def test_sky_models_io(tmp_path):
# TODO: maybe change to a test case where we create a model programatically?
filename = get_pkg_data_filename("data/examples.yaml")
models = SkyModels.from_yaml(filename)
models.to_yaml(tmp_path / "tmp.yaml")
models = SkyModels.from_yaml(tmp_path / "tmp.yaml")
assert_allclose(models.parameters["lat_0"].min, -90.0)
def set_model(self, model=None, filename=""):
"""Read the model from dict or filename and attach it to datasets.
Parameters
----------
model: dict or string
Dictionary or string in YAML format with the serialized model.
filename : string
Name of the model YAML file describing the model.
"""
if not self._validate_set_model():
return False
log.info(f"Reading model.")
if isinstance(model, str):
model = yaml.safe_load(model)
if model:
self.model = SkyModels(dict_to_models(model))
elif filename:
filepath = make_path(filename)
self.model = SkyModels.from_yaml(filepath)
else:
return False
# TODO: Deal with multiple components
for dataset in self.datasets.datasets:
if isinstance(dataset, MapDataset):
dataset.model = self.model
else:
if len(self.model.skymodels) > 1:
raise ValueError(
"Can only fit a single spectral model at one time."
)
dataset.model = self.model.skymodels[0].spectral_model
log.info(self.model)
def test_missing_parameters():
filename = get_pkg_data_filename("data/examples.yaml")
models = SkyModels.from_yaml(filename)
assert models["source1"].spatial_model.e in models.parameters
assert len(models["source1"].spatial_model.parameters) == 6