def _check_append_library(libraries, item):
for libitem in libraries:
if util.is_sequence(libitem):
if util.is_sequence(item):
if item[0]==libitem[0]:
if item[1] is libitem[1]:
return
warnings.warn("[0] libraries list contains %r with"
" different build_info" % (item[0],))
break
else:
if item==libitem[0]:
warnings.warn("[1] libraries list contains %r with"
" no build_info" % (item[0],))
break
else:
if util.is_sequence(item):
if item[0]==libitem:
warnings.warn("[2] libraries list contains %r with"
" no build_info" % (item[0],))
break
else:
if item==libitem:
return
libraries.append(item)
def assign_properties(node):
properties = stylesheet.get().node_properties(node, self)
style = node.attr('style')
if style:
if default_stylesheet_type.get() == 'text/css':
stream = StringIO.StringIO(style)
declarations = css.parse_stream(
stream, grammar=css.properties_grammar)
if util.is_sequence(declarations):
for d in declarations:
properties[d.name] = d.value
else:
errors.append(
Stylesheet_Parse_Error(
description="Parse error in stylesheet",
data='inline'))
elif not default_stylesheet_type:
errors.append(
No_Stylesheet_Type_Error(
node=node,
description=
"Style without stylesheet type defined",
data=style))
else:
errors.append(
Unknown_Stylesheet_Type_Error(
node=node,
description="Unknown stylesheet type",
data=style))
node.set_style(properties)
def test_is_sequence(self):
self.longMessage = True
self.assertTrue(util.is_sequence((1, 2, 3)), 'sequence not a sequence')
self.assertTrue(util.is_sequence(()), 'sequence not a sequence')
self.assertTrue(util.is_sequence([]), 'sequence not a sequence')
self.assertTrue(util.is_sequence([1]), 'sequence not a sequence')
self.assertFalse(util.is_sequence(None), 'non-sequence as sequence')
self.assertFalse(util.is_sequence(self), 'non-sequence as sequence')
self.assertFalse(util.is_sequence({}), 'non-sequence as sequence')
def display_multi(list):
"""**display_multi** (ImageList *list*)
Displays a list of images in a grid-like window. This function has
no effect if the `Gamera GUI`__ is not running.
.. __: gui.html"""
# If it's not a list, we'll get errors, so make it one
if not util.is_sequence(list):
list = [list]
if not len(list):
raise ValueError("Given list is empty.")
return has_gui.gui.ShowImages(list)
def _parse_mime_type(self, mime_type):
default_mime_type = (
None,
None,
)
s_mime_type = S.make(mime_type)
if s_mime_type:
mime_type = string.split(s_mime_type, '/')
elif not util.is_sequence(mime_type):
mime_type = default_mime_type
if len(mime_type) != 2:
mime_type = default_mime_type
return tuple([str(s) for s in mime_type])
def __init__(self, name=None, range=(-DEFAULT_MAX_ARG_NUMBER, DEFAULT_MAX_ARG_NUMBER), default=None):
Arg.__init__(self, name)
if not (util.is_sequence(range) and len(range) == 2 and
type(range[0]) in (int, float) and type(range[1]) in (int, float)):
raise TypeError("'range' must be a 2-tuple of numbers")
self.rng = range
if default is None:
self.has_default = False
self.default = 0
else:
self.has_default = True
self.default = default
if not isinstance(self.default,CNoneDefault) and type(self.default) != int:
raise TypeError("'default' must be an int")
def __init__(self, name=None, range=None, default=None):
Arg.__init__(self, name)
if range is None:
range = (-DEFAULT_MAX_ARG_NUMBER, DEFAULT_MAX_ARG_NUMBER)
if not (util.is_sequence(range) and len(range) == 2 and type(range[0])
in (int, float) and type(range[1]) in (int, float)):
raise TypeError("'range' must be a 2-tuple of numbers")
self.rng = range
if default is None:
self.has_default = False
self.default = 0.0
else:
self.has_default = True
self.default = default
if type(self.default) != float:
raise TypeError("'default' must be a float")
def _params(param_dict=None, collapse=False):
""" Given a dict of parameter key/value pairs, filter out the ones
whose values are None, and comma-join any parameters with lists/tuples.
