src.it.unimi.dsi.util.XorShift1024StarPhiRandomGenerator Maven / Gradle / Ivy
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package it.unimi.dsi.util;
/*
* DSI utilities
*
* Copyright (C) 2013-2019 Sebastiano Vigna
*
* This library is free software; you can redistribute it and/or modify it
* under the terms of the GNU Lesser General Public License as published by the Free
* Software Foundation; either version 3 of the License, or (at your option)
* any later version.
*
* This library is distributed in the hope that it will be useful, but
* WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
* or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License
* for more details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with this program; if not, see .
*
*/
import java.io.Serializable;
import java.security.SecureRandom;
import java.util.Random;
import java.util.SplittableRandom;
import org.apache.commons.math3.random.AbstractRandomGenerator;
import org.apache.commons.math3.random.RandomGenerator;
import it.unimi.dsi.Util;
import it.unimi.dsi.fastutil.HashCommon;
/** A fast, high-quality {@linkplain RandomGenerator pseudorandom number generator} that
* combines a long-period instance of George Marsaglia's Xorshift generators (described in “Xorshift RNGs”, Journal of
* Statistical Software, 8:1−6, 2003) with a multiplication.
* More information can be found at our PRNG page.
*
* By using the supplied {@link #jump()} method it is possible to generate non-overlapping long sequences
* for parallel computations. This class provides also a {@link #split()} method to support recursive parallel computations, in the spirit of
* {@link SplittableRandom}.
*
*
Note that this is not a {@linkplain SecureRandom secure generator}.
*
* @see it.unimi.dsi.util
* @see Random
* @see XorShift1024StarPhiRandom
*/
public class XorShift1024StarPhiRandomGenerator extends AbstractRandomGenerator implements Serializable {
private static final long serialVersionUID = 0L;
/** The internal state of the algorithm. */
private final long[] s = new long[16];
private int p;
/** Creates a new generator seeded using {@link Util#randomSeed()}. */
public XorShift1024StarPhiRandomGenerator() {
this(Util.randomSeed());
}
/** Creates a new generator using a given seed.
*
* @param seed a seed for the generator.
*/
public XorShift1024StarPhiRandomGenerator(final long seed) {
setSeed(seed);
}
@Override
public long nextLong() {
final long s0 = s[p];
long s1 = s[p = (p + 1) & 15];
s1 ^= s1 << 31;
return (s[p] = s1 ^ s0 ^ (s1 >>> 11) ^ (s0 >>> 30)) * 0x9e3779b97f4a7c13L;
}
@Override
public int nextInt() {
return (int)(nextLong() >>> 32);
}
@Override
public int nextInt(final int n) {
return (int)nextLong(n);
}
/** Returns a pseudorandom uniformly distributed {@code long} value
* between 0 (inclusive) and the specified value (exclusive), drawn from
* this random number generator's sequence. The algorithm used to generate
* the value guarantees that the result is uniform, provided that the
* sequence of 64-bit values produced by this generator is.
*
* @param n the positive bound on the random number to be returned.
* @return the next pseudorandom {@code long} value between {@code 0} (inclusive) and {@code n} (exclusive).
*/
public long nextLong(final long n) {
if (n <= 0) throw new IllegalArgumentException("illegal bound " + n + " (must be positive)");
long t = nextLong();
final long nMinus1 = n - 1;
// Shortcut for powers of two--high bits
if ((n & nMinus1) == 0) return t >>> Long.numberOfLeadingZeros(nMinus1) & nMinus1;
// Rejection-based algorithm to get uniform integers in the general case
for (long u = t >>> 1; u + nMinus1 - (t = u % n) < 0; u = nextLong() >>> 1);
return t;
}
@Override
public double nextDouble() {
return (nextLong() >>> 11) * 0x1.0p-53;
}
/**
* Returns the next pseudorandom, uniformly distributed
* {@code double} value between {@code 0.0} and
* {@code 1.0} from this random number generator's sequence,
* using a fast multiplication-free method which, however,
* can provide only 52 significant bits.
