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Posted to commits@commons.apache.org by ah...@apache.org on 2019/03/06 15:46:57 UTC
[commons-rng] branch master updated (fccc73e -> f5ac625)
This is an automated email from the ASF dual-hosted git repository.
aherbert pushed a change to branch master
in repository https://gitbox.apache.org/repos/asf/commons-rng.git.
from fccc73e InternalUtilsTest: Test for NegativeArraySizeException
new fbeeb08 RNG-73: Add methods used from UniformRandomProvider to the samplers.
new cf51f2c Merge branch 'improvement-RNG-73'
new bfef2b6 Track changes.
new ac929bf RNG-79: Benchmark methods for producing nextDouble and nextFloat
new d03726b RNG-79: Updated testFloatGeneration internal order
new 5a6c2f5 RNG-79: Updated testFloat/DoubleGeneration delta.
new d4950ef RNG-79: NumberFactoryTest floating-point precision uses commons-math3
new 80c94a5 RNG-79: Modify benchmark to use uniform random generator.
new 5262744 Merge branch 'feature-RNG-79'
new f5ac625 Track changes.
The 10 revisions listed above as "new" are entirely new to this
repository and will be described in separate emails. The revisions
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Summary of changes:
commons-rng-core/pom.xml | 7 +
.../commons/rng/core/util/NumberFactoryTest.java | 103 +++++++++----
.../rng/examples/jmh/NextDoublePerformance.java | 162 +++++++++++++++++++++
.../commons/rng/sampling/CollectionSampler.java | 2 +
.../commons/rng/sampling/CombinationSampler.java | 8 +-
.../DiscreteProbabilityCollectionSampler.java | 2 +
.../apache/commons/rng/sampling/ListSampler.java | 10 +-
.../commons/rng/sampling/PermutationSampler.java | 8 +-
.../commons/rng/sampling/SubsetSamplerUtils.java | 6 +-
.../commons/rng/sampling/UnitSphereSampler.java | 7 +
.../AhrensDieterExponentialSampler.java | 2 +
.../AhrensDieterMarsagliaTsangGammaSampler.java | 7 +
.../distribution/BoxMullerGaussianSampler.java | 2 +
.../distribution/BoxMullerLogNormalSampler.java | 2 +
.../BoxMullerNormalizedGaussianSampler.java | 2 +
.../sampling/distribution/ChengBetaSampler.java | 2 +
.../distribution/ContinuousUniformSampler.java | 2 +
.../distribution/DiscreteUniformSampler.java | 4 +
.../sampling/distribution/GeometricSampler.java | 10 +-
.../InverseTransformContinuousSampler.java | 4 +-
.../InverseTransformDiscreteSampler.java | 4 +-
.../InverseTransformParetoSampler.java | 2 +
.../distribution/LargeMeanPoissonSampler.java | 11 +-
.../MarsagliaNormalizedGaussianSampler.java | 2 +
.../rng/sampling/distribution/PoissonSampler.java | 7 +
.../sampling/distribution/PoissonSamplerCache.java | 19 ++-
.../RejectionInversionZipfSampler.java | 2 +
.../distribution/SmallMeanPoissonSampler.java | 8 +-
.../ZigguratNormalizedGaussianSampler.java | 11 +-
src/changes/changes.xml | 6 +
30 files changed, 371 insertions(+), 53 deletions(-)
create mode 100644 commons-rng-examples/examples-jmh/src/main/java/org/apache/commons/rng/examples/jmh/NextDoublePerformance.java
[commons-rng] 04/10: RNG-79: Updated testFloat/DoubleGeneration
delta.
Posted by ah...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
aherbert pushed a commit to branch master
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commit 5a6c2f5f0402fa27efa3b2bcdd2d131a5dc971f6
Author: Alex Herbert <ah...@apache.org>
AuthorDate: Mon Mar 4 22:41:19 2019 +0000
RNG-79: Updated testFloat/DoubleGeneration delta.
The delta is set to be within 1 or 2 ulp of 1.
---
.../commons/rng/core/util/NumberFactoryTest.java | 20 ++++++++++++--------
1 file changed, 12 insertions(+), 8 deletions(-)
diff --git a/commons-rng-core/src/test/java/org/apache/commons/rng/core/util/NumberFactoryTest.java b/commons-rng-core/src/test/java/org/apache/commons/rng/core/util/NumberFactoryTest.java
index 5638768..6fb909e 100644
--- a/commons-rng-core/src/test/java/org/apache/commons/rng/core/util/NumberFactoryTest.java
+++ b/commons-rng-core/src/test/java/org/apache/commons/rng/core/util/NumberFactoryTest.java
@@ -145,10 +145,12 @@ public class NumberFactoryTest {
public void testFloatGeneration() {
final int allBits = 0xffffffff;
- // Not capable of generating 1
- Assert.assertEquals(1, (allBits >>> 9) * 0x1.0p-23f, 1e-6);
- Assert.assertEquals(1, (allBits >>> 8) * 0x1.0p-24f, 1e-6);
- Assert.assertEquals(1, Float.intBitsToFloat(0x7f << 23 | allBits >>> 9) - 1.0f, 1e-6);
+ // Not capable of generating 1. Set the delta with 1 or 2 ULP of 1.
+ final float deltaUlp2 = 1f - Math.nextAfter(Math.nextAfter(1f, -1), -1);
+ final float deltaUlp1 = 1f - Math.nextAfter(1f, -1);
+ Assert.assertEquals(1, (allBits >>> 9) * 0x1.0p-23f, deltaUlp2);
+ Assert.assertEquals(1, (allBits >>> 8) * 0x1.0p-24f, deltaUlp1);
+ Assert.assertEquals(1, Float.intBitsToFloat(0x7f << 23 | allBits >>> 9) - 1.0f, deltaUlp2);
final int noBits = 0;
Assert.assertEquals(0, (noBits >>> 9) * 0x1.0p-23f, 0);
@@ -160,10 +162,12 @@ public class NumberFactoryTest {
public void testDoubleGeneration() {
final long allBits = 0xffffffffffffffffL;
- // Not capable of generating 1
- Assert.assertEquals(1, (allBits >>> 12) * 0x1.0p-52d, 1e-10);
- Assert.assertEquals(1, (allBits >>> 11) * 0x1.0p-53d, 1e-10);
- Assert.assertEquals(1, Double.longBitsToDouble(0x3ffL << 52 | allBits >>> 12) - 1.0, 1e-10);
+ // Not capable of generating 1. Set the delta with 1 or 2 ULP of 1.
+ final double deltaUlp2 = 1 - Math.nextAfter(Math.nextAfter(1, -1), -1);
+ final double deltaUlp1 = 1 - Math.nextAfter(1, -1);
+ Assert.assertEquals(1, (allBits >>> 12) * 0x1.0p-52d, deltaUlp2);
+ Assert.assertEquals(1, (allBits >>> 11) * 0x1.0p-53d, deltaUlp1);
+ Assert.assertEquals(1, Double.longBitsToDouble(0x3ffL << 52 | allBits >>> 12) - 1.0, deltaUlp2);
final long noBits = 0;
Assert.assertEquals(0, (noBits >>> 12) * 0x1.0p-52d, 0);
[commons-rng] 01/10: RNG-73: Add methods used from
UniformRandomProvider to the samplers.
Posted by ah...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
aherbert pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/commons-rng.git
commit fbeeb08208c1f92f7ae395451f86a32f54564fe6
Author: Alex Herbert <ah...@apache.org>
AuthorDate: Thu Feb 28 21:15:19 2019 +0000
RNG-73: Add methods used from UniformRandomProvider to the samplers.