:param dict param_dict: the full set of parameters
:param boolean collapse: if True, collapses lists/tuples to comma-separated
lists
:returns: (dict) the refined set of params
"""
param_dict = param_dict or {}
params = dict(filter(lambda (k, v): v is not None, param_dict.iteritems()))
if collapse:
for key in params:
if is_sequence(params[key]):
params[key] = ','.join(params[key])
return params
def _params(param_dict=None, collapse=False):
""" Given a dict of parameter key/value pairs, filter out the ones
whose values are None, and comma-join any parameters with lists/tuples.
:param dict param_dict: the full set of parameters
:param boolean collapse: if True, collapses lists/tuples to comma-separated
lists
:returns: (dict) the refined set of params
"""
param_dict = param_dict or {}
params = dict(filter(lambda (k, v): v is not None, param_dict.iteritems()))
if collapse:
for key in params:
if is_sequence(params[key]):
params[key] = ','.join(params[key])
return params
def __init__(self, pixel_types, name=None, list_of=False, default=None):
import core
Arg.__init__(self, name)
if not util.is_sequence(pixel_types):
pixel_types = (pixel_types,)
if not util.is_homogenous_list(pixel_types, (int,)):
raise TypeError("'pixel_types' must be a list of integers.")
if not core is None:
self.klass = core.ImageBase
else:
self.klass = None
self.pixel_types = pixel_types
self.list_of = bool(list_of)
if default is None:
self.has_default = False
self.default = None
else:
self.has_default = True
self.default = default
if self.has_default and not isinstance(self.default,CNoneDefault):
raise TypeError("'default' can only be NoneDefault")
def __init__(self, pixel_types, name=None, list_of=False, default=None):
import core
Arg.__init__(self, name)
if not util.is_sequence(pixel_types):
pixel_types = (pixel_types, )
if not util.is_homogenous_list(pixel_types, (int, )):
raise TypeError("'pixel_types' must be a list of integers.")
if not core is None:
self.klass = core.ImageBase
else:
self.klass = None
self.pixel_types = pixel_types
self.list_of = bool(list_of)
if default is None:
self.has_default = False
self.default = None
else:
self.has_default = True
self.default = default
if self.has_default and not isinstance(self.default, CNoneDefault):
raise TypeError("'default' can only be NoneDefault")
class ForTemplateNode(TemplateNode):
def __init__(self, parent, s):
TemplateNode.__init__(self, parent, s)
match = re_for_loop.match(s)
if match == None:
raise self.parent.parser_exception(
"[[%s]] is not a valid for-loop expression" % self.s)
else:
self.vars_temp = match.group(1).split(",")
self.vars = []
for v in self.vars_temp:
self.vars.append(v.strip())
self.expression = match.group(2)
def execute(self, stream, data):
remember_vars = {}
for var in self.vars:
if data.has_key(var):
remember_vars[var] = data[var]
try:
x = eval(self.expression, globals(), data)
except Exception, e:
self.parent.parser_exception(self.expression, e)
for list in x:
if util.is_sequence(list):
if len(self.vars) == 1:
data[self.vars[0]] = list
elif len(self.vars) == len(list):
for index, value in util.enumerate(list):
data[self.vars[index]] = value
else:
self.parent.parser_exception(
"Unable to unpack tuples in [[%s]]" % self.s)
else:
data[self.vars[0]] = list
TemplateNode.execute(self, stream, data)
for key, value in remember_vars.items():
data[key] = value
def build_a_library(self, build_info, lib_name, libraries):
libraries = convert_ulist(build_info.get("libraries") or [])
library_dirs = convert_ulist(build_info.get("library_dirs") or [])
runtime_library_dirs = convert_ulist(build_info.get("runtime_library_dirs"))
extra_preargs = build_info.get("extra_compiler_args") or []
extra_postargs = build_info.get("extra_link_args") or []
## Conditional recompile
target_library = self.compiler.library_filename(lib_name, lib_type="shared", output_dir="")
target_path = os.path.join(self.build_clib, target_library)
recompile = False
if not os.path.exists(target_path) or self.force:
recompile = True
else:
for src in build_info.get("sources"):
if os.path.getmtime(target_path) < os.path.getmtime(src):
recompile = True
break
if not recompile:
return
library_dirs += [self.build_clib]
########################################
## Copied verbatim from numpy.distutils.command.build_clib
# default compilers
compiler = self.compiler
fcompiler = getattr(self, "_f_compiler", self.fcompiler)
sources = build_info.get("sources")
if sources is None or not is_sequence(sources):
raise DistutilsSetupError, (
"in 'libraries' option (library '%s'), "
+ "'sources' must be present and must be "
+ "a list of source filenames"
) % lib_name
sources = list(sources)
c_sources, cxx_sources, f_sources, fmodule_sources = filter_sources(sources)
requiref90 = not not fmodule_sources or build_info.get("language", "c") == "f90"
