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 */
017package org.apache.commons.math3.random;
018
019import org.apache.commons.math3.exception.NotStrictlyPositiveException;
020import org.apache.commons.math3.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 $Id: AbstractRandomGenerator.java 1538368 2013-11-03 13:57:37Z erans $
035 */
036public 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}. Implementations 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 underlying 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 >>= 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) ((2d * nextDouble() - 1d) * 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) ((2d * nextDouble() - 1d) * 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}