ExcessMapEstimator

class gammapy.estimators.ExcessMapEstimator(correlation_radius='0.1 deg', nsigma=1, nsigma_ul=3)

Bases: object

Computes correlated excess, significance and errors for MapDatasets.

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.

Attributes Summary

correlation_radius

Methods Summary

run(self, dataset[, steps])

Compute correlated excess, Li & Ma significance and flux maps

Attributes Documentation

correlation_radius

Methods Documentation

run(self, dataset, steps='all')

Compute correlated excess, Li & Ma significance and flux maps

Parameters

datasetMapDataset or MapDatasetOnOff

input image-like dataset

stepslist of str

Which steps to execute. Available options are:

• “ts”: estimate delta TS and significance

• “err”: estimate symmetric error

• “errn-errp”: estimate asymmetric errors.

• “ul”: estimate upper limits.

By default all steps are executed.

Returns

imagesdict

Dictionary containing result correlated maps. Keys are:

• counts : correlated counts map

• background : correlated background map

• excess : correlated excess map

• ts : delta TS map

• significance : sqrt(delta TS), or Li-Ma significance map

• err : symmetric error map (from covariance)

• errn : negative error map

• errp : positive error map

• ul : upper limit map