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projektAI/venv/Lib/site-packages/scipy/special/_generate_pyx.py

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"""
python _generate_pyx.py
Generate Ufunc definition source files for scipy.special. Produces
files '_ufuncs.c' and '_ufuncs_cxx.c' by first producing Cython.
This will generate both calls to PyUFunc_FromFuncAndData and the
required ufunc inner loops.
The functions signatures are contained in 'functions.json', the syntax
for a function signature is
<function>: <name> ':' <input> '*' <output>
'->' <retval> '*' <ignored_retval>
<input>: <typecode>*
<output>: <typecode>*
<retval>: <typecode>?
<ignored_retval>: <typecode>?
<headers>: <header_name> [',' <header_name>]*
The input parameter types are denoted by single character type
codes, according to
'f': 'float'
'd': 'double'
'g': 'long double'
'F': 'float complex'
'D': 'double complex'
'G': 'long double complex'
'i': 'int'
'l': 'long'
'v': 'void'
If multiple kernel functions are given for a single ufunc, the one
which is used is determined by the standard ufunc mechanism. Kernel
functions that are listed first are also matched first against the
ufunc input types, so functions listed earlier take precedence.
In addition, versions with casted variables, such as d->f,D->F and
i->d are automatically generated.
There should be either a single header that contains all of the kernel
functions listed, or there should be one header for each kernel
function. Cython pxd files are allowed in addition to .h files.
Cython functions may use fused types, but the names in the list
should be the specialized ones, such as 'somefunc[float]'.
Function coming from C++ should have ``++`` appended to the name of
the header.
Floating-point exceptions inside these Ufuncs are converted to
special function errors --- which are separately controlled by the
user, and off by default, as they are usually not especially useful
for the user.
The C++ module
--------------
In addition to ``_ufuncs`` module, a second module ``_ufuncs_cxx`` is
generated. This module only exports function pointers that are to be
used when constructing some of the ufuncs in ``_ufuncs``. The function
pointers are exported via Cython's standard mechanism.
This mainly avoids build issues --- Python distutils has no way to
figure out what to do if you want to link both C++ and Fortran code in
the same shared library.
"""
#---------------------------------------------------------------------------------
# Extra code
#---------------------------------------------------------------------------------
UFUNCS_EXTRA_CODE_COMMON = """\
# This file is automatically generated by _generate_pyx.py.
# Do not edit manually!
include "_ufuncs_extra_code_common.pxi"
"""
UFUNCS_EXTRA_CODE = """\
include "_ufuncs_extra_code.pxi"
"""
UFUNCS_EXTRA_CODE_BOTTOM = """\
#
# Aliases
#
jn = jv
"""
CYTHON_SPECIAL_PXD = """\
# This file is automatically generated by _generate_pyx.py.
# Do not edit manually!
ctypedef fused number_t:
double complex
double
cpdef number_t spherical_jn(long n, number_t z, bint derivative=*) nogil
cpdef number_t spherical_yn(long n, number_t z, bint derivative=*) nogil
cpdef number_t spherical_in(long n, number_t z, bint derivative=*) nogil
cpdef number_t spherical_kn(long n, number_t z, bint derivative=*) nogil
"""
CYTHON_SPECIAL_PYX = """\
# This file is automatically generated by _generate_pyx.py.
# Do not edit manually!
\"\"\"
.. highlight:: cython
Cython API for special functions
================================
Scalar, typed versions of many of the functions in ``scipy.special``
can be accessed directly from Cython; the complete list is given
below. Functions are overloaded using Cython fused types so their
names match their Python counterpart. The module follows the following
conventions:
- If a function's Python counterpart returns multiple values, then the
function returns its outputs via pointers in the final arguments.
- If a function's Python counterpart returns a single value, then the
function's output is returned directly.
The module is usable from Cython via::
cimport scipy.special.cython_special
Error handling
--------------
Functions can indicate an error by returning ``nan``; however they
cannot emit warnings like their counterparts in ``scipy.special``.
Available functions
-------------------
FUNCLIST
Custom functions
----------------
Some functions in ``scipy.special`` which are not ufuncs have custom
Cython wrappers.
Spherical Bessel functions
~~~~~~~~~~~~~~~~~~~~~~~~~~
The optional ``derivative`` boolean argument is replaced with an
optional Cython ``bint``, leading to the following signatures.
- :py:func:`~scipy.special.spherical_jn`::
double complex spherical_jn(long, double complex)
double complex spherical_jn(long, double complex, bint)
double spherical_jn(long, double)
double spherical_jn(long, double, bint)
- :py:func:`~scipy.special.spherical_yn`::
double complex spherical_yn(long, double complex)
double complex spherical_yn(long, double complex, bint)
double spherical_yn(long, double)
double spherical_yn(long, double, bint)
- :py:func:`~scipy.special.spherical_in`::
double complex spherical_in(long, double complex)
double complex spherical_in(long, double complex, bint)
double spherical_in(long, double)
double spherical_in(long, double, bint)
- :py:func:`~scipy.special.spherical_kn`::
double complex spherical_kn(long, double complex)
double complex spherical_kn(long, double complex, bint)
double spherical_kn(long, double)
double spherical_kn(long, double, bint)
\"\"\"
include "_cython_special.pxi"
include "_cython_special_custom.pxi"
"""
STUBS = """\
# This file is automatically generated by _generate_pyx.py.
# Do not edit manually!
from typing import Any, Dict
import numpy as np
__all__ = [
'geterr',
'seterr',
'errstate',
{ALL}
]
def geterr() -> Dict[str, str]: ...
def seterr(**kwargs: str) -> Dict[str, str]: ...
class errstate:
def __init__(self, **kargs: str) -> None: ...
def __enter__(self) -> None: ...
def __exit__(
self,
exc_type: Any, # Unused
exc_value: Any, # Unused
traceback: Any, # Unused
) -> None: ...
