MapDatasetEventSampler

class gammapy.cube.MapDatasetEventSampler(random_state='random-seed')

Bases: object

Sample events from a map dataset

Parameters

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

Defines random number generator initialisation. Passed to get_random_state.

Methods Summary

event_list_meta(dataset, observation)	Event list meta info.
run(self, dataset[, observation])	Run the event sampler, applying IRF corrections.
sample_background(self, dataset)	Sample background
sample_edisp(self, edisp_map, events)	Sample energy dispersion map.
sample_psf(self, psf_map, events)	Sample psf map.
sample_sources(self, dataset)	Sample source model components.

Methods Documentation

static event_list_meta(dataset, observation)

Event list meta info.

Parameters

datasetMapDataset

Map dataset.

observationObservation

In memory observation.

Returns

metadict

Meta dictionary.

run(self, dataset, observation=None)

Run the event sampler, applying IRF corrections.

Parameters

datasetMapDataset

Map dataset

observationObservation

In memory observation.

edispBool

It allows to include or exclude the Edisp in the simulation.

Returns

eventsEventList

Event list.

sample_background(self, dataset)

Sample background

Parameters

datasetMapDataset

Map dataset

Returns

eventsgammapy.data.EventList

Background events

sample_edisp(self, edisp_map, events)

Sample energy dispersion map.

Parameters

edisp_mapEDispMap

Energy dispersion map

eventsEventList

Event list with the true energies

Returns

eventsEventList

Event list with reconstructed energy column.

sample_psf(self, psf_map, events)

Sample psf map.

Parameters

psf_mapPSFMap

PSF map.

eventsEventList

Event list.

Returns

eventsEventList

Event list with reconstructed position columns.

sample_sources(self, dataset)

Sample source model components.

Parameters

datasetMapDataset

Map dataset.

Returns

eventsEventList

Event list