Source code for gammapy.datasets.simulate

# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Simulate observations"""
import numpy as np
import astropy.units as u
from astropy.coordinates import AltAz, SkyCoord, SkyOffsetFrame
from astropy.table import Table
import gammapy
from gammapy.data import EventList, observatory_locations
from gammapy.maps import MapCoord
from gammapy.modeling.models import ConstantTemporalModel
from gammapy.utils.random import get_random_state

__all__ = ["MapDatasetEventSampler"]


[docs]class MapDatasetEventSampler: """Sample events from a map dataset Parameters ---------- random_state : {int, 'random-seed', 'global-rng', `~numpy.random.RandomState`} Defines random number generator initialisation. Passed to `~gammapy.utils.random.get_random_state`. """ def __init__(self, random_state="random-seed"): self.random_state = get_random_state(random_state) def _sample_coord_time(self, npred, temporal_model, gti): data = npred.data[np.isfinite(npred.data)] n_events = self.random_state.poisson(np.sum(data)) coords = npred.sample_coord(n_events=n_events, random_state=self.random_state) table = Table() try: energy = coords["energy_true"] except KeyError: energy = coords["energy"] table["ENERGY_TRUE"] = energy table["RA_TRUE"] = coords.skycoord.icrs.ra.to("deg") table["DEC_TRUE"] = coords.skycoord.icrs.dec.to("deg") time_start, time_stop, time_ref = (gti.time_start, gti.time_stop, gti.time_ref) time = temporal_model.sample_time( n_events=n_events, t_min=time_start, t_max=time_stop, random_state=self.random_state, ) table["TIME"] = u.Quantity(((time.mjd - time_ref.mjd) * u.day).to(u.s)).to("s") return table
[docs] def sample_sources(self, dataset): """Sample source model components. Parameters ---------- dataset : `~gammapy.datasets.MapDataset` Map dataset. Returns ------- events : `~gammapy.data.EventList` Event list """ events_all = [] for idx, evaluator in enumerate(dataset.evaluators.values()): if evaluator.needs_update: evaluator.update( dataset.exposure, dataset.psf, dataset.edisp, dataset._geom, dataset.mask, ) flux = evaluator.compute_flux() npred = evaluator.apply_exposure(flux) if evaluator.model.temporal_model is None: temporal_model = ConstantTemporalModel() else: temporal_model = evaluator.model.temporal_model table = self._sample_coord_time(npred, temporal_model, dataset.gti) if len(table) == 0: mcid = table.Column(name="MC_ID", length=0, dtype=int) table.add_column(mcid) table["MC_ID"] = idx + 1 table.meta["MID{:05d}".format(idx + 1)] = idx + 1 table.meta["MMN{:05d}".format(idx + 1)] = evaluator.model.name events_all.append(EventList(table)) return EventList.from_stack(events_all)
[docs] def sample_background(self, dataset): """Sample background Parameters ---------- dataset : `~gammapy.datasets.MapDataset` Map dataset Returns ------- events : `gammapy.data.EventList` Background events """ background = dataset.npred_background() temporal_model = ConstantTemporalModel() table = self._sample_coord_time(background, temporal_model, dataset.gti) table["MC_ID"] = 0 table["ENERGY"] = table["ENERGY_TRUE"] table["RA"] = table["RA_TRUE"] table["DEC"] = table["DEC_TRUE"] table.meta["MID{:05d}".format(0)] = 0 table.meta["MMN{:05d}".format(0)] = dataset.background_model.name return EventList(table)
