def __resolve_config_file_path(cmdline_arg):
"""
Search for the absolute file name of the configuration file.
starting from `-c` value provided by the user.
:param cmdline_arg:
:return:
"""
if not cmdline_arg:
raise IOError("\nNo configuration file has been provided, did you "
"forget '-c' command argument?{}".format(EPILOG_STRING))
# Resolve relative configuration file location
config_file_path = os.path.expanduser(cmdline_arg)
try:
config_file_path = resolve_file_name(
config_file_path, ('.', NIFTYNET_HOME))
if os.path.isfile(config_file_path):
return config_file_path
except (IOError, TypeError):
config_file_path = os.path.expanduser(cmdline_arg)
config_file_path = os.path.join(
NiftyNetGlobalConfig().get_default_examples_folder(),
config_file_path, config_file_path + "_config.ini")
if os.path.isfile(config_file_path):
return config_file_path
# could not proceed without a configuration file
raise IOError("\nConfiguration file not found: {}.{}".format(
os.path.expanduser(cmdline_arg), EPILOG_STRING))
def __resolve_config_file_path(cmdline_arg):
"""
Search for the absolute file name of the configuration file.
starting from `-c` value provided by the user.
:param cmdline_arg:
:return:
"""
if not cmdline_arg:
raise IOError("\nNo configuration file has been provided, did you "
"forget '-c' command argument?{}".format(EPILOG_STRING))
# Resolve relative configuration file location
config_file_path = os.path.expanduser(cmdline_arg)
try:
config_file_path = resolve_file_name(config_file_path,
('.', NIFTYNET_HOME))
if os.path.isfile(config_file_path):
return config_file_path
except (IOError, TypeError):
config_file_path = os.path.expanduser(cmdline_arg)
config_file_path = os.path.join(
NiftyNetGlobalConfig().get_default_examples_folder(), config_file_path,
config_file_path + "_config.ini")
if os.path.isfile(config_file_path):
return config_file_path
# could not proceed without a configuration file
raise IOError("\nConfiguration file not found: {}.{}".format(
os.path.expanduser(cmdline_arg), EPILOG_STRING))
def create_instance(cls, file_path, **kwargs):
"""
Read image headers and create image instance.
:param file_path: a file path or a sequence of file paths
:param kwargs: output properties for transforming the image data
array into a desired format
:return: an image instance
"""
if file_path is None:
tf.logging.fatal('No file_path provided, '
'please check input sources in config file')
raise ValueError
ndims = 0
image_type = None
home_folder = NiftyNetGlobalConfig().get_niftynet_home_folder()
try:
file_path = resolve_file_name(file_path, ('.', home_folder))
if os.path.isfile(file_path):
loader = kwargs.get('loader', None) or None
ndims = misc.infer_ndims_from_file(file_path, loader)
image_type = cls.INSTANCE_DICT.get(ndims, None)
except (TypeError, IOError, AttributeError):
pass
if image_type is None:
try:
file_path = [
resolve_file_name(path, ('.', home_folder))
for path in file_path
]
loader = kwargs.get('loader', None) or (None, )
ndims = misc.infer_ndims_from_file(file_path[0], loader[0])
ndims = ndims + (1 if len(file_path) > 1 else 0)
image_type = cls.INSTANCE_DICT.get(ndims, None)
except (AssertionError, TypeError, IOError, AttributeError):
tf.logging.fatal('Could not load file: %s', file_path)
raise IOError
if image_type is None:
tf.logging.fatal('Not supported image type from:\n%s', file_path)
raise NotImplementedError(
"unrecognised spatial rank {}".format(ndims))
return image_type(file_path, **kwargs)
def create_instance(cls, file_path, **kwargs):
"""
Read image headers and create image instance.
:param file_path: a file path or a sequence of file paths
:param kwargs: output properties for transforming the image data
array into a desired format
:return: an image instance
"""
if file_path is None:
tf.logging.fatal('No file_path provided, '
'please check input sources in config file')
raise ValueError
ndims = 0
image_type = None
home_folder = NiftyNetGlobalConfig().get_niftynet_home_folder()
try:
file_path = resolve_file_name(file_path, ('.', home_folder))
if os.path.isfile(file_path):
loader = kwargs.get('loader', None) or None
ndims = misc.infer_ndims_from_file(file_path, loader)
image_type = cls.INSTANCE_DICT.get(ndims, None)
except (TypeError, IOError, AttributeError):
pass
if image_type is None:
try:
file_path = [resolve_file_name(path, ('.', home_folder))
for path in file_path]
loader = kwargs.get('loader', None) or (None,)
ndims = misc.infer_ndims_from_file(file_path[0], loader[0])
ndims = ndims + (1 if len(file_path) > 1 else 0)
image_type = cls.INSTANCE_DICT.get(ndims, None)
except (AssertionError, TypeError, IOError, AttributeError):
tf.logging.fatal('Could not load file: %s', file_path)
raise IOError
if image_type is None:
tf.logging.fatal('Not supported image type from:\n%s', file_path)
raise NotImplementedError(
"unrecognised spatial rank {}".format(ndims))
return image_type(file_path, **kwargs)
def file_path(self, path_array):
if isinstance(path_array, string_types):
path_array = (path_array,)
home_folder = NiftyNetGlobalConfig().get_niftynet_home_folder()
try:
self._file_path = tuple(resolve_file_name(path, ('.', home_folder))
for path in path_array)
except (TypeError, AssertionError, AttributeError, IOError):
tf.logging.fatal(
"unrecognised file path format, should be a valid filename,"
"or a sequence of filenames %s", path_array)
raise IOError
def file_path(self, path_array):
if isinstance(path_array, string_types):
path_array = (path_array,)
home_folder = NiftyNetGlobalConfig().get_niftynet_home_folder()
try:
self._file_path = tuple(resolve_file_name(path, ('.', home_folder))
for path in path_array)
except (TypeError, AssertionError, AttributeError, IOError):
tf.logging.fatal(
"unrecognised file path format, should be a valid filename,"
"or a sequence of filenames %s", path_array)
raise IOError
def run():
"""
meta_parser is first used to find out location
of the configuration file. Based on the application_name
or meta_parser.prog name, the section parsers are organised
to find system parameters and application specific
parameters.