{STUBS}
"""
#---------------------------------------------------------------------------------
# Code generation
#---------------------------------------------------------------------------------
import itertools
import json
import os
import optparse
import re
import textwrap
from typing import List
import numpy
BASE_DIR = os.path.abspath(os.path.dirname(__file__))
add_newdocs = __import__('add_newdocs')
CY_TYPES = {
'f': 'float',
'd': 'double',
'g': 'long double',
'F': 'float complex',
'D': 'double complex',
'G': 'long double complex',
'i': 'int',
'l': 'long',
'v': 'void',
}
C_TYPES = {
'f': 'npy_float',
'd': 'npy_double',
'g': 'npy_longdouble',
'F': 'npy_cfloat',
'D': 'npy_cdouble',
'G': 'npy_clongdouble',
'i': 'npy_int',
'l': 'npy_long',
'v': 'void',
}
TYPE_NAMES = {
'f': 'NPY_FLOAT',
'd': 'NPY_DOUBLE',
'g': 'NPY_LONGDOUBLE',
'F': 'NPY_CFLOAT',
'D': 'NPY_CDOUBLE',
'G': 'NPY_CLONGDOUBLE',
'i': 'NPY_INT',
'l': 'NPY_LONG',
}
CYTHON_SPECIAL_BENCHFUNCS = {
'airy': ['d*dddd', 'D*DDDD'],
'beta': ['dd'],
'erf': ['d', 'D'],
'exprel': ['d'],
'gamma': ['d', 'D'],
'jv': ['dd', 'dD'],
'loggamma': ['D'],
'logit': ['d'],
'psi': ['d', 'D'],
}
def underscore(arg):
return arg.replace(" ", "_")
def cast_order(c):
return ['ilfdgFDG'.index(x) for x in c]
# These downcasts will cause the function to return NaNs, unless the
# values happen to coincide exactly.
DANGEROUS_DOWNCAST = set([
('F', 'i'), ('F', 'l'), ('F', 'f'), ('F', 'd'), ('F', 'g'),
('D', 'i'), ('D', 'l'), ('D', 'f'), ('D', 'd'), ('D', 'g'),
('G', 'i'), ('G', 'l'), ('G', 'f'), ('G', 'd'), ('G', 'g'),
('f', 'i'), ('f', 'l'),
('d', 'i'), ('d', 'l'),
('g', 'i'), ('g', 'l'),
('l', 'i'),
])
NAN_VALUE = {
'f': 'NPY_NAN',
'd': 'NPY_NAN',
'g': 'NPY_NAN',
'F': 'NPY_NAN',
'D': 'NPY_NAN',
'G': 'NPY_NAN',
'i': '0xbad0bad0',
'l': '0xbad0bad0',
}
def generate_loop(func_inputs, func_outputs, func_retval,
ufunc_inputs, ufunc_outputs):
"""
Generate a UFunc loop function that calls a function given as its
data parameter with the specified input and output arguments and
return value.
This function can be passed to PyUFunc_FromFuncAndData.
Parameters
----------
func_inputs, func_outputs, func_retval : str
Signature of the function to call, given as type codes of the
input, output and return value arguments. These 1-character
codes are given according to the CY_TYPES and TYPE_NAMES
lists above.
The corresponding C function signature to be called is:
retval func(intype1 iv1, intype2 iv2, ..., outtype1 *ov1, ...);
If len(ufunc_outputs) == len(func_outputs)+1, the return value
is treated as the first output argument. Otherwise, the return
value is ignored.
ufunc_inputs, ufunc_outputs : str
Ufunc input and output signature.
This does not have to exactly match the function signature,
as long as the type casts work out on the C level.
Returns
-------
loop_name
Name of the generated loop function.
loop_body
Generated C code for the loop.
"""
if len(func_inputs) != len(ufunc_inputs):
raise ValueError("Function and ufunc have different number of inputs")
if len(func_outputs) != len(ufunc_outputs) and not (
func_retval != "v" and len(func_outputs)+1 == len(ufunc_outputs)):
raise ValueError("Function retval and ufunc outputs don't match")
name = "loop_%s_%s_%s_As_%s_%s" % (
func_retval, func_inputs, func_outputs, ufunc_inputs, ufunc_outputs
)
body = "cdef void %s(char **args, np.npy_intp *dims, np.npy_intp *steps, void *data) nogil:\n" % name
body += " cdef np.npy_intp i, n = dims[0]\n"
body += " cdef void *func = (<void**>data)[0]\n"
body += " cdef char *func_name = <char*>(<void**>data)[1]\n"
for j in range(len(ufunc_inputs)):
body += " cdef char *ip%d = args[%d]\n" % (j, j)
for j in range(len(ufunc_outputs)):
body += " cdef char *op%d = args[%d]\n" % (j, j + len(ufunc_inputs))
ftypes = []
fvars = []
outtypecodes = []
for j in range(len(func_inputs)):
ftypes.append(CY_TYPES[func_inputs[j]])
fvars.append("<%s>(<%s*>ip%d)[0]" % (
CY_TYPES[func_inputs[j]],
CY_TYPES[ufunc_inputs[j]], j))
if len(func_outputs)+1 == len(ufunc_outputs):
func_joff = 1
outtypecodes.append(func_retval)
body += " cdef %s ov0\n" % (CY_TYPES[func_retval],)
else:
func_joff = 0
for j, outtype in enumerate(func_outputs):
body += " cdef %s ov%d\n" % (CY_TYPES[outtype], j+func_joff)
ftypes.append("%s *" % CY_TYPES[outtype])
fvars.append("&ov%d" % (j+func_joff))
outtypecodes.append(outtype)
body += " for i in range(n):\n"
if len(func_outputs)+1 == len(ufunc_outputs):
rv = "ov0 = "
else:
rv = ""
funcall = " %s(<%s(*)(%s) nogil>func)(%s)\n" % (
rv, CY_TYPES[func_retval], ", ".join(ftypes), ", ".join(fvars))
# Cast-check inputs and call function
input_checks = []
for j in range(len(func_inputs)):
if (ufunc_inputs[j], func_inputs[j]) in DANGEROUS_DOWNCAST:
chk = "<%s>(<%s*>ip%d)[0] == (<%s*>ip%d)[0]" % (
CY_TYPES[func_inputs[j]], CY_TYPES[ufunc_inputs[j]], j,
CY_TYPES[ufunc_inputs[j]], j)
input_checks.append(chk)
if input_checks:
body += " if %s:\n" % (" and ".join(input_checks))
body += " " + funcall
body += " else:\n"
body += " sf_error.error(func_name, sf_error.DOMAIN, \"invalid input argument\")\n"
for j, outtype in enumerate(outtypecodes):
body += " ov%d = <%s>%s\n" % (
j, CY_TYPES[outtype], NAN_VALUE[outtype])
else:
body += funcall
# Assign and cast-check output values
for j, (outtype, fouttype) in enumerate(zip(ufunc_outputs, outtypecodes)):
if (fouttype, outtype) in DANGEROUS_DOWNCAST:
body += " if ov%d == <%s>ov%d:\n" % (j, CY_TYPES[outtype], j)
body += " (<%s *>op%d)[0] = <%s>ov%d\n" % (
CY_TYPES[outtype], j, CY_TYPES[outtype], j)
body += " else:\n"
body += " sf_error.error(func_name, sf_error.DOMAIN, \"invalid output\")\n"
body += " (<%s *>op%d)[0] = <%s>%s\n" % (
CY_TYPES[outtype], j, CY_TYPES[outtype], NAN_VALUE[outtype])
else:
body += " (<%s *>op%d)[0] = <%s>ov%d\n" % (
CY_TYPES[outtype], j, CY_TYPES[outtype], j)
for j in range(len(ufunc_inputs)):
body += " ip%d += steps[%d]\n" % (j, j)
for j in range(len(ufunc_outputs)):
body += " op%d += steps[%d]\n" % (j, j + len(ufunc_inputs))
body += " sf_error.check_fpe(func_name)\n"
return name, body
def generate_fused_type(codes):
"""
Generate name of and cython code for a fused type.
