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 4041757bc60cdf20dc9617c1f717a89ecf500aa9
Author: aherbert <aherb...@apache.org>
AuthorDate: Mon Nov 11 13:24:04 2019 +0000
Update release notes using the 1.3-release branch.
---
RELEASE-NOTES.txt | 205 +++++++++++++++++
.../resources/release-notes/RELEASE-NOTES-1.3.txt | 251 +++++++++++++++++++++
2 files changed, 456 insertions(+)
diff --git a/RELEASE-NOTES.txt b/RELEASE-NOTES.txt
index a6a99a0..b429d75 100644
--- a/RELEASE-NOTES.txt
+++ b/RELEASE-NOTES.txt
@@ -1,4 +1,125 @@
+ 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:
+ 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).
+
+Changes in this version include:
+
+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.
+o RNG-117: "RandomSource": Support creating a byte[] seed suitable for the
implementing
+ 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.
+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.
+o RNG-110: Factory methods for Discrete and Continuous distribution samplers.
The factory method
+ 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.
+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.
+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.
+o RNG-100: New "GuideTableDiscreteSampler" that can sample from any discrete
distribution defined
+ by an array of probabilities.
+o RNG-98: New "LongJumpableUniformRandomProvider" interface extends
JumpableUniformRandomProvider
+ 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.
+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.
+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.
+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.
+
+Fixed Bugs:
+o RNG-115: "JDKRandom": Fixed the restore state method to function when the
instance has not
+ 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.
+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.
+
+Changes:
+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.
+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.
+o RNG-114: "ListSampler": Select the shuffle algorithm based on the list
type. This improves
+ 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.
+o RNG-106: Ensure SeedFactory produces non-zero seed arrays. This avoids
invalid seeding of
+ generators that cannot recover from a seed of zeros.
+o RNG-103: "LargeMeanPoissonSampler: Switch from SmallMeanPoissonSampler to
use
+ 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.
+o RNG-74: "DiscreteUniformSampler": Algorithms for small and large integer
ranges have
+ been delegated to specialised classes.
+o RNG-68: "AhrensDieterMarsagliaTsangGammaSampler": Algorithms for small and
large theta have
+ been delegated to specialised classes.
+
+
+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 1.2 RELEASE NOTES
The Apache Commons RNG team is pleased to announce the release of Apache
Commons RNG 1.2
@@ -44,3 +165,87 @@ patches, or suggestions for improvement, see the Apache
Commons RNG website:
https://commons.apache.org/proper/commons-rng/
+=============================================================================
+
+ Apache Commons RNG 1.1 RELEASE NOTES
+
+The Apache Commons RNG team is pleased to announce the release of Apache
Commons RNG 1.1
+
+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 1.1 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+.
+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).
+
+Changes in this version include:
+
+New features:
+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".
+o RNG-39: "UnitSphereSampler": generate random vectors isotropically located
+ 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).
+o RNG-35: New generic "GaussianSampler" based on "NormalizedGaussianSampler"
+ marker interface.
+ Implementation of "BoxMullerNormalizedGaussianSampler" deprecates
+ "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.
+
+Changes:
+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.
+
+
+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 1.0 RELEASE NOTES
+
+The Apache Commons RNG team is pleased to announce the release of Apache
Commons RNG 1.0
+
+The Apache Commons RNG project provides pure-Java implementation of
pseudo-random generators.
+
+This is the first release of Apache Commons RNG.
+Apache Commons RNG 1.0 contains the following 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)
+ commons-rng-jmh (requires Java 6)
+ commons-rng-examples (requires Java 7)
+
+No changes defined in this version.
+
+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/
+
+
diff --git a/src/site/resources/release-notes/RELEASE-NOTES-1.3.txt
b/src/site/resources/release-notes/RELEASE-NOTES-1.3.txt
new file mode 100644
index 0000000..b429d75
--- /dev/null
+++ b/src/site/resources/release-notes/RELEASE-NOTES-1.3.txt
@@ -0,0 +1,251 @@
+
+ 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:
+ 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).
+
+Changes in this version include:
+
+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.
+o RNG-117: "RandomSource": Support creating a byte[] seed suitable for the
implementing
+ 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.
+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.
+o RNG-110: Factory methods for Discrete and Continuous distribution samplers.
The factory method
+ 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.
+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.
+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.
+o RNG-100: New "GuideTableDiscreteSampler" that can sample from any discrete
distribution defined
+ by an array of probabilities.
+o RNG-98: New "LongJumpableUniformRandomProvider" interface extends
JumpableUniformRandomProvider
+ 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.
+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.
+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.
+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.
+
+Fixed Bugs:
+o RNG-115: "JDKRandom": Fixed the restore state method to function when the
instance has not
+ 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.
+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.
+
+Changes:
+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.
+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.
+o RNG-114: "ListSampler": Select the shuffle algorithm based on the list
type. This improves
+ 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.
+o RNG-106: Ensure SeedFactory produces non-zero seed arrays. This avoids
invalid seeding of
+ generators that cannot recover from a seed of zeros.
+o RNG-103: "LargeMeanPoissonSampler: Switch from SmallMeanPoissonSampler to
use
+ 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.
+o RNG-74: "DiscreteUniformSampler": Algorithms for small and large integer
ranges have
+ been delegated to specialised classes.
+o RNG-68: "AhrensDieterMarsagliaTsangGammaSampler": Algorithms for small and
large theta have
+ been delegated to specialised classes.
+
+
+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 1.2 RELEASE NOTES
+
+The Apache Commons RNG team is pleased to announce the release of Apache
Commons RNG 1.2
+
+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:
+ 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).
+
+Changes in this version include:
+
+New features:
+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-55: "UnitSphereSampler": Prevent returning NaN components and forbid
+ 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-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.
+
+
+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 1.1 RELEASE NOTES
+
+The Apache Commons RNG team is pleased to announce the release of Apache
Commons RNG 1.1
+
+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 1.1 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+.
+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).
+
+Changes in this version include:
+
+New features:
+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".
+o RNG-39: "UnitSphereSampler": generate random vectors isotropically located
+ 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).
+o RNG-35: New generic "GaussianSampler" based on "NormalizedGaussianSampler"
+ marker interface.
+ Implementation of "BoxMullerNormalizedGaussianSampler" deprecates
+ "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.
+
+Changes:
+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.
+
+
+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 1.0 RELEASE NOTES
+
+The Apache Commons RNG team is pleased to announce the release of Apache
Commons RNG 1.0
+
+The Apache Commons RNG project provides pure-Java implementation of
pseudo-random generators.
+
+This is the first release of Apache Commons RNG.
+Apache Commons RNG 1.0 contains the following 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)
+ commons-rng-jmh (requires Java 6)
+ commons-rng-examples (requires Java 7)
+
+No changes defined in this version.
+
+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/
+
+