:return: system parameters is a group of parameters including
SYSTEM_SECTIONS and app_module.REQUIRED_CONFIG_SECTION
input_data_args is a group of input data sources to be
used by niftynet.io.ImageReader
"""
meta_parser = argparse.ArgumentParser(
description="Launch a NiftyNet application.",
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog=textwrap.dedent(EPILOG_STRING))
version_string = get_niftynet_version_string()
meta_parser.add_argument("action",
help="train networks, run inferences "
"or evaluate inferences",
metavar='ACTION',
choices=list(ACTIONS))
meta_parser.add_argument("-v",
"--version",
action='version',
version=version_string)
meta_parser.add_argument("-c",
"--conf",
help="specify configurations from a file",
metavar="CONFIG_FILE")
meta_parser.add_argument("-a",
"--application_name",
help="specify an application module name",
metavar='APPLICATION_NAME',
default="")
meta_args, args_from_cmdline = meta_parser.parse_known_args()
print(version_string)
# read configurations, to be parsed by sections
config_file_name = __resolve_config_file_path(meta_args.conf)
config = NiftyNetLaunchConfig()
config.read([config_file_name])
# infer application name from command
app_name = None
try:
parser_prog = meta_parser.prog.replace('.py', '')
app_name = parser_prog if parser_prog in SUPPORTED_APP \
else meta_args.application_name
assert app_name
except (AttributeError, AssertionError):
raise ValueError("\nUnknown application {}, or did you forget '-a' "
"command argument?{}".format(app_name, EPILOG_STRING))
# load application by name
app_module = ApplicationFactory.create(app_name)
try:
assert app_module.REQUIRED_CONFIG_SECTION, \
"\nREQUIRED_CONFIG_SECTION should be static variable " \
"in {}".format(app_module)
has_section_in_config(config, app_module.REQUIRED_CONFIG_SECTION)
except AttributeError:
raise AttributeError(
"Application code doesn't have REQUIRED_CONFIG_SECTION property. "
"{} should be an instance of "
"niftynet.application.base_application".format(app_module))
except ValueError:
raise ValueError(
"\n{} requires [{}] section in the config file.{}".format(
app_name, app_module.REQUIRED_CONFIG_SECTION, EPILOG_STRING))
# check keywords in configuration file
_check_config_file_keywords(config)
# using configuration as default, and parsing all command line arguments
# command line args override the configure file options
all_args = {}
for section in config.sections():
# try to rename user-specified sections for consistency
section = standardise_section_name(config, section)
section_defaults = dict(config.items(section))
section_args, args_from_cmdline = \
_parse_arguments_by_section([],
section,
section_defaults,
args_from_cmdline,
app_module.REQUIRED_CONFIG_SECTION)
all_args[section] = section_args
# check if any args from command line not recognised
_check_cmd_remaining_keywords(list(args_from_cmdline))
# split parsed results in all_args
# into dictionaries of system_args and input_data_args
system_args, input_data_args = {}, {}
for section in all_args:
# copy system default sections to ``system_args``
if section in SYSTEM_SECTIONS:
system_args[section] = all_args[section]
continue
# copy application specific sections to ``system_args``
if section == app_module.REQUIRED_CONFIG_SECTION:
system_args['CUSTOM'] = all_args[section]
vars(system_args['CUSTOM'])['name'] = app_name
continue
# copy non-default sections to ``input_data_args``
input_data_args[section] = all_args[section]
# set the output path of csv list if not exists
try:
csv_path = resolve_file_name(
input_data_args[section].csv_file,
(os.path.dirname(config_file_name), NIFTYNET_HOME))
input_data_args[section].csv_file = csv_path
# don't search files if csv specified in config
try:
delattr(input_data_args[section], 'path_to_search')
except AttributeError:
pass
except (IOError, TypeError):
input_data_args[section].csv_file = ''
# preserve ``config_file`` and ``action parameter`` from the meta_args
system_args['CONFIG_FILE'] = argparse.Namespace(path=config_file_name)
# mapping the captured action argument to a string in ACTIONS
system_args['SYSTEM'].action = \
look_up_operations(meta_args.action, ACTIONS)
if not system_args['SYSTEM'].model_dir:
system_args['SYSTEM'].model_dir = os.path.join(
os.path.dirname(config_file_name), 'model')
return system_args, input_data_args
def run():
"""
meta_parser is first used to find out location
of the configuration file. Based on the application_name
or meta_parser.prog name, the section parsers are organised
to find system parameters and application specific
parameters.
