def test_iaf_cond_alpha_functional(self):
path = str(
os.path.realpath(
os.path.join(
os.path.dirname(__file__),
os.path.join('..', 'models', 'iaf_cond_alpha.nestml'))))
params = list()
params.append('-path')
params.append(path)
# params.append('-dry')
params.append('-logging_level')
params.append('NO')
params.append('-target')
params.append('target')
params.append('-dev')
FrontendConfiguration.config(params)
compilation_unit = ModelParser.parse_model(path)
iaf_cond_alpha_functional = list()
iaf_cond_alpha_functional.append(compilation_unit.get_neuron_list()[0])
generate_nest_module_code(iaf_cond_alpha_functional)
analyse_and_generate_neurons(iaf_cond_alpha_functional)
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
