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/ random / sfc64.pypy3-71-x86_64-linux-gnu.so
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LHwHGÐ1LLHH uG G$Ð1LLHH uW O$ HH %.200s.%.200s is not a type object %.200s.%.200s size changed, may indicate binary incompatibility. Expected %zd from C header, got %zd from PyObject %s.%s size changed, may indicate binary incompatibility. Expected %zd from C header, got %zd from PyObject %.200s does not export expected C variable %.200s C variable %.200s.%.200s has wrong signature (expected %.500s, got %.500s) __int__ returned non-int (type %.200s). The ability to return an instance of a strict subclass of int is deprecated, and may be removed in a future version of Python. __%.4s__ returned non-%.4s (type %.200s) value too large to convert to uint32_t can't convert negative value to uint32_t calling %R should have returned an instance of BaseException, not %R raise: exception class must be a subclass of BaseException numpy.random.sfc64.SFC64.__reduce_cython__ numpy.random.sfc64.SFC64.__setstate_cython__ numpy.random.sfc64.SFC64.state.__get__ %s() got multiple values for keyword argument '%U' %.200s() keywords must be strings %s() got an unexpected keyword argument '%U' Cannot convert %.200s to %.200s numpy.random.sfc64.SFC64.__init__ %.200s() takes %.8s %zd positional argument%.1s (%zd given) value too large to convert to int numpy.random.sfc64.SFC64.state.__set__ compiletime version %s of module '%.100s' does not match runtime version %s Unable to initialize pickling for %s invalid vtable found for imported type
SFC64(seed=None)
BitGenerator for Chris Doty-Humphrey's Small Fast Chaotic PRNG.
Parameters
----------
seed : {None, int, array_like[ints], ISeedSequence}, optional
A seed to initialize the `BitGenerator`. If None, then fresh,
unpredictable entropy will be pulled from the OS. If an ``int`` or
``array_like[ints]`` is passed, then it will be passed to
`SeedSequence` to derive the initial `BitGenerator` state. One may also
pass in an implementor of the `ISeedSequence` interface like
`SeedSequence`.
Notes
-----
``SFC64`` is a 256-bit implementation of Chris Doty-Humphrey's Small Fast
Chaotic PRNG ([1]_). ``SFC64`` has a few different cycles that one might be
on, depending on the seed; the expected period will be about
:math:`2^{255}` ([2]_). ``SFC64`` incorporates a 64-bit counter which means
that the absolute minimum cycle length is :math:`2^{64}` and that distinct
seeds will not run into each other for at least :math:`2^{64}` iterations.
``SFC64`` provides a capsule containing function pointers that produce
doubles, and unsigned 32 and 64- bit integers. These are not
directly consumable in Python and must be consumed by a ``Generator``
or similar object that supports low-level access.
**State and Seeding**
The ``SFC64`` state vector consists of 4 unsigned 64-bit values. The last
is a 64-bit counter that increments by 1 each iteration.
The input seed is processed by `SeedSequence` to generate the first
3 values, then the ``SFC64`` algorithm is iterated a small number of times
to mix.
**Compatibility Guarantee**
``SFC64`` makes a guarantee that a fixed seed will always produce the same
random integer stream.
References
----------
.. [1] `"PractRand"
<http://pracrand.sourceforge.net/RNG_engines.txt>`_
.. [2] `"Random Invertible Mapping Statistics"
<http://www.pcg-random.org/posts/random-invertible-mapping-statistics.html>`_
Get or set the PRNG state
Returns
-------
state : dict
Dictionary containing the information required to describe the
state of the PRNG
__pyx_capi__ name '%U' is not defined numpy/random/sfc64.c %s (%s:%d) an integer is required stringsource sfc64.pyx at most at least __init__ Missing type object __del__ %d.%d %s builtins cython_runtime __builtins__ __init__.pxd BitGenerator numpy.random.bit_generator type.pxd numpy dtype flatiter broadcast ndarray ufunc bit_generator.pxd SeedSequence SeedlessSequence double LEGACY_POISSON_LAM_MAX uint64_t MAXSIZE init numpy.random.sfc64 numpy.random.common numpy.random.sfc64.SFC64 state __reduce_cython__ __setstate_cython__ Format string allocated too short. self._bitgen cannot be converted to a Python object for pickling numpy.core.umath failed to import ndarray is not Fortran contiguous Non-native byte order not supported Format string allocated too short, see comment in numpy.pxd unknown dtype code in numpy.pxd (%d) numpy.core.multiarray failed to import ndarray is not C contiguous state must be for a {0} RNG state must be a dict cline_in_traceback __setstate_cython__ generate_state __reduce_cython__ bit_generator RuntimeError ImportError __pyx_vtable__ has_uint32 ValueError __reduce_ex__ TypeError uinteger __setstate__ __getstate__ uint64 __reduce__ __import__ format state range numpy empty dtype __class__ SFC64 __test__ seed __name__ __main__ __init__ get __all__ np <; x8 ܡ Ԣ` գ P 8h ( ؼ 8 p x h 8 X h( H X (P h zR x $ FJ w ?;*3$" D 8 \ > t ȹk S h py غ& Da $ T AAG HAAT ̟ BBE A(D0PIgAX0D(A BBB D l l BBE B(D0A8Q@8C0A(B BBB4 (U AAJ X
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