Parameters
----------
typecodes : str
Valid inputs to CY_TYPES (i.e. f, d, g, ...).
"""
cytypes = [CY_TYPES[x] for x in codes]
name = codes + "_number_t"
declaration = ["ctypedef fused " + name + ":"]
for cytype in cytypes:
declaration.append(" " + cytype)
declaration = "\n".join(declaration)
return name, declaration
def generate_bench(name, codes):
tab = " "*4
top, middle, end = [], [], []
tmp = codes.split("*")
if len(tmp) > 1:
incodes = tmp[0]
outcodes = tmp[1]
else:
incodes = tmp[0]
outcodes = ""
inargs, inargs_and_types = [], []
for n, code in enumerate(incodes):
arg = "x{}".format(n)
inargs.append(arg)
inargs_and_types.append("{} {}".format(CY_TYPES[code], arg))
line = "def {{}}(int N, {}):".format(", ".join(inargs_and_types))
top.append(line)
top.append(tab + "cdef int n")
outargs = []
for n, code in enumerate(outcodes):
arg = "y{}".format(n)
outargs.append("&{}".format(arg))
line = "cdef {} {}".format(CY_TYPES[code], arg)
middle.append(tab + line)
end.append(tab + "for n in range(N):")
end.append(2*tab + "{}({})")
pyfunc = "_bench_{}_{}_{}".format(name, incodes, "py")
cyfunc = "_bench_{}_{}_{}".format(name, incodes, "cy")
pytemplate = "\n".join(top + end)
cytemplate = "\n".join(top + middle + end)
pybench = pytemplate.format(pyfunc, "_ufuncs." + name, ", ".join(inargs))
cybench = cytemplate.format(cyfunc, name, ", ".join(inargs + outargs))
return pybench, cybench
def generate_doc(name, specs):
tab = " "*4
doc = ["- :py:func:`~scipy.special.{}`::\n".format(name)]
for spec in specs:
incodes, outcodes = spec.split("->")
incodes = incodes.split("*")
intypes = list(map(lambda x: CY_TYPES[x], incodes[0]))
if len(incodes) > 1:
types = map(lambda x: "{} *".format(CY_TYPES[x]), incodes[1])
intypes.extend(types)
outtype = CY_TYPES[outcodes]
line = "{} {}({})".format(outtype, name, ", ".join(intypes))
doc.append(2*tab + line)
doc[-1] = "{}\n".format(doc[-1])
doc = "\n".join(doc)
return doc
def npy_cdouble_from_double_complex(var):
"""Cast a Cython double complex to a NumPy cdouble."""
res = "_complexstuff.npy_cdouble_from_double_complex({})".format(var)
return res
def double_complex_from_npy_cdouble(var):
"""Cast a NumPy cdouble to a Cython double complex."""
res = "_complexstuff.double_complex_from_npy_cdouble({})".format(var)
return res
def iter_variants(inputs, outputs):
"""
Generate variants of UFunc signatures, by changing variable types,
within the limitation that the corresponding C types casts still
work out.
This does not generate all possibilities, just the ones required
for the ufunc to work properly with the most common data types.
Parameters
----------
inputs, outputs : str
UFunc input and output signature strings
Yields
------
new_input, new_output : str
Modified input and output strings.
Also the original input/output pair is yielded.
"""
maps = [
# always use long instead of int (more common type on 64-bit)
('i', 'l'),
]
# float32-preserving signatures
if not ('i' in inputs or 'l' in inputs):
# Don't add float32 versions of ufuncs with integer arguments, as this
# can lead to incorrect dtype selection if the integer arguments are
# arrays, but float arguments are scalars.
# For instance sph_harm(0,[0],0,0).dtype == complex64
# This may be a NumPy bug, but we need to work around it.
# cf. gh-4895, https://github.com/numpy/numpy/issues/5895
maps = maps + [(a + 'dD', b + 'fF') for a, b in maps]
# do the replacements
for src, dst in maps:
new_inputs = inputs
new_outputs = outputs
for a, b in zip(src, dst):
new_inputs = new_inputs.replace(a, b)
new_outputs = new_outputs.replace(a, b)
yield new_inputs, new_outputs
class Func(object):
"""
Base class for Ufunc and FusedFunc.
