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 */
035public 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} 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}. Implementations that do not override the
057     * default implementation of {@code nextGaussian} 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 underlying random number generator using a
083     * {@code long} 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} 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 >>= 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}
123     * value from this random number generator's sequence.
124     * All 2<font size="-1"><sup>32</sup></font> possible {@code int} 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}
133     *  value from this random number generator's sequence
134     */
135    public int nextInt() {
136        return (int) ((2d * nextDouble() - 1d) * Integer.MAX_VALUE);
137    }
138
139    /**
140     * Returns a pseudorandom, uniformly distributed {@code int} 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 {@code int}
152     * value between 0 (inclusive) and n (exclusive).
153     * @throws NotStrictlyPositiveException if {@code n <= 0}.
154     */
155    public int nextInt(int n) {
156        if (n <= 0 ) {
157            throw new NotStrictlyPositiveException(n);
158        }
159        int result = (int) (nextDouble() * n);
160        return result < n ? result : n - 1;
161    }
162
163     /**
164     * Returns the next pseudorandom, uniformly distributed {@code long}
165     * value from this random number generator's sequence.  All
166     * 2<font size="-1"><sup>64</sup></font> possible {@code long} values
167     * should be produced with (approximately) equal probability.
168     * <p>
169     * The default implementation returns
170     * <pre>
171     * <code>(long) (nextDouble() * Long.MAX_VALUE)</code>
172     * </pre></p>
173     *
174     * @return  the next pseudorandom, uniformly distributed {@code long}
175     *value from this random number generator's sequence
176     */
177    public long nextLong() {
178        return (long) ((2d * nextDouble() - 1d) * Long.MAX_VALUE);
179    }
180
181    /**
182     * Returns the next pseudorandom, uniformly distributed
183     * {@code boolean} value from this random number generator's
184     * sequence.
185     * <p>
186     * The default implementation returns
187     * <pre>
188     * <code>nextDouble() <= 0.5</code>
189     * </pre></p>
190     *
191     * @return  the next pseudorandom, uniformly distributed
192     * {@code boolean} value from this random number generator's
193     * sequence
194     */
195    public boolean nextBoolean() {
196        return nextDouble() <= 0.5;
197    }
198
199     /**
200     * Returns the next pseudorandom, uniformly distributed {@code float}
201     * value between {@code 0.0} and {@code 1.0} from this random
202     * number generator's sequence.
203     * <p>
204     * The default implementation returns
205     * <pre>
206     * <code>(float) nextDouble() </code>
207     * </pre></p>
208     *
209     * @return  the next pseudorandom, uniformly distributed {@code float}
210     * value between {@code 0.0} and {@code 1.0} from this
211     * random number generator's sequence
212     */
213    public float nextFloat() {
214        return (float) nextDouble();
215    }
216
217    /**
218     * Returns the next pseudorandom, uniformly distributed
219     * {@code double} value between {@code 0.0} and
220     * {@code 1.0} from this random number generator's sequence.
221     * <p>
222     * This method provides the underlying source of random data used by the
223     * other methods.</p>
224     *
225     * @return  the next pseudorandom, uniformly distributed
226     *  {@code double} value between {@code 0.0} and
227     *  {@code 1.0} from this random number generator's sequence
228     */
229    public abstract double nextDouble();
230
231    /**
232     * Returns the next pseudorandom, Gaussian ("normally") distributed
233     * {@code double} value with mean {@code 0.0} and standard
234     * deviation {@code 1.0} from this random number generator's sequence.
235     * <p>
236     * The default implementation uses the <em>Polar Method</em>
237     * due to G.E.P. Box, M.E. Muller and G. Marsaglia, as described in
238     * D. Knuth, <u>The Art of Computer Programming</u>, 3.4.1C.</p>
239     * <p>
240     * The algorithm generates a pair of independent random values.  One of
241     * these is cached for reuse, so the full algorithm is not executed on each
242     * activation.  Implementations that do not override this method should
243     * make sure to call {@link #clear} to clear the cached value in the
244     * implementation of {@link #setSeed(long)}.</p>
245     *
246     * @return  the next pseudorandom, Gaussian ("normally") distributed
247     * {@code double} value with mean {@code 0.0} and
248     * standard deviation {@code 1.0} from this random number
249     *  generator's sequence
250     */
251    public double nextGaussian() {
252        if (!Double.isNaN(cachedNormalDeviate)) {
253            double dev = cachedNormalDeviate;
254            cachedNormalDeviate = Double.NaN;
255            return dev;
256        }
257        double v1 = 0;
258        double v2 = 0;
259        double s = 1;
260        while (s >=1 ) {
261            v1 = 2 * nextDouble() - 1;
262            v2 = 2 * nextDouble() - 1;
263            s = v1 * v1 + v2 * v2;
264        }
265        if (s != 0) {
266            s = FastMath.sqrt(-2 * FastMath.log(s) / s);
267        }
268        cachedNormalDeviate = v2 * s;
269        return v1 * s;
270    }
271}