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/*
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* Copyright (c) 2013, 2019, Oracle and/or its affiliates. All rights reserved.
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* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
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*
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* This code is free software; you can redistribute it and/or modify it
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* under the terms of the GNU General Public License version 2 only, as
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* published by the Free Software Foundation. Oracle designates this
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* particular file as subject to the "Classpath" exception as provided
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* by Oracle in the LICENSE file that accompanied this code.
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*
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* This code is distributed in the hope that it will be useful, but WITHOUT
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* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
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* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
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* version 2 for more details (a copy is included in the LICENSE file that
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* accompanied this code).
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*
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* You should have received a copy of the GNU General Public License version
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* 2 along with this work; if not, write to the Free Software Foundation,
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* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
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*
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* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
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* or visit www.oracle.com if you need additional information or have any
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* questions.
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*/
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package java.util;
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import java.math.BigInteger;
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import java.util.concurrent.atomic.AtomicLong;
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/**
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* A generator of uniform pseudorandom values applicable for use in
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* (among other contexts) isolated parallel computations that may
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* generate subtasks. Class {@code Xoshiro256StarStar} implements
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* interfaces {@link java.util.Rng} and {@link java.util.LeapableRng},
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* and therefore supports methods for producing pseudorandomly chosen
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* numbers of type {@code int}, {@code long}, {@code float}, and {@code double}
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* as well as creating new {@code Xoshiro256StarStar} objects
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* by "jumping" or "leaping".
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*
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* <p>Series of generated values pass the TestU01 BigCrush and PractRand test suites
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* that measure independence and uniformity properties of random number generators.
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* (Most recently validated with
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* <a href="http://simul.iro.umontreal.ca/testu01/tu01.html">version 1.2.3 of TestU01</a>
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* and <a href="http://pracrand.sourceforge.net">version 0.90 of PractRand</a>.
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* Note that TestU01 BigCrush was used to test not only values produced by the {@code nextLong()}
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* method but also the result of bit-reversing each value produced by {@code nextLong()}.)
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* These tests validate only the methods for certain
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* types and ranges, but similar properties are expected to hold, at
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* least approximately, for others as well.
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*
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* <p>The class {@code Xoshiro256StarStar} uses the {@code xoshiro256} algorithm,
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* version 1.0 (parameters 17, 45), with the "**" scrambler (a mixing function).
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* Its state consists of four {@code long} fields {@code x0}, {@code x1}, {@code x2},
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* and {@code x3}, which can take on any values provided that they are not all zero.
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* The period of this generator is 2<sup>256</sup>-1.
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*
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* <p>The 64-bit values produced by the {@code nextLong()} method are equidistributed.
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* To be precise, over the course of the cycle of length 2<sup>256</sup>-1,
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* each nonzero {@code long} value is generated 2<sup>192</sup> times,
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* but the value 0 is generated only 2<sup>192</sup>-1 times.
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* The values produced by the {@code nextInt()}, {@code nextFloat()}, and {@code nextDouble()}
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* methods are likewise equidistributed.
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*
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* <p>In fact, the 64-bit values produced by the {@code nextLong()} method are 4-equidistributed.
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* To be precise: consider the (overlapping) length-4 subsequences of the cycle of 64-bit
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* values produced by {@code nextLong()} (assuming no other methods are called that would
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* affect the state). There are 2<sup>256</sup>-1 such subsequences, and each subsequence,
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* which consists of 4 64-bit values, can have one of 2<sup>256</sup> values. Of those
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* 2<sup>256</sup> subsequence values, each one is generated exactly once over the course
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* of the entire cycle, except that the subsequence (0, 0, 0, 0) never appears.
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* The values produced by the {@code nextInt()}, {@code nextFloat()}, and {@code nextDouble()}
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* methods are likewise 4-equidistributed, but note that that the subsequence (0, 0, 0, 0)
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* can also appear (but occurring somewhat less frequently than all other subsequences),
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* because the values produced by those methods have fewer than 64 randomly chosen bits.
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*
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* <p>Instances {@code Xoshiro256StarStar} are <em>not</em> thread-safe.
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* They are designed to be used so that each thread as its own instance.
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* The methods {@link #jump} and {@link #leap} and {@link #jumps} and {@link #leaps}
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* can be used to construct new instances of {@code Xoshiro256StarStar} that traverse
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* other parts of the state cycle.
