def spectrum_dataset():
energy = np.logspace(-1, 1, 31) * u.TeV
livetime = 100 * u.s
pwl = PowerLawSpectralModel(
index=2.1,
amplitude="1e5 cm-2 s-1 TeV-1",
reference="0.1 TeV",
)
model = SkyModel(spectral_model=pwl, name="test-source")
aeff = EffectiveAreaTable.from_constant(energy, "1 cm2")
axis = MapAxis.from_edges(energy, interp="log", name="energy")
background = RegionNDMap.create(region="icrs;circle(0, 0, 0.1)", axes=[axis])
bkg_rate = np.ones(30) / u.s
background.quantity = bkg_rate * livetime
dataset = SpectrumDataset(
models=model,
aeff=aeff,
livetime=livetime,
background=background,
name="test",
)
dataset.fake(random_state=23)
return dataset
def spectrum_dataset():
name = "test"
energy = np.logspace(-1, 1, 31) * u.TeV
livetime = 100 * u.s
pwl = PowerLawSpectralModel(
index=2.1, amplitude="1e5 cm-2 s-1 TeV-1", reference="0.1 TeV",
)
temp_mod = ConstantTemporalModel()
model = SkyModel(spectral_model=pwl, temporal_model=temp_mod, name="test-source")
axis = MapAxis.from_edges(energy, interp="log", name="energy")
axis_true = MapAxis.from_edges(energy, interp="log", name="energy_true")
background = RegionNDMap.create(region="icrs;circle(0, 0, 0.1)", axes=[axis])
models = Models([model])
exposure = RegionNDMap.create(region="icrs;circle(0, 0, 0.1)", axes=[axis_true])
exposure.quantity = u.Quantity("1 cm2") * livetime
bkg_rate = np.ones(30) / u.s
background.quantity = bkg_rate * livetime
start = [1, 3, 5] * u.day
stop = [2, 3.5, 6] * u.day
t_ref = Time(55555, format="mjd")
gti = GTI.create(start, stop, reference_time=t_ref)
dataset = SpectrumDataset(
models=models, exposure=exposure, background=background, name=name, gti=gti,
)
dataset.fake(random_state=23)
return dataset
