Author: aherbert
Date: Mon Sep 13 09:20:00 2021
New Revision: 49911
Log:
Release Commons RNG v1.4 (from RC3).
Added:
release/commons/rng/binaries/commons-rng-1.4-bin.tar.gz (with props)
release/commons/rng/binaries/commons-rng-1.4-bin.tar.gz.asc
release/commons/rng/binaries/commons-rng-1.4-bin.tar.gz.sha512
release/commons/rng/binaries/commons-rng-1.4-bin.zip (with props)
release/commons/rng/binaries/commons-rng-1.4-bin.zip.asc
release/commons/rng/binaries/commons-rng-1.4-bin.zip.sha512
release/commons/rng/source/commons-rng-1.4-src.tar.gz (with props)
release/commons/rng/source/commons-rng-1.4-src.tar.gz.asc
release/commons/rng/source/commons-rng-1.4-src.tar.gz.sha512
release/commons/rng/source/commons-rng-1.4-src.zip (with props)
release/commons/rng/source/commons-rng-1.4-src.zip.asc
release/commons/rng/source/commons-rng-1.4-src.zip.sha512
Removed:
release/commons/rng/binaries/commons-rng-1.3-bin.tar.gz
release/commons/rng/binaries/commons-rng-1.3-bin.tar.gz.asc
release/commons/rng/binaries/commons-rng-1.3-bin.tar.gz.sha512
release/commons/rng/binaries/commons-rng-1.3-bin.zip
release/commons/rng/binaries/commons-rng-1.3-bin.zip.asc
release/commons/rng/binaries/commons-rng-1.3-bin.zip.sha512
release/commons/rng/source/commons-rng-1.3-src.tar.gz
release/commons/rng/source/commons-rng-1.3-src.tar.gz.asc
release/commons/rng/source/commons-rng-1.3-src.tar.gz.sha512
release/commons/rng/source/commons-rng-1.3-src.zip
release/commons/rng/source/commons-rng-1.3-src.zip.asc
release/commons/rng/source/commons-rng-1.3-src.zip.sha512
Modified:
release/commons/rng/CONTRIBUTING.md
release/commons/rng/README.html
release/commons/rng/RELEASE-NOTES.txt
Modified: release/commons/rng/CONTRIBUTING.md
==============================================================================
--- release/commons/rng/CONTRIBUTING.md (original)
+++ release/commons/rng/CONTRIBUTING.md Mon Sep 13 09:20:00 2021
@@ -50,7 +50,7 @@ Getting Started
+ Make sure you have a [JIRA account](https://issues.apache.org/jira/).
+ Make sure you have a [GitHub account](https://github.com/signup/free).
-+ If you're planning to implement a new feature it makes sense to discuss
you're changes on the [dev list](https://commons.apache.org/mail-lists.html)
first. This way you can make sure you're not wasting your time on something
that isn't considered to be in Apache Commons RNG's scope.
++ If you're planning to implement a new feature it makes sense to discuss your
changes on the [dev list](https://commons.apache.org/mail-lists.html) first.
This way you can make sure you're not wasting your time on something that isn't
considered to be in Apache Commons RNG's scope.
+ Submit a ticket for your issue, assuming one does not already exist.
+ Clearly describe the issue including steps to reproduce when it is a bug.
+ Make sure you fill in the earliest version that you know has the issue.
Modified: release/commons/rng/README.html
==============================================================================
--- release/commons/rng/README.html (original)
+++ release/commons/rng/README.html Mon Sep 13 09:20:00 2021
@@ -14,9 +14,9 @@
See the License for the specific language governing permissions and
limitations under the License.
