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Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍 https://github.com/madlabunimib/PyCTBN
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PyCTBN/venv/lib/python3.9/site-packages/scipy/_lib/_ccallback.py

227 lines
6.1 KiB

from . import _ccallback_c
import ctypes
PyCFuncPtr = ctypes.CFUNCTYPE(ctypes.c_void_p).__bases__[0]
ffi = None
class CData(object):
pass
def _import_cffi():
global ffi, CData
if ffi is not None:
return
try:
import cffi
ffi = cffi.FFI()
CData = ffi.CData
except ImportError:
ffi = False
class LowLevelCallable(tuple):
"""
Low-level callback function.
Parameters
----------
function : {PyCapsule, ctypes function pointer, cffi function pointer}
Low-level callback function.
user_data : {PyCapsule, ctypes void pointer, cffi void pointer}
User data to pass on to the callback function.
signature : str, optional
Signature of the function. If omitted, determined from *function*,
if possible.
Attributes
----------
function
Callback function given.
user_data
User data given.
signature
Signature of the function.
Methods
-------
from_cython
Class method for constructing callables from Cython C-exported
functions.
Notes
-----
The argument ``function`` can be one of:
- PyCapsule, whose name contains the C function signature
- ctypes function pointer
- cffi function pointer
The signature of the low-level callback must match one of those expected
by the routine it is passed to.
If constructing low-level functions from a PyCapsule, the name of the
capsule must be the corresponding signature, in the format::
return_type (arg1_type, arg2_type, ...)
For example::
"void (double)"
"double (double, int *, void *)"
The context of a PyCapsule passed in as ``function`` is used as ``user_data``,
if an explicit value for ``user_data`` was not given.
"""
# Make the class immutable
__slots__ = ()
def __new__(cls, function, user_data=None, signature=None):
# We need to hold a reference to the function & user data,
# to prevent them going out of scope
item = cls._parse_callback(function, user_data, signature)
return tuple.__new__(cls, (item, function, user_data))
def __repr__(self):
return "LowLevelCallable({!r}, {!r})".format(self.function, self.user_data)
@property
def function(self):
return tuple.__getitem__(self, 1)
@property
def user_data(self):
return tuple.__getitem__(self, 2)
@property
def signature(self):
return _ccallback_c.get_capsule_signature(tuple.__getitem__(self, 0))
def __getitem__(self, idx):
raise ValueError()
@classmethod
def from_cython(cls, module, name, user_data=None, signature=None):
"""
Create a low-level callback function from an exported Cython function.
Parameters
----------
module : module
Cython module where the exported function resides
name : str
Name of the exported function
user_data : {PyCapsule, ctypes void pointer, cffi void pointer}, optional
User data to pass on to the callback function.
signature : str, optional
Signature of the function. If omitted, determined from *function*.
"""
try:
function = module.__pyx_capi__[name]
except AttributeError:
raise ValueError("Given module is not a Cython module with __pyx_capi__ attribute")
except KeyError:
raise ValueError("No function {!r} found in __pyx_capi__ of the module".format(name))
return cls(function, user_data, signature)
@classmethod
def _parse_callback(cls, obj, user_data=None, signature=None):
_import_cffi()
if isinstance(obj, LowLevelCallable):
func = tuple.__getitem__(obj, 0)
elif isinstance(obj, PyCFuncPtr):
func, signature = _get_ctypes_func(obj, signature)
elif isinstance(obj, CData):
func, signature = _get_cffi_func(obj, signature)
elif _ccallback_c.check_capsule(obj):
func = obj
else:
raise ValueError("Given input is not a callable or a low-level callable (pycapsule/ctypes/cffi)")
if isinstance(user_data, ctypes.c_void_p):
context = _get_ctypes_data(user_data)
elif isinstance(user_data, CData):
context = _get_cffi_data(user_data)
elif user_data is None:
context = 0
elif _ccallback_c.check_capsule(user_data):
context = user_data
else:
raise ValueError("Given user data is not a valid low-level void* pointer (pycapsule/ctypes/cffi)")
return _ccallback_c.get_raw_capsule(func, signature, context)
#
# ctypes helpers
#
def _get_ctypes_func(func, signature=None):
# Get function pointer
func_ptr = ctypes.cast(func, ctypes.c_void_p).value
# Construct function signature
if signature is None:
signature = _typename_from_ctypes(func.restype) + " ("
for j, arg in enumerate(func.argtypes):
if j == 0:
signature += _typename_from_ctypes(arg)
else:
signature += ", " + _typename_from_ctypes(arg)
signature += ")"
return func_ptr, signature
def _typename_from_ctypes(item):
if item is None:
return "void"
elif item is ctypes.c_void_p:
return "void *"
name = item.__name__
pointer_level = 0
while name.startswith("LP_"):
pointer_level += 1
name = name[3:]
if name.startswith('c_'):
name = name[2:]
if pointer_level > 0:
name += " " + "*"*pointer_level
return name
def _get_ctypes_data(data):
# Get voidp pointer
return ctypes.cast(data, ctypes.c_void_p).value
#
# CFFI helpers
#
def _get_cffi_func(func, signature=None):
# Get function pointer
func_ptr = ffi.cast('uintptr_t', func)
# Get signature
if signature is None:
signature = ffi.getctype(ffi.typeof(func)).replace('(*)', ' ')
return func_ptr, signature
def _get_cffi_data(data):
# Get pointer
return ffi.cast('uintptr_t', data)