def setup(self):
filename = 'tardis_configv1_artis_density.yml'
self.config = Configuration.from_yaml(data_path(filename))
self.config.model.abundances.type = 'file'
self.config.model.abundances.filename = 'artis_abundances.dat'
self.config.model.abundances.filetype = 'artis'
self.model = Radial1DModel.from_config(self.config)
def setup(self):
filename = "tardis_configv1_artis_density_v_slice.yml"
self.config = Configuration.from_yaml(data_path(filename))
self.config.model.abundances.type = "file"
self.config.model.abundances.filename = "artis_abundances.dat"
self.config.model.abundances.filetype = "artis"
self.model = Radial1DModel.from_config(self.config)
def test_ascii_reader_exponential_law():
filename = "tardis_configv1_density_exponential_test.yml"
config = Configuration.from_yaml(data_path(filename))
model = Radial1DModel.from_config(config)
expected_densites = [
5.18114795e-14,
4.45945537e-14,
3.83828881e-14,
3.30364579e-14,
2.84347428e-14,
2.44740100e-14,
2.10649756e-14,
1.81307925e-14,
1.56053177e-14,
1.34316215e-14,
1.15607037e-14,
9.95038990e-15,
8.56437996e-15,
7.37143014e-15,
6.34464872e-15,
5.46088976e-15,
4.70023138e-15,
4.04552664e-15,
3.48201705e-15,
2.99699985e-15,
]
expected_unit = "g / (cm3)"
assert model.no_of_shells == 20
for i, mdens in enumerate(expected_densites):
assert_almost_equal(model.density[i].value, mdens)
assert model.density[i].unit == u.Unit(expected_unit)
def test_ascii_reader_power_law():
filename = "tardis_configv1_density_power_law_test.yml"
config = Configuration.from_yaml(data_path(filename))
model = Radial1DModel.from_config(config)
expected_densites = [
3.29072513e-14,
2.70357804e-14,
2.23776573e-14,
1.86501954e-14,
1.56435277e-14,
1.32001689e-14,
1.12007560e-14,
9.55397475e-15,
8.18935779e-15,
7.05208050e-15,
6.09916083e-15,
5.29665772e-15,
4.61758699e-15,
4.04035750e-15,
3.54758837e-15,
3.12520752e-15,
2.76175961e-15,
2.44787115e-15,
2.17583442e-15,
1.93928168e-15,
]
assert model.no_of_shells == 20
for i, mdens in enumerate(expected_densites):
assert_almost_equal(model.density[i].to(u.Unit("g / (cm3)")).value,
mdens)
def from_config(cls, config, **kwargs):
"""
Create a new Simulation instance from a Configuration object.
Parameters
----------
config : tardis.io.config_reader.Configuration
**kwargs
Allow overriding some structures, such as model, plasma, atomic data
and the runner, instead of creating them from the configuration
object.
Returns
-------
Simulation
"""
# Allow overriding some config structures. This is useful in some
# unit tests, and could be extended in all the from_config classmethods.
if 'model' in kwargs:
model = kwargs['model']
else:
model = Radial1DModel.from_config(config)
if 'plasma' in kwargs:
plasma = kwargs['plasma']
else:
plasma = assemble_plasma(config, model,
atom_data=kwargs.get('atom_data', None))
if 'runner' in kwargs:
runner = kwargs['runner']
else:
runner = MontecarloRunner.from_config(config)
luminosity_nu_start = config.supernova.luminosity_wavelength_end.to(
u.Hz, u.spectral())
try:
luminosity_nu_end = config.supernova.luminosity_wavelength_start.to(
u.Hz, u.spectral())
except ZeroDivisionError:
luminosity_nu_end = np.inf * u.Hz
last_no_of_packets = config.montecarlo.last_no_of_packets
if last_no_of_packets is None or last_no_of_packets < 0:
last_no_of_packets = config.montecarlo.no_of_packets
last_no_of_packets = int(last_no_of_packets)
return cls(iterations=config.montecarlo.iterations,
model=model,
plasma=plasma,
runner=runner,
no_of_packets=int(config.montecarlo.no_of_packets),
no_of_virtual_packets=int(
config.montecarlo.no_of_virtual_packets),
luminosity_nu_start=luminosity_nu_start,
luminosity_nu_end=luminosity_nu_end,
last_no_of_packets=last_no_of_packets,
luminosity_requested=config.supernova.luminosity_requested.cgs,
convergence_strategy=config.montecarlo.convergence_strategy,
nthreads=config.montecarlo.nthreads)