-->
-<h1>Commons-RNG v1.3.</h1>
+<h1>Commons-RNG v1.4.</h1>
-<p>This is the 1.3 version of commons-rng. It is available in both binary and
source distributions.</p>
+<p>This is the 1.4 version of commons-rng. It is available in both binary and
source distributions.</p>
<p><font color="red" size="+2">Note:</font>
@@ -55,12 +55,12 @@
<pre>Always test available signatures, <i>e.g.</i>,
$ pgpk -a KEYS
-$ pgpv commons-rng-1.3-bin.tar.gz.asc
+$ pgpv commons-rng-1.4-bin.tar.gz.asc
or,
$ pgp -ka KEYS
-$ pgp commons-rng-1.3-bin.tar.gz.asc
+$ pgp commons-rng-1.4-bin.tar.gz.asc
or,
$ gpg --import KEYS
-$ gpg --verify commons-rng-1.3-bin.tar.gz.asc
+$ gpg --verify commons-rng-1.4-bin.tar.gz.asc
</pre>
<p>
\ No newline at end of file
Modified: release/commons/rng/RELEASE-NOTES.txt
==============================================================================
--- release/commons/rng/RELEASE-NOTES.txt (original)
+++ release/commons/rng/RELEASE-NOTES.txt Mon Sep 13 09:20:00 2021
@@ -1,115 +1,234 @@
+ Apache Commons RNG 1.4 RELEASE NOTES
+
+The Apache Commons RNG team is pleased to announce the release of Apache
Commons RNG 1.4
+
+The Apache Commons RNG project provides pure-Java implementation
+of pseudo-random generators.
+
+This is a minor release of Apache Commons RNG, containing a
+few new features and performance improvements.
+
+Apache Commons RNG 1.4 contains the following library modules:
+ commons-rng-client-api (requires Java 8)
+ commons-rng-core (requires Java 8)
+ commons-rng-simple (requires Java 8)
+ commons-rng-sampling (requires Java 8)
+
+The code in module 'commons-rng-core' should not be accessed
+directly by applications as a future release might make use of
+the JPMS modularization feature available in Java 11+.
+
+Additional code is provided in the following modules:
+ commons-rng-examples-quadrature (requires Java 8)
+ commons-rng-examples-jmh (requires Java 8)
+ commons-rng-examples-sampling (requires Java 8)
+ commons-rng-examples-stress (requires Java 8)
+ commons-rng-examples-jpms (requires Java 11)
+
+It is however not part of the official API and no compatibility
+should be expected in subsequent releases.
+
+It must be noted that, due to the nature of random number generation, some
unit tests
+are bound to fail with some probability. The 'maven-surefire-plugin' is
configured
+to 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).
+
+Changes in this version include:
+
+New features:
+o RNG-156: New "DirichletSampler" class to sample from a Dirichlet
distribution.
+o RNG-137: New "StableSampler" class to sample from a stable distribution.
+o RNG-138: New "CompositeSamplers" class to sample from a weighted combination
of samplers.
+o RNG-140: New "LongSampler" interface for sampling a long. New
"UniformLongSampler" to sample
+ from a range.
+o RNG-151: New "ZigguratSampler" implementation of the modified "Ziggurat"
algorithm for
+ Gaussian and exponential sampling.
+o RNG-147: New "LevySampler" to sample from a Levy distribution.
+o RNG-145: "ContinuousUniformSampler": Add optional support for an open
interval: (lower, upper).
+o RNG-143: "RandomSource": Add an instance create method. Deprecate the static
create method.
+o RNG-136: New "ObjectSampler<T>" and "SharedStateObjectSampler<T>" interfaces.
+ These interfaces are implemented by samplers returning an object.
+ This changes the functional compatibility of existing samplers that
implement
+ SharedStatedSampler<R>: CollectionSampler<T>; CombinationSampler;
+ DiscreteProbabilityCollectionSampler<T>; PermutationSampler; and
UnitSphereSampler.
+ The method signature of the SharedStateSampler<R> interface remains
+ 'public R withUniformRandomProvider(UniformRandomProvider)'. The
result can still be
+ assigned to an instance of the same class R; it can no longer be
assigned to an instance
+ of SharedStatedSampler<R>. It can now be assigned to
SharedStateObjectSampler<T>
+ which can be used to generate samples of type <T>.
+ Code that assigned to SharedStatedSampler<R> should be updated.
+o RNG-135: New "TetrahedronSampler" to sample uniformly from a tetrahedron.
+o RNG-134: New "BoxSampler" to sample uniformly from a box (or hyperrectangle).
