def from_geoms(
cls,
geom,
geom_exposure,
geom_psf,
geom_edisp,
reference_time="2000-01-01",
name="",
**kwargs,
):
"""
Create a MapDatasetOnOff object with zero filled maps according to the specified geometries
Parameters
----------
geom : `Geom`
geometry for the counts, counts_off, acceptance and acceptance_off maps
geom_exposure : `Geom`
geometry for the exposure map
geom_psf : `Geom`
geometry for the psf map
geom_edisp : `Geom`
geometry for the energy dispersion map
reference_time : `~astropy.time.Time`
the reference time to use in GTI definition
name : str
Name of the dataset.
Returns
-------
empty_maps : `MapDatasetOnOff`
A MapDatasetOnOff containing zero filled maps
"""
maps = {}
for name in ["counts", "counts_off", "acceptance", "acceptance_off"]:
maps[name] = Map.from_geom(geom, unit="")
exposure = Map.from_geom(geom_exposure, unit="m2 s")
edisp = EDispMap.from_geom(geom_edisp)
psf = PSFMap.from_geom(geom_psf)
gti = GTI.create([] * u.s, [] * u.s, reference_time=reference_time)
mask_safe = Map.from_geom(geom, dtype=bool)
return cls(
counts=maps["counts"],
counts_off=maps["counts_off"],
acceptance=maps["acceptance"],
acceptance_off=maps["acceptance_off"],
exposure=exposure,
psf=psf,
edisp=edisp,
gti=gti,
mask_safe=mask_safe,
name=name,
**kwargs,
)
def from_hdulist(cls, hdulist, name=""):
"""Create map dataset from list of HDUs.
Parameters
----------
hdulist : `~astropy.io.fits.HDUList`
List of HDUs.
Returns
-------
dataset : `MapDataset`
Map dataset.
"""
kwargs = {"name": name}
if "COUNTS" in hdulist:
kwargs["counts"] = Map.from_hdulist(hdulist, hdu="counts")
if "EXPOSURE" in hdulist:
kwargs["exposure"] = Map.from_hdulist(hdulist, hdu="exposure")
if "BACKGROUND" in hdulist:
background_map = Map.from_hdulist(hdulist, hdu="background")
kwargs["background_model"] = BackgroundModel(background_map)
if "EDISP_MATRIX" in hdulist:
kwargs["edisp"] = EnergyDispersion.from_hdulist(
hdulist, hdu1="EDISP_MATRIX", hdu2="EDISP_MATRIX_EBOUNDS"
)
if "EDISP" in hdulist:
edisp_map = Map.from_hdulist(hdulist, hdu="edisp")
exposure_map = Map.from_hdulist(hdulist, hdu="edisp_exposure")
kwargs["edisp"] = EDispMap(edisp_map, exposure_map)
if "PSF_KERNEL" in hdulist:
psf_map = Map.from_hdulist(hdulist, hdu="psf_kernel")
kwargs["psf"] = PSFKernel(psf_map)
if "PSF" in hdulist:
psf_map = Map.from_hdulist(hdulist, hdu="psf")
exposure_map = Map.from_hdulist(hdulist, hdu="psf_exposure")
kwargs["psf"] = PSFMap(psf_map, exposure_map)
if "MASK_SAFE" in hdulist:
mask_safe = Map.from_hdulist(hdulist, hdu="mask_safe")
mask_safe.data = mask_safe.data.astype(bool)
kwargs["mask_safe"] = mask_safe
if "MASK_FIT" in hdulist:
mask_fit = Map.from_hdulist(hdulist, hdu="mask_fit")
mask_fit.data = mask_fit.data.astype(bool)
kwargs["mask_fit"] = mask_fit
if "GTI" in hdulist:
gti = GTI(Table.read(hdulist, hdu="GTI"))
kwargs["gti"] = gti
return cls(**kwargs)
def from_geoms(
cls,
geom,
geom_exposure,
geom_psf,
geom_edisp,
reference_time="2000-01-01",
name="",
**kwargs,
):
"""
Create a MapDataset object with zero filled maps according to the specified geometries
Parameters
----------
geom : `Geom`
geometry for the counts and background maps
geom_exposure : `Geom`
geometry for the exposure map
geom_psf : `Geom`
geometry for the psf map
geom_edisp : `Geom`
geometry for the energy dispersion map
reference_time : `~astropy.time.Time`
the reference time to use in GTI definition
name : str
Name of the dataset.
Returns
-------
empty_maps : `MapDataset`
A MapDataset containing zero filled maps
"""
counts = Map.from_geom(geom, unit="")
background = Map.from_geom(geom, unit="")
background_model = BackgroundModel(background)
exposure = Map.from_geom(geom_exposure, unit="m2 s")
edisp = EDispMap.from_geom(geom_edisp)
psf = PSFMap.from_geom(geom_psf)
gti = GTI.create([] * u.s, [] * u.s, reference_time=reference_time)
mask_safe = Map.from_geom(geom, unit="", dtype=bool)
return cls(
counts=counts,
exposure=exposure,
psf=psf,
edisp=edisp,
background_model=background_model,
gti=gti,
mask_safe=mask_safe,
name=name,
**kwargs,
)
def create(
cls,
geom,
geom_irf=None,
migra_axis=None,
rad_axis=None,
reference_time="2000-01-01",
name="",
**kwargs
):
"""Creates a MapDataset object with zero filled maps
Parameters
----------
geom: `~gammapy.maps.WcsGeom`
Reference target geometry in reco energy, used for counts and background maps
geom_irf: `~gammapy.maps.WcsGeom`
Reference image geometry in true energy, used for IRF maps.
migra_axis: `~gammapy.maps.MapAxis`
Migration axis for the energy dispersion map
rad_axis: `~gammapy.maps.MapAxis`
Rad axis for the psf map
name : str
Name of the dataset.
"""
geom_irf = geom_irf or geom.to_binsz(BINSZ_IRF)
migra_axis = migra_axis or MIGRA_AXIS_DEFAULT
rad_axis = rad_axis or RAD_AXIS_DEFAULT
counts = Map.from_geom(geom, unit="")
background = Map.from_geom(geom, unit="")
background_model = BackgroundModel(background)
energy_axis = geom_irf.get_axis_by_name("ENERGY")
exposure_geom = geom.to_image().to_cube([energy_axis])
exposure = Map.from_geom(exposure_geom, unit="m2 s")
exposure_irf = Map.from_geom(geom_irf, unit="m2 s")
mask_safe = np.zeros(geom.data_shape, dtype=bool)
gti = GTI.create([] * u.s, [] * u.s, reference_time=reference_time)
geom_migra = geom_irf.to_image().to_cube([migra_axis, energy_axis])
edisp_map = Map.from_geom(geom_migra, unit="")
loc = migra_axis.edges.searchsorted(1.0)
edisp_map.data[:, loc, :, :] = 1.0
edisp = EDispMap(edisp_map, exposure_irf)
geom_rad = geom_irf.to_image().to_cube([rad_axis, energy_axis])
psf_map = Map.from_geom(geom_rad, unit="sr-1")
psf = PSFMap(psf_map, exposure_irf)
return cls(
counts=counts,
exposure=exposure,
psf=psf,
edisp=edisp,
background_model=background_model,
gti=gti,
mask_safe=mask_safe,
name=name,
**kwargs
)