[docs] def sample_edisp(self, edisp_map, events): """Sample energy dispersion map. Parameters ---------- edisp_map : `~gammapy.irf.EDispMap` Energy dispersion map events : `~gammapy.data.EventList` Event list with the true energies Returns ------- events : `~gammapy.data.EventList` Event list with reconstructed energy column. """ coord = MapCoord( { "lon": events.table["RA_TRUE"].quantity, "lat": events.table["DEC_TRUE"].quantity, "energy_true": events.table["ENERGY_TRUE"].quantity, }, frame="icrs", ) coords_reco = edisp_map.sample_coord(coord, self.random_state) events.table["ENERGY"] = coords_reco["energy"] return events
[docs] def sample_psf(self, psf_map, events): """Sample psf map. Parameters ---------- psf_map : `~gammapy.irf.PSFMap` PSF map. events : `~gammapy.data.EventList` Event list. Returns ------- events : `~gammapy.data.EventList` Event list with reconstructed position columns. """ coord = MapCoord( { "lon": events.table["RA_TRUE"].quantity, "lat": events.table["DEC_TRUE"].quantity, "energy_true": events.table["ENERGY_TRUE"].quantity, }, frame="icrs", ) coords_reco = psf_map.sample_coord(coord, self.random_state) events.table["RA"] = coords_reco["lon"] * u.deg events.table["DEC"] = coords_reco["lat"] * u.deg return events
[docs] @staticmethod def event_det_coords(observation, events): """Add columns of detector coordinates (DETX-DETY) to the event list. Parameters ---------- observation : `~gammapy.data.Observation` In memory observation. events : `~gammapy.data.EventList` Event list. Returns ------- events : `~gammapy.data.EventList` Event list with columns of event detector coordinates. """ sky_coord = SkyCoord(events.table["RA"], events.table["DEC"], frame="icrs") frame = SkyOffsetFrame(origin=observation.pointing_radec.icrs) pseudo_fov_coord = sky_coord.transform_to(frame) events.table["DETX"] = pseudo_fov_coord.lon events.table["DETY"] = pseudo_fov_coord.lat return events
[docs] @staticmethod def event_list_meta(dataset, observation): """Event list meta info. Parameters ---------- dataset : `~gammapy.datasets.MapDataset` Map dataset. observation : `~gammapy.data.Observation` In memory observation. Returns ------- meta : dict Meta dictionary. """ # See: https://gamma-astro-data-formats.readthedocs.io/en/latest/events/events.html#mandatory-header-keywords meta = {} meta["HDUCLAS1"] = "EVENTS" meta["EXTNAME"] = "EVENTS" meta[ "HDUDOC" ] = "https://github.com/open-gamma-ray-astro/gamma-astro-data-formats" meta["HDUVERS"] = "0.2" meta["HDUCLASS"] = "GADF" meta["OBS_ID"] = observation.obs_id meta["TSTART"] = ( ((observation.tstart.mjd - dataset.gti.time_ref.mjd) * u.day).to(u.s).value ) meta["TSTOP"] = ( ((observation.tstop.mjd - dataset.gti.time_ref.mjd) * u.day).to(u.s).value ) meta["ONTIME"] = observation.observation_time_duration.to("s").value meta["LIVETIME"] = observation.observation_live_time_duration.to("s").value meta["DEADC"] = 1 - observation.observation_dead_time_fraction meta["RA_PNT"] = observation.pointing_radec.icrs.ra.deg meta["DEC_PNT"] = observation.pointing_radec.icrs.dec.deg meta["EQUINOX"] = "J2000" meta["RADECSYS"] = "icrs" meta["CREATOR"] = "Gammapy {}".format(gammapy.