+o RNG-133: New "LineSampler" to sample uniformly on a line segment.
+o RNG-131: New "TriangleSampler" to sample uniformly from a triangle.
+o RNG-132: New "o.a.c.rng.sampling.shape" package for sampling coordinates
from shapes.
+o RNG-128: New "UnitBallSampler" to generate coordinates uniformly within an
n-unit ball.
+o RNG-126: "PoissonSamplerCache": Method to return a
SharedStateDiscreteSampler.
+o RNG-124: Add fixed increment versions of the PCG generators.
+
+Fixed Bugs:
+o RNG-159: "ZigguratSampler.NormalizedGaussian": Corrected biased sampling
within convex regions
+ at the edge of the ziggurat.
+o RNG-146: "GaussianSampler": Prevent infinite mean and standard deviation.
+o RNG-144: "AhrensDieterExponentialSampler": Avoid possible infinite loop
during sampling if the
+ underlying UniformRandomProvider creates a zero for the uniform
deviate.
+o RNG-130: "UnitSphereSampler": Fix 1 dimension sampling to only return
vectors containing 1 or -1.
+
+Changes:
+o RNG-163: Update test suite to JUnit 5.
+o Simplify assertions with simpler equivalent. Thanks to Arturo
Bernal.
+o RNG-162: Update the minimum Java version to 1.8.
+o RNG-160: "ZigguratSampler.NormalizedGaussian": Performance improvement by
extracting ziggurat
+ edge sampling to a separate method.
+o RNG-157: "UnitSphereSampler": Deprecate public constructor. Use the factory
constructor to create
+ an optimal sampler.
+o RNG-155: "ZigguratNormalizedGaussianSampler": Update to a table size of 256.
+o RNG-152: Update samplers to use ZigguratSampler.NormalizedGaussian for
Gaussian deviates.
+o RNG-154: Update Gaussian samplers to avoid infinity in the tails of the
distribution. Applies
+ to: ZigguratNormalisedGaussianSampler;
BoxMullerNormalizedGaussianSampler; and
+ BoxMullerGaussianSampler.
+o RNG-153: "UnitBallSampler": Update to use the ZigguratSampler for an
exponential deviate for
+ ball point picking.
+o RNG-150: Update "LargeMeanPoissonSampler" and "GeometricSampler" to use the
ZigguratSampler for
+ exponential deviates.
+o RNG-129: "UnitSphereSampler": Improve performance with specialisations for
low order dimensions.
+ Added a factory constructor to create the sampler.
+
+
+For complete information on Apache Commons RNG, including instructions on how
to submit bug reports,
+patches, or suggestions for improvement, see the Apache Commons RNG website:
+
+https://commons.apache.org/proper/commons-rng/
+
+
+=============================================================================
+
Apache Commons RNG 1.3 RELEASE NOTES
The Apache Commons RNG team is pleased to announce the release of Apache
Commons RNG 1.3
The Apache Commons RNG project provides pure-Java implementation of
pseudo-random generators.
-This is a minor release of Apache Commons RNG, containing a few new features
and performance improvements. Apache Commons RNG 1.3 contains the following
library modules:
+This is a minor release of Apache Commons RNG, containing a
+few new features and performance improvements.
+
+Apache Commons RNG 1.3 contains the following library modules:
commons-rng-client-api (requires Java 6)
commons-rng-core (requires Java 6)
commons-rng-simple (requires Java 6)
- commons-rng-sampling (requires Java 6) The code in module 'commons-rng-core'
should not be accessed directly by applications as a future release might make
use of the JPMS modularization feature available in Java 9+.
-Additional code is provided in the following module:
- commons-rng-examples (requires Java 9) It is however not part of the official
API and no compatibility should be expected in subsequent releases.
-It must be noted that, due to the nature of random number generation, some of
unit tests are bound to fail with some probability.
-The 'maven-surefire-plugin' is configured to 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).
+ commons-rng-sampling (requires Java 6)
-Changes in this version include:
+The code in module 'commons-rng-core' should not be accessed
+directly by applications as a future release might make use of
+the JPMS modularization feature available in Java 9+.