# save source type information so that build_ext can use it.
source_languages = []
if c_sources:
source_languages.append("c")
if cxx_sources:
source_languages.append("c++")
if requiref90:
source_languages.append("f90")
elif f_sources:
source_languages.append("f77")
specified = build_info.get("language", None)
if specified:
source_languages.append(specified)
if specified == "c++": ## force c++ compiler
cxx_sources += c_sources
c_sources = []
build_info["source_languages"] = source_languages
lib_file = compiler.library_filename(lib_name, lib_type="shared", output_dir=self.build_clib)
depends = sources + build_info.get("depends", [])
if not (self.force or newer_group(depends, lib_file, "newer")):
log.debug("skipping '%s' library (up-to-date)", lib_name)
return
else:
log.info("building '%s' library", lib_name)
if have_numpy:
config_fc = build_info.get("config_fc", {})
if fcompiler is not None and config_fc:
log.info("using additional config_fc from setup script " "for fortran compiler: %s" % (config_fc,))
from numpy.distutils.fcompiler import new_fcompiler
fcompiler = new_fcompiler(
compiler=fcompiler.compiler_type,
verbose=self.verbose,
dry_run=self.dry_run,
force=self.force,
requiref90=requiref90,
c_compiler=self.compiler,
)
if fcompiler is not None:
dist = self.distribution
base_config_fc = dist.get_option_dict("config_fc").copy()
base_config_fc.update(config_fc)
fcompiler.customize(base_config_fc)
# check availability of Fortran compilers
if (f_sources or fmodule_sources) and fcompiler is None:
ver = "77"
if requiref90:
ver = "90"
raise DistutilsError, "library %s has Fortran%s sources" " but no Fortran compiler found" % (
lib_name,
ver,
)
"""
if fcompiler is not None:
fcompiler.extra_f77_compile_args = build_info.get('extra_f77_compile_args') or []
fcompiler.extra_f90_compile_args = build_info.get('extra_f90_compile_args') or []
"""
macros = build_info.get("macros")
include_dirs = build_info.get("include_dirs")
if include_dirs is None:
include_dirs = []
extra_postargs = build_info.get("extra_compiler_args") or []
if have_numpy:
include_dirs.extend(get_numpy_include_dirs())
# where compiled F90 module files are:
module_dirs = build_info.get("module_dirs") or []
module_build_dir = os.path.dirname(lib_file)
if requiref90:
self.mkpath(module_build_dir)
if compiler.compiler_type == "msvc":
# this hack works around the msvc compiler attributes
# problem, msvc uses its own convention :(
c_sources += cxx_sources
cxx_sources = []
objects = []
if c_sources:
log.info("compiling C sources")
objects = compiler.compile(
c_sources,
output_dir=self.build_temp,
macros=macros,
include_dirs=include_dirs,
debug=self.debug,
extra_postargs=extra_postargs,
)
if cxx_sources:
log.info("compiling C++ sources")
cxx_compiler = compiler.cxx_compiler()
cxx_objects = cxx_compiler.compile(
cxx_sources,
output_dir=self.build_temp,
macros=macros,
include_dirs=include_dirs,
debug=self.debug,
extra_postargs=extra_postargs,
)
objects.extend(cxx_objects)
if f_sources or fmodule_sources:
if not have_numpy:
raise Exception("Fortran sources, but no NumPy to compile them.")
