Fixed a bug in LCG128Mix that resulted in inc not being correctly set when initialized without a user-provided inc.
Added the Tyche PRNG of Neves and Araujo. Supports two variants. One is the original implementation in the 2012 paper. The second implementation matches the version in OpenRand.
Added the Squares PRNG of Widynski. Supports two variants. The default uses 5 rounds of the middle square algorithm and outputs a 64-bit value. If variant=32, then 4 rounds are used but only 32 bits returned.
Added the helper function generate_keys() for Squares. This function can be used to pre-generate keys for use with Squares.
Refactored the broadcasting helper functions out of randomgen.common to randomgen.broadcast. Tests have been added and some edge case bugs have been found and fixed.
Improve test coverage.
Additional code clean-up.
Final compatibility with NumPy 2
Minimum NumPy is now 1.22.3.
Removed "legacy" seeding in favor of using SeedSequence.
Removed the vendored copy of SeedSequence.
Deprecated using the mode keyword argument to set the seed mode, since only SeedSequences are supported.
Changed randomgen.common.BitGenerator to inherit from numpy.random.BitGenerator so that numpy will recognize these as BitGenerators.
Removed C distribution functions that are available in NumPy (see libnpyrandom)`.
General code cleanup and modernization.
Initial compatability with Cython 3 and NumPy 2
Fixed a bug that affected the randomgen.xoroshiro128.Xoroshiro128.jumped() method of randomgen.xoroshiro128.Xoroshiro128 where the ** version was swapped with the standard version.
Fixed a bug where numpy.random.SeedSequence was not copied when advancing generators using jumped.
Small compatibility fixes for change in NumPy.
Changes the documentation theme to sphinx-immaterial.
Added builds for Python 3.11.
Increased the minimum Python to 3.8.
Registered the bit generators included in randomgen with NumPy so that NumPy Generator instances can be pickled and unpickled when using a randomstate bit generator.
Changed the canonical name of the bit generators to be their fully qualified name. For example, PCG64 is not named "randomgen.pcg64.PCG64" instead of "PCG64". This was done to avoid ambiguity with NumPy’s supplied bit generators with the same name.
Removed Generator and RandomState.
Fixed a bug in SFC64 the used the wrong value from the Weyl sequence. In the original implementation, the current value is added to the next random integer and then incremented. The buggy version was incrementing then adding, and so was shifted by one value. This sequence should be similarly random in appearance, but it does not match the original specification and so has been changed.
Added mode="numpy" support to PCG64, MT19937, Philox, and SFC64. When using this mode, the sequence generated is guaranteed to match the sequence produced using the NumPy implementations as long as a randomgen.seed_sequence.SeedSequence or numpy.random.SeedSequence is used with the same initial seed values.
Added random() with support for dtype="longdouble" to produce extended precision random floats.
In [1]: import numpy as np
In [2]: from randomgen import ExtendedGenerator, PCG64
In [3]: eg = ExtendedGenerator(PCG64(20210501))
In [4]: eg.random(5, dtype=np.longdouble)
Out[4]:
array([0.66851489, 0.01769784, 0.87316102, 0.86532386, 0.85384162],
dtype=float128)
Fixed a bug that affects standard_gamma when used with out and a Fortran contiguous array.
Added standard_wishart() and wishart() variate generators.
Sync upstream changes from NumPy
Added typing information
Fixed a bug in AESCounter that prevented a small number of counter values from being directly set.
Future proofed setup against setuptools and distutils changes.
Enhanced documentation for RDRAND.
Corrected RDRAND to retry on failures with pause between retries. Add a parameter retry which allows the number of retries to be set. It defaults to the Intel recommended value of 10. Also sets an exception when the number of retries has been exhausted (very unlikely). See the RDRAND docstring with unique considerations when using RDRAND that do not occur with deterministic PRNGs.
Added randomgen.romu.Romu which is among the fastest available bit generators.
Added weyl_increments() to simplify generating increments for use in parallel applications of SFC64.
Completed * Quality Assurance of all bit generators to at least 4TB.
Tested all bit generators out to at least 1TB using PractRand.
Added randomgen.pcg64.PCG64DXSM which is an alias for randomgen.pcg64.PCG64 with variant="dxsm" and mode="sequence". This is the 2.0 version of PCG64 and will likely become the default bit generator in NumPy in the near future.
Added randomgen.efiix64.EFIIX64 which is both fast and high-quality.
Added randomgen.sfc.SFC64 which supports generating streams using distinct Weyl constants.
Added a randomgen.pcg64.LCG128Mix which supports setting the LCG multiplier, changing the output function (including support for user-defined output functions) and pre- or post-state update generation.
Added a randomgen.lxm.LXM which generates variates using a mix of two simple, but flawed generators: an Xorshift and a 64-bit LCG. This has been proposed for including in in Java.