def test_model_decay(simple_isotope_abundance):
filename = "tardis_configv1_verysimple.yml"
config = Configuration.from_yaml(data_path(filename))
model = Radial1DModel.from_config(config)
model.raw_isotope_abundance = simple_isotope_abundance
decayed = simple_isotope_abundance.decay(model.time_explosion).as_atoms()
norm_factor = 1.4
assert_almost_equal(
model.abundance.loc[8][0],
model.raw_abundance.loc[8][0] / norm_factor,
decimal=4,
)
assert_almost_equal(
model.abundance.loc[14][0],
(model.raw_abundance.loc[14][0] + decayed.loc[14][0]) / norm_factor,
decimal=4,
)
assert_almost_equal(
model._abundance.loc[12][5],
(model.raw_abundance.loc[12][5] + decayed.loc[12][5]) / norm_factor,
decimal=4,
)
assert_almost_equal(
model.abundance.loc[6][12],
(decayed.loc[6][12]) / norm_factor,
decimal=4,
)
def setup(self):
filename = 'tardis_configv1_artis_density_v_slice.yml'
self.config = Configuration.from_yaml(data_path(filename))
self.config.model.abundances.type = 'file'
self.config.model.abundances.filename = 'artis_abundances.dat'
self.config.model.abundances.filetype = 'artis'
self.model = Radial1DModel.from_config(self.config)
def test_compare_models(model_config_fnames):
"""Compare identical models produced by .from_config and
.from_csvy to check that velocities, densities and abundances
(pre and post decay) are the same"""
csvy_config_file, old_config_file = model_config_fnames
tardis_config = Configuration.from_yaml(csvy_config_file)
tardis_config_old = Configuration.from_yaml(old_config_file)
csvy_model = Radial1DModel.from_csvy(tardis_config)
config_model = Radial1DModel.from_config(tardis_config_old)
csvy_model_props = csvy_model.get_properties().keys()
config_model_props = config_model.get_properties().keys()
npt.assert_array_equal(csvy_model_props, config_model_props)
for prop in config_model_props:
csvy_model_val = csvy_model.get_properties()[prop]
config_model_val = config_model.get_properties()[prop]
if prop == "homologous_density":
npt.assert_array_almost_equal(
csvy_model_val.density_0.value, config_model_val.density_0.value
)
npt.assert_array_almost_equal(
csvy_model_val.time_0.value, config_model_val.time_0.value
)
else:
if hasattr(config_model_val, "value"):
config_model_val = config_model_val.value
csvy_model_val = csvy_model_val.value
npt.assert_array_almost_equal(csvy_model_val, config_model_val)
assert csvy_model.raw_abundance.shape == config_model.raw_abundance.shape
assert (
csvy_model.raw_isotope_abundance.shape
== config_model.raw_isotope_abundance.shape
)
assert csvy_model.abundance.shape == config_model.abundance.shape
npt.assert_array_almost_equal(
csvy_model.raw_abundance.to_numpy(),
config_model.raw_abundance.to_numpy(),
)
npt.assert_array_almost_equal(
csvy_model.raw_isotope_abundance.to_numpy(),
config_model.raw_isotope_abundance.to_numpy(),
)
npt.assert_array_almost_equal(
csvy_model.abundance.to_numpy(), config_model.abundance.to_numpy()
)
def test_compare_models(full_filename):
tardis_config = Configuration.from_yaml(full_filename)
csvy_model = Radial1DModel.from_csvy(tardis_config)
config_model = Radial1DModel.from_config(tardis_config)
csvy_model_props = csvy_model.get_properties().keys()
config_model_props = config_model.get_properties().keys()
npt.assert_array_equal(csvy_model_props, config_model_props)
for prop in config_model_props:
csvy_model_val = csvy_model.get_properties()[prop]
config_model_val = config_model.get_properties()[prop]
if prop == 'homologous_density':
npt.assert_array_almost_equal(csvy_model_val.density_0.value, config_model_val.density_0.value)
npt.assert_array_almost_equal(csvy_model_val.time_0.value, config_model_val.time_0.value)
else:
if hasattr(config_model_val, 'value'):
config_model_val = config_model_val.value
csvy_model_val = csvy_model_val.value
npt.assert_array_almost_equal(csvy_model_val, config_model_val)
