ExcessMapEstimator¶
-
class
gammapy.estimators.
ExcessMapEstimator
(correlation_radius='0.1 deg', n_sigma=1, n_sigma_ul=3, selection_optional=None, energy_edges=None, apply_mask_fit=False, correlate_off=False, spectral_model=None)[source]¶ Bases:
gammapy.estimators.Estimator
Computes correlated excess, sqrt TS (i.e. Li-Ma significance) and errors for MapDatasets.
If a model is set on the dataset the excess map estimator will compute the excess taking into account the predicted counts of the model.
Some background estimation techniques like ring background or adaptive ring background will provide already correlated data for OFF. In the case of already correlated OFF data, the OFF data should not be correlated again, and so the option correlate_off should set to False (default).
- Parameters
- correlation_radius~astropy.coordinate.Angle
correlation radius to use
- n_sigmafloat
Confidence level for the asymmetric errors expressed in number of sigma. Default is 1.
- n_sigma_ulfloat
Confidence level for the upper limits expressed in number of sigma. Default is 3.
- selection_optionallist of str
Which additional maps to estimate besides delta TS, significance and symmetric error. Available options are:
“all”: all the optional steps are executed
“errn-errp”: estimate asymmetric errors.
“ul”: estimate upper limits.
Default is None so the optionnal steps are not executed.
- energy_edges
Quantity
Energy edges of the target excess maps bins.
- apply_mask_fitBool
Apply a mask for the computation. A
mask_fit
must be present on the input dataset- correlate_offBool
Correlate OFF events in the case of a MapDatasetOnOff
- spectral_model
SpectralModel
Spectral model used for the computation of the flux map. If None, a Power Law of index 2 is assumed (default).
Attributes Summary
Config parameters
Methods Summary
copy
()Copy estimator
estimate_excess_map
(dataset)Estimate excess and ts maps for single dataset.
get_sqrt_ts
(ts, norm)Compute sqrt(TS) value.
run
(dataset)Compute correlated excess, Li & Ma significance and flux maps
Attributes Documentation
-
config_parameters
¶ Config parameters
-
correlation_radius
¶
-
selection_optional
¶
-
tag
= 'ExcessMapEstimator'¶
Methods Documentation
-
copy
()¶ Copy estimator
-
estimate_excess_map
(dataset)[source]¶ Estimate excess and ts maps for single dataset.
If exposure is defined, a flux map is also computed.
- Parameters
- dataset
MapDataset
Map dataset
- dataset
-
static
get_sqrt_ts
(ts, norm)¶ Compute sqrt(TS) value.
Compute sqrt(TS) as defined by:
\[\begin{split}\sqrt{TS} = \left \{ \begin{array}{ll} -\sqrt{TS} & : \text{if} \ norm < 0 \\ \sqrt{TS} & : \text{else} \end{array} \right.\end{split}\]
-
run
(dataset)[source]¶ Compute correlated excess, Li & Ma significance and flux maps
If a model is set on the dataset the excess map estimator will compute the excess taking into account the predicted counts of the model.
- Parameters
- dataset
MapDataset
orMapDatasetOnOff
input dataset
- dataset
- Returns
- imagesdict
Dictionary containing result correlated maps. Keys are:
counts : correlated counts map
background : correlated background map
excess : correlated excess map
ts : TS map
sqrt_ts : sqrt(delta TS), or Li-Ma significance map
err : symmetric error map (from covariance)
flux : flux map. An exposure map must be present in the dataset to compute flux map
errn : negative error map
errp : positive error map
ul : upper limit map