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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) %.200s does not export expected C variable %.200s C variable %.200s.%.200s has wrong signature (expected %.500s, got %.500s) %.200s does not export expected C function %.200s C function %.200s.%.200s has wrong signature (expected %.500s, got %.500s) Interpreter change detected - this module can only be loaded into one interpreter per process. metaclass conflict: the metaclass of a derived class must be a (non-strict) subclass of the metaclasses of all its bases Unable to initialize pickling for %s __annotations__ must be set to a dict object __kwdefaults__ must be set to a dict object __defaults__ must be set to a tuple object function's dictionary may not be deleted setting function's dictionary to a non-dict __qualname__ must be set to a string object __name__ must be set to a string object %.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 Unexpected format string character: '%c' %s() got multiple values for keyword argument '%U' %.200s() keywords must be strings %s() got an unexpected keyword argument '%U' calling %R should have returned an instance of BaseException, not %R raise: exception class must be a subclass of BaseException join() result is too long for a Python string Buffer dtype mismatch, expected %s%s%s but got %s Buffer dtype mismatch, expected '%s' but got %s in '%s.%s' Expected a dimension of size %zu, got %zu Expected %d dimensions, got %d Python does not define a standard format string size for long double ('g').. Buffer dtype mismatch; next field is at offset %zd but %zd expected Big-endian buffer not supported on little-endian compiler Buffer acquisition: Expected '{' after 'T' Cannot handle repeated arrays in format string Does not understand character buffer dtype format string ('%c') Expected a dimension of size %zu, got %d Expected a comma in format string, got '%c' Expected %d dimension(s), got %d Unexpected end of format string, expected ')' Buffer has wrong number of dimensions (expected %d, got %d) Item size of buffer (%zd byte%s) does not match size of '%s' (%zd byte%s) can't convert negative value to uint32_t value too large to convert to uint32_t value too large to convert to int unbound method %.200S() needs an argument %.200s() takes no arguments (%zd given) %.200s() takes exactly one argument (%zd given) Bad call flags in __Pyx_CyFunction_Call. METH_OLDARGS is no longer supported! %.200s() takes no keyword arguments %.200s() takes %.8s %zd positional argument%.1s (%zd given) numpy.random.bit_generator.ISpawnableSeedSequence.spawn numpy.random.bit_generator.__defaults__ numpy.random.bit_generator.ISeedSequence.generate_state Out of bounds on buffer access (axis %d) numpy.random.bit_generator.SeedSequence.mix_entropy numpy.random.bit_generator.BitGenerator.__setstate__ numpy.random.bit_generator.BitGenerator.__getstate__ object of type 'NoneType' has no len() hasattr(): attribute name must be string numpy.random.bit_generator.__pyx_unpickle_SeedlessSeedSequence__set_state numpy.random.bit_generator.SeedlessSeedSequence.__setstate_cython__ numpy.random.bit_generator.SeedlessSeedSequence.spawn numpy.random.bit_generator.SeedSequence.state.__get__ numpy.random.bit_generator.SeedSequence.__repr__ numpy.random.bit_generator.BitGenerator.cffi.__get__ numpy.random.bit_generator.BitGenerator.ctypes.__get__ numpy.random.bit_generator.BitGenerator._benchmark numpy.random.bit_generator.BitGenerator.random_raw numpy.random.bit_generator.BitGenerator.__reduce__ Module 'bit_generator' has already been imported. Re-initialisation is not supported. compiletime version %s of module '%.100s' does not match runtime version %s Shared Cython type %.200s is not a type object Shared Cython type %.200s has the wrong size, try recompiling PyObject *(bitgen_t *, PyObject *, Py_ssize_t, PyObject *) PyObject *(bitgen_t *, PyObject *, PyObject *, PyObject *) _ARRAY_API is not PyCapsule object module compiled against ABI version 0x%x but this version of numpy is 0x%x module compiled against API version 0x%x but this version of numpy is 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 init numpy.random.bit_generator numpy.random.bit_generator.BitGenerator.state.