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²E:ÍF ðìêübuö67ÛíÍ®V×p½ú4û÷-g{ùåüç³?Ï_üzùûã={$Ó _sfc64 name loader __loader__ origin __file__ parent __package__ submodule_search_locations __path__ Interpreter change detected - this module can only be loaded into one interpreter per process. Module '_sfc64' has already been imported. Re-initialisation is not supported. builtins cython_runtime __builtins__ numpy.random._sfc64 init numpy.random._sfc64 numpy/random/_sfc64.pyx <stringsource> compile time Python version %d.%d of module '%.100s' %s runtime version %d.%d does not match zlib decompress Failed to import '%.20s.decompress' - cannot initialise module strings. String compression was configured with the C macro 'CYTHON_COMPRESS_STRINGS=%d'. numpy.core.multiarray failed to import (auto-generated because you didn't call 'numpy.import_array()' after cimporting numpy; use '<void>numpy._import_array' to disable if you are certain you don't need it). numpy._core._multiarray_umath numpy.core._multiarray_umath _ARRAY_API _ARRAY_API is not PyCapsule object _ARRAY_API is NULL pointer module compiled against ABI version 0x%x but this version of numpy is 0x%x module was compiled against NumPy C-API version 0x%x (NumPy 1.23) but the running NumPy has C-API version 0x%x. Check the section C-API incompatibility at the Troubleshooting ImportError section at https://numpy.org/devdocs/user/troubleshooting-importerror.html#c-api-incompatibility for indications on how to solve this problem. FATAL: module compiled as unknown endian FATAL: module compiled as little endian, but detected different endianness at runtime _cython_3_2_5 Shared Cython type %.200s is not a type object Shared Cython type %.200s has the wrong size, try recompiling _cython_3_2_5._common_types_metatype __module__ _cython_3_2_5.cython_function_or_method <cyfunction %U at %p> unbound method %.200S() needs an argument keywords must be strings takes no arguments takes exactly one argument Bad call flags for CyFunction takes no keyword arguments %.200s() %s (%zd given) %.200s() %s __reduce__ __vectorcalloffset__ __weaklistoffset__ func_doc __doc__ func_name __name__ __qualname__ func_dict __dict__ func_globals __globals__ func_closure __closure__ func_code __code__ func_defaults __defaults__ __kwdefaults__ __annotations__ _is_coroutine __name__ must be set to a string object __qualname__ must be set to a string object __defaults__ must be set to a tuple object changes to cyfunction.__defaults__ will not currently affect the values used in function calls __kwdefaults__ must be set to a dict object changes to cyfunction.__kwdefaults__ will not currently affect the values used in function calls __annotations__ must be set to a dict object numpy.random.bit_generator BitGenerator %.200s.%.200s is not a type object %.200s.%.200s size changed, may indicate binary incompatibility. Expected %zd from C header, got %zd from PyObject numpy.random._sfc64.SFC64 SFC64(seed=None)
--
BitGenerator for Chris Doty-Humphrey's Small Fast Chaotic PRNG.
Parameters
----------
seed : {None, int, array_like[ints], SeedSequence}, 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 a `SeedSequence` instance.
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"
<https://pracrand.sourceforge.net/RNG_engines.txt>`_
.. [2] `"Random Invertible Mapping Statistics"
<https://www.pcg-random.org/posts/random-invertible-mapping-statistics.html>`_
__reduce_cython__ __setstate_cython__ at least at most exactly %.200s() takes %.8s %zd positional argument%.1s (%zd given) s %s() got an unexpected keyword argument '%U' numpy.random._sfc64.SFC64.__reduce_cython__ instance exception may not have a separate value calling %R should have returned an instance of BaseException, not %R raise: exception class must be a subclass of BaseException numpy.random._sfc64.SFC64.__setstate_cython__ %s() got multiple values for keyword argument '%U' %.200s() keywords must be strings state
Get or set the PRNG state
Returns
-------
state : dict
Dictionary containing the information required to describe the
state of the PRNG
numpy.random._sfc64.SFC64.state.__get__ name '%U' is not defined while calling a Python object NULL result without error in PyObject_Call __del__ numpy.random._sfc64.SFC64.state.__set__ '%.200s' object does not support slice %.10s assignment value too large to convert to int an integer is required __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. __int__ returned non-int (type %.200s) value too large to convert to uint32_t can't convert negative value to uint32_t __init__ numpy.random._sfc64.SFC64.__init__ Missing type object Cannot convert %.200s to %.200s base class '%.200s' is not a heap type extension type '%.200s' has no __dict__ slot, but base type '%.200s' has: either add 'cdef dict __dict__' to the extension type or add '__slots__ = [...]' to the base type multiple bases have vtable conflict: '%.200s' and '%.200s' invalid vtable found for imported type Unable to initialize pickling for %.200s type numpy dtype flatiter broadcast ndarray generic number integer signedinteger unsignedinteger inexact floating complexfloating flexible character ufunc SeedSequence SeedlessSeedSequence SeedlessSequence numpy.random._common variable __pyx_capi__ %.200s does not export expected C %.8s %.200s C %.8s %.200s.%.200s has wrong signature (expected %.500s, got %.500s) needs an argument 4 4 ÑX ! a ð X X '
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