SpectrumSimulation¶
-
class
gammapy.spectrum.
SpectrumSimulation
(livetime, source_model, aeff=None, edisp=None, e_true=None, background_model=None, alpha=None)[source]¶ Bases:
object
Simulate
SpectrumObservation
.For a usage example see spectrum_simulation.html
Parameters: livetime :
Quantity
Livetime
source_model :
SpectralModel
Source model
aeff :
EffectiveAreaTable
, optionalEffective Area
edisp :
EnergyDispersion
, optionalEnergy Dispersion
e_true :
Quantity
, optionalDesired energy axis of the prediced counts vector if no IRFs are given
background_model :
SpectralModel
, optionalBackground model
alpha : float, optional
Exposure ratio between source and background
Attributes Summary
e_reco
Reconstructed energy binning. npred_background
Predicted background ( CountsSpectrum
).npred_source
Predicted source CountsSpectrum
.Methods Summary
reset
()Clear all results. run
(seed)Simulate SpectrumObservationList
.simulate_background_counts
(rand)Simulate background PHACountsSpectrum
.simulate_obs
(obs_id[, seed])Simulate one SpectrumObservation
.simulate_source_counts
(rand)Simulate source PHACountsSpectrum
.Attributes Documentation
-
e_reco
¶ Reconstructed energy binning.
-
npred_background
¶ Predicted background (
CountsSpectrum
).Calls
gammapy.spectrum.utils.CountsPredictor()
.
-
npred_source
¶ Predicted source
CountsSpectrum
.Calls
gammapy.spectrum.utils.CountsPredictor()
.
Methods Documentation
-
run
(seed)[source]¶ Simulate
SpectrumObservationList
.The seeds will be set as observation ID. Previously produced results will be overwritten.
Parameters: seed : array of ints
Random number generator seeds
-
simulate_background_counts
(rand)[source]¶ Simulate background
PHACountsSpectrum
.Background counts are added to the on vector. Furthermore background counts divided by alpha are added to the off vector.
TODO: At the moment the source IRFs are used. Make it possible to pass dedicated background IRFs.
Parameters: rand :
RandomState
random state
-
simulate_obs
(obs_id, seed='random-seed')[source]¶ Simulate one
SpectrumObservation
.The result is stored as
obs
attributeParameters: obs_id : int
Observation identifier
seed : {int, ‘random-seed’, ‘global-rng’,
RandomState
}see :func:~`gammapy.utils.random.get_random_state`
-
simulate_source_counts
(rand)[source]¶ Simulate source
PHACountsSpectrum
.Source counts are added to the on vector.
Parameters: rand :
RandomState
random state
-