---
.../commons/rng/sampling/CollectionSampler.java | 2 ++
.../commons/rng/sampling/CombinationSampler.java | 8 +++++---
.../DiscreteProbabilityCollectionSampler.java | 2 ++
.../org/apache/commons/rng/sampling/ListSampler.java | 10 +++++++++-
.../commons/rng/sampling/PermutationSampler.java | 8 ++++++--
.../commons/rng/sampling/SubsetSamplerUtils.java | 6 ++++--
.../commons/rng/sampling/UnitSphereSampler.java | 7 +++++++
.../distribution/AhrensDieterExponentialSampler.java | 2 ++
.../AhrensDieterMarsagliaTsangGammaSampler.java | 7 +++++++
.../distribution/BoxMullerGaussianSampler.java | 2 ++
.../distribution/BoxMullerLogNormalSampler.java | 2 ++
.../BoxMullerNormalizedGaussianSampler.java | 2 ++
.../rng/sampling/distribution/ChengBetaSampler.java | 2 ++
.../distribution/ContinuousUniformSampler.java | 2 ++
.../sampling/distribution/DiscreteUniformSampler.java | 4 ++++
.../rng/sampling/distribution/GeometricSampler.java | 10 ++++++----
.../InverseTransformContinuousSampler.java | 4 +++-
.../distribution/InverseTransformDiscreteSampler.java | 4 +++-
.../distribution/InverseTransformParetoSampler.java | 2 ++
.../distribution/LargeMeanPoissonSampler.java | 11 +++++++++--
.../MarsagliaNormalizedGaussianSampler.java | 2 ++
.../rng/sampling/distribution/PoissonSampler.java | 7 +++++++
.../sampling/distribution/PoissonSamplerCache.java | 19 +++++++++++++------
.../distribution/RejectionInversionZipfSampler.java | 2 ++
.../distribution/SmallMeanPoissonSampler.java | 8 +++++---
.../ZigguratNormalizedGaussianSampler.java | 11 +++++++++--
26 files changed, 119 insertions(+), 27 deletions(-)
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/CollectionSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/CollectionSampler.java
index 34c7247..54f9ee9 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/CollectionSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/CollectionSampler.java
@@ -26,6 +26,8 @@ import org.apache.commons.rng.UniformRandomProvider;
/**
* Sampling from a {@link Collection}.
*
+ * <p>Sampling uses {@link UniformRandomProvider#nextInt(int)}.</p>
+ *
* @param <T> Type of items in the collection.
*
* @since 1.0
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/CombinationSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/CombinationSampler.java
index 58d4fe8..eeae0d5 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/CombinationSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/CombinationSampler.java
@@ -26,14 +26,16 @@ import org.apache.commons.rng.UniformRandomProvider;
* <p>A combination is a selection of items from a collection, such that (unlike
* permutations) the order of selection <strong>does not matter</strong>. This
* sampler can be used to generate a combination in an unspecified order and is
- * faster than the corresponding {@link PermutationSampler}.
+ * faster than the corresponding {@link PermutationSampler}.</p>
*
* <p>Note that the sample order is unspecified. For example a sample
* combination of 2 from 4 may return {@code [0,1]} or {@code [1,0]} as the two are
- * equivalent, and the order of a given combination may change in subsequent samples.
+ * equivalent, and the order of a given combination may change in subsequent samples.</p>
*
* <p>The sampler can be used to generate indices to select subsets where the
- * order of the subset is not important.
+ * order of the subset is not important.</p>
+ *
+ * <p>Sampling uses {@link UniformRandomProvider#nextInt(int)}.</p>
*
* @see PermutationSampler
*/
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/DiscreteProbabilityCollectionSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/DiscreteProbabilityCollectionSampler.java
index f85ff14..9bdeaab 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/DiscreteProbabilityCollectionSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/DiscreteProbabilityCollectionSampler.java
@@ -32,6 +32,8 @@ import org.apache.commons.rng.UniformRandomProvider;
* Note that if all unique items are assigned the same probability,
* it is much more efficient to use {@link CollectionSampler}.
*
+ * <p>Sampling uses {@link UniformRandomProvider#nextDouble()}.</p>
+ *
* @param <T> Type of items in the collection.
*
* @since 1.1
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/ListSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/ListSampler.java
index 40e4ddd..db31105 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/ListSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/ListSampler.java
@@ -25,7 +25,7 @@ import org.apache.commons.rng.UniformRandomProvider;
/**
* Sampling from a {@link List}.
*
- * This class also contains utilities for shuffling a {@link List} in-place.
+ * <p>This class also contains utilities for shuffling a {@link List} in-place.</p>
*
* @since 1.0
*/
@@ -45,6 +45,10 @@ public class ListSampler {
* contains identical objects, the sample may include repeats.
* </p>
*
+ * <p>
+ * Sampling uses {@link UniformRandomProvider#nextInt(int)}.
+ * </p>
+ *
* @param <T> Type of the list items.
* @param rng Generator of uniformly distributed random numbers.
* @param collection List to be sampled from.
@@ -89,6 +93,10 @@ public class ListSampler {
* The {@code start} and {@code pos} parameters select which part
* of the array is randomized and which is left untouched.
*
+ * <p>
+ * Sampling uses {@link UniformRandomProvider#nextInt(int)}.
+ * </p>
+ *
* @param <T> Type of the list items.
* @param rng Random number generator.
* @param list List whose entries will be shuffled (in-place).
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/PermutationSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/PermutationSampler.java
index a5a30c2..7cb72cc 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/PermutationSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/PermutationSampler.java
@@ -23,7 +23,9 @@ import org.apache.commons.rng.UniformRandomProvider;
* Class for representing <a href="https://en.wikipedia.org/wiki/Permutation">permutations</a>
* of a sequence of integers.
*
- * <p>This class also contains utilities for shuffling an {@code int[]} array in-place.
+ * <p>Sampling uses {@link UniformRandomProvider#nextInt(int)}.</p>
+ *
+ * <p>This class also contains utilities for shuffling an {@code int[]} array in-place.</p>
*/
public class PermutationSampler {
/** Domain of the permutation. */
@@ -40,7 +42,7 @@ public class PermutationSampler {
* length {@code k} whose entries are selected randomly, without
* repetition, from the integers 0, 1, ..., {@code n}-1 (inclusive).
* The returned array represents a permutation of {@code n} taken
- * {@code k}.
+ * {@code k}.</p>
*
* @param rng Generator of uniformly distributed random numbers.
* @param n Domain of the permutation.
@@ -86,6 +88,8 @@ public class PermutationSampler {
* The {@code start} and {@code towardHead} parameters select which part
* of the array is randomized and which is left untouched.
*
+ * <p>Sampling uses {@link UniformRandomProvider#nextInt(int)}.</p>
+ *
* @param rng Random number generator.
* @param list Array whose entries will be shuffled (in-place).
* @param start Index at which shuffling begins.
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/SubsetSamplerUtils.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/SubsetSamplerUtils.java
index 32d58a1..0ac25f0 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/SubsetSamplerUtils.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/SubsetSamplerUtils.java
@@ -31,7 +31,7 @@ final class SubsetSamplerUtils {
* Checks the subset of length {@code k} from {@code n} is valid.
*
* <p>If {@code n <= 0} or {@code k <= 0} or {@code k > n} then no subset
- * is required and an exception is raised.
+ * is required and an exception is raised.</p>
*
* @param n Size of the set.
* @param k Size of the subset.
@@ -57,7 +57,9 @@ final class SubsetSamplerUtils {
* shuffled section.
*
* <p>The returned combination will have a length of {@code steps} for
- * {@code upper=true}, or {@code domain.length - steps} otherwise.
+ * {@code upper=true}, or {@code domain.length - steps} otherwise.</p>
+ *
+ * <p>Sampling uses {@link UniformRandomProvider#nextInt(int)}.</p>
*
* @param domain The domain.
