--- a/src/java.base/share/classes/java/util/random/L64X1024Random.java Fri Jul 26 15:20:31 2019 -0300
+++ b/src/java.base/share/classes/java/util/random/L64X1024Random.java Fri Jul 26 15:37:05 2019 -0300
@@ -27,12 +27,14 @@
import java.math.BigInteger;
import java.util.concurrent.atomic.AtomicLong;
+import java.util.random.RandomGenerator.SplittableGenerator;
+import java.util.random.RandomSupport.AbstractSplittableGenerator;
/**
* A generator of uniform pseudorandom values applicable for use in
* (among other contexts) isolated parallel computations that may
* generate subtasks. Class {@link L64X1024Random} implements
- * interfaces {@link RandomNumberGenerator} and {@link SplittableRNG},
+ * interfaces {@link RandomGenerator} and {@link SplittableGenerator},
* 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 {@link L64X1024Random} objects,
@@ -132,7 +134,7 @@
*
* @since 14
*/
-public final class L64X1024Random extends AbstractSplittableRNG {
+public final class L64X1024Random extends AbstractSplittableGenerator {
/*
* Implementation Overview.
@@ -172,7 +174,7 @@
/**
* The seed generator for default constructors.
*/
- private static final AtomicLong defaultGen = new AtomicLong(RNGSupport.initialSeed());
+ private static final AtomicLong defaultGen = new AtomicLong(RandomSupport.initialSeed());
/*
* The period of this generator, which is (2**1024 - 1) * 2**64.
@@ -261,7 +263,7 @@
// 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) {
for (int j = 0; j < N; j++) {
- this.x[j] = RNGSupport.mixStafford13(s += RNGSupport.GOLDEN_RATIO_64);
+ this.x[j] = RandomSupport.mixStafford13(s += RandomSupport.GOLDEN_RATIO_64);
}
}
}
@@ -284,24 +286,24 @@
// 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),
+ this(RandomSupport.mixMurmur64(seed ^= RandomSupport.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));
+ RandomSupport.mixStafford13(seed),
+ RandomSupport.mixStafford13(seed += RandomSupport.GOLDEN_RATIO_64),
+ RandomSupport.mixStafford13(seed += RandomSupport.GOLDEN_RATIO_64),
+ RandomSupport.mixStafford13(seed += RandomSupport.GOLDEN_RATIO_64),
+ RandomSupport.mixStafford13(seed += RandomSupport.GOLDEN_RATIO_64),
+ RandomSupport.mixStafford13(seed += RandomSupport.GOLDEN_RATIO_64),
+ RandomSupport.mixStafford13(seed += RandomSupport.GOLDEN_RATIO_64),
+ RandomSupport.mixStafford13(seed += RandomSupport.GOLDEN_RATIO_64),
+ RandomSupport.mixStafford13(seed += RandomSupport.GOLDEN_RATIO_64),
+ RandomSupport.mixStafford13(seed += RandomSupport.GOLDEN_RATIO_64),
+ RandomSupport.mixStafford13(seed += RandomSupport.GOLDEN_RATIO_64),
+ RandomSupport.mixStafford13(seed += RandomSupport.GOLDEN_RATIO_64),
+ RandomSupport.mixStafford13(seed += RandomSupport.GOLDEN_RATIO_64),
+ RandomSupport.mixStafford13(seed += RandomSupport.GOLDEN_RATIO_64),
+ RandomSupport.mixStafford13(seed += RandomSupport.GOLDEN_RATIO_64),
+ RandomSupport.mixStafford13(seed + RandomSupport.GOLDEN_RATIO_64));
}
/**
@@ -312,7 +314,7 @@
*/
public L64X1024Random() {
// Using GOLDEN_RATIO_64 here gives us a good Weyl sequence of values.
- this(defaultGen.getAndAdd(RNGSupport.GOLDEN_RATIO_64));
+ this(defaultGen.getAndAdd(RandomSupport.GOLDEN_RATIO_64));
}
/**
@@ -324,7 +326,7 @@
*/
public L64X1024Random(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[] data = RandomSupport.convertSeedBytesToLongs(seed, 18, 16);
long a = data[0], s = data[1];
// Force a to be odd.
this.a = a | 1;
@@ -348,12 +350,12 @@
* and the same expected statistical properties apply to the
* entire set of generators constructed by such recursive splitting.
*
- * @param source a {@link SplittableRNG} instance to be used instead
+ * @param source a {@link SplittableGenerator} 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 {@link L64X1024Random}
*/
- public L64X1024Random split(SplittableRNG source) {
+ public L64X1024Random split(SplittableGenerator source) {
// Literally pick a new instance "at random".
return new L64X1024Random(source.nextLong(), source.nextLong(),
source.nextLong(), source.nextLong(),