using a
63 * <code>long</code> seed. Sequences of values generated starting with the
64 * same seeds should be identical.
65 * <p>
66 * Implementations that do not override the default implementation of
67 * <code>nextGaussian</code> should include a call to {@link #clear} in the
68 * implementation of this method.
69 *
70 * @param seed the seed value
71 */
72 public abstract void setSeed(long seed);
73
74 /**
75 * Generates random bytes and places them into a user-supplied
76 * byte array. The number of random bytes produced is equal to
77 * the length of the byte array.
78 * <p>
79 * The default implementation fills the array with bytes extracted from
80 * random integers generated using {@link #nextInt}.
81 *
82 * @param bytes the non-null byte array in which to put the
83 * random bytes
84 */
85 public void nextBytes(byte[] bytes) {
86 int bytesOut = 0;
87 while (bytesOut < bytes.length) {
88 int randInt = nextInt();
89 for (int i = 0; i < 3; i++) {
90 if ( i > 0) {
91 randInt = randInt >> 8;
92 }
93 bytes[bytesOut++] = (byte) randInt;
94 if (bytesOut == bytes.length) {
95 return;
96 }
97 }
98 }
99 }
100
101 /**
102 * Returns the next pseudorandom, uniformly distributed <code>int</code>
103 * value from this random number generator's sequence.
104 * All 2<font size="-1"><sup>32</sup></font> possible <tt>int</tt> values
105 * should be produced with (approximately) equal probability.
106 * <p>
107 * The default implementation provided here returns
108 * <pre>
109 * <code>(int) (nextDouble() * Integer.MAX_VALUE)</code>
110 * </pre>
111 *
112 * @return the next pseudorandom, uniformly distributed <code>int</code>
113 * value from this random number generator's sequence
114 */
115 public int nextInt() {
116 return (int) (nextDouble() * Integer.MAX_VALUE);
117 }
118
119 /**
120 * Returns a pseudorandom, uniformly distributed <tt>int</tt> value
121 * between 0 (inclusive) and the specified value (exclusive), drawn from
122 * this random number generator's sequence.
123 * <p>
124 * The default implementation returns
125 * <pre>
126 * <code>(int) (nextDouble() * n</code>
127 * </pre>
128 *
129 * @param n the bound on the random number to be returned. Must be
130 * positive.
131 * @return a pseudorandom, uniformly distributed <tt>int</tt>
132 * value between 0 (inclusive) and n (exclusive).
133 * @throws IllegalArgumentException if n is not positive.
134 */
135 public int nextInt(int n) {
136 if (n <= 0 ) {
137 throw new IllegalArgumentException("upper bound must be positive");
138 }
139 int result = (int) (nextDouble() * n);
140 return result < n ? result : n - 1;
141 }
142
143 /**
144 * Returns the next pseudorandom, uniformly distributed <code>long</code>
145 * value from this random number generator's sequence. All
146 * 2<font size="-1"><sup>64</sup></font> possible <tt>long</tt> values
147 * should be produced with (approximately) equal probability.
148 * <p>
149 * The default implementation returns
150 * <pre>
151 * <code>(long) (nextDouble() * Long.MAX_VALUE)</code>
152 * </pre>
153 *
154 * @return the next pseudorandom, uniformly distributed <code>long</code>
155 *value from this random number generator's sequence
156 */
157 public long nextLong() {
158 return (long) (nextDouble() * Long.MAX_VALUE);
159 }
160
161 /**
162 * Returns the next pseudorandom, uniformly distributed
163 * <code>boolean</code> value from this random number generator's
164 * sequence.
165 * <p>
166 * The default implementation returns
167 * <pre>
168 * <code>nextDouble() <= 0.5</code>
169 * </pre>
170 *
171 * @return the next pseudorandom, uniformly distributed
172 * <code>boolean</code> value from this random number generator's
173 * sequence
174 */
175 public boolean nextBoolean() {
176 return nextDouble() <= 0.5;
177 }
178
179 /**
180 * Returns the next pseudorandom, uniformly distributed <code>float</code>
181 * value between <code>0.0</code> and <code>1.0</code> from this random
182 * number generator's sequence.
183 * <p>
184 * The default implementation returns
185 * <pre>
186 * <code>(float) nextDouble() </code>
187 * </pre>
188 *
189 * @return the next pseudorandom, uniformly distributed <code>float</code>
190 * value between <code>0.0</code> and <code>1.0</code> from this
191 * random number generator's sequence
192 */
193 public float nextFloat() {
194 return (float) nextDouble();
195 }
196
197 /**
198 * Returns the next pseudorandom, uniformly distributed
199 * <code>double</code> value between <code>0.0</code> and
200 * <code>1.0</code> from this random number generator's sequence.
201 * <p>
202 * This method provides the underlying source of random data used by the
203 * other methods.
204 *
205 * @return the next pseudorandom, uniformly distributed
206 * <code>double</code> value between <code>0.0</code> and
207 * <code>1.0</code> from this random number generator's sequence
208 */
209 public abstract double nextDouble();
210
211 /**
212 * Returns the next pseudorandom, Gaussian ("normally") distributed
213 * <code>double</code> value with mean <code>0.0</code> and standard
214 * deviation <code>1.0</code> from this random number generator's sequence.
215 * <p>
216 * The default implementation uses the <em>Polar Method</em>
217 * due to G.E.P. Box, M.E. Muller and G. Marsaglia, as described in
218 * D. Knuth, <u>The Art of Computer Programming</u>, 3.4.1C.
219 * <p>
220 * The algorithm generates a pair of independent random values. One of
221 * these is cached for reuse, so the full algorithm is not executed on each
222 * activation. Implementations that do not override this method should
223 * make sure to call {@link #clear} to clear the cached value in the
224 * implementation of {@link #setSeed(long)}.
225 *
226 * @return the next pseudorandom, Gaussian ("normally") distributed
227 * <code>double</code> value with mean <code>0.0</code> and
228 * standard deviation <code>1.0</code> from this random number
229 * generator's sequence
230 */
231 public double nextGaussian() {
232 if (!Double.isNaN(cachedNormalDeviate)) {
233 double dev = cachedNormalDeviate;
234 cachedNormalDeviate = Double.NaN;
235 return dev;
236 }
237 double v1 = 0;
238 double v2 = 0;
239 double s = 1;
240 while (s >=1 ) {
241 v1 = 2 * nextDouble() - 1;
242 v2 = 2 * nextDouble() - 1;
243 s = v1 * v1 + v2 * v2;
244 }
245 if (s != 0) {
246 s = Math.sqrt(-2 * Math.log(s) / s);
247 }
248 cachedNormalDeviate = v2 * s;
249 return v1 * s;
250 }
251 }