"""
def __init__(self, name, signatures):
self.name = name
self.signatures = []
self.function_name_overrides = {}
for header in signatures.keys():
for name, sig in signatures[header].items():
inarg, outarg, ret = self._parse_signature(sig)
self.signatures.append((name, inarg, outarg, ret, header))
def _parse_signature(self, sig):
m = re.match(r"\s*([fdgFDGil]*)\s*\*\s*([fdgFDGil]*)\s*->\s*([*fdgFDGil]*)\s*$", sig)
if m:
inarg, outarg, ret = [x.strip() for x in m.groups()]
if ret.count('*') > 1:
raise ValueError("{}: Invalid signature: {}".format(self.name, sig))
return inarg, outarg, ret
m = re.match(r"\s*([fdgFDGil]*)\s*->\s*([fdgFDGil]?)\s*$", sig)
if m:
inarg, ret = [x.strip() for x in m.groups()]
return inarg, "", ret
raise ValueError("{}: Invalid signature: {}".format(self.name, sig))
def get_prototypes(self, nptypes_for_h=False):
prototypes = []
for func_name, inarg, outarg, ret, header in self.signatures:
ret = ret.replace('*', '')
c_args = ([C_TYPES[x] for x in inarg]
+ [C_TYPES[x] + ' *' for x in outarg])
cy_args = ([CY_TYPES[x] for x in inarg]
+ [CY_TYPES[x] + ' *' for x in outarg])
c_proto = "%s (*)(%s)" % (C_TYPES[ret], ", ".join(c_args))
if header.endswith("h") and nptypes_for_h:
cy_proto = c_proto + "nogil"
else:
cy_proto = "%s (*)(%s) nogil" % (CY_TYPES[ret], ", ".join(cy_args))
prototypes.append((func_name, c_proto, cy_proto, header))
return prototypes
def cython_func_name(self, c_name, specialized=False, prefix="_func_",
override=True):
# act on function name overrides
if override and c_name in self.function_name_overrides:
c_name = self.function_name_overrides[c_name]
prefix = ""
# support fused types
m = re.match(r'^(.*?)(\[.*\])$', c_name)
if m:
c_base_name, fused_part = m.groups()
else:
c_base_name, fused_part = c_name, ""
if specialized:
return "%s%s%s" % (prefix, c_base_name, fused_part.replace(' ', '_'))
else:
return "%s%s" % (prefix, c_base_name,)
class Ufunc(Func):
"""
Ufunc signature, restricted format suitable for special functions.
Parameters
----------
name
Name of the ufunc to create
signature
String of form 'func: fff*ff->f, func2: ddd->*i' describing
the C-level functions and types of their input arguments
and return values.
The syntax is 'function_name: inputparams*outputparams->output_retval*ignored_retval'
Attributes
----------
name : str
Python name for the Ufunc
signatures : list of (func_name, inarg_spec, outarg_spec, ret_spec, header_name)
List of parsed signatures
doc : str
Docstring, obtained from add_newdocs
function_name_overrides : dict of str->str
Overrides for the function names in signatures
"""
def __init__(self, name, signatures):
super(Ufunc, self).__init__(name, signatures)
self.doc = add_newdocs.get(name)
if self.doc is None:
raise ValueError("No docstring for ufunc %r" % name)
self.doc = textwrap.dedent(self.doc).strip()
def _get_signatures_and_loops(self, all_loops):
inarg_num = None
outarg_num = None
seen = set()
variants = []
def add_variant(func_name, inarg, outarg, ret, inp, outp):
if inp in seen:
return
seen.add(inp)
sig = (func_name, inp, outp)
if "v" in outp:
raise ValueError("%s: void signature %r" % (self.name, sig))
if len(inp) != inarg_num or len(outp) != outarg_num:
raise ValueError("%s: signature %r does not have %d/%d input/output args" % (
self.name, sig,
inarg_num, outarg_num))
loop_name, loop = generate_loop(inarg, outarg, ret, inp, outp)
all_loops[loop_name] = loop
variants.append((func_name, loop_name, inp, outp))
# First add base variants
for func_name, inarg, outarg, ret, header in self.signatures:
outp = re.sub(r'\*.*', '', ret) + outarg
ret = ret.replace('*', '')
if inarg_num is None:
inarg_num = len(inarg)
outarg_num = len(outp)
inp, outp = list(iter_variants(inarg, outp))[0]
add_variant(func_name, inarg, outarg, ret, inp, outp)
# Then the supplementary ones
for func_name, inarg, outarg, ret, header in self.signatures:
outp = re.sub(r'\*.*', '', ret) + outarg
ret = ret.replace('*', '')
for inp, outp in iter_variants(inarg, outp):
add_variant(func_name, inarg, outarg, ret, inp, outp)
# Then sort variants to input argument cast order
# -- the sort is stable, so functions earlier in the signature list
# are still preferred
variants.sort(key=lambda v: cast_order(v[2]))
return variants, inarg_num, outarg_num
def generate(self, all_loops):
toplevel = ""
variants, inarg_num, outarg_num = self._get_signatures_and_loops(all_loops)
loops = []
funcs = []
types = []
for func_name, loop_name, inputs, outputs in variants:
for x in inputs:
types.append(TYPE_NAMES[x])
for x in outputs:
types.append(TYPE_NAMES[x])
loops.append(loop_name)
funcs.append(func_name)
toplevel += "cdef np.PyUFuncGenericFunction ufunc_%s_loops[%d]\n" % (self.name, len(loops))
toplevel += "cdef void *ufunc_%s_ptr[%d]\n" % (self.name, 2*len(funcs))
toplevel += "cdef void *ufunc_%s_data[%d]\n" % (self.name, len(funcs))
toplevel += "cdef char ufunc_%s_types[%d]\n" % (self.name, len(types))
toplevel += 'cdef char *ufunc_%s_doc = (\n "%s")\n' % (
self.name,
self.doc.replace("\\", "\\\\").replace('"', '\\"').replace('\n', '\\n\"\n "')
)
for j, function in enumerate(loops):
toplevel += "ufunc_%s_loops[%d] = <np.PyUFuncGenericFunction>%s\n" % (self.name, j, function)
for j, type in enumerate(types):
toplevel += "ufunc_%s_types[%d] = <char>%s\n" % (self.name, j, type)
for j, func in enumerate(funcs):
toplevel += "ufunc_%s_ptr[2*%d] = <void*>%s\n" % (self.name, j,
self.cython_func_name(func, specialized=True))
toplevel += "ufunc_%s_ptr[2*%d+1] = <void*>(<char*>\"%s\")\n" % (self.name, j,
self.name)
for j, func in enumerate(funcs):
toplevel += "ufunc_%s_data[%d] = &ufunc_%s_ptr[2*%d]\n" % (
self.name, j, self.name, j)
toplevel += ('@ = np.PyUFunc_FromFuncAndData(ufunc_@_loops, '
'ufunc_@_data, ufunc_@_types, %d, %d, %d, 0, '
'"@", ufunc_@_doc, 0)\n' % (len(types)/(inarg_num+outarg_num),
inarg_num, outarg_num)
).replace('@', self.name)
return toplevel
class FusedFunc(Func):
"""
Generate code for a fused-type special function that can be
cimported in Cython.
