--- a/src/java.base/share/classes/java/util/random/L64X1024MixRandom.java Thu Jun 27 18:02:51 2019 -0300
+++ b/src/java.base/share/classes/java/util/random/L64X1024MixRandom.java Thu Jun 27 18:30:27 2019 -0300
@@ -22,7 +22,8 @@
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
-package java.util;
+
+package java.util.random;
import java.math.BigInteger;
import java.util.concurrent.atomic.AtomicLong;
@@ -30,14 +31,14 @@
/**
* A generator of uniform pseudorandom values applicable for use in
* (among other contexts) isolated parallel computations that may
- * generate subtasks. Class {@code L64X1024MixRandom} implements
- * interfaces {@link java.util.Rng} and {@link java.util.SplittableRng},
+ * generate subtasks. Class {@link L64X1024MixRandom} implements
+ * interfaces {@link RandomNumberGenerator} and {@link SplittableRNG},
* 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 split-off {@code L64X1024MixRandom} objects,
+ * as well as creating new split-off {@link L64X1024MixRandom} objects,
* with similar usages as for class {@link java.util.SplittableRandom}.
- *
- * <p>Series of generated values pass the TestU01 BigCrush and PractRand test suites
+ * <p>
+ * Series of generated values pass the TestU01 BigCrush and PractRand test suites
* that measure independence and uniformity properties of random number generators.
* (Most recently validated with
* <a href="http://simul.iro.umontreal.ca/testu01/tu01.html">version 1.2.3 of TestU01</a>
@@ -47,47 +48,47 @@
* These tests validate only the methods for certain
* types and ranges, but similar properties are expected to hold, at
* least approximately, for others as well.
- *
- * <p>{@code L64X1024MixRandom} is a specific member of the LXM family of algorithms
+ * <p>
+ * {@link L64X1024MixRandom} is a specific member of the LXM family of algorithms
* for pseudorandom number generators. Every LXM generator consists of two
* subgenerators; one is an LCG (Linear Congruential Generator) and the other is
* an Xorshift generator. Each output of an LXM generator is the sum of one
* output from each subgenerator, possibly processed by a final mixing function
- * (and {@code L64X1024MixRandom} does use a mixing function).
- *
- * <p>The LCG subgenerator for {@code L64X1024MixRandom} has an update step of the
+ * (and {@link L64X1024MixRandom} does use a mixing function).
+ * <p>
+ * The LCG subgenerator for {@link L64X1024MixRandom} has an update step of the
* form {@code s = m * s + a}, where {@code s}, {@code m}, and {@code a} are all
* of type {@code long}; {@code s} is the mutable state, the multiplier {@code m}
- * is fixed (the same for all instances of {@code L64X1024MixRandom}}) and the addend
+ * is fixed (the same for all instances of {@link L64X1024MixRandom}}) and the addend
* {@code a} is a parameter (a final field of the instance). The parameter
* {@code a} is required to be odd (this allows the LCG to have the maximal
* period, namely 2<sup>64</sup>); therefore there are 2<sup>63</sup> distinct choices
* of parameter.
- *
- * <p>The Xorshift subgenerator for {@code L64X1024MixRandom} is the {@code xoroshiro1024}
+ * <p>
+ * The Xorshift subgenerator for {@link L64X1024MixRandom} is the {@code xoroshiro1024}
* algorithm (parameters 25, 27, and 36), without any final scrambler such as "+" or "**".
* Its state consists of an array {@code x} of sixteen {@code long} values,
* which can take on any values provided that they are not all zero.
* The period of this subgenerator is 2<sup>1024</sup>-1.
- *
- * <p> The mixing function for {@code L64X256MixRandom} is the 64-bit MurmurHash3 finalizer.
- *
- * <p> Because the periods 2<sup>64</sup> and 2<sup>1024</sup>-1 of the two subgenerators
- * are relatively prime, the <em>period</em> of any single {@code L64X1024MixRandom} object
+ * <p>
+ * The mixing function for {@link L64X256MixRandom} is the 64-bit MurmurHash3 finalizer.
