def test_from_parametrization():
# Log center of this is 100 GeV
area_ref = 1.65469579e07 * u.cm ** 2
axis = MapAxis.from_energy_edges([80, 125] * u.GeV, name="energy_true")
area = EffectiveAreaTable2D.from_parametrization(axis, "HESS")
assert_allclose(area.quantity, area_ref)
assert area.unit == area_ref.unit
# Log center of this is 0.1, 2 TeV
area_ref = [1.65469579e07, 1.46451957e09] * u.cm * u.cm
axis = MapAxis.from_energy_edges([0.08, 0.125, 32] * u.TeV, name="energy_true")
area = EffectiveAreaTable2D.from_parametrization(axis, "HESS")
assert_allclose(area.quantity[:, 0], area_ref)
assert area.unit == area_ref.unit
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 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])
import matplotlib.pyplot as plt
from gammapy.data import Observation, observatory_locations
from gammapy.datasets import SpectrumDataset
from gammapy.datasets.map import MIGRA_AXIS_DEFAULT
from gammapy.irf import EffectiveAreaTable2D, EnergyDispersion2D
from gammapy.makers import SpectrumDatasetMaker
from gammapy.maps import MapAxis, RegionGeom
from gammapy.modeling.models import PowerLawSpectralModel, SkyModel
energy_true = MapAxis.from_energy_bounds(
"0.1 TeV", "20 TeV", nbin=20, per_decade=True, name="energy_true"
)
energy_reco = MapAxis.from_energy_bounds("0.2 TeV", "10 TeV", nbin=10, per_decade=True)
aeff = EffectiveAreaTable2D.from_parametrization(
energy_axis_true=energy_true, instrument="HESS"
)
offset_axis = MapAxis.from_bounds(0 * u.deg, 5 * u.deg, nbin=2, name="offset")
edisp = EnergyDispersion2D.from_gauss(
energy_axis_true=energy_true,
offset_axis=offset_axis,
migra_axis=MIGRA_AXIS_DEFAULT,
bias=0,
sigma=0.2,
)
observation = Observation.create(
obs_id=0,
pointing=SkyCoord("0d", "0d", frame="icrs"),
irfs={"aeff": aeff, "edisp": edisp},
import matplotlib.pyplot as plt
from astropy import units as u
from gammapy.irf import EffectiveAreaTable2D
for instrument in ["HESS", "HESS2", "CTA"]:
aeff = EffectiveAreaTable2D.from_parametrization(instrument=instrument)
ax = aeff.plot_energy_dependence(label=instrument, offset=[0] * u.deg)
ax.set_yscale("log")
ax.set_xlim([1e-3, 1e3])
ax.set_ylim([1e3, 1e12])
plt.legend(loc="best")
plt.show()
