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package java.util.random;

import java.math.BigInteger;

import java.util.concurrent.atomic.AtomicLong;

import java.util.random.RandomGenerator.LeapableGenerator;

/**

 * A generator of uniform pseudorandom values applicable for use in

 * (among other contexts) isolated parallel computations that may

 * generate subtasks.  Class {@link Xoroshiro128StarStar} implements

 * interfaces {@link RandomGenerator} and {@link LeapableGenerator},

 * and therefore supports methods for producing pseudorandomly chosen

 * numbers of type {@code int}, {@code long}, {@code float}, and {@code double}

 * as well as creating new {@link Xoroshiro128StarStar} objects

 * by "jumping" or "leaping".

 * <p>

 * Series of generated values pass the TestU01 BigCrush and PractRand test suites

 * that measure independence and uniformity properties of random number generators.

 * <p>

 * The class {@link Xoroshiro128StarStar} uses the {@code xoroshiro128} algorithm,

 * version 1.0 (parameters 24, 16, 37), with the "**" scrambler (a mixing function).

 * Its state consists of two {@code long} fields {@code x0} and {@code x1},

 * which can take on any values provided that they are not both zero.

 * The period of this generator is 2<sup>128</sup>-1.

 * <p>

 * The 64-bit values produced by the {@code nextLong()} method are equidistributed.

 * To be precise, over the course of the cycle of length 2<sup>128</sup>-1,

 * each nonzero {@code long} value is generated 2<sup>64</sup> times,

 * but the value 0 is generated only 2<sup>64</sup>-1 times.

 * The values produced by the {@code nextInt()}, {@code nextFloat()}, and {@code nextDouble()}

 * methods are likewise equidistributed.

 * <p>

 * In fact, the 64-bit values produced by the {@code nextLong()} method are 2-equidistributed.

 * To be precise: consider the (overlapping) length-2 subsequences of the cycle of 64-bit

 * values produced by {@code nextLong()} (assuming no other methods are called that would

 * affect the state).  There are 2<sup>128</sup>-1 such subsequences, and each subsequence,

 * which consists of 2 64-bit values, can have one of 2<sup>128</sup> values.  Of those

 * 2<sup>128</sup> subsequence values, each one is generated exactly once over the course

 * of the entire cycle, except that the subsequence (0, 0) never appears.

 * The values produced by the {@code nextInt()}, {@code nextFloat()}, and {@code nextDouble()}

 * methods are likewise 2-equidistributed, but note that that the subsequence (0, 0)

 * can also appear (but occurring somewhat less frequently than all other subsequences),

 * because the values produced by those methods have fewer than 64 randomly chosen bits.

 * <p>

 * Instances {@link Xoroshiro128StarStar} are <em>not</em> thread-safe.

 * They are designed to be used so that each thread as its own instance.

 * The methods {@link #jump} and {@link #leap} and {@link #jumps} and {@link #leaps}

 * can be used to construct new instances of {@link Xoroshiro128StarStar} that traverse

 * other parts of the state cycle.

 * <p>

 * Instances of {@link Xoroshiro128StarStar} are not cryptographically

 * secure.  Consider instead using {@link java.security.SecureRandom}

 * in security-sensitive applications. Additionally,

 * default-constructed instances do not use a cryptographically random

 * seed unless the {@linkplain System#getProperty system property}

 * {@code java.util.secureRandomSeed} is set to {@code true}.

 *

 * @since 14

 */

public final class Xoroshiro128StarStar implements LeapableGenerator {

    /*

     * Implementation Overview.

     *

     * This is an implementation of the xoroshiro128** algorithm written

     * in 2016 by David Blackman and Sebastiano Vigna (vigna@acm.org),

     * and updated with improved parameters in 2018.