+
+Additional code is provided in the following module:
+ commons-rng-examples (requires Java 9)
+It is however not part of the official API and no compatibility
+should be expected in subsequent releases.
+
+We would like to also note that unit tests in module 'commons-rng-sampling'
+are bound to fail with some probability; this is expected due to the nature
+of random number generation. The 'maven-surefire-plugin' can be configured
+to re-run tests that fail and pass the build if they succeed (the test will
+be marked as 'flaky' in the report).
New features:
o RNG-117: Additional "XorShiRo" family generators. This adds 4 PlusPlus
general purpose variants
- of existing generators and 3 variants of a large state (1024-bit)
generator.
+ of existing generators and 3 variants of a large state (1024-bit)
generator.
o RNG-117: "RandomSource": Support creating a byte[] seed suitable for the
implementing
- generator class.
+ generator class.
o RNG-116: "RandomSource": Expose interfaces supported by the implementing
generator class
- with methods isJumpable() and isLongJumpable().
-o RNG-111: New "JenkinsSmallFast32" and "JenkinsSmallFast64" generators.
+ with methods isJumpable() and isLongJumpable().
+o RNG-111: New "JenkinsSmallFast32" and "JenkinsSmallFast64" generators.
o RNG-19: "JDKRandomWrapper": Wraps an instance of java.util.Random for use
as a
UniformRandomProvider. Can wrap a SecureRandom to use functionality
provided by the JDK for cryptographic random numbers and platform
dependent
- features such as reading /dev/urandom on Linux.
-o RNG-112: New "DotyHumphreySmallFastCounting32" and
"DotyHumphreySmallFastCounting64" generators.
-o RNG-85: New "MiddleSquareWeylSequence" generator.
+ features such as reading /dev/urandom on Linux.
+o RNG-112: New "DotyHumphreySmallFastCounting32" and
"DotyHumphreySmallFastCounting64" generators.
+o RNG-85: New "MiddleSquareWeylSequence" generator.
o RNG-110: Factory methods for Discrete and Continuous distribution samplers.
The factory method
- can choose the optimal implementation for the distribution parameters.
+ can choose the optimal implementation for the distribution parameters.
o RNG-84: New Permuted Congruential Generators (PCG) from the PCG family.
Added the LCG and MCG 32 bit output versions of the XSH-RS and XSH-RR
operations,
- along with the 64 bit RXS-M-XS edition. Thanks to Abhishek Singh
Dhadwal.
+ along with the 64 bit RXS-M-XS edition. Thanks to Abhishek Singh
Dhadwal.
o RNG-102: New "SharedStateSampler" interface to allow a sampler to create a
new instance with
- a new source of randomness. Any pre-computed state can be shared
between the samplers.
-o RNG-108: Update "SeedFactory" to improve performance.
+ a new source of randomness. Any pre-computed state can be shared
between the samplers.
+o RNG-108: Update "SeedFactory" to improve performance.
o RNG-99: New "AliasMethodDiscreteSampler" that can sample from any discrete
distribution defined
- by an array of probabilities. Set-up is O(n) time and sampling is O(1)
time.
+ by an array of probabilities. Set-up is O(n) time and sampling is O(1)
time.
o RNG-100: New "GuideTableDiscreteSampler" that can sample from any discrete
distribution defined
- by an array of probabilities.
+ by an array of probabilities.
o RNG-98: New "LongJumpableUniformRandomProvider" interface extends
JumpableUniformRandomProvider
- with a long jump method.
+ with a long jump method.
o RNG-97: New "JumpableUniformRandomProvider" interface provides a jump
method that advances
the generator a large number of steps of the output sequence in a
single operation. A
copy is returned allowing repeat invocations to create a series of
generators
- for use in parallel computations.
+ for use in parallel computations.
o RNG-101: New "MarsagliaTsangWangDiscreteSampler" that provides samples from
a discrete
distribution stored as a look-up table using a single random integer
deviate. Computes
tables for the Poisson or Binomial distributions, and generically any
provided discrete
- probability distribution.