* @param steps The number of shuffle steps.
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/UnitSphereSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/UnitSphereSampler.java
index 3dbdb03..661702b 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/UnitSphereSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/UnitSphereSampler.java
@@ -25,6 +25,13 @@ import org.apache.commons.rng.sampling.distribution.ZigguratNormalizedGaussianSa
* Generate vectors <a href="http://mathworld.wolfram.com/SpherePointPicking.html">
* isotropically located on the surface of a sphere</a>.
*
+ * <p>Sampling uses:</p>
+ *
+ * <ul>
+ * <li>{@link UniformRandomProvider#nextLong()}
+ * <li>{@link UniformRandomProvider#nextDouble()}
+ * </ul>
+ *
* @since 1.1
*/
public class UnitSphereSampler {
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/AhrensDieterExponentialSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/AhrensDieterExponentialSampler.java
index 56e57b4..3f8a2e7 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/AhrensDieterExponentialSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/AhrensDieterExponentialSampler.java
@@ -21,6 +21,8 @@ import org.apache.commons.rng.UniformRandomProvider;
/**
* Sampling from an <a href="http://mathworld.wolfram.com/ExponentialDistribution.html">exponential distribution</a>.
*
+ * <p>Sampling uses {@link UniformRandomProvider#nextDouble()}.</p>
+ *
* @since 1.0
*/
public class AhrensDieterExponentialSampler
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/AhrensDieterMarsagliaTsangGammaSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/AhrensDieterMarsagliaTsangGammaSampler.java
index 946475b..bb17d54 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/AhrensDieterMarsagliaTsangGammaSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/AhrensDieterMarsagliaTsangGammaSampler.java
@@ -39,6 +39,13 @@ import org.apache.commons.rng.UniformRandomProvider;
* </li>
* </ul>
*
+ * <p>Sampling uses:</p>
+ *
+ * <ul>
+ * <li>{@link UniformRandomProvider#nextDouble()} (both algorithms)
+ * <li>{@link UniformRandomProvider#nextLong()} (only for {@code theta >= 1})
+ * </ul>
+ *
* @since 1.0
*/
public class AhrensDieterMarsagliaTsangGammaSampler
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/BoxMullerGaussianSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/BoxMullerGaussianSampler.java
index c04f09a..b140823 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/BoxMullerGaussianSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/BoxMullerGaussianSampler.java
@@ -22,6 +22,8 @@ import org.apache.commons.rng.UniformRandomProvider;
* <a href="https://en.wikipedia.org/wiki/Box%E2%80%93Muller_transform">
* Box-Muller algorithm</a> for sampling from a Gaussian distribution.
*
+ * <p>Sampling uses {@link UniformRandomProvider#nextDouble()}.</p>
+ *
* @since 1.0
*
* @deprecated Since version 1.1. Please use {@link BoxMullerNormalizedGaussianSampler}
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/BoxMullerLogNormalSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/BoxMullerLogNormalSampler.java
index fba683e..de8fc29 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/BoxMullerLogNormalSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/BoxMullerLogNormalSampler.java
@@ -23,6 +23,8 @@ import org.apache.commons.rng.UniformRandomProvider;
* log-normal distribution</a>.
* Uses {@link BoxMullerNormalizedGaussianSampler} as the underlying sampler.
*
+ * <p>Sampling uses {@link UniformRandomProvider#nextDouble()}.</p>
+ *
* @since 1.0
*
* @deprecated Since version 1.1. Please use {@link LogNormalSampler} instead.
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/BoxMullerNormalizedGaussianSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/BoxMullerNormalizedGaussianSampler.java
index 78a6b74..49824f2 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/BoxMullerNormalizedGaussianSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/BoxMullerNormalizedGaussianSampler.java
@@ -23,6 +23,8 @@ import org.apache.commons.rng.UniformRandomProvider;
* Box-Muller algorithm</a> for sampling from Gaussian distribution with
* mean 0 and standard deviation 1.
*
+ * <p>Sampling uses {@link UniformRandomProvider#nextDouble()}.</p>
+ *
* @since 1.1
*/
public class BoxMullerNormalizedGaussianSampler
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/ChengBetaSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/ChengBetaSampler.java
index 8ed0e3e..fd68958 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/ChengBetaSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/ChengBetaSampler.java
@@ -29,6 +29,8 @@ import org.apache.commons.rng.UniformRandomProvider;
* </pre>
* </blockquote>
*
+ * <p>Sampling uses {@link UniformRandomProvider#nextDouble()}.</p>
+ *
* @since 1.0
*/
public class ChengBetaSampler
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/ContinuousUniformSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/ContinuousUniformSampler.java
index 2c972f8..e7d749e 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/ContinuousUniformSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/ContinuousUniformSampler.java
@@ -21,6 +21,8 @@ import org.apache.commons.rng.UniformRandomProvider;
/**
* Sampling from a uniform distribution.
*
+ * <p>Sampling uses {@link UniformRandomProvider#nextDouble()}.</p>
+ *
* @since 1.0
*/
public class ContinuousUniformSampler
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/DiscreteUniformSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/DiscreteUniformSampler.java
index 00e308b..2b5ea52 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/DiscreteUniformSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/DiscreteUniformSampler.java
@@ -22,6 +22,10 @@ import org.apache.commons.rng.UniformRandomProvider;
/**
* Discrete uniform distribution sampler.
*
+ * <p>Sampling uses {@link UniformRandomProvider#nextInt(int)} when
+ * the range {@code (upper - lower) <} {@link Integer#MAX_VALUE}, otherwise
+ * {@link UniformRandomProvider#nextInt()}.</p>
+ *
* @since 1.0
*/
public class DiscreteUniformSampler
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/GeometricSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/GeometricSampler.java
index 92b8df2..f4683ac 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/GeometricSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/GeometricSampler.java
@@ -23,19 +23,21 @@ import org.apache.commons.rng.UniformRandomProvider;
* distribution</a>.
*
* <p>This distribution samples the number of failures before the first success taking values in the
- * set {@code [0, 1, 2, ...]}.
+ * set {@code [0, 1, 2, ...]}.</p>
*
* <p>The sample is computed using a related exponential distribution. If \( X \) is an
* exponentially distributed random variable with parameter \( \lambda \), then
* \( Y = \left \lfloor X \right \rfloor \) is a geometrically distributed random variable with
- * parameter \( p = 1 − e^\lambda \), with \( p \) the probability of success.
+ * parameter \( p = 1 − e^\lambda \), with \( p \) the probability of success.</p>
*
* <p>This sampler outperforms using the {@link InverseTransformDiscreteSampler} with an appropriate
- * Geometric inverse cumulative probability function.
+ * Geometric inverse cumulative probability function.</p>
*
* <p>Usage note: As the probability of success (\( p \)) tends towards zero the mean of the
* distribution (\( \frac{1-p}{p} \)) tends towards infinity and due to the use of {@code int}
- * for the sample this can result in truncation of the distribution.
+ * for the sample this can result in truncation of the distribution.</p>
+ *
+ * <p>Sampling uses {@link UniformRandomProvider#nextDouble()}.</p>
*
* @see <a
* href="https://en.wikipedia.org/wiki/Geometric_distribution#Related_distributions">Geometric
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/InverseTransformContinuousSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/InverseTransformContinuousSampler.java
index ccaa138..5ba32fd 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/InverseTransformContinuousSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/InverseTransformContinuousSampler.java
@@ -24,7 +24,9 @@ import org.apache.commons.rng.UniformRandomProvider;
* inversion method</a>.
*
* It can be used to sample any distribution that provides access to its
- * <em>inverse cumulative probabilty function</em>.
+ * <em>inverse cumulative probability function</em>.
