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import os
import sys
from bento.commands import hooks
import waflib
import waflib.Errors
from waflib.Task \
import \
Task
waflib.Logs.verbose = 1
# Importing this adds new checkers to waf configure context - I don't like this
# way of working, should find a more explicit way to attach new functions to
# context.
import numpy.build_utils.waf
from code_generators.numpy_api \
import \
multiarray_api, ufunc_api
from code_generators import generate_numpy_api, generate_ufunc_api, \
generate_umath
from setup_common \
import \
OPTIONAL_STDFUNCS_MAYBE, OPTIONAL_STDFUNCS, C99_FUNCS_EXTENDED, \
C99_FUNCS_SINGLE, C99_COMPLEX_TYPES, C99_COMPLEX_FUNCS, \
MANDATORY_FUNCS, C_ABI_VERSION, C_API_VERSION
ENABLE_SEPARATE_COMPILATION = (os.environ.get('NPY_SEPARATE_COMPILATION', "1") != "0")
NPY_RELAXED_STRIDES_CHECKING = (os.environ.get('NPY_RELAXED_STRIDES_CHECKING', "0") != "0")
NUMPYCONFIG_SYM = []
# FIXME
if ENABLE_SEPARATE_COMPILATION:
NUMPYCONFIG_SYM.append(('DEFINE_NPY_ENABLE_SEPARATE_COMPILATION', '#define NPY_ENABLE_SEPARATE_COMPILATION 1'))
else:
NUMPYCONFIG_SYM.append(('DEFINE_NPY_ENABLE_SEPARATE_COMPILATION', ''))
if NPY_RELAXED_STRIDES_CHECKING:
NUMPYCONFIG_SYM.append(('DEFINE_NPY_RELAXED_STRIDES_CHECKING', '#define NPY_RELAXED_STRIDES_CHECKING 1'))
else:
NUMPYCONFIG_SYM.append(('DEFINE_NPY_RELAXED_STRIDES_CHECKING', ''))
NUMPYCONFIG_SYM.append(('VISIBILITY_HIDDEN', '__attribute__((visibility("hidden")))'))
NUMPYCONFIG_SYM.append(('NPY_ABI_VERSION', '0x%.8X' % C_ABI_VERSION))
NUMPYCONFIG_SYM.append(('NPY_API_VERSION', '0x%.8X' % C_API_VERSION))
global PYTHON_HAS_UNICODE_WIDE
def is_npy_no_signal():
"""Return True if the NPY_NO_SIGNAL symbol must be defined in configuration
header."""
return sys.platform == 'win32'
def define_no_smp():
"""Returns True if we should define NPY_NOSMP, False otherwise."""
#--------------------------------
# Checking SMP and thread options
#--------------------------------
# Python 2.3 causes a segfault when
# trying to re-acquire the thread-state
# which is done in error-handling
# ufunc code. NPY_ALLOW_C_API and friends
# cause the segfault. So, we disable threading
# for now.
if sys.version[:5] < '2.4.2':
nosmp = 1
else:
# Perhaps a fancier check is in order here.
# so that threads are only enabled if there
# are actually multiple CPUS? -- but
# threaded code can be nice even on a single
# CPU so that long-calculating code doesn't
# block.
try:
nosmp = os.environ['NPY_NOSMP']
nosmp = 1
except KeyError:
nosmp = 0
return nosmp == 1
def write_numpy_config(conf):
subst_dict = {}
for key, value in NUMPYCONFIG_SYM:
subst_dict["@%s@" % key] = str(value)
node = conf.path.find_node("include/numpy/_numpyconfig.h.in")
cnt = node.read()
for k, v in subst_dict.items():
cnt = cnt.replace(k, v)
assert node is not None
onode = conf.bldnode.make_node(node.path_from(conf.srcnode)).change_ext("")
onode.write(cnt)
def write_numpy_inifiles(conf):
subst_dict = dict([("@sep@", os.path.sep), ("@pkgname@", "numpy.core")])
for inifile in ["mlib.ini.in", "npymath.ini.in"]:
node = conf.path.find_node(inifile)
cnt = node.read()
for k, v in subst_dict.items():
cnt = cnt.replace(k, v)
assert node is not None
outfile = os.path.join("lib", "npy-pkg-config", inifile)
onode = conf.bldnode.make_node(node.path_from(conf.srcnode).replace(
inifile, outfile)).change_ext("")
onode.write(cnt)
def type_checks(conf):
header_name = "Python.h"
features = "c pyext"
for c_type in ("int", "long", "short"):
macro_name = "SIZEOF_%s" % numpy.build_utils.waf.sanitize_string(c_type)
conf.check_declaration(macro_name, header_name=header_name,
features=features)
NUMPYCONFIG_SYM.append((macro_name, macro_name))
for c_type, e_size in (("float", 4), ("double", 8), ("long double", [12, 16])):
macro_name = "SIZEOF_%s" % numpy.build_utils.waf.sanitize_string(c_type)
size = conf.check_type_size(c_type, header_name=header_name,
features=features, expected_sizes=e_size)
NUMPYCONFIG_SYM.append((macro_name, str(size)))
macro_name = "SIZEOF_COMPLEX_%s" % numpy.build_utils.waf.sanitize_string(c_type)
complex_def = "struct {%s __x; %s __y;}" % (c_type, c_type)
size = conf.check_type_size(complex_def, header_name=header_name,
features=features, expected_sizes=2*size)
NUMPYCONFIG_SYM.append((macro_name, str(size)))
if sys.platform != 'darwin':
conf.check_ldouble_representation()
size = conf.check_type_size("Py_intptr_t", header_name=header_name,
expected_sizes=[4, 8], features=features)
NUMPYCONFIG_SYM.append(('SIZEOF_%s' % numpy.build_utils.waf.sanitize_string("Py_intptr_t"),
'%d' % size))
