    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 java.io.Serializable;
    020
    021
    022    /** This abstract class implements the WELL class of pseudo-random number generator
    023     * from Fran&ccedil;ois Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
    024
    025     * <p>This generator is described in a paper by Fran&ccedil;ois Panneton,
    026     * Pierre L'Ecuyer and Makoto Matsumoto <a
    027     * href="http://www.iro.umontreal.ca/~lecuyer/myftp/papers/wellrng.pdf">Improved
    028     * Long-Period Generators Based on Linear Recurrences Modulo 2</a> ACM
    029     * Transactions on Mathematical Software, 32, 1 (2006). The errata for the paper
    030     * are in <a href="http://www.iro.umontreal.ca/~lecuyer/myftp/papers/wellrng-errata.txt">wellrng-errata.txt</a>.</p>
    031
    032     * @see <a href="http://www.iro.umontreal.ca/~panneton/WELLRNG.html">WELL Random number generator</a>
    033     * @version $Revision: 1003892 $ $Date: 2010-10-02 23:28:56 +0200 (sam. 02 oct. 2010) $
    034     * @since 2.2
    035
    036     */
    037    public abstract class AbstractWell extends BitsStreamGenerator implements Serializable {
    038
    039        /** Serializable version identifier. */
    040        private static final long serialVersionUID = -817701723016583596L;
    041
    042        /** Current index in the bytes pool. */
    043        protected int index;
    044
    045        /** Bytes pool. */
    046        protected final int[] v;
    047
    048        /** Index indirection table giving for each index its predecessor taking table size into account. */
    049        protected final int[] iRm1;
    050
    051        /** Index indirection table giving for each index its second predecessor taking table size into account. */
    052        protected final int[] iRm2;
    053
    054        /** Index indirection table giving for each index the value index + m1 taking table size into account. */
    055        protected final int[] i1;
    056
    057        /** Index indirection table giving for each index the value index + m2 taking table size into account. */
    058        protected final int[] i2;
    059
    060        /** Index indirection table giving for each index the value index + m3 taking table size into account. */
    061        protected final int[] i3;
    062
    063        /** Creates a new random number generator.
    064         * <p>The instance is initialized using the current time as the
    065         * seed.</p>
    066         * @param k number of bits in the pool (not necessarily a multiple of 32)
    067         * @param m1 first parameter of the algorithm
    068         * @param m2 second parameter of the algorithm
    069         * @param m3 third parameter of the algorithm
    070         */
    071        protected AbstractWell(final int k, final int m1, final int m2, final int m3) {
    072            this(k, m1, m2, m3, System.currentTimeMillis());
    073        }
    074
    075        /** Creates a new random number generator using a single int seed.
    076         * @param k number of bits in the pool (not necessarily a multiple of 32)
    077         * @param m1 first parameter of the algorithm
    078         * @param m2 second parameter of the algorithm
    079         * @param m3 third parameter of the algorithm
    080         * @param seed the initial seed (32 bits integer)
    081         */
    082        protected AbstractWell(final int k, final int m1, final int m2, final int m3, final int seed) {
    083            this(k, m1, m2, m3, new int[] { seed });
    084        }
    085
    086        /** Creates a new random number generator using an int array seed.
    087         * @param k number of bits in the pool (not necessarily a multiple of 32)
    088         * @param m1 first parameter of the algorithm
    089         * @param m2 second parameter of the algorithm
    090         * @param m3 third parameter of the algorithm
    091         * @param seed the initial seed (32 bits integers array), if null
    092         * the seed of the generator will be related to the current time
    093         */
    094        protected AbstractWell(final int k, final int m1, final int m2, final int m3, final int[] seed) {
    095
    096            // the bits pool contains k bits, k = r w - p where r is the number
    097            // of w bits blocks, w is the block size (always 32 in the original paper)
    098            // and p is the number of unused bits in the last block
    099            final int w = 32;
    100            final int r = (k + w - 1) / w;
    101            this.v      = new int[r];
    102            this.index  = 0;
    103
    104            // precompute indirection index tables. These tables are used for optimizing access
    105            // they allow saving computations like "(j + r - 2) % r" with costly modulo operations
    106            iRm1 = new int[r];
    107            iRm2 = new int[r];
    108            i1   = new int[r];
    109            i2   = new int[r];
    110            i3   = new int[r];
    111            for (int j = 0; j < r; ++j) {
    112                iRm1[j] = (j + r - 1) % r;
    113                iRm2[j] = (j + r - 2) % r;
    114                i1[j]   = (j + m1)    % r;
    115                i2[j]   = (j + m2)    % r;
    116                i3[j]   = (j + m3)    % r;
    117            }
    118
    119            // initialize the pool content
    120            setSeed(seed);
    121
    122        }
    123
    124        /** Creates a new random number generator using a single long seed.
    125         * @param k number of bits in the pool (not necessarily a multiple of 32)
    126         * @param m1 first parameter of the algorithm
    127         * @param m2 second parameter of the algorithm
    128         * @param m3 third parameter of the algorithm
    129         * @param seed the initial seed (64 bits integer)
    130         */
    131        protected AbstractWell(final int k, final int m1, final int m2, final int m3, final long seed) {
    132            this(k, m1, m2, m3, new int[] { (int) (seed >>> 32), (int) (seed & 0xffffffffl) });
    133        }
    134
    135        /** Reinitialize the generator as if just built with the given int seed.
    136         * <p>The state of the generator is exactly the same as a new
    137         * generator built with the same seed.</p>
    138         * @param seed the initial seed (32 bits integer)
    139         */
    140        @Override
    141        public void setSeed(final int seed) {
    142            setSeed(new int[] { seed });
    143        }
    144
    145        /** Reinitialize the generator as if just built with the given int array seed.
    146         * <p>The state of the generator is exactly the same as a new
    147         * generator built with the same seed.</p>
    148         * @param seed the initial seed (32 bits integers array), if null
    149         * the seed of the generator will be related to the current time
    150         */
    151        @Override
    152        public void setSeed(final int[] seed) {
    153
    154            if (seed == null) {
    155                setSeed(System.currentTimeMillis());
    156                return;
    157            }
    158
    159            System.arraycopy(seed, 0, v, 0, Math.min(seed.length, v.length));
    160
    161            if (seed.length < v.length) {
    162                for (int i = seed.length; i < v.length; ++i) {
    163                    final long l = v[i - seed.length];
    164                    v[i] = (int) ((1812433253l * (l ^ (l >> 30)) + i) & 0xffffffffL);
    165                }
    166            }
    167
    168            index = 0;
    169
    170        }
    171
    172        /** Reinitialize the generator as if just built with the given long seed.
    173         * <p>The state of the generator is exactly the same as a new
    174         * generator built with the same seed.</p>
    175         * @param seed the initial seed (64 bits integer)
    176         */
    177        @Override
    178        public void setSeed(final long seed) {
    179            setSeed(new int[] { (int) (seed >>> 32), (int) (seed & 0xffffffffl) });
    180        }
    181
    182        /** {@inheritDoc} */
    183        @Override
    184        protected abstract int next(final int bits);
    185
    186    }