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*
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* <p>Instances of {@code Xoshiro256StarStar} are not cryptographically
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* secure. Consider instead using {@link java.security.SecureRandom}
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* in security-sensitive applications. Additionally,
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* default-constructed instances do not use a cryptographically random
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* seed unless the {@linkplain System#getProperty system property}
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* {@code java.util.secureRandomSeed} is set to {@code true}.
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*
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* @author Guy Steele
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* @since 1.9
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*/
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public final class Xoshiro256StarStar implements LeapableRng {
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/*
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* Implementation Overview.
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*
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* This is an implementation of the xoroshiro128** algorithm written
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* in 2018 by David Blackman and Sebastiano Vigna (vigna@acm.org).
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* See http://xoshiro.di.unimi.it and these two papers:
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*
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* Sebastiano Vigna. 2016. An Experimental Exploration of Marsaglia's
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* xorshift Generators, Scrambled. ACM Transactions on Mathematical
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* Software 42, 4, Article 30 (June 2016), 23 pages.
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* https://doi.org/10.1145/2845077
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*
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* David Blackman and Sebastiano Vigna. 2018. Scrambled Linear
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* Pseudorandom Number Generators. Computing Research Repository (CoRR).
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* http://arxiv.org/abs/1805.01407
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*
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* The jump operation moves the current generator forward by 2*128
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* steps; this has the same effect as calling nextLong() 2**128
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* times, but is much faster. Similarly, the leap operation moves
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* the current generator forward by 2*192 steps; this has the same
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* effect as calling nextLong() 2**192 times, but is much faster.
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* The copy method may be used to make a copy of the current
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* generator. Thus one may repeatedly and cumulatively copy and
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* jump to produce a sequence of generators whose states are well
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* spaced apart along the overall state cycle (indeed, the jumps()
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* and leaps() methods each produce a stream of such generators).
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* The generators can then be parceled out to other threads.
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*
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* File organization: First static fields, then instance
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* fields, then constructors, then instance methods.
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*/
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/* ---------------- static fields ---------------- */
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/**
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* The seed generator for default constructors.
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*/
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private static final AtomicLong defaultGen = new AtomicLong(RngSupport.initialSeed());
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/*
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* The period of this generator, which is 2**256 - 1.
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*/
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private static final BigInteger thePeriod =
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BigInteger.ONE.shiftLeft(256).subtract(BigInteger.ONE);
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/* ---------------- instance fields ---------------- */
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/**
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* The per-instance state.
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* At least one of the four fields x0, x1, x2, and x3 must be nonzero.
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*/
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private long x0, x1, x2, x3;
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/* ---------------- constructors ---------------- */
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/**
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* Basic constructor that initializes all fields from parameters.
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* It then adjusts the field values if necessary to ensure that
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* all constraints on the values of fields are met.
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*
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* @param x0 first word of the initial state
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* @param x1 second word of the initial state
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* @param x2 third word of the initial state
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* @param x3 fourth word of the initial state
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*/
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public Xoshiro256StarStar(long x0, long x1, long x2, long x3) {
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this.x0 = x0;
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this.x1 = x1;
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this.x2 = x2;
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this.x3 = x3;
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// If x0, x1, x2, and x3 are all zero, we must choose nonzero values.
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if ((x0 | x1 | x2 | x3) == 0) {
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// At least three of the four values generated here will be nonzero.
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this.x0 = RngSupport.mixStafford13(x0 += RngSupport.GOLDEN_RATIO_64);
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this.x1 = (x0 += RngSupport.GOLDEN_RATIO_64);
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this.x2 = (x0 += RngSupport.GOLDEN_RATIO_64);
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this.x3 = (x0 += RngSupport.GOLDEN_RATIO_64);
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}
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}
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/**
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* Creates a new instance of {@code Xoshiro256StarStar} using the
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* specified {@code long} value as the initial seed. Instances of
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* {@code Xoshiro256StarStar} created with the same seed in the same
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* program generate identical sequences of values.
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*
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* @param seed the initial seed
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*/
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public Xoshiro256StarStar(long seed) {
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// Using a value with irregularly spaced 1-bits to xor the seed
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// argument tends to improve "pedestrian" seeds such as 0 or
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// other small integers. We may as well use SILVER_RATIO_64.