:return: system parameters is a group of parameters including
SYSTEM_SECTIONS and app_module.REQUIRED_CONFIG_SECTION
input_data_args is a group of input data sources to be
used by niftynet.io.ImageReader
"""
meta_parser = argparse.ArgumentParser(
description="Launch a NiftyNet application.",
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog=textwrap.dedent(EPILOG_STRING))
version_string = get_niftynet_version_string()
meta_parser.add_argument("action",
help="train networks, run inferences "
"or evaluate inferences",
metavar='ACTION',
choices=['train', 'inference', 'evaluation'])
meta_parser.add_argument("-v", "--version",
action='version',
version=version_string)
meta_parser.add_argument("-c", "--conf",
help="specify configurations from a file",
metavar="CONFIG_FILE")
meta_parser.add_argument("-a", "--application_name",
help="specify an application module name",
metavar='APPLICATION_NAME',
default="")
meta_args, args_from_cmdline = meta_parser.parse_known_args()
print(version_string)
# read configurations, to be parsed by sections
config_file_name = __resolve_config_file_path(meta_args.conf)
config = configparser.ConfigParser()
config.read([config_file_name])
# infer application name from command
app_name = None
try:
parser_prog = meta_parser.prog.replace('.py', '')
app_name = parser_prog if parser_prog in SUPPORTED_APP \
else meta_args.application_name
assert app_name
except (AttributeError, AssertionError):
raise ValueError(
"\nUnknown application {}, or did you forget '-a' "
"command argument?{}".format(app_name, EPILOG_STRING))
# load application by name
app_module = ApplicationFactory.create(app_name)
try:
assert app_module.REQUIRED_CONFIG_SECTION, \
"\nREQUIRED_CONFIG_SECTION should be static variable " \
"in {}".format(app_module)
has_section_in_config(config, app_module.REQUIRED_CONFIG_SECTION)
except AttributeError:
raise AttributeError(
"Application code doesn't have REQUIRED_CONFIG_SECTION property. "
"{} should be an instance of "
"niftynet.application.base_application".format(app_module))
except ValueError:
raise ValueError(
"\n{} requires [{}] section in the config file.{}".format(
app_name, app_module.REQUIRED_CONFIG_SECTION, EPILOG_STRING))
# check keywords in configuration file
_check_config_file_keywords(config)
# using configuration as default, and parsing all command line arguments
# command line args override the configure file options
all_args = {}
for section in config.sections():
# try to rename user-specified sections for consistency
section = standardise_section_name(config, section)
section_defaults = dict(config.items(section))
section_args, args_from_cmdline = \
_parse_arguments_by_section([],
section,
section_defaults,
args_from_cmdline,
app_module.REQUIRED_CONFIG_SECTION)
all_args[section] = section_args
# check if any args from command line not recognised
_check_cmd_remaining_keywords(list(args_from_cmdline))
# split parsed results in all_args
# into dictionaries of system_args and input_data_args
system_args, input_data_args = {}, {}
for section in all_args:
# copy system default sections to ``system_args``
if section in SYSTEM_SECTIONS:
system_args[section] = all_args[section]
continue
# copy application specific sections to ``system_args``
if section == app_module.REQUIRED_CONFIG_SECTION:
system_args['CUSTOM'] = all_args[section]
vars(system_args['CUSTOM'])['name'] = app_name
continue
# copy non-default sections to ``input_data_args``
input_data_args[section] = all_args[section]
# set the output path of csv list if not exists
try:
csv_path = resolve_file_name(
input_data_args[section].csv_file,
(os.path.dirname(config_file_name), NIFTYNET_HOME))
input_data_args[section].csv_file = csv_path
# don't search files if csv specified in config
try:
delattr(input_data_args[section], 'path_to_search')
except AttributeError:
pass
except (IOError, TypeError):
input_data_args[section].csv_file = ''
# preserve ``config_file`` and ``action parameter`` from the meta_args
system_args['CONFIG_FILE'] = argparse.Namespace(path=config_file_name)
system_args['SYSTEM'].action = meta_args.action
if not system_args['SYSTEM'].model_dir:
system_args['SYSTEM'].model_dir = os.path.join(
os.path.dirname(config_file_name), 'model')
return system_args, input_data_args
