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 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	Configuration parameters.
selection_optional
tag

Methods Summary

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

Attributes Documentation

config_parameters

Configuration parameters.

selection_optional

tag = 'SensitivityEstimator'

Methods Documentation

copy()

Copy estimator.

estimate_min_e2dnde(excess, dataset)

Estimate dnde from a given minimum 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.