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The DSI utilities are a mishmash of classes accumulated during the last twenty years in projects developed at the DSI (Dipartimento di Scienze dell'Informazione, i.e., Information Sciences Department), now DI (Dipartimento di Informatica, i.e., Informatics Department), of the Universita` degli Studi di Milano.
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/*
 * DSI utilities
 *
 * Copyright (C) 2013-2020 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 .
 *
 */

package it.unimi.dsi.util;

import java.security.SecureRandom;
import java.util.Random;
import java.util.SplittableRandom;

import org.apache.commons.math3.random.RandomGenerator;

import it.unimi.dsi.Util;
import it.unimi.dsi.logging.ProgressLogger;

/** A fast, all-purpose, rock-solid, small-state {@linkplain Random pseudorandom number generator}. It has excellent speed,
 * but its state space (128 bits) that is large enough for
 * mild parallelism only; it passes all tests we are aware of.
 * In Java, it is slightly slower than a {@link XoRoShiRo128PlusPlusRandom}.
 * More information can be found at our PRNG page.
 *
 * If you need to generate just floating-point numbers, {@link XoRoShiRo128PlusRandom} is slightly faster. If you can use more space,
 * you might try {@link XoShiRo256StarStarRandom}.
 *
 * 
By using the supplied {@link #jump()} method it is possible to generate non-overlapping long sequences
 * for parallel computations; {@link #longJump()} makes it possible to create several
 * starting points, each providing several non-overlapping sequences, for distributed computations. This class provides also a {@link #split()} method to support recursive parallel computations, in the spirit of
 * {@link SplittableRandom}.
 *
 * 
Warning: before release 2.6.3, the {@link #split()} method
 * would not alter the state of the caller, and it would return instances initialized in the same
 * way if called multiple times. This was a major mistake in the implementation and it has been fixed,
 * but as a consequence the output of the caller after a call to {@link #split()} is
 * now different, and the result of {@link #split()} is initialized in a different way.
 *
 * 
Note that this is not a {@linkplain SecureRandom secure generator}.
 *
 * @version 1.0
 * @see it.unimi.dsi.util
 * @see RandomGenerator
 * @see XoRoShiRo128StarStarRandomGenerator
 */

public class XoRoShiRo128StarStarRandom extends Random {
	private static final long serialVersionUID = 1L;
	/** The internal state of the algorithm. */
	private long s0, s1;

	protected XoRoShiRo128StarStarRandom(final long s0, final long s1) {
		this.s0 = s0;
		this.s1 = s1;
	}

	/** Creates a new generator seeded using {@link Util#randomSeed()}. */
	public XoRoShiRo128StarStarRandom() {
		this(Util.randomSeed());
	}

	/** Creates a new generator using a given seed.
	 *
	 * @param seed a seed for the generator.
	 */
	public XoRoShiRo128StarStarRandom(final long seed) {
		setSeed(seed);
	}

	/** Returns a copy of this generator. The sequences produced by this generator and by the returned generator will be identical.
	 *
	 * 
This method is particularly useful in conjunction with the {@link #jump()} (or {@link #longJump()}) method: by calling repeatedly
	 * {@link #jump() jump().copy()} over a generator it is possible to create several generators producing non-overlapping sequences.
	 *
	 * @return a copy of this generator.
	 */
	public XoRoShiRo128StarStarRandom copy() {
		return new XoRoShiRo128StarStarRandom(s0, s1);
	}


	@Override
	public long nextLong() {
		final long s0 = this.s0;

		long result = s0;
		result = Long.rotateLeft(result + (result << 2), 7);
		result += result << 3;

		long s1 = this.s1;

		s1 ^= s0;
		this.s0 = Long.rotateLeft(s0, 24) ^ s1 ^ s1 << 16;
		this.s1 = Long.rotateLeft(s1, 37);
		return result;
	}

	@Override
	public int nextInt() {
		return (int)nextLong();
	}

	@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;
		// 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. Before
	 * version 2.4.1, this was actually the standard implementation of
	 * {@link #nextDouble()}, so you can use this method if you need to
	 * reproduce exactly results obtained using previous versions.
	 *
	 * 
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.
	 *
	 * @since 2.4.1
	 */
	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;
		}
	}

	protected XoRoShiRo128StarStarRandom jump(final long[] jump) {
		long s0 = 0;
		long s1 = 0;
		for (final long element : jump)
			for(int b = 0; b < 64; b++) {
				if ((element & 1L << b) != 0) {
					s0 ^= this.s0;
					s1 ^= this.s1;
				}
				nextLong();
			}

		this.s0 = s0;
		this.s1 = s1;
		return this;
	}


	private static final long[] JUMP = { 0xdf900294d8f554a5L, 0x170865df4b3201fcL };