extra_postargs = []
f_objects = []
if requiref90:
if fcompiler.module_dir_switch is None:
existing_modules = glob("*.mod")
extra_postargs += fcompiler.module_options(module_dirs, module_build_dir)
if fmodule_sources:
log.info("compiling Fortran 90 module sources")
f_objects += fcompiler.compile(
fmodule_sources,
output_dir=self.build_temp,
macros=macros,
include_dirs=include_dirs,
debug=self.debug,
extra_postargs=extra_postargs,
)
if requiref90 and fcompiler.module_dir_switch is None:
# move new compiled F90 module files to module_build_dir
for f in glob("*.mod"):
if f in existing_modules:
continue
t = os.path.join(module_build_dir, f)
if os.path.abspath(f) == os.path.abspath(t):
continue
if os.path.isfile(t):
os.remove(t)
try:
self.move_file(f, module_build_dir)
except DistutilsFileError:
log.warn("failed to move %r to %r" % (f, module_build_dir))
if f_sources:
log.info("compiling Fortran sources")
f_objects += fcompiler.compile(
f_sources,
output_dir=self.build_temp,
macros=macros,
include_dirs=include_dirs,
debug=self.debug,
extra_postargs=extra_postargs,
)
else:
f_objects = []
objects.extend(f_objects)
# assume that default linker is suitable for
# linking Fortran object files
########################################
link_compiler = compiler
if cxx_sources:
link_compiler = cxx_compiler
extra_postargs = build_info.get("extra_link_args") or []
## May be dependent on other libs we're builing
shlib_libraries = []
for libinfo in build_info.get("libraries", []):
if isinstance(libinfo, basestring):
shlib_libraries.append(convert_ulist([libinfo])[0])
else:
shlib_libraries.append(libinfo[0])
## Alternate ending
link_compiler.link(
target_desc=link_compiler.SHARED_LIBRARY,
objects=objects,
output_filename=target_library,
output_dir=self.build_clib,
libraries=shlib_libraries,
library_dirs=library_dirs,
runtime_library_dirs=runtime_library_dirs,
debug=self.debug,
extra_preargs=extra_preargs,
extra_postargs=extra_postargs,
)
def function(*args, **kwargs):
assert 'size' in kwargs, "Need size information"
assert 'name' in kwargs, "Need name for output"
assert len(args) > 0, "Empty arguments in function {}".format(
kwargs["name"])
size = kwargs["size"]
name = kwargs["name"]
config = kwargs.get("config", {})
for k, v in config.iteritems():
if not k in kwargs:
kwargs[k] = v
user_act = kwargs.get("act")
use_bias = kwargs.get("use_bias", True)
weight_factor = kwargs.get("weight_factor", 1.0)
use_weight_norm = kwargs.get("use_weight_norm", False)
layers_num = kwargs.get("layers_num")
reuse = kwargs.get("reuse", False)
use_batch_norm = kwargs.get("use_batch_norm", False)
scope_name = kwargs.get("scope_name", "")
if scope_name:
name = "{}/{}".format(scope_name, name)
if use_weight_norm:
use_bias = False
epsilon = 1e-03
if not is_sequence(size):
size = (size, )
if not layers_num is None:
size = size * layers_num
if layers_num is None:
layers_num = len(size)
else:
assert layers_num == len(
size
), "Got layers num not matched with size information. layers_num: {}, size: {}".format(
layers_num, size)
act = None
if user_act:
act = user_act
assert not act is None or use_weight_norm == False, "Can't use batch normalization with linear activation function"
with tf.variable_scope(name, reuse=reuse) as scope:
inputs = args
for l_id in xrange(layers_num):
nout = size[l_id]
layer_out = None #tf.zeros([None, nout], dtype=tf.float32)
for idx, a in enumerate(inputs):
a_shape = a.get_shape().as_list()
nin = a_shape[-1]
init = lambda shape, dtype, partition_info: xavier_init(
nin, nout, const=weight_factor)
vec_init = lambda shape, dtype, partition_info: xavier_vec_init(