+ *
+ * <p>Sampling uses {@link UniformRandomProvider#nextDouble()}.</p>
*
* <p>Example:</p>
* <pre><code>
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/InverseTransformDiscreteSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/InverseTransformDiscreteSampler.java
index 5c43b58..276fb8e 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/InverseTransformDiscreteSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/InverseTransformDiscreteSampler.java
@@ -24,7 +24,9 @@ import org.apache.commons.rng.UniformRandomProvider;
* inversion method</a>.
*
* It can be used to sample any distribution that provides access to its
- * <em>inverse cumulative probabilty function</em>.
+ * <em>inverse cumulative probability function</em>.
+ *
+ * <p>Sampling uses {@link UniformRandomProvider#nextDouble()}.</p>
*
* <p>Example:</p>
* <pre><code>
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/InverseTransformParetoSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/InverseTransformParetoSampler.java
index 3b59483..4fd619b 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/InverseTransformParetoSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/InverseTransformParetoSampler.java
@@ -21,6 +21,8 @@ import org.apache.commons.rng.UniformRandomProvider;
/**
* Sampling from a <a href="https://en.wikipedia.org/wiki/Pareto_distribution">Pareto distribution</a>.
*
+ * <p>Sampling uses {@link UniformRandomProvider#nextDouble()}.</p>
+ *
* @since 1.0
*/
public class InverseTransformParetoSampler
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/LargeMeanPoissonSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/LargeMeanPoissonSampler.java
index 47ecab7..52af0ed 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/LargeMeanPoissonSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/LargeMeanPoissonSampler.java
@@ -32,9 +32,16 @@ import org.apache.commons.rng.sampling.distribution.InternalUtils.FactorialLog;
* </li>
* </ul>
*
- * @since 1.1
+ * <p>This sampler is suitable for {@code mean >= 40}.</p>
+ *
+ * <p>Sampling uses:</p>
+ *
+ * <ul>
+ * <li>{@link UniformRandomProvider#nextLong()}
+ * <li>{@link UniformRandomProvider#nextDouble()}
+ * </ul>
*
- * This sampler is suitable for {@code mean >= 40}.
+ * @since 1.1
*/
public class LargeMeanPoissonSampler
implements DiscreteSampler {
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/MarsagliaNormalizedGaussianSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/MarsagliaNormalizedGaussianSampler.java
index 4b64461..af50b55 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/MarsagliaNormalizedGaussianSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/MarsagliaNormalizedGaussianSampler.java
@@ -25,6 +25,8 @@ import org.apache.commons.rng.UniformRandomProvider;
* This is a variation of the algorithm implemented in
* {@link BoxMullerNormalizedGaussianSampler}.
*
+ * <p>Sampling uses {@link UniformRandomProvider#nextDouble()}.</p>
+ *
* @since 1.1
*/
public class MarsagliaNormalizedGaussianSampler
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/PoissonSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/PoissonSampler.java
index 2889108..599e1cd 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/PoissonSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/PoissonSampler.java
@@ -36,6 +36,13 @@ import org.apache.commons.rng.UniformRandomProvider;
* </li>
* </ul>
*
+ * <p>Sampling uses:</p>
+ *
+ * <ul>
+ * <li>{@link UniformRandomProvider#nextDouble()}
+ * <li>{@link UniformRandomProvider#nextLong()} (large means only)
+ * </ul>
+ *
* @since 1.0
*/
public class PoissonSampler
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/PoissonSamplerCache.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/PoissonSamplerCache.java
index 130feac..61aa73b 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/PoissonSamplerCache.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/PoissonSamplerCache.java
@@ -25,14 +25,14 @@ import org.apache.commons.rng.sampling.distribution.LargeMeanPoissonSampler.Larg
* distribution</a> using a cache to minimise construction cost.
*
* <p>The cache will return a sampler equivalent to
- * {@link PoissonSampler#PoissonSampler(UniformRandomProvider, double)}.
+ * {@link PoissonSampler#PoissonSampler(UniformRandomProvider, double)}.</p>
*
* <p>The cache allows the {@link PoissonSampler} construction cost to be minimised
* for low size Poisson samples. The cache stores state for a range of integers where
* integer value {@code n} can be used to construct a sampler for the range
- * {@code n <= mean < n+1}.
+ * {@code n <= mean < n+1}.</p>
*
- * <p>The cache is advantageous under the following conditions:
+ * <p>The cache is advantageous under the following conditions:</p>
*
* <ul>
* <li>The mean of the Poisson distribution falls within a known range.
@@ -44,15 +44,22 @@ import org.apache.commons.rng.sampling.distribution.LargeMeanPoissonSampler.Larg
*
* <p>If the sample size to be made with the <strong>same</strong> sampler is large
* then the construction cost is low compared to the sampling time and the cache
- * has minimal benefit.
+ * has minimal benefit.</p>
*
* <p>Performance improvement is dependent on the speed of the
* {@link UniformRandomProvider}. A fast provider can obtain a two-fold speed
- * improvement for a single-use Poisson sampler.
+ * improvement for a single-use Poisson sampler.</p>
*
* <p>The cache is thread safe. Note that concurrent threads using the cache
* must ensure a thread safe {@link UniformRandomProvider} is used when creating
- * samplers, e.g. a unique sampler per thread.
+ * samplers, e.g. a unique sampler per thread.</p>
+ *
+ * <p>Sampling uses:</p>
+ *
+ * <ul>
+ * <li>{@link UniformRandomProvider#nextDouble()}
+ * <li>{@link UniformRandomProvider#nextLong()} (large means only)
+ * </ul>
*
* @since 1.2
*/
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/RejectionInversionZipfSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/RejectionInversionZipfSampler.java
index 2e25934..d948c4b 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/RejectionInversionZipfSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/RejectionInversionZipfSampler.java
@@ -22,6 +22,8 @@ import org.apache.commons.rng.UniformRandomProvider;
/**
* Implementation of the <a href="https://en.wikipedia.org/wiki/Zipf's_law">Zipf distribution</a>.
*
+ * <p>Sampling uses {@link UniformRandomProvider#nextDouble()}.</p>
+ *
* @since 1.0
*/
public class RejectionInversionZipfSampler
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/SmallMeanPoissonSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/SmallMeanPoissonSampler.java
index 15a0d69..607feef 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/SmallMeanPoissonSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/SmallMeanPoissonSampler.java
@@ -29,10 +29,12 @@ import org.apache.commons.rng.UniformRandomProvider;
* </li>
* </ul>
*
- * @since 1.1
+ * <p>This sampler is suitable for {@code mean < 40}.
+ * For large means, {@link LargeMeanPoissonSampler} should be used instead.</p>
+ *
+ * <p>Sampling uses {@link UniformRandomProvider#nextDouble()}.</p>
*
- * This sampler is suitable for {@code mean < 40}.
- * For large means, {@link LargeMeanPoissonSampler} should be used instead.
+ * @since 1.1
*/
public class SmallMeanPoissonSampler
implements DiscreteSampler {
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/ZigguratNormalizedGaussianSampler.java b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/ZigguratNormalizedGaussianSampler.java
index cbd5e06..bd7345d 100644
--- a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/ZigguratNormalizedGaussianSampler.java
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/ZigguratNormalizedGaussianSampler.java
@@ -24,9 +24,16 @@ import org.apache.commons.rng.UniformRandomProvider;
* Marsaglia and Tsang "Ziggurat" method</a> for sampling from a Gaussian
* distribution with mean 0 and standard deviation 1.
*
- * The algorithm is explained in this
+ * <p>The algorithm is explained in this
* <a href="http://www.jstatsoft.org/article/view/v005i08/ziggurat.pdf">paper</a>
- * and this implementation has been adapted from the C code provided therein.