	/** The jump function for this generator. It is equivalent to 2⁶⁴
	 * calls to {@link #nextLong()}; it can be used to generate 2⁶⁴
	 * non-overlapping subsequences for parallel computations.
	 *
	 * @return this generator.
	 * @see #copy()
	 */

	public XoRoShiRo128StarStarRandom jump() {
		return jump(JUMP);
	}

	private static final long[] LONG_JUMP = { 0xd2a98b26625eee7bL, 0xdddf9b1090aa7ac1L };

	/** The long-jump function for this generator. It is equivalent to 2⁹⁶
	 * calls to {@link #nextLong()}; it can be used to generate 2³² starting points,
	 * from each of which {@link #jump()} will generate 2³² non-overlapping
	 * subsequences for parallel distributed computations.
	 *
	 * @return this generator.
	 * @see #copy()
	 */

	public XoRoShiRo128StarStarRandom longJump() {
		return jump(LONG_JUMP);
	}



	/**
	 * 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.
	 *
	 * 
Warning: before release 2.6.3, this method
	 * would not alter the state of the caller, and it would return instances initialized in the same
	 * way if called multiple times. This was a major mistake in the implementation and it has been fixed,
	 * but as a consequence the output of this instance after a call to this method is
	 * now different, and the returned instance is initialized in a different way.
	 *
	 * @return the new instance.
	 */
	public XoRoShiRo128StarStarRandom split() {
		nextLong();
		final XoRoShiRo128StarStarRandom split = copy();

		long h0 = s0;
		long h1 = s1;
		long h2 = s0 + 0x55a650a4c1dac3e9L; // Random constants
		long h3 = s1 + 0xb39ae98dfa439b73L;

		// A round of SpookyHash ShortMix
		h2 = Long.rotateLeft(h2, 50);
		h2 += h3;
		h0 ^= h2;
		h3 = Long.rotateLeft(h3, 52);
		h3 += h0;
		h1 ^= h3;
		h0 = Long.rotateLeft(h0, 30);
		h0 += h1;
		h2 ^= h0;
		h1 = Long.rotateLeft(h1, 41);
		h1 += h2;
		h3 ^= h1;
		h2 = Long.rotateLeft(h2, 54);
		h2 += h3;
		h0 ^= h2;
		h3 = Long.rotateLeft(h3, 48);
		h3 += h0;
		h1 ^= h3;
		h0 = Long.rotateLeft(h0, 38);
		h0 += h1;
		h2 ^= h0;
		h1 = Long.rotateLeft(h1, 37);
		h1 += h2;
		h3 ^= h1;
		h2 = Long.rotateLeft(h2, 62);
		h2 += h3;
		h0 ^= h2;
		h3 = Long.rotateLeft(h3, 34);
		h3 += h0;
		h1 ^= h3;
		h0 = Long.rotateLeft(h0, 5);
		h0 += h1;
		h2 ^= h0;
		h1 = Long.rotateLeft(h1, 36);
		h1 += h2;
		//h3 ^= h1;

		split.s0 = h0;
		split.s1 = h1;

		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 this generator.
	 */
	@Override
	public void setSeed(final long seed) {
		final SplitMix64RandomGenerator r = new SplitMix64RandomGenerator(seed);
		s0 = r.nextLong();
		s1 = 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 2 longs; at least one must be nonzero.
	 */
	public void setState(final long[] state) {
		if (state.length != 2) throw new IllegalArgumentException("The argument array contains " + state.length + " longs instead of " + 2);
		s0 = state[0];
		s1 = state[1];
	}

	public static void main(final String[] arg) {
		final long n = Long.parseLong(arg[0]);
		long x = 0;
		final ProgressLogger pl = new ProgressLogger();
		final XoRoShiRo128StarStarRandom r = new XoRoShiRo128StarStarRandom(0);
		for(int k = 10; k-- != 0;) {
			pl.start("Measuring...");
			for (long i = n; i-- != 0;)
				x ^= r.nextLong();
			pl.done(n);
			if (x == 0) System.out.println(x);
		}
	}
}