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//
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// The x values are then filled in as if by a SplitMix PRNG with
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// GOLDEN_RATIO_64 as the gamma value and Stafford13 as the mixer.
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this(RngSupport.mixStafford13(seed ^= RngSupport.SILVER_RATIO_64),
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RngSupport.mixStafford13(seed += RngSupport.GOLDEN_RATIO_64),
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RngSupport.mixStafford13(seed += RngSupport.GOLDEN_RATIO_64),
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RngSupport.mixStafford13(seed + RngSupport.GOLDEN_RATIO_64));
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}
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/**
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* Creates a new instance of {@code Xoshiro256StarStar} that is likely to
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* generate sequences of values that are statistically independent
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* of those of any other instances in the current program execution,
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* but may, and typically does, vary across program invocations.
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*/
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public Xoshiro256StarStar() {
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// Using GOLDEN_RATIO_64 here gives us a good Weyl sequence of values.
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this(defaultGen.getAndAdd(RngSupport.GOLDEN_RATIO_64));
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}
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/**
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* Creates a new instance of {@code Xoshiro256StarStar} using the specified array of
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* initial seed bytes. Instances of {@code Xoshiro256StarStar} created with the same
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* seed array in the same program execution generate identical sequences of values.
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*
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* @param seed the initial seed
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*/
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public Xoshiro256StarStar(byte[] seed) {
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// Convert the seed to 4 long values, which are not all zero.
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long[] data = RngSupport.convertSeedBytesToLongs(seed, 4, 4);
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long x0 = data[0], x1 = data[1], x2 = data[2], x3 = data[3];
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this.x0 = x0;
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this.x1 = x1;
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this.x2 = x2;
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this.x3 = x3;
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}
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/* ---------------- public methods ---------------- */
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public Xoshiro256StarStar copy() { return new Xoshiro256StarStar(x0, x1, x2, x3); }
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/**
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* Returns a pseudorandom {@code long} value.
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*
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* @return a pseudorandom {@code long} value
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*/
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public long nextLong() {
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final long z = x0;
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long q0 = x0, q1 = x1, q2 = x2, q3 = x3;
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{ long t = q1 << 17; q2 ^= q0; q3 ^= q1; q1 ^= q2; q0 ^= q3; q2 ^= t; q3 = Long.rotateLeft(q3, 45); } // xoshiro256 1.0
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x0 = q0; x1 = q1; x2 = q2; x3 = q3;
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return Long.rotateLeft(z * 5, 7) * 9; // "starstar" mixing function
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}
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public BigInteger period() { return thePeriod; }
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public double defaultJumpDistance() { return 0x1.0p64; }
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public double defaultLeapDistance() { return 0x1.0p96; }
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private static final long[] JUMP_TABLE = {
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0x180ec6d33cfd0abaL, 0xd5a61266f0c9392cL, 0xa9582618e03fc9aaL, 0x39abdc4529b1661cL };
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private static final long[] LEAP_TABLE = {
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0x76e15d3efefdcbbfL, 0xc5004e441c522fb3L, 0x77710069854ee241L, 0x39109bb02acbe635L };
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/* This is the jump function for the generator. It is equivalent
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to 2**128 calls to next(); it can be used to generate 2**128
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non-overlapping subsequences for parallel computations. */
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public void jump() { jumpAlgorithm(JUMP_TABLE); }
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/* This is the long-jump function for the generator. It is equivalent to
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2**192 calls to next(); it can be used to generate 2**64 starting points,
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from each of which jump() will generate 2**64 non-overlapping
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subsequences for parallel distributed computations. */
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public void leap() { jumpAlgorithm(LEAP_TABLE); }
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private void jumpAlgorithm(long[] table) {
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long s0 = 0, s1 = 0, s2 = 0, s3 = 0;
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for (int i = 0; i < table.length; i++) {
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for (int b = 0; b < 64; b++) {
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if ((table[i] & (1L << b)) != 0) {
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s0 ^= x0;
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s1 ^= x1;
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s2 ^= x2;
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s3 ^= x3;
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}
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nextLong();
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}
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x0 = s0;
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x1 = s1;
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x2 = s2;
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x3 = s3;
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}
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}
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}
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