     * See http://xoshiro.di.unimi.it and these two papers:

     *

     *    Sebastiano Vigna. 2016. An Experimental Exploration of Marsaglia's

     *    xorshift Generators, Scrambled. ACM Transactions on Mathematical

     *    Software 42, 4, Article 30 (June 2016), 23 pages.

     *    https://doi.org/10.1145/2845077

     *

     *    David Blackman and Sebastiano Vigna.  2018.  Scrambled Linear

     *    Pseudorandom Number Generators.  Computing Research Repository (CoRR).

     *    http://arxiv.org/abs/1805.01407

     *

     * The jump operation moves the current generator forward by 2*64

     * steps; this has the same effect as calling nextLong() 2**64

     * times, but is much faster.  Similarly, the leap operation moves

     * the current generator forward by 2*96 steps; this has the same

     * effect as calling nextLong() 2**96 times, but is much faster.

     * The copy method may be used to make a copy of the current

     * generator.  Thus one may repeatedly and cumulatively copy and

     * jump to produce a sequence of generators whose states are well

     * spaced apart along the overall state cycle (indeed, the jumps()

     * and leaps() methods each produce a stream of such generators).

     * The generators can then be parceled out to other threads.

     *

     * File organization: First the non-public methods that constitute the

     * main algorithm, then the public methods.  Note that many methods are

     * defined by classes {@link AbstractJumpableGenerator} and {@link AbstractGenerator}.

     */

    /* ---------------- static fields ---------------- */

    /**

     * The seed generator for default constructors.

     */

    private static final AtomicLong DEFAULT_GEN = new AtomicLong(RandomSupport.initialSeed());

    /*

     * The period of this generator, which is 2**128 - 1.

     */

    private static final BigInteger PERIOD =

        BigInteger.ONE.shiftLeft(128).subtract(BigInteger.ONE);

    /* ---------------- instance fields ---------------- */

    /**

     * The per-instance state.

     * At least one of the two fields x0 and x1 must be nonzero.

     */

    private long x0, x1;

    /* ---------------- constructors ---------------- */

    /**

     * Basic constructor that initializes all fields from parameters.

     * It then adjusts the field values if necessary to ensure that

     * all constraints on the values of fields are met.

      *

     * @param x0 first word of the initial state

     * @param x1 second word of the initial state

    */

    public Xoroshiro128StarStar(long x0, long x1) {

        this.x0 = x0;

        this.x1 = x1;

        // If x0 and x1 are both zero, we must choose nonzero values.

        if ((x0 | x1) == 0) {

            this.x0 = RandomSupport.GOLDEN_RATIO_64;

            this.x1 = RandomSupport.SILVER_RATIO_64;

        }

    }

    /**

     * Creates a new instance of {@link Xoroshiro128StarStar} using the

     * specified {@code long} value as the initial seed. Instances of

     * {@link Xoroshiro128StarStar} created with the same seed in the same

     * program generate identical sequences of values.

     *

     * @param seed the initial seed

     */

    public Xoroshiro128StarStar(long seed) {

        // Using a value with irregularly spaced 1-bits to xor the seed

        // argument tends to improve "pedestrian" seeds such as 0 or

        // other small integers.  We may as well use SILVER_RATIO_64.

        //

        // The x values are then filled in as if by a SplitMix PRNG with

        // GOLDEN_RATIO_64 as the gamma value and Stafford13 as the mixer.

        this(RandomSupport.mixStafford13(seed ^= RandomSupport.SILVER_RATIO_64),

             RandomSupport.mixStafford13(seed + RandomSupport.GOLDEN_RATIO_64));

    }

    /**

     * Creates a new instance of {@link Xoroshiro128StarStar} that is likely to

     * generate sequences of values that are statistically independent

     * of those of any other instances in the current program execution,

     * but may, and typically does, vary across program invocations.