Added a randomgen.wrapper.UserBitGenerator which allows bit generators to be written in Python or numba.
Added randomgen.generator.ExtendedGenerator which contains features not in numpy.random.Generator.
Added support for the dxsm and dxsm-128 variants of randomgen.pcg64.PCG64. The dxsm variant is the official PCG 2.0 generator.
Added support for broadcasting inputs in randomgen.generator.ExtendedGenerator.multivariate_normal.
Added support for the ++ variant of randomgen.xoroshiro128.Xoroshiro128.
Fixed a bug the produced incorrect results in jumped().
Fixed multiple bugs in Generator that were fixed in numpy.random.Generator.
choice pulled in upstream performance improvement that use a hash set when choosing without replacement and without user-provided probabilities.
Added support for randomgen.seed_sequence.SeedSequence (and NumPy’s SeedSequence).
Fixed a bug that affected both randomgen.generator.Generator.randint in Generator and randint in RandomState when high=2**32. This value is inbounds for a 32-bit unsigned closed interval generator, and so should have been redirected to a 32-bit generator. It was erroneously sent to the 64-bit path. The random values produced are fully random but inefficient. This fix breaks the stream in randomgen.generator.Generator is the value for high is used. The fix restores RandomState to NumPy 1.16 compatibility. only affects the output if dtype is 'int64'
This release brings many breaking changes. Most of these have been implemented using DeprecationWarnings. This has been done to bring randomgen in-line with the API changes of the version going into NumPy.
Two changes that are more abrupt are:
The .generator method of the bit generators raise NotImplementedError
The internal structures that is used in C have been renamed. The main rename is brng_t to bitgen_t
The other key changes are:
Rename RandomGenerator to Generator.
Rename randint to integers.
Rename random_integers to integers.
Rename random_sample to random.
Change jump which operated in-place to jumped() which returns a new BitGenerator.
Rename Basic RNG to bit generator, which has been consistently applied across the docs and references
Add the integer-based SIMD-based Fast Mersenne Twister (SFMT) generator SFMT.
Add the 64-bit Mersenne Twister (MT64) generator MT64.
Renamed Xoshiro256StarStar to Xoshiro256 and Xoshiro512StarStar to Xoshiro512
This release was skipped
Changed the default jump step size to phi times the period of the generator for PCG32 and PCG64.
Improved the performance of PCG64 on Windows.
Improves backward compatibility of RandomState
Fixed bugs in laplace, gumbel, logseries, normal, standard_normal, standard_exponential, exponential, and logistic that could result in nan values in rare circumstances (about 1 in \(10^{53}\) draws).
Added keyword closed to randint which changes sampling from the half-open interval [low, high) to the closed interval [low, high].
Fixed a bug in random_integers that could lead to valid values being treated as invalid.
Add a fast path for broadcasting randint when using uint64 or int64.
Refactor PCG64 so that it does not rely on Cython conditional compilation.
Add brng to access the basic RNG.
Allow multidimensional arrays in choice.
Speed-up choice when not replacing. The gains can be very large (1000x or more) when the input array is large but the sample size is small.
Add parameter checks in multinomial.
Fix an edge-case bug in zipf.
Allow 0 for sample in hypergeometric.
Add broadcasting to multinomial (see NumPy issue 9710)
Release fixing Python 2.7 issues
Updated Xoroshiro120 to use Author’s latest parametrization
Closely synchronized with the version of randomgen being integrated into NumPy, including removing:
random_raw, which have been moved to the individual bit generators
random_uintegers, which can be replaced with randint.
Added RandomState as a clone of NumPy’s RandomState.
Removed LegacyGenerator since this is no longer needed
Fixed many small bugs, including in cffi and ctype interfaces
Synchronized with upstream changes.
Fixed a bug in gamma generation if the shape parameters is 0.0.
Fixed a bug that affected DSFMT when calling jump() or seed() that failed to reset the buffer. This resulted in up to 381 values from the previous state being used before the buffer was refilled at the new state.
Fixed bugs in Xoshiro512 and Xorshift1024 where the fallback entropy initialization used too few bytes. This bug is unlikely to be encountered since this path is only encountered if the system random number generator fails.
Synchronized with upstream changes.
Added Xoshiro256** and Xoshiro512**, the preferred generators of this class.
Fixed bug in jump method of Random123 generators which did not specify a default value.
Added support for generating bounded uniform integers using Lemire’s method.
Synchronized with upstream changes, which requires moving the minimum supported NumPy to 1.13.
Synced empty choice changes
Synced upstream docstring changes
Synced upstream changes in permutation
Synced upstream doc fixes
Added absolute_import to avoid import noise on Python 2.7
Add legacy generator which allows NumPy replication
Improve type handling of integers
Switch to array-fillers for 0 parameter distribution to improve performance
Small changes to build on manylinux
Build wheels using multibuild
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