+ probability distribution.
o RNG-91: New "KempSmallMeanPoissonSampler" that provides Poisson samples
using only 1 random
deviate per sample. This algorithm outperforms the
SmallMeanPoissonSampler
- when the generator is slow.
+ when the generator is slow.
o RNG-70: New "XorShiRo" family of generators. This adds 6 new general
purpose generators with
different periods and 4 related generators with improved performance
for floating-point
- generation.
-o RNG-82: New "XorShift1024StarPhi" generator. This is a modified
implementation of XorShift1024Star
- that improves randomness of the output sequence. The XOR_SHIFT_1024_S
enum has been marked
- deprecated as a note to users to switch to the new
XOR_SHIFT_1024_S_PHI version.
-o RNG-78: New "ThreadLocalRandomSource" class provides thread safe access to
random generators.
-o RNG-79: Benchmark methods for producing nextDouble and nextFloat.
-o RNG-72: Add new JMH benchmark ConstructionPerformance.
-o RNG-71: Validate parameters for the distribution samplers.
-o RNG-67: Instructions for how to build and run the examples-stress code.
-o RNG-69: New "GeometricSampler" class.
+ generation.
+o RNG-82: New "XorShift1024StarPhi" generator. This is a modified
implementation of
+ XorShift1024Star that improves randomness of the output sequence. The
XOR_SHIFT_1024_S
+ enum has been marked deprecated as a note to users to switch to the new
+ XOR_SHIFT_1024_S_PHI version.
+o RNG-78: New "ThreadLocalRandomSource" class provides thread safe access to
random generators.
+o RNG-79: Benchmark methods for producing nextDouble and nextFloat.
+o RNG-72: Add new JMH benchmark ConstructionPerformance.
+o RNG-71: Validate parameters for the distribution samplers.
+o RNG-67: Instructions for how to build and run the examples-stress code.
+o RNG-69: New "GeometricSampler" class.
Fixed Bugs:
o RNG-115: "JDKRandom": Fixed the restore state method to function when the
instance has not
- previously been used to save state.
+ previously been used to save state.
o RNG-96: "AhrensDieterMarsagliaTsangGammaSampler": Fix parameter
interpretation so that alpha
is a 'shape' parameter and theta is a 'scale' parameter. This reverses
the functionality
of the constructor parameters from previous versions. Dependent code
should be checked
- and parameters reversed to ensure existing functionality is
maintained.
+ and parameters reversed to ensure existing functionality is maintained.
o RNG-93: "SmallMeanPoissonSampler": Requires the Poisson probability for
p(x=0) to be positive
- setting an upper bound on the mean of approximately 744.44.
-o RNG-92: "LargeMeanPoissonSampler": Requires mean >= 1.
+ setting an upper bound on the mean of approximately 744.44.
+o RNG-92: "LargeMeanPoissonSampler": Requires mean >= 1.
Changes:
-o RNG-122: "SeedFactory": Use XoRoShiRo1024PlusPlus as the default source of
randomness.
+o RNG-122: "SeedFactory": Use XoRoShiRo1024PlusPlus as the default source of
randomness.
o RNG-121: "ChengBetaSampler": Algorithms for different distribution
parameters have
- been delegated to specialised classes.
+ been delegated to specialised classes.
o RNG-120: Update security of serialization code for java.util.Random
instances. Implement
- look-ahead deserialization or remove the use of
ObjectInputStream.readObject().
-o RNG-76: "SplitMix64": Added primitive long constructor.
-o RNG-119: Add LongJumpable support to XoShiRo generators previously only
supporting Jumpable.
+ look-ahead deserialization or remove the use of
ObjectInputStream.readObject().
+o RNG-76: "SplitMix64": Added primitive long constructor.
+o RNG-119: Add LongJumpable support to XoShiRo generators previously only
supporting Jumpable.
o RNG-114: "ListSampler": Select the shuffle algorithm based on the list
type. This improves
- performance for non-RandomAccess lists such as LinkedList.
+ performance for non-RandomAccess lists such as LinkedList.
o RNG-109: "DiscreteProbabilityCollectionSampler": Use a faster enumerated
probability
- distribution sampler to replace the binary search algorithm.