def test_csvy_abundance():
csvypath = os.path.join(DATA_PATH, 'config_v_filter.yml')
config = Configuration.from_yaml(csvypath)
csvy_model = Radial1DModel.from_csvy(config)
csvy_abund = csvy_model.abundance
ref_abund = pd.DataFrame(
np.array([[0.35, 0.3, 0.6, 0.4], [0.65, 0.7, 0.4, 0.6]]))
ref_abund.index.name = 'atomic_number'
ref_abund.index = np.array([1, 2])
assert csvy_abund.equals(ref_abund)
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 test_ascii_reader_power_law():
filename = 'tardis_configv1_density_power_law_test.yml'
config = Configuration.from_yaml(data_path(filename))
model = Radial1DModel.from_config(config)
expected_densites = [3.29072513e-14, 2.70357804e-14, 2.23776573e-14,
1.86501954e-14, 1.56435277e-14, 1.32001689e-14,
1.12007560e-14, 9.55397475e-15, 8.18935779e-15,
7.05208050e-15, 6.09916083e-15, 5.29665772e-15,
4.61758699e-15, 4.04035750e-15, 3.54758837e-15,
3.12520752e-15, 2.76175961e-15, 2.44787115e-15,
2.17583442e-15, 1.93928168e-15]
assert model.no_of_shells == 20
for i, mdens in enumerate(expected_densites):
assert_almost_equal(model.density[i].to(u.Unit('g / (cm3)')).value,
mdens)
def grid_row_to_model(self, row_index):
"""
Generates a TARDIS Radial1DModel object using the base
self.config modified by the specified grid row.
Parameters
----------
row_index : int
Row index in grid.
Returns
-------
model : tardis.model.base.Radial1DModel
"""
rowconfig = self.grid_row_to_config(row_index)
model = Radial1DModel.from_config(rowconfig)
return model
def test_ascii_reader_exponential_law():
filename = 'tardis_configv1_density_exponential_test.yml'
config = Configuration.from_yaml(data_path(filename))
model = Radial1DModel.from_config(config)
expected_densites = [5.18114795e-14, 4.45945537e-14, 3.83828881e-14,
3.30364579e-14, 2.84347428e-14, 2.44740100e-14,
2.10649756e-14, 1.81307925e-14, 1.56053177e-14,
1.34316215e-14, 1.15607037e-14, 9.95038990e-15,
8.56437996e-15, 7.37143014e-15, 6.34464872e-15,
5.46088976e-15, 4.70023138e-15, 4.04552664e-15,
3.48201705e-15, 2.99699985e-15]
expected_unit = 'g / (cm3)'
assert model.no_of_shells == 20
for i, mdens in enumerate(expected_densites):
assert_almost_equal(model.density[i].value, mdens)
assert model.density[i].unit == u.Unit(expected_unit)
def test_model_decay(simple_isotope_abundance):
filename = 'tardis_configv1_verysimple.yml'
config = Configuration.from_yaml(data_path(filename))
model = Radial1DModel.from_config(config)
model.raw_isotope_abundance = simple_isotope_abundance
decayed = simple_isotope_abundance.decay(
model.time_explosion).as_atoms()
norm_factor = 1.4
assert_almost_equal(
model.abundance.loc[8][0], model.raw_abundance.loc[8][0] / norm_factor, decimal=4)
assert_almost_equal(model.abundance.loc[14][0], (
model.raw_abundance.loc[14][0] + decayed.loc[14][0]) / norm_factor, decimal=4)
assert_almost_equal(model._abundance.loc[12][5], (
model.raw_abundance.loc[12][5] + decayed.loc[12][5]) / norm_factor, decimal=4)
assert_almost_equal(
model.abundance.loc[6][12], (decayed.loc[6][12]) / norm_factor, decimal=4)
def setup(self):
filename = "tardis_configv1_artis_density.yml"
self.config = Configuration.from_yaml(data_path(filename))
self.model = Radial1DModel.from_config(self.config)
def raw_model(tardis_config):
return Radial1DModel.from_config(tardis_config)
def setup(self):
filename = 'tardis_configv1_uniform_density.yml'
self.config = Configuration.from_yaml(data_path(filename))
self.config.plasma.initial_t_inner = 2508 * u.K
self.model = Radial1DModel.from_config(self.config)
def raw_model(tardis_model_density_config):
return Radial1DModel.from_config(tardis_model_density_config)
def setup(self):
filename = "paper1_tardis_configv1.yml"
self.config = Configuration.from_yaml(data_path(filename))
self.model = Radial1DModel.from_config(self.config)
def setup(self):
filename = 'paper1_tardis_configv1.yml'