+ * and this implementation has been adapted from the C code provided therein.</p>
+ *
+ * <p>Sampling uses:</p>
+ *
+ * <ul>
+ * <li>{@link UniformRandomProvider#nextLong()}
+ * <li>{@link UniformRandomProvider#nextDouble()}
+ * </ul>
*
* @since 1.1
*/
[commons-rng] 02/10: RNG-79: Benchmark methods for producing
nextDouble and nextFloat
Posted by ah...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
aherbert pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/commons-rng.git
commit ac929bf427059c957ace0ee880d6b6801d153601
Author: Alex Herbert <ah...@apache.org>
AuthorDate: Mon Mar 4 21:40:17 2019 +0000
RNG-79: Benchmark methods for producing nextDouble and nextFloat
---
.../commons/rng/core/util/NumberFactoryTest.java | 63 +++++----
.../rng/examples/jmh/NextDoublePerformance.java | 152 +++++++++++++++++++++
2 files changed, 189 insertions(+), 26 deletions(-)
diff --git a/commons-rng-core/src/test/java/org/apache/commons/rng/core/util/NumberFactoryTest.java b/commons-rng-core/src/test/java/org/apache/commons/rng/core/util/NumberFactoryTest.java
index 3088ca4..40e2989 100644
--- a/commons-rng-core/src/test/java/org/apache/commons/rng/core/util/NumberFactoryTest.java
+++ b/commons-rng-core/src/test/java/org/apache/commons/rng/core/util/NumberFactoryTest.java
@@ -29,29 +29,12 @@ public class NumberFactoryTest {
final int LONG_SIZE = 8;
/** Test values. */
- private static final long[] LONG_TEST_VALUES = new long[] {
- 0L,
- 1L,
- -1L,
- 19337L,
- 1234567891011213L,
- -11109876543211L,
- Long.valueOf(Integer.MAX_VALUE),
- Long.valueOf(Integer.MIN_VALUE),
- Long.MAX_VALUE,
- Long.MIN_VALUE,
- };
+ private static final long[] LONG_TEST_VALUES = new long[] { 0L, 1L, -1L, 19337L, 1234567891011213L,
+ -11109876543211L, Long.valueOf(Integer.MAX_VALUE), Long.valueOf(Integer.MIN_VALUE), Long.MAX_VALUE,
+ Long.MIN_VALUE, };
/** Test values. */
- private static final int[] INT_TEST_VALUES = new int[] {
- 0,
- 1,
- -1,
- 19337,
- 1234567891,
- -1110987656,
- Integer.MAX_VALUE,
- Integer.MIN_VALUE,
- };
+ private static final int[] INT_TEST_VALUES = new int[] { 0, 1, -1, 19337, 1234567891, -1110987656,
+ Integer.MAX_VALUE, Integer.MIN_VALUE, };
@Test
public void testMakeIntFromLong() {
@@ -85,8 +68,7 @@ public class NumberFactoryTest {
@Test
public void testLongArrayFromByteArray2LongArray() {
final byte[] b = NumberFactory.makeByteArray(LONG_TEST_VALUES);
- Assert.assertArrayEquals(LONG_TEST_VALUES,
- NumberFactory.makeLongArray(b));
+ Assert.assertArrayEquals(LONG_TEST_VALUES, NumberFactory.makeLongArray(b));
}
@Test
@@ -100,8 +82,7 @@ public class NumberFactoryTest {
@Test
public void testIntArrayFromByteArray2IntArray() {
final byte[] b = NumberFactory.makeByteArray(INT_TEST_VALUES);
- Assert.assertArrayEquals(INT_TEST_VALUES,
- NumberFactory.makeIntArray(b));
+ Assert.assertArrayEquals(INT_TEST_VALUES, NumberFactory.makeIntArray(b));
}
@Test
@@ -159,4 +140,34 @@ public class NumberFactoryTest {
}
}
}
+
+ @Test
+ public void testFloatGeneration() {
+ final int allBits = 0xffffffff;
+
+ // Not capable of generating 1
+ Assert.assertEquals(1, (allBits >>> 9) * 0x1.0p-23f, 1e-6);
+ Assert.assertEquals(1, (allBits >>> 8) * 0x1.0p-24f, 1e-6);
+ Assert.assertEquals(1, Float.intBitsToFloat(0x7f << 23 | allBits >>> 9) - 1.0f, 1e-6);
+
+ final int noBits = 0;
+ Assert.assertEquals(0, (noBits >>> 8) * 0x1.0p-24f, 0);
+ Assert.assertEquals(0, (noBits >>> 9) * 0x1.0p-23f, 0);
+ Assert.assertEquals(0, Float.intBitsToFloat(0x7f << 23 | noBits >>> 9) - 1.0f, 0);
+ }
+
+ @Test
+ public void testDoubleGeneration() {
+ final long allBits = 0xffffffffffffffffL;
+
+ // Not capable of generating 1
+ Assert.assertEquals(1, (allBits >>> 12) * 0x1.0p-52d, 1e-10);
+ Assert.assertEquals(1, (allBits >>> 11) * 0x1.0p-53d, 1e-10);
+ Assert.assertEquals(1, Double.longBitsToDouble(0x3ffL << 52 | allBits >>> 12) - 1.0, 1e-10);
+
+ final long noBits = 0;
+ Assert.assertEquals(0, (noBits >>> 12) * 0x1.0p-52d, 0);
+ Assert.assertEquals(0, (noBits >>> 11) * 0x1.0p-53d, 0);
+ Assert.assertEquals(0, Double.longBitsToDouble(0x3ffL << 52 | noBits >>> 12) - 1.0, 0);
+ }
}
diff --git a/commons-rng-examples/examples-jmh/src/main/java/org/apache/commons/rng/examples/jmh/NextDoublePerformance.java b/commons-rng-examples/examples-jmh/src/main/java/org/apache/commons/rng/examples/jmh/NextDoublePerformance.java
new file mode 100644
index 0000000..f182955
--- /dev/null
+++ b/commons-rng-examples/examples-jmh/src/main/java/org/apache/commons/rng/examples/jmh/NextDoublePerformance.java
@@ -0,0 +1,152 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.commons.rng.examples.jmh;
+
+import org.openjdk.jmh.annotations.Benchmark;
+import org.openjdk.jmh.annotations.BenchmarkMode;
+import org.openjdk.jmh.annotations.Mode;
+import org.openjdk.jmh.annotations.Warmup;
+import org.openjdk.jmh.annotations.Measurement;
+import org.openjdk.jmh.annotations.State;
+import org.openjdk.jmh.annotations.Fork;
+import org.openjdk.jmh.annotations.Scope;
+import org.openjdk.jmh.annotations.OutputTimeUnit;
+
+import java.util.concurrent.ThreadLocalRandom;
+import java.util.concurrent.TimeUnit;
+
+/**
+ * Executes benchmark to compare the speed of generation of floating point
+ * numbers from the integer primitives.
+ */
+@BenchmarkMode(Mode.Throughput)
+@OutputTimeUnit(TimeUnit.MICROSECONDS)
+@Warmup(iterations = 5, time = 1, timeUnit = TimeUnit.SECONDS)
+@Measurement(iterations = 5, time = 1, timeUnit = TimeUnit.SECONDS)
+@State(Scope.Benchmark)
+@Fork(value = 1, jvmArgs = { "-server", "-Xms128M", "-Xmx128M" })
+public class NextDoublePerformance {
+ // Mimic the generation of the SplitMix64 algorithm
+ // and a SplitMix32 algorithm to get a spread of input numbers.
+
+ /**
+ * The 64-bit golden ratio number.
+ */
+ private static final long GOLDEN_64 = 0x9e3779b97f4a7c15L;
+ /**
+ * The 32-bit golden ratio number.