-o RNG-90: "BaseProvider": Updated to use faster algorithm for nextInt(int).
-o RNG-95: "DiscreteUniformSampler": Updated to use faster algorithms for
generation of ranges.
+ distribution sampler to replace the binary search algorithm.
+o RNG-90: "BaseProvider": Updated to use faster algorithm for nextInt(int).
+o RNG-95: "DiscreteUniformSampler": Updated to use faster algorithms for
generation of ranges.
o RNG-106: Ensure SeedFactory produces non-zero seed arrays. This avoids
invalid seeding of
- generators that cannot recover from a seed of zeros.
+ generators that cannot recover from a seed of zeros.
o RNG-103: "LargeMeanPoissonSampler: Switch from SmallMeanPoissonSampler to
use
- KempSmallMeanPoissonSampler for the fractional mean sample.
+ KempSmallMeanPoissonSampler for the fractional mean sample.
o RNG-75: "RandomSource.create(...)": Refactor internal components to allow
custom seeding routines
per random source. Improvements were made to the speed of creating
generators with small
- seeds.
-o RNG-77: "NumberFactory": Improve performance of int and long array to/from
byte array conversions.
-o RNG-88: Update the generation performance JMH benchmarks to have a
reference baseline.
-o RNG-87: "MultiplyWithCarry256": Performance improvement by advancing state
one step per sample.
-o RNG-81: "NumberFactory": Evenly sample all dyadic rationals between 0 and
1.
-o RNG-73: Add the methods used from UniformRandomProvider to each sampler in
the sampling module.
+ seeds.
+o RNG-77: "NumberFactory": Improve performance of int and long array to/from
byte array
+ conversions.
+o RNG-88: Update the generation performance JMH benchmarks to have a
reference baseline.
+o RNG-87: "MultiplyWithCarry256": Performance improvement by advancing state
one step per sample.
+o RNG-81: "NumberFactory": Evenly sample all dyadic rationals between 0 and 1.
+o RNG-73: Add the methods used from UniformRandomProvider to each sampler in
the sampling module.
o RNG-74: "DiscreteUniformSampler": Algorithms for small and large integer
ranges have
- been delegated to specialised classes.
+ been delegated to specialised classes.
o RNG-68: "AhrensDieterMarsagliaTsangGammaSampler": Algorithms for small and
large theta have
- been delegated to specialised classes.
+ been delegated to specialised classes.
For complete information on Apache Commons RNG, including instructions on how
to submit bug reports,
@@ -117,7 +236,6 @@ patches, or suggestions for improvement,
https://commons.apache.org/proper/commons-rng/
-
=============================================================================
Apache Commons RNG 1.2 RELEASE NOTES
@@ -126,37 +244,53 @@ The Apache Commons RNG team is pleased t
The Apache Commons RNG project provides pure-Java implementation of
pseudo-random generators.
-This is a minor release of Apache Commons RNG, containing a few new features
and performance improvements. Apache Commons RNG 1.2 contains the following
library modules:
+This is a minor release of Apache Commons RNG, containing a
+few new features and performance improvements.
+
+Apache Commons RNG 1.2 contains the following library modules:
commons-rng-client-api (requires Java 6)
commons-rng-core (requires Java 6)
commons-rng-simple (requires Java 6)
- commons-rng-sampling (requires Java 6) The code in module 'commons-rng-core'
should not be accessed directly by applications as a future release might make
use of the JPMS modularization feature available in Java 9+.
+ commons-rng-sampling (requires Java 6)
+
+The code in module 'commons-rng-core' should not be accessed
+directly by applications as a future release might make use of
+the JPMS modularization feature available in Java 9+.
+
Additional code is provided in the following module:
- commons-rng-examples (requires Java 9) It is however not part of the official
API and no compatibility should be expected in subsequent releases.
-It must be noted that, due to the nature of random number generation, some of
unit tests are bound to fail with some probability.
-The 'maven-surefire-plugin' is configured to 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).
+ commons-rng-examples (requires Java 9)
+It is however not part of the official API and no compatibility
+should be expected in subsequent releases.
