ObservationStats

class gammapy.data.ObservationStats(n_on=None, n_off=None, a_on=None, a_off=None, obs_id=None, livetime=None, alpha=None, gamma_rate=None, bg_rate=None)

Bases: gammapy.stats.Stats

Observation statistics.

Class allowing to summarize observation (DataStoreObservation) statistics

Parameters:

n_on : int

Number of on events

n_off : int

Number of off events

a_on : float

Relative background exposure of the on region

a_off : float

Relative background exposure of the off region

obs_id : int

ID of the observation

livetime : float

Livetime of the observation

alpha : float

Normalisation between the on and the off exposure

bg_rate : float

Background rate (/min)

gamma_rate : float

Gamma rate (/min)

Attributes Summary

alpha	Alpha (on / off exposure ratio)
background	Background estimate (float)
excess	Excess (float)
sigma	Li-Ma significance for observation statistics (float).

Methods Summary

from_obs(obs, bg_estimate)	Create from DataStoreObservation.
stack(stats_list)	Stack (concatenate) list of ObservationStats.
to_dict()	Data as a dict.

Attributes Documentation

alpha

Alpha (on / off exposure ratio)

Override member function from Stats to take into account weighted alpha by number of Off events

background

Background estimate (float)

\[\mu_\mathrm{bg} = \alpha\ n_\mathrm{off}\]

excess

Excess (float)

\[n_\mathrm{ex} = n_\mathrm{on} - \mu_\mathrm{bg}\]

sigma

Li-Ma significance for observation statistics (float).

Methods Documentation

classmethod from_obs(obs, bg_estimate)

Create from DataStoreObservation.

Parameters:

obs : DataStoreObservation

IACT data store observation

bg_estimate : BackgroundEstimate

Background estimate

classmethod stack(stats_list)

Stack (concatenate) list of ObservationStats.

Parameters:

stats_list : list

List of ObservationStats

Returns:

total_stats : ObservationStats

Statistics for stacked observation

to_dict()

Data as a dict.

This is useful for serialisation or putting the info in a table.