*
*
This method is faster than {@link #nextDouble()}, but it
* can return only dyadic rationals of the form k / 2−52,
* instead of the standard k / 2−53.
*
*
The only difference between the output of this method and that of
* {@link #nextDouble()} is an additional least significant bit set in half of the
* returned values. For most applications, this difference is negligible.
*
* @return the next pseudorandom, uniformly distributed {@code double}
* value between {@code 0.0} and {@code 1.0} from this
* random number generator's sequence, using 52 significant bits only.
*/
public double nextDoubleFast() {
return Double.longBitsToDouble(0x3FFL << 52 | nextLong() >>> 12) - 1.0;
}
@Override
public float nextFloat() {
return (nextLong() >>> 40) * 0x1.0p-24f;
}
@Override
public boolean nextBoolean() {
return nextLong() < 0;
}
@Override
public void nextBytes(final byte[] bytes) {
int i = bytes.length, n = 0;
while(i != 0) {
n = Math.min(i, 8);
for (long bits = nextLong(); n-- != 0; bits >>= 8) bytes[--i] = (byte)bits;
}
}
private static final long JUMP[] = { 0x84242f96eca9c41dL,
0xa3c65b8776f96855L, 0x5b34a39f070b5837L, 0x4489affce4f31a1eL,
0x2ffeeb0a48316f40L, 0xdc2d9891fe68c022L, 0x3659132bb12fea70L,
0xaac17d8efa43cab8L, 0xc4cb815590989b13L, 0x5ee975283d71c93bL,
0x691548c86c1bd540L, 0x7910c41d10a1e6a5L, 0x0b5fc64563b3e2a8L,
0x047f7684e9fc949dL, 0xb99181f2d8f685caL, 0x284600e3f30e38c3L
};
/** The jump function for this generator. It is equivalent to 2512
* calls to {@link #nextLong()}; it can be used to generate 2512
* non-overlapping subsequences for parallel computations. */
public void jump() {
final long[] t = new long[16];
for (int i = 0; i < JUMP.length; i++)
for (int b = 0; b < 64; b++) {
if ((JUMP[i] & 1L << b) != 0)
for (int j = 0; j < 16; j++)
t[j] ^= s[(j + p) & 15];
nextLong();
}
for (int j = 0; j < 16; j++)
s[(j + p) & 15] = t[j];
}
/**
* Returns a new instance that shares no mutable state
* with this instance. The sequence generated by the new instance
* depends deterministically from the state of this instance,
* but the probability that the sequence generated by this
* instance and by the new instance overlap is negligible.
*
* @return the new instance.
*/
public XorShift1024StarPhiRandomGenerator split() {
final XorShift1024StarPhiRandomGenerator split = new XorShift1024StarPhiRandomGenerator();
for(int i = s.length; i-- != 0;) split.s[i] = HashCommon.murmurHash3(s[i]);
split.p = p;
return split;
}
/** Sets the seed of this generator.
*
*
The argument will be used to seed a {@link SplitMix64RandomGenerator}, whose output
* will in turn be used to seed this generator. This approach makes “warmup” unnecessary,
* and makes the probability of starting from a state
* with a large fraction of bits set to zero astronomically small.
*
* @param seed a seed for the generator.
*/
@Override
public void setSeed(final long seed) {
p = 0;
final SplitMix64RandomGenerator r = new SplitMix64RandomGenerator(seed);
for(int i = s.length; i-- != 0;) s[i] = r.nextLong();
}
/** Sets the state of this generator.
*
*
The internal state of the generator will be reset, and the state array filled with the provided array.
*
* @param state an array of 16 longs; at least one must be nonzero.
* @param p the internal index.
*/
public void setState(final long[] state, final int p) {
if (state.length != s.length) throw new IllegalArgumentException("The argument array contains " + state.length + " longs instead of " + s.length);
System.arraycopy(state, 0, s, 0, s.length);
this.p = p;
}
}