def process():
"""
Returns
-------
errors_occurred : bool
Flag indicating whether errors occurred during processing
"""
errors_occurred = False
# init log dir
create_report_dir()
# The handed over parameters seem to be correct, proceed with the main routine
init_predefined()
# now proceed to parse all models
compilation_units = list()
nestml_files = FrontendConfiguration.get_files()
if not type(nestml_files) is list:
nestml_files = [nestml_files]
for nestml_file in nestml_files:
parsed_unit = ModelParser.parse_model(nestml_file)
if parsed_unit is not None:
compilation_units.append(parsed_unit)
if len(compilation_units) > 0:
# generate a list of all neurons
neurons = list()
for compilationUnit in compilation_units:
neurons.extend(compilationUnit.get_neuron_list())
# check if across two files two neurons with same name have been defined
CoCosManager.check_not_two_neurons_across_units(compilation_units)
# now exclude those which are broken, i.e. have errors.
if not FrontendConfiguration.is_dev:
for neuron in neurons:
if Logger.has_errors(neuron):
code, message = Messages.get_neuron_contains_errors(
neuron.get_name())
Logger.log_message(
node=neuron,
code=code,
message=message,
error_position=neuron.get_source_position(),
log_level=LoggingLevel.INFO)
neurons.remove(neuron)
errors_occurred = True
# perform code generation
_codeGenerator = CodeGenerator.from_target_name(
FrontendConfiguration.get_target(),
options=FrontendConfiguration.get_codegen_opts())
_codeGenerator.generate_code(neurons)
for neuron in neurons:
if Logger.has_errors(neuron):
errors_occurred = True
break
if FrontendConfiguration.store_log:
store_log_to_file()
return errors_occurred
def generate_neurons(self, neurons: List[ASTNode]):
"""
Generate code for the given neurons.
:param neurons: a list of neurons.
:type neurons: List[ASTNode]
"""
from pynestml.frontend.frontend_configuration import FrontendConfiguration
for neuron in neurons:
self.generate_neuron_code(neuron)
if not Logger.has_errors(neuron):
code, message = Messages.get_code_generated(neuron.get_name(), FrontendConfiguration.get_target_path())
Logger.log_message(neuron, code, message, neuron.get_source_position(), LoggingLevel.INFO)
def generate_neurons(self, neurons):
# type: (list(ASTNeuron)) -> None
"""
Analyse a list of neurons, solve them and generate the corresponding code.
:param neurons: a list of neurons.
"""
from pynestml.frontend.frontend_configuration import FrontendConfiguration
for neuron in neurons:
self.generate_neuron_code(neuron)
if not Logger.has_errors(neuron):
code, message = Messages.get_code_generated(
neuron.get_name(), FrontendConfiguration.get_target_path())
Logger.log_message(neuron, code, message,
neuron.get_source_position(),
LoggingLevel.INFO)
def main(args):
try:
FrontendConfiguration.config(args)
except InvalidPathException:
print('Not a valid path to model or directory: "%s"!' %
FrontendConfiguration.get_path())
return
# init log dir
create_report_dir()
# The handed over parameters seem to be correct, proceed with the main routine
init_predefined()
# now proceed to parse all models
compilation_units = list()
for file in FrontendConfiguration.get_files():
parsed_unit = ModelParser.parse_model(file)
if parsed_unit is not None:
compilation_units.append(parsed_unit)
# generate a list of all neurons
neurons = list()
for compilationUnit in compilation_units:
neurons.extend(compilationUnit.get_neuron_list())
# check if across two files two neurons with same name have been defined
CoCosManager.check_not_two_neurons_across_units(compilation_units)
# now exclude those which are broken, i.e. have errors.
if not FrontendConfiguration.is_dev():
for neuron in neurons:
if Logger.has_errors(neuron):
code, message = Messages.get_neuron_contains_errors(
neuron.get_name())
Logger.log_message(neuron=neuron,
code=code,
message=message,
error_position=neuron.get_source_position(),
log_level=LoggingLevel.INFO)
neurons.remove(neuron)
if not FrontendConfiguration.is_dry_run():
analyse_and_generate_neurons(neurons)
generate_nest_module_code(neurons)
else:
code, message = Messages.get_dry_run()
Logger.log_message(neuron=None,
code=code,
message=message,
log_level=LoggingLevel.INFO)
if FrontendConfiguration.store_log:
store_log_to_file()
return