# Change Log¶

Deprecated

Generator and RandomState have been REMOVED in 1.23. You should be using numpy.random.Generator or numpy.random.RandomState which are maintained.

## v1.23.1¶

• 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.

## v1.23.0¶

• Removed Generator and RandomState.

## v1.20.2¶

• 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 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)

## v1.20.1¶

• Fixed a bug that affects standard_gamma when used with out and a Fortran contiguous array.

• Added standard_wishart() and wishart() variate generators.

## v1.20.0¶

• Sync upstream changes from NumPy

• Corrected a buffer access in ThreeFry and Philox.

• Fixed a bug in AESCounter that prevented a small number of counter values from being directly set.

## v1.19.3¶

• Future proofed setup against setuptools and distutils changes.

• Enhanced documentation for RDRAND.

## v1.19.2¶

• 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.

## v1.18.0¶

• choice pulled in upstream performance improvement that use a hash set when choosing without replacement and without user-provided probabilities.

• Added support for SeedSequence (and NumPy’s SeedSequence).

• Fixed a bug that affected both 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 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

## v1.17.0¶

• This release was skipped

## v1.16.6¶

• 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.

• Improved performance of jump() and jumped().

• Improves backward compatibility of RandomState

## v1.16.5¶

• 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.

## v1.16.4¶

• 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.

## v1.16.3¶

• Release fixing Python 2.7 issues

## v1.16.2¶

• 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

## v1.16.1¶

• Synchronized with upstream changes.

• Fixed a bug in gamma generation if the shape parameters is 0.0.

## v1.16.0¶

• 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.

## v1.15.1¶

• 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.

## v1.15¶

• 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