+ * <p>
+ * Because the periods 2<sup>64</sup> and 2<sup>1024</sup>-1 of the two subgenerators
+ * are relatively prime, the <em>period</em> of any single {@link L64X1024MixRandom} object
* (the length of the series of generated 64-bit values before it repeats) is the product
* of the periods of the subgenerators, that is, 2<sup>64</sup>(2<sup>1024</sup>-1),
* which is just slightly smaller than 2<sup>1088</sup>. Moreover, if two distinct
- * {@code L64X1024MixRandom} objects have different {@code a} parameters, then their
+ * {@link L64X1024MixRandom} objects have different {@code a} parameters, then their
* cycles of produced values will be different.
- *
- * <p>The 64-bit values produced by the {@code nextLong()} method are exactly equidistributed.
- * For any specific instance of {@code L64X1024MixRandom}, over the course of its cycle each
+ * <p>
+ * The 64-bit values produced by the {@code nextLong()} method are exactly equidistributed.
+ * For any specific instance of {@link L64X1024MixRandom}, over the course of its cycle each
* of the 2<sup>64</sup> possible {@code long} values will be produced 2<sup>1024</sup>-1 times.
* The values produced by the {@code nextInt()}, {@code nextFloat()}, and {@code nextDouble()}
* methods are likewise exactly equidistributed.
- *
- * <p>In fact, the 64-bit values produced by the {@code nextLong()} method are 16-equidistributed.
- * To be precise: for any specific instance of {@code L64X1024MixRandom}, consider
+ * <p>
+ * In fact, the 64-bit values produced by the {@code nextLong()} method are 16-equidistributed.
+ * To be precise: for any specific instance of {@link L64X1024MixRandom}, consider
* the (overlapping) length-16 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>64</sup>(2<sup>1024</sup>-1) such subsequences, and each subsequence,
@@ -98,43 +99,42 @@
* of the probability of getting one of the less common subsequence values and the
* probability of getting one of the more common subsequence values is 1-2<sup>-64</sup>.
* (Note that the set of 2<sup>64</sup> less-common subsequence values will differ from
- * one instance of {@code L64X1024MixRandom} to another, as a function of the additive
+ * one instance of {@link L64X1024MixRandom} to another, as a function of the additive
* parameter of the LCG.) The values produced by the {@code nextInt()}, {@code nextFloat()},
* and {@code nextDouble()} methods are likewise 16-equidistributed.
- *
- * <p>Method {@link #split} constructs and returns a new {@code L64X1024MixRandom}
+ * <p>
+ * Method {@link #split} constructs and returns a new {@link L64X1024MixRandom}
* instance that shares no mutable state with the current instance. However, with
* very high probability, the values collectively generated by the two objects
* have the same statistical properties as if the same quantity of values were
- * generated by a single thread using a single {@code L64X1024MixRandom} object.
- * This is because, with high probability, distinct {@code L64X1024MixRandom} objects
+ * generated by a single thread using a single {@link L64X1024MixRandom} object.
+ * This is because, with high probability, distinct {@link L64X1024MixRandom} objects
* have distinct {@code a} parameters and therefore use distinct members of the
* algorithmic family; and even if their {@code a} parameters are the same, with
* very high probability they will traverse different parts of their common state
* cycle.
- *
- * <p>As with {@link java.util.SplittableRandom}, instances of
- * {@code L64X1024MixRandom} are <em>not</em> thread-safe.
+ * <p>
+ * As with {@link java.util.SplittableRandom}, instances of
+ * {@link L64X1024MixRandom} are <em>not</em> thread-safe.
* They are designed to be split, not shared, across threads. For
* example, a {@link java.util.concurrent.ForkJoinTask} fork/join-style
* computation using random numbers might include a construction
* of the form {@code new Subtask(someL64X1024MixRandom.split()).fork()}.
- *
- * <p>This class provides additional methods for generating random
+ * <p>
+ * This class provides additional methods for generating random
* streams, that employ the above techniques when used in
* {@code stream.parallel()} mode.
- *
- * <p>Instances of {@code L64X1024MixRandom} are not cryptographically
+ * <p>
+ * Instances of {@link L64X1024MixRandom} 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}.
*
- * @author Guy Steele
- * @since 1.9
+ * @since 14
*/
-public final class L64X1024MixRandom extends AbstractSplittableRng {
+public final class L64X1024MixRandom extends AbstractSplittableRNG {
/*
* Implementation Overview.