+
+We would like to also note that unit tests in module 'commons-rng-sampling'
+are bound to fail with some probability; this is expected due to the nature
+of random number generation. The 'maven-surefire-plugin' can be configured
+to re-run tests that fail and pass the build if they succeed (the test will
+be marked as 'flaky' in the report).
Changes in this version include:
New features:
-o RNG-62: New "CombinationSampler" class. Thanks to Alex D. Herbert.
+o RNG-62: New "CombinationSampler" class. Thanks to Alex D. Herbert.
Fixed Bugs:
-o RNG-59: Use JDK's "SecureRandom" to seed the "SeedFactory".
-o RNG-56: "ZigguratNormalizedGaussianSampler": Missing statements in least
used branch.
+o RNG-59: Use JDK's "SecureRandom" to seed the "SeedFactory".
+o RNG-56: "ZigguratNormalizedGaussianSampler": Missing statements in least
used branch.
o RNG-55: "UnitSphereSampler": Prevent returning NaN components and forbid
- negative dimension. Thanks to Alex D. Herbert.
+ negative dimension. Thanks to Alex D. Herbert.
Changes:
-o RNG-63: "NumberFactory": Some methods have become obsolete following
RNG-57.
-o RNG-64: "PermutationSampler" and "CombinationSampler" shared code moved to
a utility class. Thanks to Alex D. Herbert.
-o RNG-61: "PermutationSampler": Performance improvement. Thanks to Alex D.
Herbert.
-o RNG-57: Cache for using up all the bits provided by the underlying source
of randomness. Thanks to Alex D. Herbert.
-o RNG-60: Use random seeds for unit testing.
-o RNG-52: Set conservative upper bound in "LargePoissonSampler" to avoid
truncation.
+o RNG-63: "NumberFactory": Some methods have become obsolete following RNG-57.
+o RNG-64: "PermutationSampler" and "CombinationSampler" shared code moved to
a utility class.
+ Thanks to Alex D. Herbert.
+o RNG-61: "PermutationSampler": Performance improvement. Thanks to Alex D.
Herbert.
+o RNG-57: Cache for using up all the bits provided by the underlying source
of randomness.
+ Thanks to Alex D. Herbert.
+o RNG-60: Use random seeds for unit testing.
+o RNG-52: Set conservative upper bound in "LargePoissonSampler" to avoid
truncation.
o RNG-58: Allow part of RNG state to be contained in base classes, e.g. to
enable
- caching in common code (see RNG-57).
-o RNG-51: "PoissonSampler": Performance improvement. Thanks to Alex D.
Herbert.
+ caching in common code (see RNG-57).
+o RNG-51: "PoissonSampler": Performance improvement. Thanks to Alex D.
Herbert.
For complete information on Apache Commons RNG, including instructions on how
to submit bug reports,
@@ -164,7 +298,6 @@ patches, or suggestions for improvement,
https://commons.apache.org/proper/commons-rng/
-
=============================================================================
Apache Commons RNG 1.1 RELEASE NOTES
@@ -173,49 +306,65 @@ The Apache Commons RNG team is pleased t
The Apache Commons RNG project provides pure-Java implementation of
pseudo-random generators.
-This is a minor release of Apache Commons RNG, containing a few new features
and performance improvements.
+This is a minor release of Apache Commons RNG, containing a
+few new features and performance improvements.
+
Apache Commons RNG 1.1 contains the following library modules:
- commons-rng-client-api (requires Java 6)
- commons-rng-core (requires Java 6)
- commons-rng-simple (requires Java 6)
- commons-rng-sampling (requires Java 6)
-The code in module 'commons-rng-core' should not be accessed directly by
applications as a future release might make use of the JPMS modularization
feature available in Java 9+.
+ commons-rng-client-api (requires Java 6)
+ commons-rng-core (requires Java 6)
+ commons-rng-simple (requires Java 6)
+ commons-rng-sampling (requires Java 6)
+
+The code in module 'commons-rng-core' should not be accessed
+directly by applications as a future release might make use of
+the JPMS modularization feature available in Java 9+.
