SpectrumSimulation

class gammapy.spectrum.SpectrumSimulation(livetime, source_model, aeff, edisp=None, background_model=None, alpha=None)

Bases: object

Simulate SpectrumObservation.

For a usage example see spectrum_simulation.ipynb

Parameters:

livetime : Quantity

Livetime

source_model : SpectralModel

Source model

aeff : EffectiveAreaTable

Effective Area

edisp : EnergyDispersion, optional

Energy Dispersion

background_model : SpectralModel, optional

Background model

alpha : float, optional

Exposure ratio between source and background

Attributes Summary

e_reco	Reconstruced 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

Reconstruced energy binning

npred_background

Predicted background CountsSpectrum

calls gammapy.spectrum.utils.CountsPredictor()

npred_source

Predicted source CountsSpectrum

calls gammapy.spectrum.utils.CountsPredictor()

Methods Documentation

reset()

Clear all results

run(seed)

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)

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: `~numpy.random.RandomState`

random state

simulate_obs(obs_id, seed='random-seed')

Simulate one SpectrumObservation.

The result is stored as obs attribute

Parameters:

obs_id : int

Observation identifier

seed : {int, ‘random-seed’, ‘global-rng’, RandomState}

see :func:~`gammapy.utils.random.get_random_state`

simulate_source_counts(rand)

Simulate source PHACountsSpectrum

Source counts are added to the on vector.

Parameters:

rand: `~numpy.random.RandomState`

random state