def make_map_background_irf_with_symmetry(fpi, symmetry="constant"):
axis = MapAxis.from_edges([0.1, 1, 10],
name="energy",
unit="TeV",
interp="log")
return make_map_background_irf(
pointing=fpi,
ontime="42 s",
bkg=bkg_3d_custom(symmetry),
geom=WcsGeom.create(npix=(3, 3),
binsz=4,
axes=[axis],
skydir=fpi.radec),
)
def test_make_map_background_irf(bkg_3d, pars, fixed_pointing_info):
m = make_map_background_irf(
pointing=fixed_pointing_info,
ontime="42 s",
bkg=bkg_3d,
geom=geom(
map_type=pars["map_type"],
ebounds=pars["ebounds"],
skydir=fixed_pointing_info.radec,
),
oversampling=10,
)
assert m.data.shape == pars["shape"]
assert m.unit == ""
assert_allclose(m.data.sum(), pars["sum"], rtol=1e-5)
offset = Angle("2 deg")
# In[ ]:
exposure = make_map_exposure_true_energy(pointing=pointing.radec,
livetime=livetime,
aeff=irfs["aeff"],
geom=geom)
exposure.slice_by_idx({
"energy": 3
}).plot(add_cbar=True)
# In[ ]:
background = make_map_background_irf(pointing=pointing,
ontime=livetime,
bkg=irfs["bkg"],
geom=geom)
background.slice_by_idx({
"energy": 3
}).plot(add_cbar=True)
# In[ ]:
psf = irfs["psf"].to_energy_dependent_table_psf(theta=offset)
psf_kernel = PSFKernel.from_table_psf(psf, geom, max_radius=0.3 * u.deg)
psf_kernel.psf_kernel_map.sum_over_axes().plot(stretch="log")
# In[ ]:
energy = axis.edges
edisp = irfs["edisp"].to_energy_dispersion(offset,
def simulate_dataset(
skymodel,
geom,
pointing,
irfs,
livetime=1 * u.h,
offset=0 * u.deg,
max_radius=0.8 * u.deg,
random_state="random-seed",
):
"""Simulate a 3D dataset.
Simulate a source defined with a sky model for a given pointing,
geometry and irfs for a given exposure time.
This will return a dataset object which includes the counts cube,
the exposure cube, the psf cube, the background model and the sky model.
Parameters
----------
skymodel : `~gammapy.modeling.models.SkyModel`
Background model map
geom : `~gammapy.maps.WcsGeom`
Geometry object for the observation
pointing : `~astropy.coordinates.SkyCoord`
Pointing position
irfs : dict
Irfs used for simulating the observation
livetime : `~astropy.units.Quantity`
Livetime exposure of the simulated observation
offset : `~astropy.units.Quantity`
Offset from the center of the pointing position.
This is used for the PSF and Edisp estimation
max_radius : `~astropy.coordinates.Angle`
The maximum radius of the PSF kernel.
random_state: {int, 'random-seed', 'global-rng', `~numpy.random.RandomState`}
Defines random number generator initialisation.
Returns
-------
dataset : `~gammapy.cube.MapDataset`
A dataset of the simulated observation.
"""
background = make_map_background_irf(
pointing=pointing, ontime=livetime, bkg=irfs["bkg"], geom=geom
)
background_model = BackgroundModel(background)
psf = irfs["psf"].to_energy_dependent_table_psf(theta=offset)
psf_kernel = PSFKernel.from_table_psf(psf, geom, max_radius=max_radius)
exposure = make_map_exposure_true_energy(
pointing=pointing, livetime=livetime, aeff=irfs["aeff"], geom=geom
)
if "edisp" in irfs:
energy = geom.axes[0].edges
edisp = irfs["edisp"].to_energy_dispersion(offset, e_reco=energy, e_true=energy)
else:
edisp = None
dataset = MapDataset(
model=skymodel,
exposure=exposure,
background_model=background_model,
psf=psf_kernel,
edisp=edisp,
)
npred_map = dataset.npred()
rng = get_random_state(random_state)
counts = rng.poisson(npred_map.data)
dataset.counts = WcsNDMap(geom, counts)
return dataset