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 from_yaml(cls, yaml_str):
"""Create from YAML string."""
from gammapy.modeling.serialize import dict_to_models
data = yaml.safe_load(yaml_str)
models = dict_to_models(data)
return cls(models)
def from_yaml(cls, filename):
"""Write to YAML file."""
from gammapy.modeling.serialize import dict_to_models
data = read_yaml(filename)
skymodels = dict_to_models(data)
return cls(skymodels)
def set_models(self, models):
"""Set models on datasets.
Parameters
----------
models : `~gammapy.modeling.models.Models` or str
Models object or YAML models string
"""
if not self.datasets or len(self.datasets) == 0:
raise RuntimeError("Missing datasets")
log.info(f"Reading model.")
if isinstance(models, str):
# FIXME: Models should offer a method to create from YAML str
models = yaml.safe_load(models)
self.models = Models(dict_to_models(models))
elif isinstance(models, Models):
self.models = models
else:
raise TypeError(f"Invalid type: {models!r}")
for dataset in self.datasets:
dataset.models = self.models
log.info(self.models)
def test_dict_to_skymodels():
filename = get_pkg_data_filename("data/examples.yaml")
models_data = read_yaml(filename)
models = dict_to_models(models_data)
assert len(models) == 3
model0 = models[0]
assert model0.spectral_model.tag == "ExpCutoffPowerLawSpectralModel"
assert model0.spatial_model.tag == "PointSpatialModel"
pars0 = model0.parameters
assert pars0["index"].value == 2.1
assert pars0["index"].unit == ""
assert np.isnan(pars0["index"].max)
assert np.isnan(pars0["index"].min)
assert pars0["index"].frozen is False
assert pars0["lon_0"].value == -50.0
assert pars0["lon_0"].unit == "deg"
assert pars0["lon_0"].max == 180.0
assert pars0["lon_0"].min == -180.0
assert pars0["lon_0"].frozen is True
assert pars0["lat_0"].value == -0.05
assert pars0["lat_0"].unit == "deg"
assert pars0["lat_0"].max == 90.0
assert pars0["lat_0"].min == -90.0
assert pars0["lat_0"].frozen is True
assert pars0["lambda_"].value == 0.06
assert pars0["lambda_"].unit == "TeV-1"
assert np.isnan(pars0["lambda_"].min)
assert np.isnan(pars0["lambda_"].max)
model1 = models[1]
assert model1.spectral_model.tag == "PowerLawSpectralModel"
assert model1.spatial_model.tag == "DiskSpatialModel"
pars1 = model1.parameters
assert pars1["index"].value == 2.2
assert pars1["index"].unit == ""
assert pars1["lat_0"].scale == 1.0
assert pars1["lat_0"].factor == pars1["lat_0"].value
assert np.isnan(pars1["index"].max)
assert np.isnan(pars1["index"].min)
assert pars1["r_0"].unit == "deg"
model2 = models[2]
assert_allclose(model2.spectral_model.energy.data,
[34.171, 44.333, 57.517])
assert model2.spectral_model.energy.unit == "MeV"
assert_allclose(model2.spectral_model.values.data,
[2.52894e-06, 1.2486e-06, 6.14648e-06])
assert model2.spectral_model.values.unit == "1 / (cm2 MeV s sr)"
assert model2.spectral_model.tag == "TemplateSpectralModel"
assert model2.spatial_model.tag == "TemplateSpatialModel"
assert model2.spatial_model.parameters["norm"].value == 1.0
assert model2.spatial_model.normalize is False
assert model2.spectral_model.parameters["norm"].value == 2.1