def setup(self):
self.atom_data_filename = os.path.expanduser(
os.path.expandvars(pytest.config.getvalue('atomic-dataset')))
assert os.path.exists(
self.atom_data_filename), ("{0} atomic datafiles"
" does not seem to "
"exist".format(self.atom_data_filename))
self.config_yaml = yaml.load(
open('tardis/io/tests/data/tardis_configv1_verysimple.yml'))
self.config_yaml['atom_data'] = self.atom_data_filename
tardis_config = Configuration.from_config_dict(self.config_yaml)
self.model = Radial1DModel(tardis_config)
self.simulation = Simulation(tardis_config)
self.simulation.legacy_run_simulation(self.model)
def raw_model(tardis_config):
return Radial1DModel(tardis_config)
def setup(self, request, reference, data_path):
"""
This method does initial setup of creating configuration and performing
a single run of integration test.
"""
# The last component in dirpath can be extracted as name of setup.
self.name = data_path['setup_name']
self.config_file = os.path.join(data_path['config_dirpath'], "config.yml")
# A quick hack to use atom data per setup. Atom data is ingested from
# local HDF or downloaded and cached from a url, depending on data_path
# keys.
atom_data_name = yaml.load(open(self.config_file))['atom_data']
# Get the path to HDF file:
if 'atom_data_url' in data_path:
# If the atom data is to be ingested from url:
atom_data_filepath = download_file(urlparse.urljoin(
base=data_path['atom_data_url'], url=atom_data_name), cache=True
)
else:
# If the atom data is to be ingested from local file:
atom_data_filepath = os.path.join(
data_path['atom_data_dirpath'], atom_data_name
)
# Load atom data file separately, pass it for forming tardis config.
self.atom_data = AtomData.from_hdf5(atom_data_filepath)
# Check whether the atom data file in current run and the atom data
# file used in obtaining the reference data are same.
# TODO: hard coded UUID for kurucz atom data file, generalize it later.
# kurucz_data_file_uuid1 = "5ca3035ca8b311e3bb684437e69d75d7"
# assert self.atom_data.uuid1 == kurucz_data_file_uuid1
# Create a Configuration through yaml file and atom data.
tardis_config = Configuration.from_yaml(
self.config_file, atom_data=self.atom_data)
# Check whether current run is with less packets.
if request.config.getoption("--less-packets"):
less_packets = request.config.integration_tests_config['less_packets']
tardis_config['montecarlo']['no_of_packets'] = (
less_packets['no_of_packets']
)
tardis_config['montecarlo']['last_no_of_packets'] = (
less_packets['last_no_of_packets']
)
# We now do a run with prepared config and get radial1d model.
self.result = Radial1DModel(tardis_config)
# If current test run is just for collecting reference data, store the
# output model to HDF file, save it at specified path. Skip all tests.
# Else simply perform the run and move further for performing
# assertions.
if request.config.getoption("--generate-reference"):
run_radial1d(self.result, hdf_path_or_buf=os.path.join(
data_path['gen_ref_dirpath'], "{0}.h5".format(self.name)
))
pytest.skip("Reference data saved at {0}".format(
data_path['gen_ref_dirpath']
))
else:
run_radial1d(self.result)
# Get the reference data through the fixture.
self.reference = reference
