def make_edisp_map_test():
etrue = [0.2, 0.7, 1.5, 2.0, 10.0] * u.TeV
migra = np.linspace(0.0, 3.0, 51)
offsets = np.array((0.0, 1.0, 2.0, 3.0)) * u.deg
pointing = SkyCoord(0, 0, unit="deg")
energy_axis = MapAxis(
nodes=[0.2, 0.7, 1.5, 2.0, 10.0],
unit="TeV",
name="energy_true",
node_type="edges",
interp="log",
)
migra_axis = MapAxis(nodes=np.linspace(0.0, 3.0, 51), unit="", name="migra")
edisp2d = EnergyDispersion2D.from_gauss(etrue, migra, 0.0, 0.2, offsets)
geom = WcsGeom.create(
skydir=pointing, binsz=1.0, width=5.0, axes=[migra_axis, energy_axis]
)
aeff2d = fake_aeff2d()
exposure_geom = geom.squash(axis_name="migra")
exposure_map = make_map_exposure_true_energy(pointing, "1 h", aeff2d, exposure_geom)
return make_edisp_map(edisp2d, pointing, geom, exposure_map)
def make_edisp_map_test():
pointing = SkyCoord(0, 0, unit="deg")
energy_axis_true = MapAxis.from_energy_edges(
energy_edges=[0.2, 0.7, 1.5, 2.0, 10.0] * u.TeV,
name="energy_true",
)
migra_axis = MapAxis(nodes=np.linspace(0.0, 3.0, 51), unit="", name="migra")
offset_axis = MapAxis.from_nodes([0.0, 1.0, 2.0, 3.0] * u.deg, name="offset")
edisp2d = EnergyDispersion2D.from_gauss(
energy_axis_true=energy_axis_true,
migra_axis=migra_axis,
offset_axis=offset_axis,
bias=0,
sigma=0.2,
)
geom = WcsGeom.create(
skydir=pointing, binsz=1.0, width=5.0, axes=[migra_axis, energy_axis_true]
)
aeff2d = fake_aeff2d()
exposure_geom = geom.squash(axis_name="migra")
exposure_map = make_map_exposure_true_energy(pointing, "1 h", aeff2d, exposure_geom)
return make_edisp_map(edisp2d, pointing, geom, exposure_map)
def test_make_map_exposure_true_energy(aeff, pars):
m = make_map_exposure_true_energy(
pointing=SkyCoord(2, 1, unit="deg"),
livetime="42 s",
aeff=aeff,
geom=pars["geom"],
)
assert m.data.shape == pars["shape"]
assert m.unit == "m2 s"
assert_allclose(m.data.sum(), pars["sum"], rtol=1e-5)
def simulate_spectrum_dataset(model, random_state=0):
energy_edges = np.logspace(-0.5, 1.5, 21) * u.TeV
energy_axis = MapAxis.from_edges(energy_edges, interp="log", name="energy")
energy_axis_true = energy_axis.copy(name="energy_true")
aeff = EffectiveAreaTable2D.from_parametrization(
energy_axis_true=energy_axis_true)
bkg_model = SkyModel(
spectral_model=PowerLawSpectralModel(index=2.5,
amplitude="1e-12 cm-2 s-1 TeV-1"),
name="background",
)
bkg_model.spectral_model.amplitude.frozen = True
bkg_model.spectral_model.index.frozen = True
geom = RegionGeom.create(region="icrs;circle(0, 0, 0.1)",
axes=[energy_axis])
acceptance = RegionNDMap.from_geom(geom=geom, data=1)
edisp = EDispKernelMap.from_diagonal_response(
energy_axis=energy_axis,
energy_axis_true=energy_axis_true,
geom=geom,
)
geom_true = RegionGeom.create(region="icrs;circle(0, 0, 0.1)",
axes=[energy_axis_true])
exposure = make_map_exposure_true_energy(pointing=SkyCoord("0d", "0d"),
aeff=aeff,
livetime=100 * u.h,
geom=geom_true)
mask_safe = RegionNDMap.from_geom(geom=geom, dtype=bool)
mask_safe.data += True
acceptance_off = RegionNDMap.from_geom(geom=geom, data=5)
dataset = SpectrumDatasetOnOff(
name="test_onoff",
exposure=exposure,
acceptance=acceptance,
acceptance_off=acceptance_off,