self.config = Configuration.from_yaml(data_path(filename))
self.model = Radial1DModel.from_config(self.config)
def setup(self):
filename = "tardis_configv1_uniform_density.yml"
self.config = Configuration.from_yaml(data_path(filename))
self.config.plasma.initial_t_inner = 2508 * u.K
self.model = Radial1DModel.from_config(self.config)
def setup(self):
filename = "tardis_configv1_ascii_density_abund.yml"
self.config = Configuration.from_yaml(data_path(filename))
self.config.model.structure.filename = "density.dat"
self.config.model.abundances.filename = "abund.dat"
self.model = Radial1DModel.from_config(self.config)
def csvy_model_test_abundances():
"""Returns Radial1DModel to use to test abundances dataframes"""
csvypath = os.path.join(DATA_PATH, "csvy_model_to_test_abundances.yml")
config = Configuration.from_yaml(csvypath)
csvy_model_test_abundances = Radial1DModel.from_csvy(config)
return csvy_model_test_abundances
def setup(self):
filename = 'tardis_configv1_ascii_density_abund.yml'
self.config = Configuration.from_yaml(data_path(filename))
self.config.model.structure.filename = 'density.dat'
self.config.model.abundances.filename = 'abund.dat'
self.model = Radial1DModel.from_config(self.config)
def raw_model(tardis_config):
return Radial1DModel(tardis_config)
def from_config(cls,
config,
packet_source=None,
virtual_packet_logging=False,
**kwargs):
"""
Create a new Simulation instance from a Configuration object.
Parameters
----------
config : tardis.io.config_reader.Configuration
**kwargs
Allow overriding some structures, such as model, plasma, atomic data
and the runner, instead of creating them from the configuration
object.
Returns
-------
Simulation
"""
# Allow overriding some config structures. This is useful in some
# unit tests, and could be extended in all the from_config classmethods.
if "model" in kwargs:
model = kwargs["model"]
else:
if hasattr(config, "csvy_model"):
model = Radial1DModel.from_csvy(config)
else:
model = Radial1DModel.from_config(config)
if "plasma" in kwargs:
plasma = kwargs["plasma"]
else:
plasma = assemble_plasma(config,
model,
atom_data=kwargs.get("atom_data", None))
if "runner" in kwargs:
if packet_source is not None:
raise ConfigurationError(
"Cannot specify packet_source and runner at the same time."
)
runner = kwargs["runner"]
else:
runner = MontecarloRunner.from_config(
config,
packet_source=packet_source,
virtual_packet_logging=virtual_packet_logging,
)
luminosity_nu_start = config.supernova.luminosity_wavelength_end.to(
u.Hz, u.spectral())
if u.isclose(config.supernova.luminosity_wavelength_start,
0 * u.angstrom):
luminosity_nu_end = np.inf * u.Hz
else:
luminosity_nu_end = (
const.c / config.supernova.luminosity_wavelength_start).to(
u.Hz)
last_no_of_packets = config.montecarlo.last_no_of_packets
if last_no_of_packets is None or last_no_of_packets < 0:
last_no_of_packets = config.montecarlo.no_of_packets
last_no_of_packets = int(last_no_of_packets)
return cls(
iterations=config.montecarlo.iterations,
model=model,
plasma=plasma,
runner=runner,
no_of_packets=int(config.montecarlo.no_of_packets),
no_of_virtual_packets=int(config.montecarlo.no_of_virtual_packets),
luminosity_nu_start=luminosity_nu_start,
luminosity_nu_end=luminosity_nu_end,
last_no_of_packets=last_no_of_packets,
luminosity_requested=config.supernova.luminosity_requested.cgs,
convergence_strategy=config.montecarlo.convergence_strategy,
nthreads=config.montecarlo.nthreads,
)
def setup(self):
filename = 'tardis_configv1_artis_density.yml'
self.config = Configuration.from_yaml(data_path(filename))
self.model = Radial1DModel.from_config(self.config)
def setup(self):
"""Initialize config and model."""
filename = "tardis_configv1_verysimple.yml"
self.config = Configuration.from_yaml(data_path(filename))
self.model = Radial1DModel.from_config(self.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