__set__ numpy.random.bit_generator.BitGenerator.state.__get__ numpy.random.bit_generator.SeedlessSeedSequence.generate_state numpy.random.bit_generator.SeedSequence.n_children_spawned.__get__ numpy.random.bit_generator.SeedSequence.pool_size.__get__ __pyx_unpickle_SeedlessSeedSequence numpy.random.bit_generator.__pyx_unpickle_SeedlessSeedSequence numpy.random.bit_generator.BitGenerator.spawn numpy.random.bit_generator.SeedlessSeedSequence.__reduce_cython__ numpy.random.bit_generator.BitGenerator.__init__ numpy.random.bit_generator.SeedSequence.__reduce_cython__ numpy.random.bit_generator._int_to_uint32_array 'NoneType' object is not subscriptable numpy.random.bit_generator.__pyx_unpickle_SeedSequence__set_state numpy.random.bit_generator.SeedSequence.__setstate_cython__ numpy.random.bit_generator.__pyx_unpickle_SeedSequence %.200s object is not an iterator numpy.random.bit_generator.SeedSequence.generate_state numpy.random.bit_generator.SeedSequence.get_assembled_entropy numpy.random.bit_generator.SeedSequence.spawn numpy.random.bit_generator._coerce_to_uint32_array numpy.random.bit_generator.SeedSequence.__init__ Cannot convert %.200s to %.200s numpy.random.bit_generator.SeedlessSeedSequence
A seed sequence for BitGenerators with no need for seed state.
See Also
--------
SeedSequence, ISeedSequence
numpy.random.bit_generator.SeedlessSequence numpy.random.bit_generator.SeedSequence
SeedSequence(entropy=None, *, spawn_key=(), pool_size=4)
SeedSequence mixes sources of entropy in a reproducible way to set the
initial state for independent and very probably non-overlapping
BitGenerators.
Once the SeedSequence is instantiated, you can call the `generate_state`
method to get an appropriately sized seed. Calling `spawn(n) ` will
create ``n`` SeedSequences that can be used to seed independent
BitGenerators, i.e. for different threads.
Parameters
----------
entropy : {None, int, sequence[int]}, optional
The entropy for creating a `SeedSequence`.
All integer values must be non-negative.
spawn_key : {(), sequence[int]}, optional
An additional source of entropy based on the position of this
`SeedSequence` in the tree of such objects created with the
`SeedSequence.spawn` method. Typically, only `SeedSequence.spawn` will
set this, and users will not.
pool_size : {int}, optional
Size of the pooled entropy to store. Default is 4 to give a 128-bit
entropy pool. 8 (for 256 bits) is another reasonable choice if working
with larger PRNGs, but there is very little to be gained by selecting
another value.
n_children_spawned : {int}, optional
The number of children already spawned. Only pass this if
reconstructing a `SeedSequence` from a serialized form.
Notes
-----
Best practice for achieving reproducible bit streams is to use
the default ``None`` for the initial entropy, and then use
`SeedSequence.entropy` to log/pickle the `entropy` for reproducibility:
>>> sq1 = np.random.SeedSequence()
>>> sq1.entropy
243799254704924441050048792905230269161 # random
>>> sq2 = np.random.SeedSequence(sq1.entropy)
>>> np.all(sq1.generate_state(10) == sq2.generate_state(10))
True
numpy.random.bit_generator.BitGenerator
BitGenerator(seed=None)
Base Class for generic BitGenerators, which provide a stream
of random bits based on different algorithms. Must be overridden.
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
`~numpy.random.SeedSequence` to derive the initial `BitGenerator` state.
One may also pass in a `SeedSequence` instance.
All integer values must be non-negative.
Attributes
----------
lock : threading.Lock
Lock instance that is shared so that the same BitGenerator can
be used in multiple Generators without corrupting the state. Code that
generates values from a bit generator should hold the bit generator's
lock.