edisp=edisp,
mask_safe=mask_safe,
)
dataset.models = bkg_model
bkg_npred = dataset.npred_signal()
dataset.models = model
dataset.fake(
random_state=random_state,
npred_background=bkg_npred,
)
return dataset
def make_psf_map_obs(geom, obs):
exposure_map = make_map_exposure_true_energy(
geom=geom.squash(axis="theta"),
pointing=obs.pointing_radec,
aeff=obs.aeff,
livetime=obs.observation_live_time_duration,
)
psf_map = make_psf_map(
geom=geom, psf=obs.psf, pointing=obs.pointing_radec, exposure_map=exposure_map
)
return psf_map
def get_exposure(geom_etrue):
filename = (
"$GAMMAPY_DATA/cta-1dc/caldb/data/cta/1dc/bcf/South_z20_50h/irf_file.fits"
)
aeff = EffectiveAreaTable2D.read(filename, hdu="EFFECTIVE AREA")
exposure_map = make_map_exposure_true_energy(
pointing=SkyCoord(1, 0.5, unit="deg", frame="galactic"),
livetime=1 * u.hr,
aeff=aeff,
geom=geom_etrue,
)
return exposure_map
def make_test_psfmap(size, shape="gauss"):
psf = fake_psf3d(size, shape)
aeff2d = fake_aeff2d()
pointing = SkyCoord(0, 0, unit="deg")
energy_axis = MapAxis(
nodes=[0.2, 0.7, 1.5, 2.0, 10.0], unit="TeV", name="energy_true"
)
rad_axis = MapAxis.from_nodes(
nodes=np.linspace(0.0, 0.6, 50), unit="deg", name="theta"
)
geom = WcsGeom.create(
skydir=pointing, binsz=0.2, width=5, axes=[rad_axis, energy_axis]
)
exposure_geom = geom.squash(axis="theta")
exposure_map = make_map_exposure_true_energy(pointing, "1 h", aeff2d, exposure_geom)
return make_psf_map(psf, pointing, geom, exposure_map)
def test_spectrum_dataset_stack_nondiagonal_no_bkg(spectrum_dataset):
energy = spectrum_dataset.counts.geom.axes["energy"]
geom = spectrum_dataset.counts.geom
edisp1 = EDispKernelMap.from_gauss(
energy_axis=energy,
energy_axis_true=energy.copy(name="energy_true"),
sigma=0.1,
bias=0,
geom=geom.to_image(),
)
edisp1.exposure_map.data += 1
aeff = EffectiveAreaTable2D.from_parametrization(
energy_axis_true=energy.copy(name="energy_true"), instrument="HESS")
livetime = 100 * u.s
geom_true = geom.as_energy_true
exposure = make_map_exposure_true_energy(geom=geom_true,
livetime=livetime,
pointing=geom_true.center_skydir,
aeff=aeff)
geom = spectrum_dataset.counts.geom
counts = RegionNDMap.from_geom(geom=geom)
gti = GTI.create(start=0 * u.s, stop=livetime)
spectrum_dataset1 = SpectrumDataset(
counts=counts,
exposure=exposure,
edisp=edisp1,
meta_table=Table({"OBS_ID": [0]}),
gti=gti.copy(),
)
edisp2 = EDispKernelMap.from_gauss(
energy_axis=energy,
energy_axis_true=energy.copy(name="energy_true"),
sigma=0.2,
bias=0.0,
geom=geom,
)
edisp2.exposure_map.data += 1
gti2 = GTI.create(start=100 * u.s, stop=200 * u.s)
spectrum_dataset2 = SpectrumDataset(
counts=counts,
exposure=exposure.copy(),
edisp=edisp2,
meta_table=Table({"OBS_ID": [1]}),
gti=gti2,
)
spectrum_dataset1.stack(spectrum_dataset2)
assert_allclose(spectrum_dataset1.meta_table["OBS_ID"][0], [0, 1])
assert spectrum_dataset1.background_model is None
assert_allclose(spectrum_dataset1.gti.time_sum.to_value("s"), 200)
assert_allclose(spectrum_dataset1.exposure.quantity[2].to_value("m2 s"),
1573851.079861)
kernel = edisp1.get_edisp_kernel()
