def _make_source_object(self, index):
"""Make one source object.
Parameters
----------
index : int
Row index
Returns
-------
source : `SourceCatalogObject`
Source object
"""
data = table_row_to_dict(self.table[index])
data[SourceCatalogObject._row_index_key] = index
if "Extended_Source_Name" in data:
name_extended = data["Extended_Source_Name"].strip()
elif "Source_Name" in data:
name_extended = data["Source_Name"].strip()
else:
name_extended = None
try:
idx = self._lookup_extended_source_idx[name_extended]
data_extended = table_row_to_dict(self.extended_sources_table[idx])
except (KeyError, AttributeError):
data_extended = None
source = self.source_object_class(data, data_extended)
return source
def _make_source_object(self, index):
"""Make one source object.
Parameters
----------
index : int
Row index
Returns
-------
source : `SourceCatalogObject`
Source object
"""
data = table_row_to_dict(self.table[index])
data[SourceCatalogObject._row_index_key] = index
fp_energy_edges = getattr(self, "flux_points_energy_edges", None)
if fp_energy_edges:
data["fp_energy_edges"] = fp_energy_edges
hist_table = getattr(self, "hist_table", None)
hist2_table = getattr(self, "hist2_table", None)
if hist_table:
try:
data["time_axis"] = TimeMapAxis.from_table(hist_table,
format="fermi-fgl")
except KeyError:
pass
if hist2_table:
try:
data["time_axis_2"] = TimeMapAxis.from_table(
hist2_table, format="fermi-fgl")
except KeyError:
pass
if "Extended_Source_Name" in data:
name_extended = data["Extended_Source_Name"].strip()
elif "Source_Name" in data:
name_extended = data["Source_Name"].strip()
else:
name_extended = None
try:
idx = self._lookup_extended_source_idx[name_extended]
data_extended = table_row_to_dict(self.extended_sources_table[idx])
except (KeyError, AttributeError):
data_extended = None
source = self.source_object_class(data, data_extended)
return source
def obs(self, obs_id):
"""Access a given `~gammapy.data.Observation`.
Parameters
----------
obs_id : int
Observation ID.
Returns
-------
observation : `~gammapy.data.Observation`
Observation container
"""
if obs_id not in self.obs_table["OBS_ID"]:
raise ValueError(f"OBS_ID = {obs_id} not in obs index table.")
if obs_id not in self.hdu_table["OBS_ID"]:
raise ValueError(f"OBS_ID = {obs_id} not in HDU index table.")
row = self.obs_table.select_obs_id(obs_id=obs_id)[0]
kwargs = {"obs_id": int(obs_id)}
kwargs["obs_info"] = table_row_to_dict(row)
hdu_list = ["events", "gti", "aeff", "edisp", "psf", "bkg"]
for hdu in hdu_list:
kwargs[hdu] = self.hdu_table.hdu_location(obs_id=obs_id,
hdu_type=hdu)
return Observation(**kwargs)
def estimate_time_bin_flux(self, datasets):
"""Estimate flux point for a single energy group.
Parameters
----------
datasets : `~gammapy.modeling.Datasets`
the list of dataset object
Returns
-------
result : dict
Dict with results for the flux point.
"""
if self.e_edges is None:
e_mins, e_maxs = datasets.energy_ranges
e_edges = e_mins.min(), e_maxs.max()
else:
e_edges = self.e_edges
fe = FluxPointsEstimator(
source=self.source,
e_edges=e_edges,
norm_min=self.norm_min,
norm_max=self.norm_max,
norm_n_values=self.norm_n_values,
norm_values=self.norm_values,
n_sigma=self.n_sigma,
n_sigma_ul=self.n_sigma_ul,
reoptimize=self.reoptimize,
selection_optional=self.selection_optional,
)
result = fe.run(datasets)
return table_row_to_dict(result.table[0])
def obs(self, obs_id):
"""Access a given `~gammapy.data.Observation`.
Parameters
----------
obs_id : int
Observation ID.
Returns
-------
observation : `~gammapy.data.Observation`
Observation container
"""
if obs_id not in self.obs_table["OBS_ID"]:
raise ValueError(f"OBS_ID = {obs_id} not in obs index table.")
if obs_id not in self.hdu_table["OBS_ID"]:
raise ValueError(f"OBS_ID = {obs_id} not in HDU index table.")
row = self.obs_table.select_obs_id(obs_id=obs_id)[0]
obs_info = table_row_to_dict(row)
aeff_hdu = self.hdu_table.hdu_location(obs_id=obs_id, hdu_type="aeff")
edisp_hdu = self.hdu_table.hdu_location(obs_id=obs_id,
hdu_type="edisp")
bkg_hdu = self.hdu_table.hdu_location(obs_id=obs_id, hdu_type="bkg")
psf_hdu = self.hdu_table.hdu_location(obs_id=obs_id, hdu_type="psf")
events_hdu = self.hdu_table.hdu_location(obs_id=obs_id,
hdu_type="events")
gti_hdu = self.hdu_table.hdu_location(obs_id=obs_id, hdu_type="gti")
return Observation(
obs_id=int(obs_id),
obs_info=obs_info,
bkg=bkg_hdu,
aeff=aeff_hdu,
edisp=edisp_hdu,
events=events_hdu,
gti=gti_hdu,
psf=psf_hdu,
)
def obs(self, obs_id):
"""Access a given `~gammapy.data.Observation`.
Parameters
----------
obs_id : int
Observation ID.
Returns
-------
observation : `~gammapy.data.Observation`
Observation container
"""
if obs_id not in self.obs_table["OBS_ID"]:
raise ValueError(f"OBS_ID = {obs_id} not in obs index table.")
if obs_id not in self.hdu_table["OBS_ID"]:
raise ValueError(f"OBS_ID = {obs_id} not in HDU index table.")
row = self.obs_table.select_obs_id(obs_id=obs_id)[0]
kwargs = {"obs_id": int(obs_id)}
# add info from table meta, e.g. the time references
kwargs["obs_info"] = {
k: v
for k, v in self.obs_table.meta.items()
if not k.startswith('HDU') # Ignore GADF structure of index table
}
kwargs["obs_info"].update(table_row_to_dict(row))
hdu_list = ["events", "gti", "aeff", "edisp", "psf", "bkg", "rad_max"]
for hdu in hdu_list:
kwargs[hdu] = self.hdu_table.hdu_location(obs_id=obs_id,
hdu_type=hdu)
return Observation(**kwargs)
def gaussian_component(self, row_idx):
"""Gaussian component (`SourceCatalogObjectHGPSComponent`)."""
data = table_row_to_dict(self.table_components[row_idx])
data[SourceCatalogObject._row_index_key] = row_idx
return SourceCatalogObjectHGPSComponent(data=data)
def _attach_identification_info(self, source):
t = self._table_identifications
idx = np.nonzero(source.name == t["Source_Name"])[0][0]
source.identification_info = table_row_to_dict(t[idx])
def obs_info(self):
"""Observation information (`~collections.OrderedDict`)."""
row = self.data_store.obs_table.select_obs_id(obs_id=self.obs_id)[0]
return table_row_to_dict(row)
def test_table_row_to_dict(table):
actual = table_row_to_dict(table[1])
expected = {"a": 2, "b": 2 * u.m, "c": "yy"}
assert actual == expected
def test_table_row_to_dict(table):
actual = table_row_to_dict(table[1])
expected = OrderedDict([("a", 2), ("b", 2 * u.m), ("c", "yy")])
assert actual == expected