nout, const=weight_factor)
zeros_init = lambda shape, dtype, partition_info: np.zeros(
(nout, ))
ones_init = lambda shape, dtype, partition_info: np.ones(
(nout, ))
if not use_weight_norm:
w = tf.get_variable("W{}-{}".format(l_id, idx),
[nin, nout],
dtype=tf.float32,
initializer=init)
a_w = tf.matmul(a, w)
else:
V = tf.get_variable(
"V{}-{}".format(l_id, idx), [nin, nout],
dtype=tf.float32,
initializer=init
) #tf.uniform_unit_scaling_initializer(factor=weight_factor))
g = tf.get_variable("g{}-{}".format(l_id, idx), [nout],
dtype=tf.float32,
initializer=vec_init)
a_w = tf.matmul(a, V)
a_w = a_w * g / tf.sqrt(tf.reduce_sum(tf.square(V), [0]))
if use_bias:
b = tf.get_variable("b{}-{}".format(l_id, idx), [nout],
tf.float32,
initializer=zeros_init)
a_w = a_w + b
if layer_out is None:
layer_out = a_w
else:
layer_out = layer_out + a_w
if use_batch_norm:
batch_mean, batch_var = tf.nn.moments(layer_out, [0])
layer_out = (layer_out - batch_mean) / tf.sqrt(batch_var +
epsilon)
gamma = tf.get_variable("gamma{}".format(l_id), [nout],
dtype=tf.float32,
initializer=ones_init)
beta = tf.get_variable("beta{}".format(l_id), [nout],
dtype=tf.float32,
initializer=zeros_init)
layer_out = gamma * layer_out + beta
inputs = (act(layer_out) if act else layer_out, )
return inputs[0]
else:
if item==libitem[0]:
warnings.warn("[1] libraries list contains %r with"
" no build_info" % (item[0],))
break
else:
if util.is_sequence(item):
if item[0]==libitem:
warnings.warn("[2] libraries list contains %r with"
" no build_info" % (item[0],))
break
else:
if item==libitem:
return
libraries.append(item)
def _check_append_ext_library(libraries, (lib_name,build_info)):
for item in libraries:
if util.is_sequence(item):
if item[0]==lib_name:
if item[1] is build_info:
return
warnings.warn("[3] libraries list contains %r with"
" different build_info" % (lib_name,))
break
elif item==lib_name:
warnings.warn("[4] libraries list contains %r with"
" no build_info" % (lib_name,))
break
libraries.append((lib_name,build_info))
def function(*args, **kwargs):
assert 'size' in kwargs, "Need size information"
assert 'name' in kwargs, "Need name for output"
assert len(args) > 0, "Empty arguments in function {}".format(kwargs["name"])
size = kwargs["size"]
name = kwargs["name"]
config = kwargs.get("config", {})
for k, v in config.iteritems():
if not k in kwargs:
kwargs[k] = v
user_act = kwargs.get("act")
use_bias = kwargs.get("use_bias", True)
weight_factor = kwargs.get("weight_factor", 1.0)
use_weight_norm = kwargs.get("use_weight_norm", False)
layers_num = kwargs.get("layers_num")
reuse = kwargs.get("reuse", False)
use_batch_norm = kwargs.get("use_batch_norm", False)
scope_name = kwargs.get("scope_name", "")
if scope_name:
name = "{}/{}".format(scope_name, name)
if use_weight_norm:
use_bias = False
epsilon = 1e-03
if not is_sequence(size):
size = (size,)
if not layers_num is None:
size = size*layers_num
if layers_num is None:
layers_num = len(size)
else:
assert layers_num == len(size), "Got layers num not matched with size information. layers_num: {}, size: {}".format(layers_num, size)
act = None
if user_act:
act = user_act
assert not act is None or use_weight_norm == False, "Can't use batch normalization with linear activation function"
with tf.variable_scope(name, reuse=reuse) as scope:
inputs = args
for l_id in xrange(layers_num):
nout = size[l_id]
layer_out = None #tf.zeros([None, nout], dtype=tf.float32)
for idx, a in enumerate(inputs):
a_shape = a.get_shape().as_list()
nin = a_shape[-1]
init = lambda shape, dtype, partition_info: xavier_init(nin, nout, const = weight_factor)