+
Additional code is provided in the following module:
- commons-rng-examples (requires Java 9) It is however not part of the official
API and no compatibility should be expected in subsequent releases.
-We would like to also note that unit tests in module 'commons-rng-sampling'
are bound to fail with some probability; this is expected due to the nature of
random number generation.
-The 'maven-surefire-plugin' can be configured to re-run tests that fail and
pass the build if they succeed (the test will be marked as 'flaky' in the
report).
+ commons-rng-examples (requires Java 9)
+It is however not part of the official API and no compatibility
+should be expected in subsequent releases.
+
+We would like to also note that unit tests in module 'commons-rng-sampling'
+are bound to fail with some probability; this is expected due to the nature
+of random number generation. The 'maven-surefire-plugin' can be configured
+to re-run tests that fail and pass the build if they succeed (the test will
+be marked as 'flaky' in the report).
Changes in this version include:
New features:
-o RNG-37: Implementation of the "Ziggurat" algorithm for Gaussian sampling.
+o RNG-37: Implementation of the "Ziggurat" algorithm for Gaussian sampling.
o RNG-47: "DiscreteProbabilityCollectionSampler": Sampling from a collection
of items
- with user-defined probabilities (feature ported from "Commons Math").
-o RNG-43: "LogNormalSampler" with user-defined underlying
"NormalizedGaussianSampler".
+ with user-defined probabilities (feature ported from "Commons Math").
+o RNG-43: "LogNormalSampler" with user-defined underlying
"NormalizedGaussianSampler".
o RNG-39: "UnitSphereSampler": generate random vectors isotropically located
- on the surface of a sphere (feature ported from "Commons Math").
+ on the surface of a sphere (feature ported from "Commons Math").
o RNG-36: "MarsagliaNormalizedGaussianSampler": Faster variation of the
Box-Muller algorithm.
This version is used within "AhrensDieterMarsagliaTsangGammaSampler"
"MarsagliaLogNormalSampler" and "PoissonSampler" (generated sequences
- will thus differ from those generated by version 1.0 of the library).
+ will thus differ from those generated by version 1.0 of the library).
o RNG-35: New generic "GaussianSampler" based on "NormalizedGaussianSampler"
marker interface.
Implementation of "BoxMullerNormalizedGaussianSampler" deprecates
- "BoxMullerGaussianSampler".
+ "BoxMullerGaussianSampler".
Fixed Bugs:
o RNG-53: Class "SamplerBase" has been deprecated. It was meant for internal
use
only but, through inheritance, it allows incorrect usage of the sampler
- classes.
+ classes.
Changes:
-o RNG-50: "PoissonSampler": Algorithms for small mean and large mean have
+o RNG-50: "PoissonSampler": Algorithms for small mean and large mean have
been separated into dedicated classes. Cache precomputation has
been disabled as it is only marginally used and is a performance
- hit for small sampling sets. Thanks to Alex D. Herbert.
-o RNG-42: Use "ZigguratNormalizedGaussianSampler" within the library.
-o RNG-46: Following RNG-43, "BoxMullerLogNormalSampler" has been deprecated.
+ hit for small sampling sets.Thanks to Alex D. Herbert.
+o RNG-42: Use "ZigguratNormalizedGaussianSampler" within the library.
+o RNG-46: Following RNG-43, "BoxMullerLogNormalSampler" has been deprecated.
+ Furthermore, its base class has been removed; although it is a binary
+ incompatibility, it cannot cause any problem that were not already
+ present in code using v1.0 of the library: Calls to the base class
+ would have raised a NPE.
For complete information on Apache Commons RNG, including instructions on how
to submit bug reports,
@@ -223,7 +372,6 @@ patches, or suggestions for improvement,
https://commons.apache.org/proper/commons-rng/
-
=============================================================================
Apache Commons RNG 1.0 RELEASE NOTES
@@ -247,5 +395,3 @@ For complete information on Apache Commo
patches, or suggestions for improvement, see the Apache Commons RNG website:
https://commons.apache.org/proper/commons-rng/
-
-
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