__version__) meta["EUNIT"] = "TeV" meta["EVTVER"] = "" meta["OBSERVER"] = "Gammapy user" meta["DSTYP1"] = "TIME" meta["DSUNI1"] = "s" meta["DSVAL1"] = "TABLE" meta["DSREF1"] = ":GTI" meta["DSTYP2"] = "ENERGY" meta["DSUNI2"] = "TeV" meta[ "DSVAL2" ] = f'{dataset._geom.axes["energy"].edges.min().value}:{dataset._geom.axes["energy"].edges.max().value}' meta["DSTYP3"] = "POS(RA,DEC) " offset_max = np.max(dataset._geom.width).to_value("deg") meta[ "DSVAL3" ] = f"CIRCLE({observation.pointing_radec.ra.deg},{observation.pointing_radec.dec.deg},{offset_max})" meta["DSUNI3"] = "deg " meta["NDSKEYS"] = " 3 " # get first non background model component for model in dataset.models: if model is not dataset.background_model: break else: model = None if model: meta["OBJECT"] = model.name meta["RA_OBJ"] = model.position.icrs.ra.deg meta["DEC_OBJ"] = model.position.icrs.dec.deg meta["TELAPSE"] = dataset.gti.time_sum.to("s").value meta["MJDREFI"] = int(dataset.gti.time_ref.mjd) meta["MJDREFF"] = dataset.gti.time_ref.mjd % 1 meta["TIMEUNIT"] = "s" meta["TIMESYS"] = dataset.gti.time_ref.scale meta["TIMEREF"] = "LOCAL" meta["DATE-OBS"] = dataset.gti.time_start.isot[0][0:10] meta["DATE-END"] = dataset.gti.time_stop.isot[0][0:10] meta["CONV_DEP"] = 0 meta["CONV_RA"] = 0 meta["CONV_DEC"] = 0 meta["NMCIDS"] = len(dataset.models) # Necessary for DataStore, but they should be ALT and AZ instead! telescope = observation.aeff.meta["TELESCOP"] instrument = observation.aeff.meta["INSTRUME"] if telescope == "CTA": if instrument == "Southern Array": loc = observatory_locations["cta_south"] elif instrument == "Northern Array": loc = observatory_locations["cta_north"] else: loc = observatory_locations["cta_south"] else: loc = observatory_locations[telescope.lower()] # this is not really correct but maybe OK for now altaz_frame = AltAz(obstime=dataset.gti.time_start, location=loc) coord_altaz = observation.pointing_radec.transform_to(altaz_frame) meta["ALT_PNT"] = str(coord_altaz.alt.deg[0]) meta["AZ_PNT"] = str(coord_altaz.az.deg[0]) # TO DO: these keywords should be taken from the IRF of the dataset meta["ORIGIN"] = "Gammapy" meta["TELESCOP"] = observation.aeff.meta["TELESCOP"] meta["INSTRUME"] = observation.aeff.meta["INSTRUME"] meta["N_TELS"] = "" meta["TELLIST"] = "" meta["CREATED"] = "" meta["OBS_MODE"] = "" meta["EV_CLASS"] = "" return meta
[docs] def run(self, dataset, observation=None): """Run the event sampler, applying IRF corrections. Parameters ---------- dataset : `~gammapy.datasets.MapDataset` Map dataset observation : `~gammapy.data.Observation` In memory observation. edisp : Bool It allows to include or exclude the Edisp in the simulation. Returns ------- events : `~gammapy.data.EventList` Event list. """ if len(dataset.models) > 1: events_src = self.sample_sources(dataset) if len(events_src.table) > 0: if dataset.psf: events_src = self.sample_psf(dataset.psf, events_src) else: events_src.table["RA"] = events_src.table["RA_TRUE"] events_src.table["DEC"] = events_src.table["DEC_TRUE"] if dataset.edisp: events_src = self.sample_edisp(dataset.edisp, events_src) else: events_src.table["ENERGY"] = events_src.table["ENERGY_TRUE"] if dataset.background: events_bkg = self.sample_background(dataset) events = EventList.from_stack([events_bkg, events_src]) else: events = events_src if len(dataset.models) == 1 and dataset.background_model is not None: events_bkg = self.sample_background(dataset) events = EventList.from_stack([events_bkg]) events = self.event_det_coords(observation, events) events.table["EVENT_ID"] = np.arange(len(events.table)) events.table.meta.update(self.event_list_meta(dataset, observation)) geom = dataset._geom selection = geom.contains(events.map_coord(geom)) return events.select_row_subset(selection)