vec_init = lambda shape, dtype, partition_info: xavier_vec_init(nout, const = weight_factor)
zeros_init = lambda shape, dtype, partition_info: np.zeros((nout,))
ones_init = lambda shape, dtype, partition_info: np.ones((nout,))
if not use_weight_norm:
w = tf.get_variable("W{}-{}".format(l_id, idx), [nin, nout], dtype = tf.float32, initializer = init)
a_w = tf.matmul(a, w)
else:
V = tf.get_variable("V{}-{}".format(l_id, idx), [nin, nout], dtype = tf.float32, initializer = init) #tf.uniform_unit_scaling_initializer(factor=weight_factor))
g = tf.get_variable("g{}-{}".format(l_id, idx), [nout], dtype = tf.float32, initializer = vec_init)
a_w = tf.matmul(a, V)
a_w = a_w * g/tf.sqrt(tf.reduce_sum(tf.square(V),[0]))
if use_bias:
b = tf.get_variable("b{}-{}".format(l_id, idx), [nout], tf.float32, initializer = zeros_init)
a_w = a_w + b
if layer_out is None:
layer_out = a_w
else:
layer_out = layer_out + a_w
if use_batch_norm:
batch_mean, batch_var = tf.nn.moments(layer_out, [0])
layer_out = (layer_out - batch_mean) / tf.sqrt(batch_var + epsilon)
gamma = tf.get_variable("gamma{}".format(l_id), [nout], dtype = tf.float32, initializer = ones_init)
beta = tf.get_variable("beta{}".format(l_id), [nout], dtype = tf.float32, initializer = zeros_init)
layer_out = gamma * layer_out + beta
inputs = (act(layer_out) if act else layer_out,)
return inputs[0]
def run(self):
if not self.executables:
return
# Make sure that library sources are complete.
languages = []
for exe in self.executables:
if not all_strings(exe.sources):
self.run_command('build_src')
l = exe.language
if l and l not in languages: languages.append(l)
from distutils.ccompiler import new_compiler
self.compiler = new_compiler(compiler=self.compiler,
dry_run=self.dry_run,
force=self.force)
self.compiler.customize(self.distribution,
need_cxx=self.have_cxx_sources())
self.compiler.customize_cmd(self)
self.compiler.show_customization()
if have_numpy and self.have_f_sources():
from numpy.distutils.fcompiler import new_fcompiler
self.fcompiler = new_fcompiler(compiler=self.fcompiler,
verbose=self.verbose,
dry_run=self.dry_run,
force=self.force,
requiref90='f90' in languages,
c_compiler=self.compiler)
if self.fcompiler is not None:
self.fcompiler.customize(self.distribution)
self.fcompiler.customize_cmd(self)
self.fcompiler.show_customization()
exes = []
for exe in self.executables:
libraries = exe.libraries or []
library_dirs = exe.library_dirs or []
runtime_library_dirs = exe.runtime_library_dirs or []
extra_preargs = exe.extra_compile_args or []
extra_postargs = exe.extra_link_args or []
## include libraries built by build_shlib and/or build_clib
library_dirs.append(self.build_temp)
## Conditional recompile
build_directory = self.build_clib
target_path = os.path.join(build_directory, exe.name)
recompile = False
if not os.path.exists(target_path) or self.force:
recompile = True
else:
for src in exe.sources:
if os.path.getmtime(target_path) < os.path.getmtime(src):
recompile = True
break
if not recompile:
return
########################################
## Copied from numpy.distutils.command.build_clib
# default compilers
compiler = self.compiler
fcompiler = self.fcompiler
sources = exe.sources
if sources is None or not is_sequence(sources):
raise DistutilsSetupError, \
("in 'libraries' option (library '%s'), " +
"'sources' must be present and must be " +
"a list of source filenames") % exe.name
sources = list(sources)
c_sources, cxx_sources, f_sources, fmodule_sources \
= filter_sources(sources)
if not exe.language:
exe.language = 'c'
requiref90 = not not fmodule_sources or exe.language =='f90'