See Also
--------
SeedSequence
Get or set the PRNG state
The base BitGenerator.state must be overridden by a subclass
Returns
-------
state : dict
Dictionary containing the information required to describe the
state of the PRNG
Get the seed sequence used to initialize the bit generator.
.. versionadded:: 1.25.0
Returns
-------
seed_seq : ISeedSequence
The SeedSequence object used to initialize the BitGenerator.
This is normally a `np.random.SeedSequence` instance.
ctypes interface
Returns
-------
interface : namedtuple
Named tuple containing ctypes wrapper
* state_address - Memory address of the state struct
* state - pointer to the state struct
* next_uint64 - function pointer to produce 64 bit integers
* next_uint32 - function pointer to produce 32 bit integers
* next_double - function pointer to produce doubles
* bitgen - pointer to the bit generator struct
CFFI interface
Returns
-------
interface : namedtuple
Named tuple containing CFFI wrapper
* state_address - Memory address of the state struct
* state - pointer to the state struct
* next_uint64 - function pointer to produce 64 bit integers
* next_uint32 - function pointer to produce 32 bit integers
* next_double - function pointer to produce doubles
* bitgen - pointer to the bit generator struct
__pyx_capi__ __loader__ loader __file__ origin __package__ parent __path__ submodule_search_locations co_argcount co_posonlyargcount co_kwonlyargcount co_nlocals co_stacksize co_flags co_code co_consts co_names co_varnames co_freevars co_cellvars co_linetable replace name '%U' is not defined cannot import name %S end unparseable format string 'complex double' 'signed char' 'unsigned char' 'short' 'unsigned short' 'int' 'unsigned int' 'long' 'unsigned long' 'long long' 'unsigned long long' 'double' 'complex long double' 'bool' 'char' 'complex float' 'float' a struct Python object a pointer a string 'long double' buffer dtype int an integer is required numpy/random/bit_generator.c %s (%s:%d) exactly spawn bit_generator.pyx at most at least generate_state stringsource tuple Expected %.16s, got %.200s _benchmark random_raw %d.%d numpy.random.bit_generator _cython_0_29_36 builtins cython_runtime __builtins__ 4294967296 numpy flatiter broadcast ndarray generic number unsignedinteger inexact complexfloating flexible character ufunc numpy.random._common double LEGACY_POISSON_LAM_MAX uint64_t MAXSIZE PyObject *(bitgen_t *) prepare_cffi prepare_ctypes numpy.core._multiarray_umath _ARRAY_API _ARRAY_API not found _ARRAY_API is NULL pointer __init__.pxd numpy.import_array __del__ bit_generator.pxd __init__ BitGenerator __pyx_unpickle_SeedSequence Missing type object cython_function_or_method __reduce__ __module__ func_doc __doc__ func_name __name__ __qualname__ __self__ func_dict __dict__ func_globals __globals__ func_closure __closure__ func_code __code__ func_defaults __defaults__ __kwdefaults__ __annotations__ __reduce_cython__ __setstate_cython__ entropy spawn_key pool_size pool n_children_spawned _seed_seq lock capsule __getstate__ __setstate__ _coerce_to_uint32_array _int_to_uint32_array npy_uint32 0o o o0o o o o o oPon o on o onnn o o o o o o o o o o o o o o o o0o0on on@oPon o on o o o0on o0o zwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwww$zwwywwwwwyywwywwyFyRyww^ywwwwwwwwwwwwwjy0zvywyyz.yww:ywww x zw xvuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuFwuuvuuuuu"w.wuu:wuuvvvuuvuuuuuuuuuuuuuvRw_vuvvvvVvuu
wuuuDvwuDvly\x\xly\x\x\x\x\x\zLz\x\xLz\x\x>> import numpy as np
>>> from numpy.random.bit_generator import _coerce_to_uint32_array
>>> _coerce_to_uint32_array(12345)
array([12345], dtype=uint32)
>>> _coerce_to_uint32_array('12345')
array([12345], dtype=uint32)
>>> _coerce_to_uint32_array('0x12345')
array([74565], dtype=uint32)
>>> _coerce_to_uint32_array([12345, '67890'])
array([12345, 67890], dtype=uint32)
>>> _coerce_to_uint32_array(np.array([12345, 67890], dtype=np.uint32))
array([12345, 67890], dtype=uint32)
>>> _coerce_to_uint32_array(np.array([12345, 67890], dtype=np.int64))
array([12345, 67890], dtype=uint32)
>>> _coerce_to_uint32_array([12345, 0x10deadbeef, 67890, 0xdeadbeef])
array([ 12345, 3735928559, 16, 67890, 3735928559],
dtype=uint32)
>>> _coerce_to_uint32_array(1234567890123456789012345678901234567890)
array([3460238034, 2898026390, 3235640248, 2697535605, 3],
dtype=uint32)
BitGenerator base class and SeedSequence used to seed the BitGenerators.