assert_allclose(kernel.get_bias(1 * u.TeV), 0.0, atol=1.2e-3)
assert_allclose(kernel.get_resolution(1 * u.TeV), 0.1581, atol=1e-2)
def test_spectrum_dataset_stack_diagonal_safe_mask(spectrum_dataset):
geom = spectrum_dataset.counts.geom
energy = MapAxis.from_energy_bounds("0.1 TeV", "10 TeV", nbin=30)
energy_true = MapAxis.from_energy_bounds("0.1 TeV",
"10 TeV",
nbin=30,
name="energy_true")
aeff = EffectiveAreaTable2D.from_parametrization(
energy_axis_true=energy_true, instrument="HESS")
livetime = 100 * u.s
gti = GTI.create(start=0 * u.s, stop=livetime)
geom_true = geom.as_energy_true
exposure = make_map_exposure_true_energy(geom=geom_true,
livetime=livetime,
pointing=geom_true.center_skydir,
aeff=aeff)
edisp = EDispKernelMap.from_diagonal_response(energy,
energy_true,
geom=geom.to_image())
edisp.exposure_map.data = exposure.data[:, :, np.newaxis, :]
background = spectrum_dataset.background
mask_safe = RegionNDMap.from_geom(geom=geom, dtype=bool)
mask_safe.data += True
spectrum_dataset1 = SpectrumDataset(
name="ds1",
counts=spectrum_dataset.counts.copy(),
exposure=exposure.copy(),
edisp=edisp.copy(),
background=background.copy(),
gti=gti.copy(),
mask_safe=mask_safe,
)
livetime2 = 0.5 * livetime
gti2 = GTI.create(start=200 * u.s, stop=200 * u.s + livetime2)
bkg2 = RegionNDMap.from_geom(geom=geom, data=2 * background.data)
geom = spectrum_dataset.counts.geom
data = np.ones(spectrum_dataset.data_shape, dtype="bool")
data[0] = False
safe_mask2 = RegionNDMap.from_geom(geom=geom, data=data)
exposure2 = exposure.copy()
edisp = edisp.copy()
edisp.exposure_map.data = exposure2.data[:, :, np.newaxis, :]
spectrum_dataset2 = SpectrumDataset(
name="ds2",
counts=spectrum_dataset.counts.copy(),
exposure=exposure2,
edisp=edisp,
background=bkg2,
mask_safe=safe_mask2,
gti=gti2,
)
spectrum_dataset1.stack(spectrum_dataset2)
reference = spectrum_dataset.counts.data
assert_allclose(spectrum_dataset1.counts.data[1:], reference[1:] * 2)
assert_allclose(spectrum_dataset1.counts.data[0], 141363)
assert_allclose(spectrum_dataset1.exposure.quantity[0],
4.755644e09 * u.Unit("cm2 s"))
assert_allclose(spectrum_dataset1.background.data[1:],
3 * background.data[1:])
assert_allclose(spectrum_dataset1.background.data[0], background.data[0])
kernel = edisp.get_edisp_kernel()
kernel_stacked = spectrum_dataset1.edisp.get_edisp_kernel()
assert_allclose(kernel_stacked.pdf_matrix[1:], kernel.pdf_matrix[1:])
assert_allclose(kernel_stacked.pdf_matrix[0], 0.5 * kernel.pdf_matrix[0])
# Define map geometry
axis = MapAxis.from_edges(np.logspace(-1.0, 1.0, 10),
unit="TeV",
name="energy")
geom = WcsGeom.create(skydir=(0, 0),
binsz=0.02,
width=(2, 2),
frame="galactic",
axes=[axis])
# Define some observation parameters
# we are not simulating many pointings / observations
pointing = SkyCoord(0.2, 0.5, unit="deg", frame="galactic")
livetime = 20 * u.hour
exposure_map = make_map_exposure_true_energy(pointing=pointing,
livetime=livetime,
aeff=aeff,
geom=geom)
dataset = MapDataset(models=models, exposure=exposure_map)
npred = dataset.npred()
dataset.fake()
fit = Fit([dataset])
results = fit.run()
print(results)
print(models)