+ */
+ private static final long GOLDEN_32 = 0x9e3779b9;
+
+ /** The long state. */
+ private long longState = ThreadLocalRandom.current().nextLong();
+ /** The int state. */
+ private int intState = ThreadLocalRandom.current().nextInt();
+
+ /**
+ * Get the next long in the sequence.
+ *
+ * @return the long
+ */
+ private long nextLong() {
+ return longState += GOLDEN_64;
+ }
+
+ /**
+ * Get the next int in the sequence.
+ *
+ * @return the int
+ */
+ private int nextInt() {
+ return intState += GOLDEN_32;
+ }
+
+ // Benchmark methods
+
+ /**
+ * @return the long
+ */
+ @Benchmark
+ public long nextDoubleBaseline() {
+ return nextLong();
+ }
+
+ /**
+ * @return the double
+ */
+ @Benchmark
+ public double nextDoubleUsingBitsToDouble() {
+ // Combine 11 bit unsigned exponent with value 1023 (768 + 255) with 52 bit mantissa
+ // 0x300L = 256 + 512 = 768
+ // 0x0ff = 255
+ // This makes a number in the range 1.0 to 2.0 so subtract 1.0
+ return Double.longBitsToDouble(0x3ffL << 52 | nextLong() >>> 12) - 1.0;
+ }
+
+ /**
+ * @return the double
+ */
+ @Benchmark
+ public double nextDoubleUsingMultiply52bits() {
+ return (nextLong() >>> 12) * 0x1.0p-52d; // 1.0 / (1L << 52)
+ }
+
+ /**
+ * @return the double
+ */
+ @Benchmark
+ public double nextDoubleUsingMultiply53bits() {
+ return (nextLong() >>> 11) * 0x1.0p-53d; // 1.0 / (1L << 53)
+ }
+
+ /**
+ * @return the int
+ */
+ @Benchmark
+ public int nextFloatBaseline() {
+ return nextInt();
+ }
+
+ /**
+ * @return the float
+ */
+ @Benchmark
+ public float nextFloatUsingBitsToFloat() {
+ // Combine 8 bit unsigned exponent with value 127 (112 + 15) with 23 bit mantissa
+ // 0x70 = 64 + 32 + 16 = 112
+ // 0x0f = 15
+ // This makes a number in the range 1.0f to 2.0f so subtract 1.0f
+ return Float.intBitsToFloat(0x7f << 23 | nextInt() >>> 9) - 1.0f;
+ }
+
+ /**
+ * @return the float
+ */
+ @Benchmark
+ public float nextFloatUsingMultiply23bits() {
+ return (nextInt() >>> 9) * 0x1.0p-23f; // 1.0f / (1 << 23)
+ }
+
+ /**
+ * @return the float
+ */
+ @Benchmark
+ public float nextFloatUsingMultiply24bits() {
+ return (nextInt() >>> 8) * 0x1.0p-24f; // 1.0f / (1 << 24)
+ }
+}
[commons-rng] 06/10: RNG-79: Modify benchmark to use uniform random
generator.
Posted by ah...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
aherbert pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/commons-rng.git
commit 80c94a5916041fef587796abcafe646387c461c0
Author: aherbert <ah...@apache.org>
AuthorDate: Tue Mar 5 12:25:14 2019 +0000
RNG-79: Modify benchmark to use uniform random generator.
---
.../rng/examples/jmh/NextDoublePerformance.java | 102 +++++++++++----------
1 file changed, 56 insertions(+), 46 deletions(-)
diff --git a/commons-rng-examples/examples-jmh/src/main/java/org/apache/commons/rng/examples/jmh/NextDoublePerformance.java b/commons-rng-examples/examples-jmh/src/main/java/org/apache/commons/rng/examples/jmh/NextDoublePerformance.java
index f182955..70620f3 100644
--- a/commons-rng-examples/examples-jmh/src/main/java/org/apache/commons/rng/examples/jmh/NextDoublePerformance.java
+++ b/commons-rng-examples/examples-jmh/src/main/java/org/apache/commons/rng/examples/jmh/NextDoublePerformance.java
@@ -41,112 +41,122 @@ import java.util.concurrent.TimeUnit;
@State(Scope.Benchmark)
@Fork(value = 1, jvmArgs = { "-server", "-Xms128M", "-Xmx128M" })
public class NextDoublePerformance {
- // Mimic the generation of the SplitMix64 algorithm
- // and a SplitMix32 algorithm to get a spread of input numbers.
-
- /**
- * The 64-bit golden ratio number.
- */
- private static final long GOLDEN_64 = 0x9e3779b97f4a7c15L;
- /**
- * The 32-bit golden ratio number.
- */
- private static final long GOLDEN_32 = 0x9e3779b9;
-
- /** The long state. */
- private long longState = ThreadLocalRandom.current().nextLong();
- /** The int state. */
- private int intState = ThreadLocalRandom.current().nextInt();
-
/**
- * Get the next long in the sequence.
+ * Mimic the generation of the SplitMix64 algorithm.
*
- * @return the long
- */
- private long nextLong() {
- return longState += GOLDEN_64;
- }
-
- /**
- * Get the next int in the sequence.
- *
- * @return the int
+ * <p>The final mixing step must be included otherwise the output numbers are sequential
+ * and the test may run with a lack of numbers with higher order bits.
*/
- private int nextInt() {
- return intState += GOLDEN_32;
+ @State(Scope.Benchmark)
+ public static class LongSource {
+ /** The state. */
+ private long state = ThreadLocalRandom.current().nextLong();
+
+ /**
+ * Get the next long.
+ *
+ * @return the long
+ */
+ public final long nextLong() {
+ long z = state += 0x9e3779b97f4a7c15L;
+ z = (z ^ (z >>> 30)) * 0xbf58476d1ce4e5b9L;
+ z = (z ^ (z >>> 27)) * 0x94d049bb133111ebL;
+ return z ^ (z >>> 31);
+ }
+
+ /**
+ * Get the next int.
+ *
+ * <p>Returns the 32 high bits of Stafford variant 4 mix64 function as int.