     */

    public Xoroshiro128StarStar() {

        // Using GOLDEN_RATIO_64 here gives us a good Weyl sequence of values.

        this(DEFAULT_GEN.getAndAdd(RandomSupport.GOLDEN_RATIO_64));

    }

    /**

     * Creates a new instance of {@link Xoroshiro128StarStar} using the specified array of

     * initial seed bytes. Instances of {@link Xoroshiro128StarStar} created with the same

     * seed array in the same program execution generate identical sequences of values.

     *

     * @param seed the initial seed

     */

    public Xoroshiro128StarStar(byte[] seed) {

        // Convert the seed to 2 long values, which are not both zero.

        long[] data = RandomSupport.convertSeedBytesToLongs(seed, 2, 2);

        long x0 = data[0], x1 = data[1];

        this.x0 = x0;

        this.x1 = x1;

    }

    /* ---------------- public methods ---------------- */

    public Xoroshiro128StarStar copy() { return new Xoroshiro128StarStar(x0, x1); }

    /*

     * To the extent possible under law, the author has dedicated all copyright and related and

     * neighboring rights to this software to the public domain worldwide. This software is

     * distributed without any warranty.

     * <p>

     * See <http://creativecommons.org/publicdomain/zero/1.0/>.

     */

    /*

     * This is the successor to xorshift128+. It is the fastest full-period generator passing

     * BigCrush without systematic failures, but due to the relatively short period it is acceptable

     * only for applications with a mild amount of parallelism; otherwise, use a xorshift1024*

     * generator.

     * <p>

     * Beside passing BigCrush, this generator passes the PractRand test suite up to (and included)

     * 16TB, with the exception of binary rank tests, which fail due to the lowest bit being an

     * LFSR; all other bits pass all tests. We suggest to use a sign test to extract a random

     * Boolean value.

     * <p>

     * Note that the generator uses a simulated rotate operation, which most C compilers will turn

     * into a single instruction. In Java, you can use Long.rotateLeft(). In languages that do not

     * make low-level rotation instructions accessible xorshift128+ could be faster.

     * <p>

     * The state must be seeded so that it is not everywhere zero. If you have a 64-bit seed, we

     * suggest to seed a splitmix64 generator and use its output to fill s.

     */

    /**

     * Returns a pseudorandom {@code long} value.

     *

     * @return a pseudorandom {@code long} value

     */

    public long nextLong() {

        final long s0 = x0;

        long s1 = x1;

	// Compute the result based on current state information

	// (this allows the computation to be overlapped with state update).

        final long result = Long.rotateLeft(s0 * 5, 7) * 9;  // "starstar" mixing function

        s1 ^= s0;

        x0 = Long.rotateLeft(s0, 24) ^ s1 ^ (s1 << 16); // a, b

        x1 = Long.rotateLeft(s1, 37); // c

        return result;

    }

    public BigInteger period() {

        return PERIOD;

    }

    public double defaultJumpDistance() {

        return 0x1.0p64;

    }

    public double defaultLeapDistance() {

        return 0x1.0p96;

    }

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

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

    /**

     * This is the jump function for the generator. It is equivalent to 2**64 calls to nextLong();

     * it can be used to generate 2**64 non-overlapping subsequences for parallel computations.

     */

    public void jump() {

        jumpAlgorithm(JUMP_TABLE);

    }

    /**

     * This is the long-jump function for the generator. It is equivalent to 2**96 calls to next();

     * it can be used to generate 2**32 starting points, from each of which jump() will generate

     * 2**32 non-overlapping subsequences for parallel distributed computations.

     */

    public void leap() {

        jumpAlgorithm(LEAP_TABLE);

    }

    private void jumpAlgorithm(long[] table) {

        long s0 = 0, s1 = 0;

        for (int i = 0; i < table.length; i++) {

            for (int b = 0; b < 64; b++) {

                if ((table[i] & (1L << b)) != 0) {

                    s0 ^= x0;

                    s1 ^= x1;

                }

                nextLong();

            }

            x0 = s0;

            x1 = s1;

        }

    }

}