# save source type information so that build_ext can use it.
source_languages = []
if c_sources: source_languages.append('c')
if cxx_sources: source_languages.append('c++')
if requiref90: source_languages.append('f90')
elif f_sources: source_languages.append('f77')
exe.source_languages = source_languages
lib_file = compiler.library_filename(exe.name,
output_dir=build_directory)
depends = sources + (exe.depends or [])
if not (self.force or newer_group(depends, lib_file, 'newer')):
log.debug("skipping '%s' library (up-to-date)", exe.name)
return
else:
log.info("building '%s' library", exe.name)
if have_numpy:
config_fc = exe.config_fc or {}
if fcompiler is not None and config_fc:
log.info('using additional config_fc from setup script '\
'for fortran compiler: %s' \
% (config_fc,))
from numpy.distutils.fcompiler import new_fcompiler
fcompiler = new_fcompiler(compiler=fcompiler.compiler_type,
verbose=self.verbose,
dry_run=self.dry_run,
force=self.force,
requiref90=requiref90,
c_compiler=self.compiler)
if fcompiler is not None:
dist = self.distribution
base_config_fc = dist.get_option_dict('config_fc').copy()
base_config_fc.update(config_fc)
fcompiler.customize(base_config_fc)
# check availability of Fortran compilers
if (f_sources or fmodule_sources) and fcompiler is None:
raise DistutilsError, "library %s has Fortran sources"\
" but no Fortran compiler found" % (exe.name)
macros = exe.define_macros
include_dirs = exe.include_dirs
if include_dirs is None:
include_dirs = []
if have_numpy:
include_dirs.extend(get_numpy_include_dirs())
# where compiled F90 module files are:
module_dirs = exe.module_dirs or []
module_build_dir = os.path.dirname(lib_file)
if requiref90: self.mkpath(module_build_dir)
if compiler.compiler_type=='msvc':
# this hack works around the msvc compiler attributes
# problem, msvc uses its own convention :(
c_sources += cxx_sources
cxx_sources = []
objects = []
if c_sources:
log.info("compiling C sources")
objects = compiler.compile(c_sources,
output_dir=self.build_temp,
macros=macros,
include_dirs=include_dirs,
debug=self.debug,
extra_postargs=extra_postargs)
if cxx_sources:
log.info("compiling C++ sources")
cxx_compiler = compiler.cxx_compiler()
cxx_objects = cxx_compiler.compile(cxx_sources,
output_dir=self.build_temp,
macros=macros,
include_dirs=include_dirs,
debug=self.debug,
extra_postargs=extra_postargs)
objects.extend(cxx_objects)
if f_sources or fmodule_sources:
extra_postargs = []
f_objects = []
if requiref90:
if fcompiler.module_dir_switch is None:
existing_modules = glob('*.mod')
extra_postargs += fcompiler.module_options(\
module_dirs,module_build_dir)
if fmodule_sources:
log.info("compiling Fortran 90 module sources")
f_objects += fcompiler.compile(fmodule_sources,
output_dir=self.build_temp,
macros=macros,
include_dirs=include_dirs,
debug=self.debug,
extra_postargs=extra_postargs)
if requiref90 and self.fcompiler.module_dir_switch is None:
# move new compiled F90 module files to module_build_dir
for f in glob('*.mod'):
if f in existing_modules:
continue
t = os.path.join(module_build_dir, f)
if os.path.abspath(f)==os.path.abspath(t):
continue
if os.path.isfile(t):
os.remove(t)
try:
self.move_file(f, module_build_dir)
except DistutilsFileError:
log.warn('failed to move %r to %r' \
% (f, module_build_dir))
if f_sources:
log.info("compiling Fortran sources")
f_objects += fcompiler.compile(f_sources,
output_dir=self.build_temp,