# We check declaration AND type because that's how distutils does it.
try:
conf.check_declaration("PY_LONG_LONG", header_name=header_name,
features=features)
size = conf.check_type_size("PY_LONG_LONG", header_name=header_name,
features=features, expected_sizes=[4, 8])
NUMPYCONFIG_SYM.append(("DEFINE_NPY_SIZEOF_LONGLONG",
"#define NPY_SIZEOF_LONGLONG %d" % size))
NUMPYCONFIG_SYM.append(("DEFINE_NPY_SIZEOF_PY_LONG_LONG",
"#define NPY_SIZEOF_PY_LONG_LONG %d" % size))
except waflib.Errors.ConfigurationError:
NUMPYCONFIG_SYM.append(("DEFINE_NPY_SIZEOF_LONGLONG", ""))
NUMPYCONFIG_SYM.append(("DEFINE_NPY_SIZEOF_PY_LONG_LONG", ""))
conf.check_declaration("CHAR_BIT", header_name=header_name, features=features)
# Check whether we need our own wide character support
global PYTHON_HAS_UNICODE_WIDE
try:
conf.check_declaration('Py_UNICODE_WIDE', header_name=header_name, features=features)
PYTHON_HAS_UNICODE_WIDE = False
except waflib.Errors.ConfigurationError:
PYTHON_HAS_UNICODE_WIDE = True
try:
conf.check_declaration('PyOS_ascii_strtod', header_name=header_name, features=features)
except waflib.Errors.ConfigurationError:
try:
conf.check_func('strtod')
conf.define('PyOS_ascii_strtod', 'strtod')
except waflib.Errors.ConfigurationError:
pass
def signal_smp_checks(conf):
if is_npy_no_signal():
NUMPYCONFIG_SYM.append(("DEFINE_NPY_NO_SIGNAL", "#define NPY_NO_SIGNAL\n"))
conf.define("__NPY_PRIVATE_NO_SIGNAL", 1)
else:
NUMPYCONFIG_SYM.append(("DEFINE_NPY_NO_SIGNAL", ""))
if define_no_smp():
NUMPYCONFIG_SYM.append(("NPY_NO_SMP", 1))
else:
NUMPYCONFIG_SYM.append(("NPY_NO_SMP", 0))
def check_math_runtime(conf):
header_name = "Python.h math.h"
features = "c cprogram pyext"
mlibs = [None, "m", "cpml"]
mathlib = os.environ.get('MATHLIB')
if mathlib:
mlibs.insert(0, mathlib)
mlib = None
for lib in mlibs:
try:
if lib is None:
kw = {}
else:
kw = {"lib": lib}
st = conf.check_functions_at_once(["exp"], uselib_store="M", **kw)
mlib = lib or []
break
except waflib.Errors.ConfigurationError:
pass
if mlib is None:
raise waflib.Errors.ConfigurationError("No math lib found !")