@@ -145,7 +145,7 @@
*
* With extremely high probability, no two generators so chosen
* will have the same `a` parameter, and testing has indicated
- * that the values generated by two instances of {@code L64X1024MixRandom}
+ * that the values generated by two instances of {@link L64X1024MixRandom}
* will be (approximately) independent if have different values for `a`.
*
* The default (no-argument) constructor, in essence, uses
@@ -174,13 +174,13 @@
/**
* The seed generator for default constructors.
*/
- private static final AtomicLong defaultGen = new AtomicLong(RngSupport.initialSeed());
+ private static final AtomicLong defaultGen = new AtomicLong(RNGSupport.initialSeed());
/*
* The period of this generator, which is (2**1024 - 1) * 2**64.
*/
- private static final BigInteger thePeriod =
- BigInteger.ONE.shiftLeft(N*64).subtract(BigInteger.ONE).shiftLeft(64);
+ private static final BigInteger PERIOD =
+ BigInteger.ONE.shiftLeft(N*64).subtract(BigInteger.ONE).shiftLeft(64);
/*
* Multiplier used in the LCG portion of the algorithm, taken from
@@ -190,8 +190,8 @@
* Table 4 (first multiplier for size 2<sup>64</sup>).
*/
- private static final long m = 2862933555777941757L;
-
+ private static final long M = 2862933555777941757L;
+
/* ---------------- instance fields ---------------- */
/**
@@ -236,16 +236,16 @@
* @param x15 sixteenth word of the initial state for the xorshift generator
*/
public L64X1024MixRandom(long a, long s,
- long x0, long x1, long x2, long x3,
- long x4, long x5, long x6, long x7,
- long x8, long x9, long x10, long x11,
- long x12, long x13, long x14, long x15) {
- // Force a to be odd.
+ long x0, long x1, long x2, long x3,
+ long x4, long x5, long x6, long x7,
+ long x8, long x9, long x10, long x11,
+ long x12, long x13, long x14, long x15) {
+ // Force a to be odd.
this.a = a | 1;
this.s = s;
- this.x = new long[N];
- this.x[0] = x0;
- this.x[1] = x1;
+ this.x = new long[N];
+ this.x[0] = x0;
+ this.x[1] = x1;
this.x[2] = x2;
this.x[3] = x3;
this.x[4] = x4;
@@ -260,113 +260,113 @@
this.x[13] = x13;
this.x[14] = x14;
this.x[15] = x15;
- // If x0, x1, ..., x15 are all zero (very unlikely), we must choose nonzero values.
+ // If x0, x1, ..., x15 are all zero (very unlikely), we must choose nonzero values.
if ((x0 | x1 | x2 | x3 | x4 | x5 | x6 | x7 | x8 | x9 | x10 | x11 | x12 | x13 | x14 | x15) == 0) {
- // At least fifteen of the sixteen values generated here will be nonzero.
- for (int j = 0; j < N; j++) {
- this.x[j] = RngSupport.mixStafford13(s += RngSupport.GOLDEN_RATIO_64);
- }
- }
+ // At least fifteen of the sixteen values generated here will be nonzero.
+ for (int j = 0; j < N; j++) {
+ this.x[j] = RNGSupport.mixStafford13(s += RNGSupport.GOLDEN_RATIO_64);
+ }
+ }
}
/**
- * Creates a new instance of {@code L64X1024MixRandom} using the
+ * Creates a new instance of {@link L64X1024MixRandom} using the
* specified {@code long} value as the initial seed. Instances of
- * {@code L64X1024MixRandom} created with the same seed in the same
+ * {@link L64X1024MixRandom} created with the same seed in the same
* program execution generate identical sequences of values.
*
* @param seed the initial seed
*/
public L64X1024MixRandom(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 seed is hashed by mixMurmur64 to produce the `a` parameter.
- // The seed is hashed by mixStafford13 to produce the initial `x[0]`,
- // which will then be used to produce the first generated value.
- // The other x values are filled in as if by a SplitMix PRNG with
- // GOLDEN_RATIO_64 as the gamma value and Stafford13 as the mixer.
