SensitivityEstimator

class gammapy.estimators.SensitivityEstimator(spectrum=None, n_sigma=5.0, gamma_min=10, bkg_syst_fraction=0.05)

Bases: gammapy.estimators.core.Estimator

Estimate differential sensitivity.

This class allows to determine for each reconstructed energy bin the flux associated to the number of gamma-ray events for which the significance is n_sigma, and being larger than gamma_min and bkg_sys percent larger than the number of background events in the ON region.

Parameters

spectrumSpectralModel

Spectral model assumption. Default is Power Law with index 2.

n_sigmafloat, optional

Minimum significance. Default is 5.

gamma_minfloat, optional

Minimum number of gamma-rays. Default is 10.

bkg_syst_fractionfloat, optional

Fraction of background counts above which the number of gamma-rays is. Default is 0.05

Examples

For a usage example see Point source sensitivity tutorial.

Attributes Summary

config_parameters	Config parameters
selection_optional
tag

Methods Summary

copy()	Copy estimator
estimate_min_e2dnde(excess, dataset)	Estimate dnde from given min.
estimate_min_excess(dataset)	Estimate minimum excess to reach the given significance.
run(dataset)	Run the sensitivity estimation

Attributes Documentation

config_parameters

Config parameters

selection_optional

tag = 'SensitivityEstimator'

Methods Documentation

copy()

Copy estimator

estimate_min_e2dnde(excess, dataset)

Estimate dnde from given min. excess

Parameters

excessRegionNDMap

Minimal excess

datasetSpectrumDataset

Spectrum dataset

Returns

e2dndeQuantity

Minimal differential flux.

estimate_min_excess(dataset)

Estimate minimum excess to reach the given significance.

Parameters

datasetSpectrumDataset

Spectrum dataset

Returns

excessRegionNDMap

Minimal excess

run(dataset)

Run the sensitivity estimation

Parameters

datasetSpectrumDatasetOnOff

Dataset to compute sensitivity for.

Returns

sensitivityTable

Sensitivity table