"""
def __init__(self, name, signatures):
super(FusedFunc, self).__init__(name, signatures)
self.doc = "See the documentation for scipy.special." + self.name
# "codes" are the keys for CY_TYPES
self.incodes, self.outcodes = self._get_codes()
self.fused_types = set()
self.intypes, infused_types = self._get_types(self.incodes)
self.fused_types.update(infused_types)
self.outtypes, outfused_types = self._get_types(self.outcodes)
self.fused_types.update(outfused_types)
self.invars, self.outvars = self._get_vars()
def _get_codes(self):
inarg_num, outarg_num = None, None
all_inp, all_outp = [], []
for _, inarg, outarg, ret, _ in self.signatures:
outp = re.sub(r'\*.*', '', ret) + outarg
if inarg_num is None:
inarg_num = len(inarg)
outarg_num = len(outp)
inp, outp = list(iter_variants(inarg, outp))[0]
all_inp.append(inp)
all_outp.append(outp)
incodes = []
for n in range(inarg_num):
codes = unique(map(lambda x: x[n], all_inp))
codes.sort()
incodes.append(''.join(codes))
outcodes = []
for n in range(outarg_num):
codes = unique(map(lambda x: x[n], all_outp))
codes.sort()
outcodes.append(''.join(codes))
return tuple(incodes), tuple(outcodes)
def _get_types(self, codes):
all_types = []
fused_types = set()
for code in codes:
if len(code) == 1:
# It's not a fused type
all_types.append((CY_TYPES[code], code))
else:
# It's a fused type
fused_type, dec = generate_fused_type(code)
fused_types.add(dec)
all_types.append((fused_type, code))
return all_types, fused_types
def _get_vars(self):
invars = ["x{}".format(n) for n in range(len(self.intypes))]
outvars = ["y{}".format(n) for n in range(len(self.outtypes))]
return invars, outvars
def _get_conditional(self, types, codes, adverb):
"""Generate an if/elif/else clause that selects a specialization of
fused types.
"""
clauses = []
seen = set()
for (typ, typcode), code in zip(types, codes):
if len(typcode) == 1:
continue
if typ not in seen:
clauses.append("{} is {}".format(typ, underscore(CY_TYPES[code])))
seen.add(typ)
if clauses and adverb != "else":
line = "{} {}:".format(adverb, " and ".join(clauses))
elif clauses and adverb == "else":
line = "else:"
else:
line = None
return line
def _get_incallvars(self, intypes, c):
"""Generate pure input variables to a specialization,
i.e., variables that aren't used to return a value.
"""
incallvars = []
for n, intype in enumerate(intypes):
var = self.invars[n]
if c and intype == "double complex":
var = npy_cdouble_from_double_complex(var)
incallvars.append(var)
return incallvars
def _get_outcallvars(self, outtypes, c):
"""Generate output variables to a specialization,
i.e., pointers that are used to return values.
"""
outcallvars, tmpvars, casts = [], [], []
# If there are more out variables than out types, we want the
# tail of the out variables
start = len(self.outvars) - len(outtypes)
outvars = self.outvars[start:]
for n, (var, outtype) in enumerate(zip(outvars, outtypes)):
if c and outtype == "double complex":
tmp = "tmp{}".format(n)
tmpvars.append(tmp)
outcallvars.append("&{}".format(tmp))
tmpcast = double_complex_from_npy_cdouble(tmp)
casts.append("{}[0] = {}".format(var, tmpcast))
else:
outcallvars.append("{}".format(var))
return outcallvars, tmpvars, casts
def _get_nan_decs(self):
"""Set all variables to nan for specializations of fused types for
which don't have signatures.
"""
# Set non fused-type variables to nan
tab = " "*4
fused_types, lines = [], [tab + "else:"]
seen = set()
for outvar, outtype, code in zip(self.outvars, self.outtypes, self.outcodes):
if len(code) == 1:
line = "{}[0] = {}".format(outvar, NAN_VALUE[code])
lines.append(2*tab + line)
else:
fused_type = outtype
name, _ = fused_type
if name not in seen:
fused_types.append(fused_type)
seen.add(name)
if not fused_types:
return lines
# Set fused-type variables to nan
all_codes = tuple([codes for _unused, codes in fused_types])
codelens = list(map(lambda x: len(x), all_codes))
last = numpy.prod(codelens) - 1
for m, codes in enumerate(itertools.product(*all_codes)):
fused_codes, decs = [], []
for n, fused_type in enumerate(fused_types):
code = codes[n]
fused_codes.append(underscore(CY_TYPES[code]))
for nn, outvar in enumerate(self.outvars):
if self.outtypes[nn] == fused_type:
line = "{}[0] = {}".format(outvar, NAN_VALUE[code])
decs.append(line)
if m == 0:
adverb = "if"
elif m == last:
adverb = "else"
else:
adverb = "elif"
cond = self._get_conditional(fused_types, codes, adverb)
lines.append(2*tab + cond)
lines.extend(map(lambda x: 3*tab + x, decs))
return lines
def _get_tmp_decs(self, all_tmpvars):
"""Generate the declarations of any necessary temporary
variables.