+ *
+ * @return the int
+ */
+ public final int nextInt() {
+ long z = state += 0x9e3779b97f4a7c15L;
+ z = (z ^ (z >>> 33)) * 0x62a9d9ed799705f5L;
+ return (int)(((z ^ (z >>> 28)) * 0xcb24d0a5c88c35b3L) >>> 32);
+ }
}
// Benchmark methods
/**
+ * @param source the source
* @return the long
*/
@Benchmark
- public long nextDoubleBaseline() {
- return nextLong();
+ public long nextDoubleBaseline(LongSource source) {
+ return source.nextLong();
}
/**
+ * @param source the source
* @return the double
*/
@Benchmark
- public double nextDoubleUsingBitsToDouble() {
+ public double nextDoubleUsingBitsToDouble(LongSource source) {
// Combine 11 bit unsigned exponent with value 1023 (768 + 255) with 52 bit mantissa
// 0x300L = 256 + 512 = 768
// 0x0ff = 255
// This makes a number in the range 1.0 to 2.0 so subtract 1.0
- return Double.longBitsToDouble(0x3ffL << 52 | nextLong() >>> 12) - 1.0;
+ return Double.longBitsToDouble(0x3ffL << 52 | source.nextLong() >>> 12) - 1.0;
}
/**
+ * @param source the source
* @return the double
*/
@Benchmark
- public double nextDoubleUsingMultiply52bits() {
- return (nextLong() >>> 12) * 0x1.0p-52d; // 1.0 / (1L << 52)
+ public double nextDoubleUsingMultiply52bits(LongSource source) {
+ return (source.nextLong() >>> 12) * 0x1.0p-52d; // 1.0 / (1L << 52)
}
/**
+ * @param source the source
* @return the double
*/
@Benchmark
- public double nextDoubleUsingMultiply53bits() {
- return (nextLong() >>> 11) * 0x1.0p-53d; // 1.0 / (1L << 53)
+ public double nextDoubleUsingMultiply53bits(LongSource source) {
+ return (source.nextLong() >>> 11) * 0x1.0p-53d; // 1.0 / (1L << 53)
}
/**
+ * @param source the source
* @return the int
*/
@Benchmark
- public int nextFloatBaseline() {
- return nextInt();
+ public int nextFloatBaseline(LongSource source) {
+ return source.nextInt();
}
/**
+ * @param source the source
* @return the float
*/
@Benchmark
- public float nextFloatUsingBitsToFloat() {
+ public float nextFloatUsingBitsToFloat(LongSource source) {
// Combine 8 bit unsigned exponent with value 127 (112 + 15) with 23 bit mantissa
// 0x70 = 64 + 32 + 16 = 112
// 0x0f = 15
// This makes a number in the range 1.0f to 2.0f so subtract 1.0f
- return Float.intBitsToFloat(0x7f << 23 | nextInt() >>> 9) - 1.0f;
+ return Float.intBitsToFloat(0x7f << 23 | source.nextInt() >>> 9) - 1.0f;
}
/**
+ * @param source the source
* @return the float
*/
@Benchmark
- public float nextFloatUsingMultiply23bits() {
- return (nextInt() >>> 9) * 0x1.0p-23f; // 1.0f / (1 << 23)
+ public float nextFloatUsingMultiply23bits(LongSource source) {
+ return (source.nextInt() >>> 9) * 0x1.0p-23f; // 1.0f / (1 << 23)
}
/**
+ * @param source the source
* @return the float
*/
@Benchmark
- public float nextFloatUsingMultiply24bits() {
- return (nextInt() >>> 8) * 0x1.0p-24f; // 1.0f / (1 << 24)
+ public float nextFloatUsingMultiply24bits(LongSource source) {
+ return (source.nextInt() >>> 8) * 0x1.0p-24f; // 1.0f / (1 << 24)
}
}
[commons-rng] 09/10: Merge branch 'feature-RNG-79'
Posted by ah...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
aherbert pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/commons-rng.git
commit 526274452b2ce4a00d8df7ebbe19825709f5bb93
Merge: bfef2b6 80c94a5
Author: Alex Herbert <ah...@apache.org>
AuthorDate: Wed Mar 6 15:44:48 2019 +0000
Merge branch 'feature-RNG-79'
Closes #28
commons-rng-core/pom.xml | 7 +
.../commons/rng/core/util/NumberFactoryTest.java | 103 +++++++++----
.../rng/examples/jmh/NextDoublePerformance.java | 162 +++++++++++++++++++++
3 files changed, 246 insertions(+), 26 deletions(-)
[commons-rng] 05/10: RNG-79: NumberFactoryTest floating-point
precision uses commons-math3
Posted by ah...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
aherbert pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/commons-rng.git
commit d4950ef16cc79c86c0ad48129009f6f0bacbeadf
Author: aherbert <ah...@apache.org>
AuthorDate: Tue Mar 5 11:22:12 2019 +0000
RNG-79: NumberFactoryTest floating-point precision uses commons-math3
---
commons-rng-core/pom.xml | 7 +++
.../commons/rng/core/util/NumberFactoryTest.java | 60 +++++++++++++++++-----
2 files changed, 55 insertions(+), 12 deletions(-)
diff --git a/commons-rng-core/pom.xml b/commons-rng-core/pom.xml
index ceeaf48..e027ec6 100644
--- a/commons-rng-core/pom.xml
+++ b/commons-rng-core/pom.xml
@@ -53,6 +53,13 @@
<artifactId>commons-rng-client-api</artifactId>
<version>1.3-SNAPSHOT</version>
</dependency>
+ <dependency>
+ <!-- For testing floating point precision -->
+ <groupId>org.apache.commons</groupId>
+ <artifactId>commons-math3</artifactId>
+ <version>3.6.1</version>
+ <scope>test</scope>
+ </dependency>
</dependencies>
<build>
diff --git a/commons-rng-core/src/test/java/org/apache/commons/rng/core/util/NumberFactoryTest.java b/commons-rng-core/src/test/java/org/apache/commons/rng/core/util/NumberFactoryTest.java
index 6fb909e..9bbcc4d 100644
--- a/commons-rng-core/src/test/java/org/apache/commons/rng/core/util/NumberFactoryTest.java
+++ b/commons-rng-core/src/test/java/org/apache/commons/rng/core/util/NumberFactoryTest.java
@@ -16,6 +16,7 @@
*/
package org.apache.commons.rng.core.util;
+import org.apache.commons.math3.util.Precision;
import org.junit.Assert;
import org.junit.Test;
@@ -141,16 +142,18 @@ public class NumberFactoryTest {
}
}
+ /**
+ * Test different methods for generation of a {@code float} from a {@code int}. The output
+ * value should be in the range between 0 and 1.
+ */
@Test
- public void testFloatGeneration() {
+ public void testFloatGenerationMethods() {
final int allBits = 0xffffffff;
// Not capable of generating 1. Set the delta with 1 or 2 ULP of 1.
- final float deltaUlp2 = 1f - Math.nextAfter(Math.nextAfter(1f, -1), -1);
- final float deltaUlp1 = 1f - Math.nextAfter(1f, -1);
- Assert.assertEquals(1, (allBits >>> 9) * 0x1.0p-23f, deltaUlp2);
- Assert.assertEquals(1, (allBits >>> 8) * 0x1.0p-24f, deltaUlp1);
- Assert.assertEquals(1, Float.intBitsToFloat(0x7f << 23 | allBits >>> 9) - 1.0f, deltaUlp2);
+ assertCloseToNotAbove1((allBits >>> 9) * 0x1.0p-23f, 2);
+ assertCloseToNotAbove1((allBits >>> 8) * 0x1.0p-24f, 1);
+ assertCloseToNotAbove1(Float.intBitsToFloat(0x7f << 23 | allBits >>> 9) - 1.0f, 2);
final int noBits = 0;
Assert.assertEquals(0, (noBits >>> 9) * 0x1.0p-23f, 0);
@@ -158,20 +161,53 @@ public class NumberFactoryTest {
Assert.assertEquals(0, Float.intBitsToFloat(0x7f << 23 | noBits >>> 9) - 1.0f, 0);
}
+ /**
+ * Test different methods for generation of a {@code double} from a {@code long}. The output
+ * value should be in the range between 0 and 1.
+ */
@Test
- public void testDoubleGeneration() {
+ public void testDoubleGenerationMethods() {
final long allBits = 0xffffffffffffffffL;
// Not capable of generating 1. Set the delta with 1 or 2 ULP of 1.
- final double deltaUlp2 = 1 - Math.nextAfter(Math.nextAfter(1, -1), -1);
- final double deltaUlp1 = 1 - Math.nextAfter(1, -1);
- Assert.assertEquals(1, (allBits >>> 12) * 0x1.0p-52d, deltaUlp2);
- Assert.assertEquals(1, (allBits >>> 11) * 0x1.0p-53d, deltaUlp1);
- Assert.assertEquals(1, Double.longBitsToDouble(0x3ffL << 52 | allBits >>> 12) - 1.0, deltaUlp2);
+ assertCloseToNotAbove1((allBits >>> 12) * 0x1.0p-52d, 2);
+ assertCloseToNotAbove1((allBits >>> 11) * 0x1.0p-53d, 1);
+ assertCloseToNotAbove1(Double.longBitsToDouble(0x3ffL << 52 | allBits >>> 12) - 1.0, 2);
final long noBits = 0;
Assert.assertEquals(0, (noBits >>> 12) * 0x1.0p-52d, 0);
Assert.assertEquals(0, (noBits >>> 11) * 0x1.0p-53d, 0);
Assert.assertEquals(0, Double.longBitsToDouble(0x3ffL << 52 | noBits >>> 12) - 1.0, 0);
}
+
+
+ /**
+ * Assert that the value is close to but <strong>not above</strong> 1. This is used to test
+ * the output from methods that produce a {@code float} value that must be in the range
+ * between 0 and 1.
