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.MathRuntimeException; 020 021 /** 022 * Abstract class implementing the {@link RandomGenerator} interface. 023 * Default implementations for all methods other than {@link #nextDouble()} and 024 * {@link #setSeed(long)} are provided. 025 * <p> 026 * All data generation methods are based on <code>nextDouble().</code> 027 * Concrete implementations <strong>must</strong> override 028 * this method and <strong>should</strong> provide better / more 029 * performant implementations of the other methods if the underlying PRNG 030 * supplies them.</p> 031 * 032 * @since 1.1 033 * @version $Revision: 796543 $ $Date: 2009-07-21 17:32:38 -0400 (Tue, 21 Jul 2009) $ 034 */ 035 public abstract class AbstractRandomGenerator implements RandomGenerator { 036 037 /** 038 * Cached random normal value. The default implementation for 039 * {@link #nextGaussian} generates pairs of values and this field caches the 040 * second value so that the full algorithm is not executed for every 041 * activation. The value <code>Double.NaN</code> signals that there is 042 * no cached value. Use {@link #clear} to clear the cached value. 043 */ 044 private double cachedNormalDeviate = Double.NaN; 045 046 /** 047 * Construct a RandomGenerator. 048 */ 049 public AbstractRandomGenerator() { 050 super(); 051 052 } 053 054 /** 055 * Clears the cache used by the default implementation of 056 * {@link #nextGaussian}. Implemementations that do not override the 057 * default implementation of <code>nextGaussian</code> should call this 058 * method in the implementation of {@link #setSeed(long)} 059 */ 060 public void clear() { 061 cachedNormalDeviate = Double.NaN; 062 } 063 064 /** {@inheritDoc} */ 065 public void setSeed(int seed) { 066 setSeed((long) seed); 067 } 068 069 /** {@inheritDoc} */ 070 public void setSeed(int[] seed) { 071 // the following number is the largest prime that fits in 32 bits (it is 2^32 - 5) 072 final long prime = 4294967291l; 073 074 long combined = 0l; 075 for (int s : seed) { 076 combined = combined * prime + s; 077 } 078 setSeed(combined); 079 } 080 081 /** 082 * Sets the seed of the underyling random number generator using a 083 * <code>long</code> seed. Sequences of values generated starting with the 084 * same seeds should be identical. 085 * <p> 086 * Implementations that do not override the default implementation of 087 * <code>nextGaussian</code> should include a call to {@link #clear} in the 088 * implementation of this method.</p> 089 * 090 * @param seed the seed value 091 */ 092 public abstract void setSeed(long seed); 093 094 /** 095 * Generates random bytes and places them into a user-supplied 096 * byte array. The number of random bytes produced is equal to 097 * the length of the byte array. 098 * <p> 099 * The default implementation fills the array with bytes extracted from 100 * random integers generated using {@link #nextInt}.</p> 101 * 102 * @param bytes the non-null byte array in which to put the 103 * random bytes 104 */ 105 public void nextBytes(byte[] bytes) { 106 int bytesOut = 0; 107 while (bytesOut < bytes.length) { 108 int randInt = nextInt(); 109 for (int i = 0; i < 3; i++) { 110 if ( i > 0) { 111 randInt = randInt >> 8; 112 } 113 bytes[bytesOut++] = (byte) randInt; 114 if (bytesOut == bytes.length) { 115 return; 116 } 117 } 118 } 119 } 120 121 /** 122 * Returns the next pseudorandom, uniformly distributed <code>int</code> 123 * value from this random number generator's sequence. 124 * All 2<font size="-1"><sup>32</sup></font> possible <tt>int</tt> values 125 * should be produced with (approximately) equal probability. 126 * <p> 127 * The default implementation provided here returns 128 * <pre> 129 * <code>(int) (nextDouble() * Integer.MAX_VALUE)</code> 130 * </pre></p> 131 * 132 * @return the next pseudorandom, uniformly distributed <code>int</code> 133 * value from this random number generator's sequence 134 */ 135 public int nextInt() { 136 return (int) (nextDouble() * Integer.MAX_VALUE); 137 } 138 139 /** 140 * Returns a pseudorandom, uniformly distributed <tt>int</tt> value 141 * between 0 (inclusive) and the specified value (exclusive), drawn from 142 * this random number generator's sequence. 143 * <p> 144 * The default implementation returns 145 * <pre> 146 * <code>(int) (nextDouble() * n</code> 147 * </pre></p> 148 * 149 * @param n the bound on the random number to be returned. Must be 150 * positive. 151 * @return a pseudorandom, uniformly distributed <tt>int</tt> 152 * value between 0 (inclusive) and n (exclusive). 153 * @throws IllegalArgumentException if n is not positive. 154 */ 155 public int nextInt(int n) { 156 if (n <= 0 ) { 157 throw MathRuntimeException.createIllegalArgumentException( 158 "upper bound must be positive ({0})", 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</code> 166 * value from this random number generator's sequence. All 167 * 2<font size="-1"><sup>64</sup></font> possible <tt>long</tt> 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</code> 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</code> 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</code> 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</code> 202 * value between <code>0.0</code> and <code>1.0</code> 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</code> 211 * value between <code>0.0</code> and <code>1.0</code> 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</code> value between <code>0.0</code> and 221 * <code>1.0</code> 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</code> value between <code>0.0</code> and 228 * <code>1.0</code> 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</code> value with mean <code>0.0</code> and standard 235 * deviation <code>1.0</code> 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</code> value with mean <code>0.0</code> and 249 * standard deviation <code>1.0</code> 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 = Math.sqrt(-2 * Math.log(s) / s); 268 } 269 cachedNormalDeviate = v2 * s; 270 return v1 * s; 271 } 272 }