macros=macros,
include_dirs=include_dirs,
debug=self.debug,
extra_postargs=extra_postargs)
else:
f_objects = []
objects.extend(f_objects)
# assume that default linker is suitable for
# linking Fortran object files
########################################
if exe.link_with_fcompiler: # if using PROGRAM
link_compiler = fcompiler
else:
link_compiler = compiler
if cxx_sources:
link_compiler = cxx_compiler
## May be dependent on other libs we're builing
shlib_libraries = []
for libinfo in exe.libraries:
if isinstance(libinfo, basestring):
shlib_libraries.append(convert_ulist([libinfo])[0])
else:
shlib_libraries.append(libinfo[0])
if not hasattr(link_compiler, 'linker_exe') or \
link_compiler.linker_exe is None:
link_compiler.linker_exe = [link_compiler.linker_so[0]]
linker_args = dict(
target_desc = link_compiler.EXECUTABLE,
objects = objects,
output_filename = exe.name,
output_dir = build_directory,
libraries = shlib_libraries,
library_dirs = library_dirs,
debug = self.debug,
extra_preargs = extra_preargs,
extra_postargs = extra_postargs,
)
if not exe.link_with_fcompiler:
linker_args['runtime_library_dirs'] = runtime_library_dirs
## Alternate ending
link_compiler.link(**linker_args)
def setup(**attr):
if len(sys.argv)<=1 and not attr.get('script_args',[]):
try:
from numpy.distutils.interactive import interactive_sys_argv
from numpy.distutils.core import _exit_interactive_session
import atexit
atexit.register(_exit_interactive_session)
sys.argv[:] = interactive_sys_argv(sys.argv)
if len(sys.argv)>1:
return setup(**attr)
except:
pass
cmdclass = my_cmdclass.copy()
new_attr = attr.copy()
if 'cmdclass' in new_attr:
cmdclass.update(new_attr['cmdclass'])
new_attr['cmdclass'] = cmdclass
if 'configuration' in new_attr:
# To avoid calling configuration if there are any errors
# or help request in command in the line.
configuration = new_attr.pop('configuration')
old_dist = distutils.core._setup_distribution
old_stop = distutils.core._setup_stop_after
distutils.core._setup_distribution = None
distutils.core._setup_stop_after = "commandline"
try:
dist = setup(**new_attr)
finally:
distutils.core._setup_distribution = old_dist
distutils.core._setup_stop_after = old_stop
if dist.help or not _command_line_ok():
# probably displayed help, skip running any commands
return dist
# create setup dictionary and append to new_attr
config = configuration()
if hasattr(config,'todict'):
config = config.todict()
_dict_append(new_attr, **config)
# Move extension source libraries to libraries
libraries = []
for ext in new_attr.get('ext_modules',[]):
new_libraries = []
for item in ext.libraries:
#[item] = util.convert_ulist([item])
if util.is_sequence(item):
lib_name, build_info = item
_check_append_ext_library(libraries, item)
new_libraries.append(lib_name)
elif util.is_string(item):
new_libraries.append(item)
else:
raise TypeError("invalid description of extension module "
"library %r" % (item,))
ext.libraries = new_libraries
if libraries:
if 'libraries' not in new_attr:
new_attr['libraries'] = []
for item in libraries:
_check_append_library(new_attr['libraries'], item)
# sources in ext_modules or libraries may contain header files
if ('ext_modules' in new_attr or 'libraries' in new_attr) \
and 'headers' not in new_attr:
new_attr['headers'] = []
# Use our custom Distribution class instead of distutils' one
new_attr['distclass'] = CustomDistribution
return old_setup(**new_attr)
