Source code for gammapy.makers.spectrum

# Licensed under a 3-clause BSD style license - see LICENSE.rst
import logging
from regions import CircleSkyRegion
from .map import MapDatasetMaker

__all__ = ["SpectrumDatasetMaker"]

log = logging.getLogger(__name__)


[docs] class SpectrumDatasetMaker(MapDatasetMaker): """Make spectrum for a single IACT observation. The IRFs and background are computed at a single fixed offset, which is recommended only for point-sources. Parameters ---------- selection : list of str, optional Select which maps to make, the available options are: 'counts', 'exposure', 'background', 'edisp'. By default, all maps are made. containment_correction : bool Apply containment correction for point sources and circular on regions. background_oversampling : int Background evaluation oversampling factor in energy. use_region_center : bool If True, approximate the IRFs by the value at the center of the region. If False, the IRFs are averaged over the entire. """ tag = "SpectrumDatasetMaker" available_selection = ["counts", "background", "exposure", "edisp"] def __init__( self, selection=None, containment_correction=False, background_oversampling=None, use_region_center=True, ): self.containment_correction = containment_correction self.use_region_center = use_region_center super().__init__( selection=selection, background_oversampling=background_oversampling )
[docs] def make_exposure(self, geom, observation): """Make exposure. Parameters ---------- geom : `~gammapy.maps.RegionGeom` Reference map geometry. observation : `~gammapy.data.Observation` Observation to compute effective area for. Returns ------- exposure : `~gammapy.maps.RegionNDMap` Exposure map. """ exposure = super().make_exposure( geom, observation, use_region_center=self.use_region_center ) is_pointlike = exposure.meta.get("is_pointlike", False) if is_pointlike and self.use_region_center is False: log.warning( "MapMaker: use_region_center=False should not be used with point-like IRF. " "Results are likely inaccurate." ) if self.containment_correction: if is_pointlike: raise ValueError( "Cannot apply containment correction for point-like IRF." ) if not isinstance(geom.region, CircleSkyRegion): raise TypeError( "Containment correction only supported for circular regions." ) offset = geom.separation(observation.get_pointing_icrs(observation.tmid)) containment = observation.psf.containment( rad=geom.region.radius, offset=offset, energy_true=geom.axes["energy_true"].center, ) exposure.quantity *= containment.reshape(geom.data_shape) return exposure
[docs] @staticmethod def make_counts(geom, observation): """Make counts map. If the `~gammapy.maps.RegionGeom` is built from a `~regions.CircleSkyRegion`, the latter will be directly used to extract the counts. If instead the `~gammapy.maps.RegionGeom` is built from a `~regions.PointSkyRegion`, the size of the ON region is taken from the `RAD_MAX_2D` table containing energy-dependent theta2 cuts. Parameters ---------- geom : `~gammapy.maps.Geom` Reference map geometry. observation : `~gammapy.data.Observation` Observation container. Returns ------- counts : `~gammapy.maps.RegionNDMap` Counts map. """ return super(SpectrumDatasetMaker, SpectrumDatasetMaker).make_counts( geom, observation )
[docs] def run(self, dataset, observation): """Make spectrum dataset. Parameters ---------- dataset : `~gammapy.spectrum.SpectrumDataset` Reference dataset. observation : `~gammapy.data.Observation` Observation. Returns ------- dataset : `~gammapy.spectrum.SpectrumDataset` Spectrum dataset. """ return super(SpectrumDatasetMaker, self).run(dataset, observation)