# XXX: this is ugly: mathlib has nothing to do in a public header file
NUMPYCONFIG_SYM.append(('MATHLIB', ','.join(mlib)))
# FIXME: look more into those additional mandatory functions
MANDATORY_FUNCS.extend(["pow"])
conf.check_functions_at_once(MANDATORY_FUNCS, use="M")
#mfuncs = ('expl', 'expf', 'log1p', 'expm1', 'asinh', 'atanhf', 'atanhl',
# 'rint', 'trunc')
#conf.check_functions_at_once(mfuncs, use="M")
header_name = "Python.h math.h"
# XXX: with MSVC compiler, one needs to have cprogram defined. Find out why.
features = "c pyext cprogram"
for f in OPTIONAL_STDFUNCS_MAYBE:
try:
conf.check_declaration("HAVE_%s" % numpy.build_utils.waf.sanitize_string(f),
header_name=header_name,
features=features)
OPTIONAL_STDFUNCS.remove(f)
except waflib.Errors.ConfigurationError:
pass
conf.check_functions_at_once(OPTIONAL_STDFUNCS,
features=features, mandatory=False, use="M")
conf.check_functions_at_once(C99_FUNCS_SINGLE,
features=features, mandatory=False, use="M")
conf.check_functions_at_once(C99_FUNCS_EXTENDED,
features=features, mandatory=False, use="M")
for f in ["isnan", "isinf", "signbit", "isfinite"]:
try:
conf.check_declaration("HAVE_DECL_%s" % f.upper(), header_name=header_name,
features=features)
NUMPYCONFIG_SYM.append(('DEFINE_NPY_HAVE_DECL_%s' % f.upper(),
'#define NPY_HAVE_DECL_%s' % f.upper()))
except waflib.Errors.ConfigurationError:
try:
conf.check_declaration(f, header_name=header_name, features=features)
NUMPYCONFIG_SYM.append(('DEFINE_NPY_HAVE_DECL_%s' % f.upper(),
'#define NPY_HAVE_DECL_%s' % f.upper()))
except waflib.Errors.ConfigurationError:
NUMPYCONFIG_SYM.append(('DEFINE_NPY_HAVE_DECL_%s' % f.upper(), ''))
def check_complex(conf):
if conf.check_header("complex.h", mandatory=False):
NUMPYCONFIG_SYM.append(('DEFINE_NPY_USE_C99_COMPLEX',
'#define NPY_USE_C99_COMPLEX 1'))
for t in C99_COMPLEX_TYPES:
try:
conf.check_type(t, header_name='complex.h')
NUMPYCONFIG_SYM.append(('DEFINE_NPY_HAVE_%s' % numpy.build_utils.waf.sanitize_string(t),
'#define NPY_HAVE_%s' % numpy.build_utils.waf.sanitize_string(t)))
except waflib.Errors.ConfigurationError:
NUMPYCONFIG_SYM.append(('DEFINE_NPY_HAVE_%s' % numpy.build_utils.waf.sanitize_string(t), ''))
for prec in ["", "f", "l"]:
flist = [f + prec for f in C99_COMPLEX_FUNCS]
conf.check_functions_at_once(flist, use="M")
else:
NUMPYCONFIG_SYM.append(('DEFINE_NPY_USE_C99_COMPLEX', ''))
for t in C99_COMPLEX_TYPES:
NUMPYCONFIG_SYM.append(('DEFINE_NPY_HAVE_%s' % numpy.build_utils.waf.sanitize_string(t), ''))
def check_win32_specifics(conf):
from numpy.distutils.misc_util import get_build_architecture
arch = get_build_architecture()
# On win32, force long double format string to be 'g', not
# 'Lg', since the MS runtime does not support long double whose
# size is > sizeof(double)
if arch == "Intel" or arch == "AMD64":
conf.define('FORCE_NO_LONG_DOUBLE_FORMATTING', 1)
@hooks.post_configure
def post_configure(context):
conf = context.waf_context
try:
conf.check_header("endian.h")
NUMPYCONFIG_SYM.append(('DEFINE_NPY_HAVE_ENDIAN_H',
'#define NPY_HAVE_ENDIAN_H 1'))
except waflib.Errors.ConfigurationError:
NUMPYCONFIG_SYM.append(('DEFINE_NPY_HAVE_ENDIAN_H', ''))
try:
conf.check_declaration('PRIdPTR', header_name='inttypes.h')
NUMPYCONFIG_SYM.append(('DEFINE_NPY_USE_C99_FORMATS', '#define NPY_USE_C99_FORMATS 1'))
except waflib.Errors.ConfigurationError:
NUMPYCONFIG_SYM.append(('DEFINE_NPY_USE_C99_FORMATS', ''))
type_checks(conf)
signal_smp_checks(conf)
check_math_runtime(conf)
numpy.build_utils.waf.check_inline(conf)
check_complex(conf)
check_win32_specifics(conf)
if ENABLE_SEPARATE_COMPILATION:
conf.define("ENABLE_SEPARATE_COMPILATION", 1)
conf.env["CONFIG_HEADER_TEMPLATE"] = """\