- this(RngSupport.mixMurmur64(seed ^= RngSupport.SILVER_RATIO_64),
- 1,
- RngSupport.mixStafford13(seed),
- RngSupport.mixStafford13(seed += RngSupport.GOLDEN_RATIO_64),
- RngSupport.mixStafford13(seed += RngSupport.GOLDEN_RATIO_64),
- RngSupport.mixStafford13(seed += RngSupport.GOLDEN_RATIO_64),
- RngSupport.mixStafford13(seed += RngSupport.GOLDEN_RATIO_64),
- RngSupport.mixStafford13(seed += RngSupport.GOLDEN_RATIO_64),
- RngSupport.mixStafford13(seed += RngSupport.GOLDEN_RATIO_64),
- RngSupport.mixStafford13(seed += RngSupport.GOLDEN_RATIO_64),
- RngSupport.mixStafford13(seed += RngSupport.GOLDEN_RATIO_64),
- RngSupport.mixStafford13(seed += RngSupport.GOLDEN_RATIO_64),
- RngSupport.mixStafford13(seed += RngSupport.GOLDEN_RATIO_64),
- RngSupport.mixStafford13(seed += RngSupport.GOLDEN_RATIO_64),
- RngSupport.mixStafford13(seed += RngSupport.GOLDEN_RATIO_64),
- RngSupport.mixStafford13(seed += RngSupport.GOLDEN_RATIO_64),
- RngSupport.mixStafford13(seed += RngSupport.GOLDEN_RATIO_64),
- RngSupport.mixStafford13(seed + RngSupport.GOLDEN_RATIO_64));
+ // 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 seed is hashed by mixMurmur64 to produce the `a` parameter.
+ // The seed is hashed by mixStafford13 to produce the initial `x[0]`,
+ // which will then be used to produce the first generated value.
+ // The other x values are filled in as if by a SplitMix PRNG with
+ // GOLDEN_RATIO_64 as the gamma value and Stafford13 as the mixer.
+ this(RNGSupport.mixMurmur64(seed ^= RNGSupport.SILVER_RATIO_64),
+ 1,
+ RNGSupport.mixStafford13(seed),
+ RNGSupport.mixStafford13(seed += RNGSupport.GOLDEN_RATIO_64),
+ RNGSupport.mixStafford13(seed += RNGSupport.GOLDEN_RATIO_64),
+ RNGSupport.mixStafford13(seed += RNGSupport.GOLDEN_RATIO_64),
+ RNGSupport.mixStafford13(seed += RNGSupport.GOLDEN_RATIO_64),
+ RNGSupport.mixStafford13(seed += RNGSupport.GOLDEN_RATIO_64),
+ RNGSupport.mixStafford13(seed += RNGSupport.GOLDEN_RATIO_64),
+ RNGSupport.mixStafford13(seed += RNGSupport.GOLDEN_RATIO_64),
+ RNGSupport.mixStafford13(seed += RNGSupport.GOLDEN_RATIO_64),
+ RNGSupport.mixStafford13(seed += RNGSupport.GOLDEN_RATIO_64),
+ RNGSupport.mixStafford13(seed += RNGSupport.GOLDEN_RATIO_64),
+ RNGSupport.mixStafford13(seed += RNGSupport.GOLDEN_RATIO_64),
+ RNGSupport.mixStafford13(seed += RNGSupport.GOLDEN_RATIO_64),
+ RNGSupport.mixStafford13(seed += RNGSupport.GOLDEN_RATIO_64),
+ RNGSupport.mixStafford13(seed += RNGSupport.GOLDEN_RATIO_64),
+ RNGSupport.mixStafford13(seed + RNGSupport.GOLDEN_RATIO_64));
}
/**
- * Creates a new instance of {@code L64X1024MixRandom} that is likely to
+ * Creates a new instance of {@link L64X1024MixRandom} 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 L64X1024MixRandom() {
- // Using GOLDEN_RATIO_64 here gives us a good Weyl sequence of values.
- this(defaultGen.getAndAdd(RngSupport.GOLDEN_RATIO_64));
+ // Using GOLDEN_RATIO_64 here gives us a good Weyl sequence of values.
+ this(defaultGen.getAndAdd(RNGSupport.GOLDEN_RATIO_64));
}
/**
- * Creates a new instance of {@code L64X1024MixRandom} using the specified array of
- * initial seed bytes. Instances of {@code L64X1024MixRandom} created with the same
+ * Creates a new instance of {@link L64X1024MixRandom} using the specified array of
+ * initial seed bytes. Instances of {@link L64X1024MixRandom} created with the same
* seed array in the same program execution generate identical sequences of values.