+ *
+ * @param value the value
+ * @param maxUlps {@code (maxUlps - 1)} is the number of floating point values between x and y.
+ * @see Precision#equals(float, float, int)
+ */
+ private static void assertCloseToNotAbove1(float value, int maxUlps) {
+ Assert.assertTrue("Not <= 1.0f", value <= 1.0f);
+ Assert.assertTrue("Not equal to 1.0f within units of least precision: " + maxUlps,
+ Precision.equals(1.0f, value, maxUlps));
+ }
+
+ /**
+ * Assert that the value is close to but <strong>not above</strong> 1. This is used to test
+ * the output from methods that produce a {@code double} value that must be in the range
+ * between 0 and 1.
+ *
+ * @param value the value
+ * @param maxUlps {@code (maxUlps - 1)} is the number of floating point values between x and y.
+ * @see Precision#equals(double, double, int)
+ */
+ private static void assertCloseToNotAbove1(double value, int maxUlps) {
+ Assert.assertTrue("Not <= 1.0", value <= 1.0);
+ Assert.assertTrue("Not equal to 1.0 within units of least precision: " + maxUlps,
+ Precision.equals(1.0, value, maxUlps));
+ }
}
[commons-rng] 03/10: RNG-79: Updated testFloatGeneration internal
order
Posted by ah...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
aherbert pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/commons-rng.git
commit d03726b337653c430789cd18f3d5b9a5d7df21be
Author: Alex Herbert <ah...@apache.org>
AuthorDate: Mon Mar 4 21:48:55 2019 +0000
RNG-79: Updated testFloatGeneration internal order
---
.../test/java/org/apache/commons/rng/core/util/NumberFactoryTest.java | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/commons-rng-core/src/test/java/org/apache/commons/rng/core/util/NumberFactoryTest.java b/commons-rng-core/src/test/java/org/apache/commons/rng/core/util/NumberFactoryTest.java
index 40e2989..5638768 100644
--- a/commons-rng-core/src/test/java/org/apache/commons/rng/core/util/NumberFactoryTest.java
+++ b/commons-rng-core/src/test/java/org/apache/commons/rng/core/util/NumberFactoryTest.java
@@ -151,8 +151,8 @@ public class NumberFactoryTest {
Assert.assertEquals(1, Float.intBitsToFloat(0x7f << 23 | allBits >>> 9) - 1.0f, 1e-6);
final int noBits = 0;
- Assert.assertEquals(0, (noBits >>> 8) * 0x1.0p-24f, 0);
Assert.assertEquals(0, (noBits >>> 9) * 0x1.0p-23f, 0);
+ Assert.assertEquals(0, (noBits >>> 8) * 0x1.0p-24f, 0);
Assert.assertEquals(0, Float.intBitsToFloat(0x7f << 23 | noBits >>> 9) - 1.0f, 0);
}
[commons-rng] 08/10: Track changes.
Posted by ah...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
aherbert pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/commons-rng.git
commit bfef2b672a9a21961c75cb024582a2fe5cbb261d
Author: Alex Herbert <ah...@apache.org>
AuthorDate: Wed Mar 6 15:43:35 2019 +0000
Track changes.
---
src/changes/changes.xml | 3 +++
1 file changed, 3 insertions(+)
diff --git a/src/changes/changes.xml b/src/changes/changes.xml
index e49e200..0f824fb 100644
--- a/src/changes/changes.xml
+++ b/src/changes/changes.xml
@@ -75,6 +75,9 @@ re-run tests that fail, and pass the build if they succeed
within the allotted number of reruns (the test will be marked
as 'flaky' in the report).
">
+ <action dev="aherbert" type="update" issue="RNG-73">
+ Add the methods used from UniformRandomProvider to each sampler in the sampling module.
+ </action>
<action dev="aherbert" type="update" issue="RNG-74">
"DiscreteUniformSampler": Algorithms for small and large integer ranges have
been delegated to specialised classes.
[commons-rng] 10/10: Track changes.
Posted by ah...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
aherbert pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/commons-rng.git
commit f5ac62537baafcbad749bbda29bd8600ce53c3aa
Author: Alex Herbert <ah...@apache.org>
AuthorDate: Wed Mar 6 15:46:16 2019 +0000
Track changes.
---
src/changes/changes.xml | 3 +++
1 file changed, 3 insertions(+)
diff --git a/src/changes/changes.xml b/src/changes/changes.xml
index 0f824fb..0e2d57f 100644
--- a/src/changes/changes.xml
+++ b/src/changes/changes.xml
@@ -75,6 +75,9 @@ re-run tests that fail, and pass the build if they succeed
within the allotted number of reruns (the test will be marked
as 'flaky' in the report).
">
+ <action dev="aherbert" type="add" issue="RNG-79">
+ Benchmark methods for producing nextDouble and nextFloat.
+ </action>
<action dev="aherbert" type="update" issue="RNG-73">
Add the methods used from UniformRandomProvider to each sampler in the sampling module.
</action>
[commons-rng] 07/10: Merge branch 'improvement-RNG-73'
Posted by ah...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
aherbert pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/commons-rng.git
commit cf51f2c28a48bdb1d5c4fd98fdd85f63392d8911
Merge: fccc73e fbeeb08
Author: Alex Herbert <ah...@apache.org>
AuthorDate: Wed Mar 6 15:41:19 2019 +0000
Merge branch 'improvement-RNG-73'
Closes #25
.../commons/rng/sampling/CollectionSampler.java | 2 ++
.../commons/rng/sampling/CombinationSampler.java | 8 +++++---
.../DiscreteProbabilityCollectionSampler.java | 2 ++
.../org/apache/commons/rng/sampling/ListSampler.java | 10 +++++++++-
.../commons/rng/sampling/PermutationSampler.java | 8 ++++++--
.../commons/rng/sampling/SubsetSamplerUtils.java | 6 ++++--
.../commons/rng/sampling/UnitSphereSampler.java | 7 +++++++
.../distribution/AhrensDieterExponentialSampler.java | 2 ++
.../AhrensDieterMarsagliaTsangGammaSampler.java | 7 +++++++
.../distribution/BoxMullerGaussianSampler.java | 2 ++
.../distribution/BoxMullerLogNormalSampler.java | 2 ++
.../BoxMullerNormalizedGaussianSampler.java | 2 ++
.../rng/sampling/distribution/ChengBetaSampler.java | 2 ++
.../distribution/ContinuousUniformSampler.java | 2 ++
.../sampling/distribution/DiscreteUniformSampler.java | 4 ++++
.../rng/sampling/distribution/GeometricSampler.java | 10 ++++++----
.../InverseTransformContinuousSampler.java | 4 +++-
.../distribution/InverseTransformDiscreteSampler.java | 4 +++-
.../distribution/InverseTransformParetoSampler.java | 2 ++
.../distribution/LargeMeanPoissonSampler.java | 11 +++++++++--
.../MarsagliaNormalizedGaussianSampler.java | 2 ++
.../rng/sampling/distribution/PoissonSampler.java | 7 +++++++
.../sampling/distribution/PoissonSamplerCache.java | 19 +++++++++++++------
.../distribution/RejectionInversionZipfSampler.java | 2 ++
.../distribution/SmallMeanPoissonSampler.java | 8 +++++---
.../ZigguratNormalizedGaussianSampler.java | 11 +++++++++--
26 files changed, 119 insertions(+), 27 deletions(-)