%(content)s
#ifndef _NPY_NPY_CONFIG_H_
#error config.h should never be included directly, include npy_config.h instead
#endif"""
conf.write_config_header("config.h")
write_numpy_config(conf)
write_numpy_inifiles(conf)
conf.env.INCLUDES = [".", "include", "include/numpy"]
# FIXME: Should be handled in bento context
conf.store()
class numpy_api_generator(Task):
vars = ["API_TUPLE"]
color = "BLUE"
before = ["c"]
def run(self):
targets = [o.path_from(self.generator.bld.srcnode) for o in self.outputs]
generate_numpy_api.do_generate_api(targets, self.env.API_TUPLE)
return 0
class ufunc_api_generator(Task):
vars = ["API_TUPLE"]
color = "BLUE"
before = ["c"]
def run(self):
targets = [o.path_from(self.generator.bld.srcnode) for o in self.outputs]
generate_ufunc_api.do_generate_api(targets, self.env.API_TUPLE)
return 0
@waflib.TaskGen.feature("numpy_api_gen")
def process_multiarray_api_generator(self):
tsk = self.create_task("numpy_api_generator")
if hasattr(self, "api_tuple"):
tsk.env.API_TUPLE = self.api_tuple
else:
if not "API_TUPLE" in tsk.env:
tsk.env.API_TUPLE = ()
header = "__%s.h" % self.pattern
source = "__%s.c" % self.pattern
txt = self.pattern + ".txt"
files = [header, source, txt]
tsk.set_outputs([self.path.find_or_declare(f) for f in files])
self.bld.register_outputs("numpy_gen_headers", "multiarray",
[output for output in tsk.outputs if output.suffix() == ".h"],
target_dir="$sitedir/numpy/core/include/numpy")
return tsk
@waflib.TaskGen.feature("ufunc_api_gen")
def process_api_ufunc_generator(self):
tsk = self.create_task("ufunc_api_generator")
if hasattr(self, "api_tuple"):
tsk.env.API_TUPLE = self.api_tuple
else:
if not "API_TUPLE" in tsk.env:
tsk.env.API_TUPLE = ()
header = "__%s.h" % self.pattern
source = "__%s.c" % self.pattern
txt = self.pattern + ".txt"
files = [header, source, txt]
tsk.set_outputs([self.path.find_or_declare(f) for f in files])
headers = [output for output in tsk.outputs if output.suffix() == ".h"]
self.bld.register_outputs("numpy_gen_headers", "ufunc", headers,
target_dir="$sitedir/numpy/core/include/numpy")
return tsk
class umath_generator(Task):
vars = ["API_TUPLE"]
color = "BLUE"
before = ["c"]
ext_in = ".in"
def run(self):
if len(self.outputs) > 1:
raise ValueError("Only one target (the .c file) is expected in the umath generator task")
code = generate_umath.make_code(generate_umath.defdict, generate_umath.__file__)
self.outputs[0].write(code)
return 0
@waflib.TaskGen.feature("umath_gen")
def process_umath_generator(self):
tsk = self.create_task("umath_generator")
source = "__%s.c" % self.pattern
tsk.set_outputs(self.path.find_or_declare(source))
return tsk
from os.path import join as pjoin
@hooks.pre_build
def pre_build(context):
bld = context.waf_context
context.register_category("numpy_gen_inifiles")
inifile_mlib = context.local_node.declare(os.path.join(
"lib", "npy-pkg-config", "mlib.ini"))
inifile_npymath = context.local_node.declare(os.path.join(
"lib", "npy-pkg-config", "npymath.ini"))
context.register_outputs("numpy_gen_inifiles", "numpyconfig",
[inifile_mlib, inifile_npymath])
context.register_category("numpy_gen_headers")
numpyconfig_h = context.local_node.declare(os.path.join("include", "numpy", "_numpyconfig.h"))
context.register_outputs("numpy_gen_headers", "numpyconfig", [numpyconfig_h])
context.tweak_library("lib/npymath", includes=["src/private", "src/npymath", "include"])
context.tweak_library("npysort",
includes=[".", "src/private", "src/npysort"],
use="npymath")
def builder_multiarray(extension):
bld(name="multiarray_api",
features="numpy_api_gen",
api_tuple=multiarray_api,
pattern="multiarray_api")
multiarray_templates = ["src/multiarray/scalartypes.c.src",