SeedSequence is derived from Melissa E. O'Neill's C++11 `std::seed_seq`
implementation, as it has a lot of nice properties that we want.
https://gist.github.com/imneme/540829265469e673d045
http://www.pcg-random.org/posts/developing-a-seed_seq-alternative.html
The MIT License (MIT)
Copyright (c) 2015 Melissa E. O'Neill
Copyright (c) 2019 NumPy Developers
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Abstract base class for seed sequences.
``BitGenerator`` implementations should treat any object that adheres to
this interface as a seed sequence.
See Also
--------
SeedSequence, SeedlessSeedSequence
__pyx_unpickle_SeedlessSeedSequence _coerce_to_uint32_array (line 79) only support uint32 or uint64 expected non-negative integer ISpawnableSeedSequence.spawn ISeedSequence.generate_state numpy.random.bit_generator __pyx_unpickle_SeedSequence unrecognized seed string _coerce_to_uint32_array ISpawnableSeedSequence seed must be integer n_children_spawned= SeedlessSeedSequence _int_to_uint32_array NotImplementedError n_children_spawned cline_in_traceback __bit_generator_ctor bit_generator.pyx SeedlessSequence __setstate_cython__ __pyx_PickleError generate_state abstractmethod __reduce_cython__ bit_generator ISeedSequence stringsource __pyx_checksum SeedSequence BitGenerator spawn_key= pool_size= concatenate PickleError ImportError startswith __pyx_vtable__ __pyx_result n_children ValueError DECIMAL_RE threading spawn_key __reduce_ex__ __pyx_state pool_size __metaclass__ itertools entropy= TypeError __setstate__ register randbits __qualname__ __pyx_type pickle __getstate__ errstate subseqs secrets __prepare__ n_words entropy compile update uint64 uint32 __reduce__ _pickle output __module__ method __import__ ignore format astype zeros state spawn range numpy match dtype cycle array view __test__ size self seed over __name__ __main__ __dict__ copy base Lock sys __new__ __doc__ cnt arr __all__ abc
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>>> from numpy.random.bit_generator import _coerce_to_uint32_array
>>> _coerce_to_uint32_array(12345)
array([12345], dtype=uint32)
>>> _coerce_to_uint32_array('12345')
array([12345], dtype=uint32)
>>> _coerce_to_uint32_array('0x12345')
array([74565], dtype=uint32)
>>> _coerce_to_uint32_array([12345, '67890'])
array([12345, 67890], dtype=uint32)
>>> _coerce_to_uint32_array(np.array([12345, 67890], dtype=np.uint32))
array([12345, 67890], dtype=uint32)
>>> _coerce_to_uint32_array(np.array([12345, 67890], dtype=np.int64))
array([12345, 67890], dtype=uint32)
>>> _coerce_to_uint32_array([12345, 0x10deadbeef, 67890, 0xdeadbeef])
array([ 12345, 3735928559, 16, 67890, 3735928559],
dtype=uint32)
>>> _coerce_to_uint32_array(1234567890123456789012345678901234567890)
array([3460238034, 2898026390, 3235640248, 2697535605, 3],
dtype=uint32)
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