*
* @param seed the initial seed
*/
public L64X1024MixRandom(byte[] seed) {
- // Convert the seed to 18 long values, of which the last 16 are not all zero.
- long[] data = RngSupport.convertSeedBytesToLongs(seed, 18, 16);
- long a = data[0], s = data[1];
- // Force a to be odd.
+ // Convert the seed to 18 long values, of which the last 16 are not all zero.
+ long[] data = RNGSupport.convertSeedBytesToLongs(seed, 18, 16);
+ long a = data[0], s = data[1];
+ // Force a to be odd.
this.a = a | 1;
this.s = s;
- this.x = new long[N];
- for (int j = 0; j < N; j++) {
- this.x[j] = data[2+j];
- }
+ this.x = new long[N];
+ for (int j = 0; j < N; j++) {
+ this.x[j] = data[2+j];
+ }
}
/* ---------------- public methods ---------------- */
/**
- * Constructs and returns a new instance of {@code L64X1024MixRandom}
+ * Constructs and returns a new instance of {@link L64X1024MixRandom}
* that shares no mutable state with this instance.
* However, with very high probability, the set of values collectively
* generated by the two objects has the same statistical properties as if
* same the quantity of values were generated by a single thread using
- * a single {@code L64X1024MixRandom} object. Either or both of the two
+ * a single {@link L64X1024MixRandom} object. Either or both of the two
* objects may be further split using the {@code split} method,
* and the same expected statistical properties apply to the
* entire set of generators constructed by such recursive splitting.
*
- * @param source a {@code SplittableRng} instance to be used instead
+ * @param source a {@link SplittableRNG} instance to be used instead
* of this one as a source of pseudorandom bits used to
* initialize the state of the new ones.
- * @return a new instance of {@code L64X1024MixRandom}
+ * @return a new instance of {@link L64X1024MixRandom}
*/
- public L64X1024MixRandom split(SplittableRng source) {
- // Literally pick a new instance "at random".
- return new L64X1024MixRandom(source.nextLong(), source.nextLong(),
- source.nextLong(), source.nextLong(),
- source.nextLong(), source.nextLong(),
- source.nextLong(), source.nextLong(),
- source.nextLong(), source.nextLong(),
- source.nextLong(), source.nextLong(),
- source.nextLong(), source.nextLong(),
- source.nextLong(), source.nextLong(),
- source.nextLong(), source.nextLong());
+ public L64X1024MixRandom split(SplittableRNG source) {
+ // Literally pick a new instance "at random".
+ return new L64X1024MixRandom(source.nextLong(), source.nextLong(),
+ source.nextLong(), source.nextLong(),
+ source.nextLong(), source.nextLong(),
+ source.nextLong(), source.nextLong(),
+ source.nextLong(), source.nextLong(),
+ source.nextLong(), source.nextLong(),
+ source.nextLong(), source.nextLong(),
+ source.nextLong(), source.nextLong(),
+ source.nextLong(), source.nextLong());
}
/**
@@ -374,23 +374,24 @@
*
* @return a pseudorandom {@code long} value
*/
-
public long nextLong() {
- // First part of xoroshiro1024: fetch array data
- final int q = p;
- final long s0 = x[p = (p + 1) & (N - 1)];
- long s15 = x[q];
+ // First part of xoroshiro1024: fetch array data
+ final int q = p;
+ final long s0 = x[p = (p + 1) & (N - 1)];
+ long s15 = x[q];
- final long z = s + s0;
- s = m * s + a; // LCG
+ final long z = s + s0;
+ s = M * s + a; // LCG
- // Second part of xoroshiro1024: update array data
- s15 ^= s0;
- x[q] = Long.rotateLeft(s0, 25) ^ s15 ^ (s15 << 27);
- x[p] = Long.rotateLeft(s15, 36);
-
- return RngSupport.mixLea64(z); // mixing function
+ // Second part of xoroshiro1024: update array data
+ s15 ^= s0;
+ x[q] = Long.rotateLeft(s0, 25) ^ s15 ^ (s15 << 27);
+ x[p] = Long.rotateLeft(s15, 36);
+
+ return RNGSupport.mixLea64(z); // mixing function
}
- public BigInteger period() { return thePeriod; }
+ public BigInteger period() {
+ return PERIOD;
+ }
}