"""
tab = " "*4
tmpvars = list(all_tmpvars)
tmpvars.sort()
tmpdecs = [tab + "cdef npy_cdouble {}".format(tmpvar)
for tmpvar in tmpvars]
return tmpdecs
def _get_python_wrap(self):
"""Generate a Python wrapper for functions which pass their
arguments as pointers.
"""
tab = " "*4
body, callvars = [], []
for (intype, _), invar in zip(self.intypes, self.invars):
callvars.append("{} {}".format(intype, invar))
line = "def _{}_pywrap({}):".format(self.name, ", ".join(callvars))
body.append(line)
for (outtype, _), outvar in zip(self.outtypes, self.outvars):
line = "cdef {} {}".format(outtype, outvar)
body.append(tab + line)
addr_outvars = map(lambda x: "&{}".format(x), self.outvars)
line = "{}({}, {})".format(self.name, ", ".join(self.invars),
", ".join(addr_outvars))
body.append(tab + line)
line = "return {}".format(", ".join(self.outvars))
body.append(tab + line)
body = "\n".join(body)
return body
def _get_common(self, signum, sig):
"""Generate code common to all the _generate_* methods."""
tab = " "*4
func_name, incodes, outcodes, retcode, header = sig
# Convert ints to longs; cf. iter_variants()
incodes = incodes.replace('i', 'l')
outcodes = outcodes.replace('i', 'l')
retcode = retcode.replace('i', 'l')
if header.endswith("h"):
c = True
else:
c = False
if header.endswith("++"):
cpp = True
else:
cpp = False
intypes = list(map(lambda x: CY_TYPES[x], incodes))
outtypes = list(map(lambda x: CY_TYPES[x], outcodes))
retcode = re.sub(r'\*.*', '', retcode)
if not retcode:
retcode = 'v'
rettype = CY_TYPES[retcode]
if cpp:
# Functions from _ufuncs_cxx are exported as a void*
# pointers; cast them to the correct types
func_name = "scipy.special._ufuncs_cxx._export_{}".format(func_name)
func_name = "(<{}(*)({}) nogil>{})"\
.format(rettype, ", ".join(intypes + outtypes), func_name)
else:
func_name = self.cython_func_name(func_name, specialized=True)
if signum == 0:
adverb = "if"
else:
adverb = "elif"
cond = self._get_conditional(self.intypes, incodes, adverb)
if cond:
lines = [tab + cond]
sp = 2*tab
else:
lines = []
sp = tab
return func_name, incodes, outcodes, retcode, \
intypes, outtypes, rettype, c, lines, sp
def _generate_from_return_and_no_outargs(self):
tab = " "*4
specs, body = [], []
for signum, sig in enumerate(self.signatures):
func_name, incodes, outcodes, retcode, intypes, outtypes, \
rettype, c, lines, sp = self._get_common(signum, sig)
body.extend(lines)
# Generate the call to the specialized function
callvars = self._get_incallvars(intypes, c)
call = "{}({})".format(func_name, ", ".join(callvars))
if c and rettype == "double complex":
call = double_complex_from_npy_cdouble(call)
line = sp + "return {}".format(call)
body.append(line)
sig = "{}->{}".format(incodes, retcode)
specs.append(sig)
if len(specs) > 1:
# Return nan for signatures without a specialization
body.append(tab + "else:")
outtype, outcodes = self.outtypes[0]
last = len(outcodes) - 1
if len(outcodes) == 1:
line = "return {}".format(NAN_VALUE[outcodes])
body.append(2*tab + line)
else:
for n, code in enumerate(outcodes):
if n == 0:
adverb = "if"
elif n == last:
adverb = "else"
else:
adverb = "elif"
cond = self._get_conditional(self.outtypes, code, adverb)
body.append(2*tab + cond)
line = "return {}".format(NAN_VALUE[code])
body.append(3*tab + line)
# Generate the head of the function
callvars, head = [], []
for n, (intype, _) in enumerate(self.intypes):
callvars.append("{} {}".format(intype, self.invars[n]))
(outtype, _) = self.outtypes[0]
dec = "cpdef {} {}({}) nogil".format(outtype, self.name, ", ".join(callvars))
head.append(dec + ":")
head.append(tab + '"""{}"""'.format(self.doc))
src = "\n".join(head + body)
return dec, src, specs
def _generate_from_outargs_and_no_return(self):
tab = " "*4
all_tmpvars = set()
specs, body = [], []
for signum, sig in enumerate(self.signatures):
func_name, incodes, outcodes, retcode, intypes, outtypes, \
rettype, c, lines, sp = self._get_common(signum, sig)
body.extend(lines)
# Generate the call to the specialized function
callvars = self._get_incallvars(intypes, c)
outcallvars, tmpvars, casts = self._get_outcallvars(outtypes, c)
callvars.extend(outcallvars)
all_tmpvars.update(tmpvars)
call = "{}({})".format(func_name, ", ".join(callvars))
body.append(sp + call)
body.extend(map(lambda x: sp + x, casts))
if len(outcodes) == 1:
sig = "{}->{}".format(incodes, outcodes)
specs.append(sig)
else:
sig = "{}*{}->v".format(incodes, outcodes)
specs.append(sig)
if len(specs) > 1:
lines = self._get_nan_decs()
body.extend(lines)
if len(self.outvars) == 1:
line = "return {}[0]".format(self.outvars[0])
body.append(tab + line)
# Generate the head of the function
callvars, head = [], []
for invar, (intype, _) in zip(self.invars, self.intypes):
callvars.append("{} {}".format(intype, invar))
if len(self.outvars) > 1:
for outvar, (outtype, _) in zip(self.outvars, self.outtypes):
callvars.append("{} *{}".format(outtype, outvar))
if len(self.outvars) == 1:
outtype, _ = self.outtypes[0]
dec = "cpdef {} {}({}) nogil".format(outtype, self.name, ", ".join(callvars))