"src/multiarray/arraytypes.c.src",
"src/multiarray/nditer_templ.c.src",
"src/multiarray/lowlevel_strided_loops.c.src",
"src/multiarray/einsum.c.src"]
bld(target="multiarray_templates", source=multiarray_templates)
if ENABLE_SEPARATE_COMPILATION:
sources = [pjoin('src', 'multiarray', 'arrayobject.c'),
pjoin('src', 'multiarray', 'arraytypes.c.src'),
pjoin('src', 'multiarray', 'array_assign.c'),
pjoin('src', 'multiarray', 'array_assign_array.c'),
pjoin('src', 'multiarray', 'array_assign_scalar.c'),
pjoin('src', 'multiarray', 'buffer.c'),
pjoin('src', 'multiarray', 'calculation.c'),
pjoin('src', 'multiarray', 'common.c'),
pjoin('src', 'multiarray', 'conversion_utils.c'),
pjoin('src', 'multiarray', 'convert.c'),
pjoin('src', 'multiarray', 'convert_datatype.c'),
pjoin('src', 'multiarray', 'ctors.c'),
pjoin('src', 'multiarray', 'datetime.c'),
pjoin('src', 'multiarray', 'datetime_busday.c'),
pjoin('src', 'multiarray', 'datetime_busdaycal.c'),
pjoin('src', 'multiarray', 'datetime_strings.c'),
pjoin('src', 'multiarray', 'descriptor.c'),
pjoin('src', 'multiarray', 'dtype_transfer.c'),
pjoin('src', 'multiarray', 'einsum.c.src'),
pjoin('src', 'multiarray', 'flagsobject.c'),
pjoin('src', 'multiarray', 'getset.c'),
pjoin('src', 'multiarray', 'hashdescr.c'),
pjoin('src', 'multiarray', 'item_selection.c'),
pjoin('src', 'multiarray', 'iterators.c'),
pjoin('src', 'multiarray', 'lowlevel_strided_loops.c.src'),
pjoin('src', 'multiarray', 'mapping.c'),
pjoin('src', 'multiarray', 'methods.c'),
pjoin('src', 'multiarray', 'multiarraymodule.c'),
pjoin('src', 'multiarray', 'nditer_templ.c.src'),
pjoin('src', 'multiarray', 'nditer_api.c'),
pjoin('src', 'multiarray', 'nditer_constr.c'),
pjoin('src', 'multiarray', 'nditer_pywrap.c'),
pjoin('src', 'multiarray', 'number.c'),
pjoin('src', 'multiarray', 'numpymemoryview.c'),
pjoin('src', 'multiarray', 'numpyos.c'),
pjoin('src', 'multiarray', 'refcount.c'),
pjoin('src', 'multiarray', 'scalarapi.c'),
pjoin('src', 'multiarray', 'scalartypes.c.src'),
pjoin('src', 'multiarray', 'sequence.c'),
pjoin('src', 'multiarray', 'shape.c'),
pjoin('src', 'multiarray', 'ucsnarrow.c'),
pjoin('src', 'multiarray', 'usertypes.c')]
else:
sources = extension.sources
includes = ["src/multiarray", "src/private"]
return context.default_builder(extension,
includes=includes,
source=sources,
use="npysort npymath")
context.register_builder("multiarray", builder_multiarray)
def build_ufunc(extension):
bld(features="ufunc_api_gen",
api_tuple=ufunc_api,
pattern="ufunc_api",
name="ufunc_api")
ufunc_templates = [
"src/umath/loops.c.src",
"src/umath/funcs.inc.src",
"src/umath/simd.inc.src"]
bld(target="ufunc_templates", source=ufunc_templates)
bld(features="umath_gen",
pattern="umath_generated",
name="umath_gen")
includes = ["src/umath", "src/private"]
if ENABLE_SEPARATE_COMPILATION:
sources = [
pjoin("src", "umath", "loops.c.src"),
pjoin('src', 'umath', 'reduction.c'),
pjoin('src', 'umath', 'ufunc_object.c'),
pjoin('src', 'umath', 'ufunc_type_resolution.c'),
pjoin("src", "umath", "umathmodule.c"),
]
else:
sources = extension.sources
return context.default_builder(extension,
includes=includes,
source=sources,
use="npymath")
context.register_builder("umath", build_ufunc)
context.tweak_extension("scalarmath", use="npymath", includes=["src/private"])
context.tweak_extension("multiarray_tests", use="npymath", includes=["src/private"])
context.tweak_extension("umath_tests", use="npymath", includes=["src/private"])
def build_dotblas(extension):
if bld.env.HAS_CBLAS:
return context.default_builder(extension, use="CBLAS", includes=["src/private"])
context.register_builder("_dotblas", build_dotblas)
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