else:
dec = "cdef void {}({}) nogil".format(self.name, ", ".join(callvars))
head.append(dec + ":")
head.append(tab + '"""{}"""'.format(self.doc))
if len(self.outvars) == 1:
outvar = self.outvars[0]
outtype, _ = self.outtypes[0]
line = "cdef {} {}".format(outtype, outvar)
head.append(tab + line)
head.extend(self._get_tmp_decs(all_tmpvars))
src = "\n".join(head + body)
return dec, src, specs
def _generate_from_outargs_and_return(self):
tab = " "*4
all_tmpvars = set()
specs, body = [], []
for signum, sig in enumerate(self.signatures):
func_name, incodes, outcodes, retcode, intypes, outtypes, \
rettype, c, lines, sp = self._get_common(signum, sig)
body.extend(lines)
# Generate the call to the specialized function
callvars = self._get_incallvars(intypes, c)
outcallvars, tmpvars, casts = self._get_outcallvars(outtypes, c)
callvars.extend(outcallvars)
all_tmpvars.update(tmpvars)
call = "{}({})".format(func_name, ", ".join(callvars))
if c and rettype == "double complex":
call = double_complex_from_npy_cdouble(call)
call = "{}[0] = {}".format(self.outvars[0], call)
body.append(sp + call)
body.extend(map(lambda x: sp + x, casts))
sig = "{}*{}->v".format(incodes, outcodes + retcode)
specs.append(sig)
if len(specs) > 1:
lines = self._get_nan_decs()
body.extend(lines)
# Generate the head of the function
callvars, head = [], []
for invar, (intype, _) in zip(self.invars, self.intypes):
callvars.append("{} {}".format(intype, invar))
for outvar, (outtype, _) in zip(self.outvars, self.outtypes):
callvars.append("{} *{}".format(outtype, outvar))
dec = "cdef void {}({}) nogil".format(self.name, ", ".join(callvars))
head.append(dec + ":")
head.append(tab + '"""{}"""'.format(self.doc))
head.extend(self._get_tmp_decs(all_tmpvars))
src = "\n".join(head + body)
return dec, src, specs
def generate(self):
_, _, outcodes, retcode, _ = self.signatures[0]
retcode = re.sub(r'\*.*', '', retcode)
if not retcode:
retcode = 'v'
if len(outcodes) == 0 and retcode != 'v':
dec, src, specs = self._generate_from_return_and_no_outargs()
elif len(outcodes) > 0 and retcode == 'v':
dec, src, specs = self._generate_from_outargs_and_no_return()
elif len(outcodes) > 0 and retcode != 'v':
dec, src, specs = self._generate_from_outargs_and_return()
else:
raise ValueError("Invalid signature")
if len(self.outvars) > 1:
wrap = self._get_python_wrap()
else:
wrap = None
return dec, src, specs, self.fused_types, wrap
def get_declaration(ufunc, c_name, c_proto, cy_proto, header, proto_h_filename):
"""
Construct a Cython declaration of a function coming either from a
pxd or a header file. Do sufficient tricks to enable compile-time
type checking against the signature expected by the ufunc.
"""
defs = []
defs_h = []
var_name = c_name.replace('[', '_').replace(']', '_').replace(' ', '_')
if header.endswith('.pxd'):
defs.append("from .%s cimport %s as %s" % (
header[:-4], ufunc.cython_func_name(c_name, prefix=""),
ufunc.cython_func_name(c_name)))
# check function signature at compile time
proto_name = '_proto_%s_t' % var_name
defs.append("ctypedef %s" % (cy_proto.replace('(*)', proto_name)))
defs.append("cdef %s *%s_var = &%s" % (
proto_name, proto_name, ufunc.cython_func_name(c_name, specialized=True)))
else:
# redeclare the function, so that the assumed
# signature is checked at compile time
new_name = "%s \"%s\"" % (ufunc.cython_func_name(c_name), c_name)
defs.append("cdef extern from \"%s\":" % proto_h_filename)
defs.append(" cdef %s" % (cy_proto.replace('(*)', new_name)))
defs_h.append("#include \"%s\"" % header)
defs_h.append("%s;" % (c_proto.replace('(*)', c_name)))
return defs, defs_h, var_name
def generate_ufuncs(fn_prefix, cxx_fn_prefix, ufuncs):
filename = fn_prefix + ".pyx"
proto_h_filename = fn_prefix + '_defs.h'
cxx_proto_h_filename = cxx_fn_prefix + '_defs.h'
cxx_pyx_filename = cxx_fn_prefix + ".pyx"
cxx_pxd_filename = cxx_fn_prefix + ".pxd"
toplevel = ""
# for _ufuncs*
defs = []
defs_h = []
all_loops = {}
# for _ufuncs_cxx*
cxx_defs = []
cxx_pxd_defs = [
"from . cimport sf_error",
"cdef void _set_action(sf_error.sf_error_t, sf_error.sf_action_t) nogil"
]
cxx_defs_h = []
ufuncs.sort(key=lambda u: u.name)
for ufunc in ufuncs:
# generate function declaration and type checking snippets
cfuncs = ufunc.get_prototypes()
for c_name, c_proto, cy_proto, header in cfuncs:
if header.endswith('++'):
header = header[:-2]
# for the CXX module
item_defs, item_defs_h, var_name = get_declaration(ufunc, c_name, c_proto, cy_proto,
header, cxx_proto_h_filename)
cxx_defs.extend(item_defs)
cxx_defs_h.extend(item_defs_h)
cxx_defs.append("cdef void *_export_%s = <void*>%s" % (
var_name, ufunc.cython_func_name(c_name, specialized=True, override=False)))
cxx_pxd_defs.append("cdef void *_export_%s" % (var_name,))
# let cython grab the function pointer from the c++ shared library
ufunc.function_name_overrides[c_name] = "scipy.special._ufuncs_cxx._export_" + var_name
else:
# usual case
item_defs, item_defs_h, _ = get_declaration(ufunc, c_name, c_proto, cy_proto, header,
proto_h_filename)
defs.extend(item_defs)
defs_h.extend(item_defs_h)
# ufunc creation code snippet
t = ufunc.generate(all_loops)
toplevel += t + "\n"
# Produce output
toplevel = "\n".join(sorted(all_loops.values()) + defs + [toplevel])
# Generate an `__all__` for the module
all_ufuncs = (
[
"'{}'".format(ufunc.name)
for ufunc in ufuncs if not ufunc.name.startswith('_')
]
+ ["'geterr'", "'seterr'", "'errstate'", "'jn'"]
)
module_all = '__all__ = [{}]'.format(', '.join(all_ufuncs))
with open(filename, 'w') as f:
f.write(UFUNCS_EXTRA_CODE_COMMON)
f.write(UFUNCS_EXTRA_CODE)
f.write(module_all)
f.write("\n")
f.write(toplevel)
f.write(UFUNCS_EXTRA_CODE_BOTTOM)
defs_h = unique(defs_h)
with open(proto_h_filename, 'w') as f:
f.write("#ifndef UFUNCS_PROTO_H\n#define UFUNCS_PROTO_H 1\n")
f.write("\n".join(defs_h))
f.write("\n#endif\n")
cxx_defs_h = unique(cxx_defs_h)
with open(cxx_proto_h_filename, 'w') as f:
f.write("#ifndef UFUNCS_PROTO_H\n#define UFUNCS_PROTO_H 1\n")
f.write("\n".join(cxx_defs_h))
f.write("\n#endif\n")
with open(cxx_pyx_filename, 'w') as f:
f.write(UFUNCS_EXTRA_CODE_COMMON)
f.write("\n")
f.write("\n".join(cxx_defs))
f.write("\n# distutils: language = c++\n")
with open(cxx_pxd_filename, 'w') as f:
f.write("\n".join(cxx_pxd_defs))
def generate_fused_funcs(modname, ufunc_fn_prefix, fused_funcs):
pxdfile = modname + ".pxd"
pyxfile = modname + ".pyx"
proto_h_filename = ufunc_fn_prefix + '_defs.h'
sources = []
declarations = []
# Code for benchmarks
bench_aux = []
fused_types = set()
# Parameters for the tests
doc = []
defs = []
for func in fused_funcs:
if func.name.startswith("_"):
# Don't try to deal with functions that have extra layers
# of wrappers.
continue
# Get the function declaration for the .pxd and the source
# code for the .pyx
dec, src, specs, func_fused_types, wrap = func.generate()
declarations.append(dec)
sources.append(src)
if wrap:
sources.append(wrap)
fused_types.update(func_fused_types)
# Declare the specializations
cfuncs = func.get_prototypes(nptypes_for_h=True)
for c_name, c_proto, cy_proto, header in cfuncs:
if header.endswith('++'):
# We grab the c++ functions from the c++ module
continue
item_defs, _, _ = get_declaration(func, c_name, c_proto,
cy_proto, header,
proto_h_filename)
defs.extend(item_defs)
# Add a line to the documentation
doc.append(generate_doc(func.name, specs))
# Generate code for benchmarks
if func.name in CYTHON_SPECIAL_BENCHFUNCS:
for codes in CYTHON_SPECIAL_BENCHFUNCS[func.name]:
pybench, cybench = generate_bench(func.name, codes)
bench_aux.extend([pybench, cybench])
fused_types = list(fused_types)
fused_types.sort()
with open(pxdfile, 'w') as f:
f.write(CYTHON_SPECIAL_PXD)
f.write("\n")
f.write("\n\n".join(fused_types))
f.write("\n\n")
f.write("\n".join(declarations))
with open(pyxfile, 'w') as f:
header = CYTHON_SPECIAL_PYX
header = header.replace("FUNCLIST", "\n".join(doc))
f.write(header)
f.write("\n")
f.write("\n".join(defs))
f.write("\n\n")
f.write("\n\n".join(sources))
f.write("\n\n")
f.write("\n\n".join(bench_aux))
def generate_ufuncs_type_stubs(module_name: str, ufuncs: List[Ufunc]):
stubs, module_all = [], []
for ufunc in ufuncs:
stubs.append(f'{ufunc.name}: np.ufunc')
if not ufunc.name.startswith('_'):
module_all.append(f"'{ufunc.name}'")
# jn is an alias for jv.
module_all.append("'jn'")
stubs.append('jn: np.ufunc')
module_all.sort()
stubs.sort()
contents = STUBS.format(
ALL=',\n '.join(module_all),
STUBS='\n'.join(stubs),
)
stubs_file = f'{module_name}.pyi'
with open(stubs_file, 'w') as f:
f.write(contents)
def unique(lst):
"""
Return a list without repeated entries (first occurrence is kept),
preserving order.
"""
seen = set()
new_lst = []
for item in lst:
if item in seen:
continue
seen.add(item)
new_lst.append(item)
return new_lst
def all_newer(src_files, dst_files):
from distutils.dep_util import newer
return all(os.path.exists(dst) and newer(dst, src)
for dst in dst_files for src in src_files)
def main():
p = optparse.OptionParser(usage=(__doc__ or '').strip())
options, args = p.parse_args()
if len(args) != 0:
p.error('invalid number of arguments')
pwd = os.path.dirname(__file__)
src_files = (os.path.abspath(__file__),
os.path.abspath(os.path.join(pwd, 'functions.json')),
os.path.abspath(os.path.join(pwd, 'add_newdocs.py')))
dst_files = ('_ufuncs.pyx',
'_ufuncs_defs.h',
'_ufuncs_cxx.pyx',
'_ufuncs_cxx.pxd',
'_ufuncs_cxx_defs.h',
'_ufuncs.pyi',
'cython_special.pyx',
'cython_special.pxd')
os.chdir(BASE_DIR)
if all_newer(src_files, dst_files):
print("scipy/special/_generate_pyx.py: all files up-to-date")
return
ufuncs, fused_funcs = [], []
with open('functions.json') as data:
functions = json.load(data)
for f, sig in functions.items():
ufuncs.append(Ufunc(f, sig))
fused_funcs.append(FusedFunc(f, sig))
generate_ufuncs("_ufuncs", "_ufuncs_cxx", ufuncs)
generate_ufuncs_type_stubs("_ufuncs", ufuncs)
generate_fused_funcs("cython_special", "_ufuncs", fused_funcs)
if __name__ == "__main__":
main()
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