def test_rad_max_roundtrip(tmp_path):
n_energy = 10
energy_axis = MapAxis.from_energy_bounds(50 * u.GeV,
100 * u.TeV,
n_energy,
name="energy")
n_offset = 5
offset_axis = MapAxis.from_bounds(0,
2,
n_offset,
unit=u.deg,
name="offset")
shape = (n_energy, n_offset)
rad_max = np.linspace(0.1, 0.5, n_energy * n_offset).reshape(shape)
rad_max_2d = RadMax2D(
axes=[
energy_axis,
offset_axis,
],
data=rad_max,
unit=u.deg,
)
rad_max_2d.write(tmp_path / "rad_max.fits")
rad_max_read = RadMax2D.read(tmp_path / "rad_max.fits")
assert np.all(rad_max_read.data == rad_max)
assert np.all(rad_max_read.data == rad_max_read.data)
def test_create_irf_point_like_energy_dependent_cuts(
temp_dir_observed_files, simulated_dl2_file
):
"""
Generating point-like IRF file from a test DL2 files, using
energy-dependent cuts
"""
from lstchain.tools.lstchain_create_irf_files import IRFFITSWriter
from gammapy.irf import RadMax2D
irf_file = temp_dir_observed_files / "pnt_irf.fits.gz"
assert (
run_tool(
IRFFITSWriter(),
argv=[
f"--input-gamma-dl2={simulated_dl2_file}",
f"--input-proton-dl2={simulated_dl2_file}",
f"--input-electron-dl2={simulated_dl2_file}",
f"--output-irf-file={irf_file}",
"--overwrite",
"--energy-dependent-gh",
"--point-like",
"--energy-dependent-theta",
"--DL3Cuts.max_theta_cut=1",
"--DL3Cuts.fill_theta_cut=1"
],
cwd=temp_dir_observed_files,
)
== 0
)
assert RadMax2D.read(irf_file, hdu="RAD_MAX")
def rad_max(self):
# prevent circular import
from gammapy.irf import RadMax2D
if self._rad_max is not None:
return self._rad_max
# load once to avoid trigger lazy loading it three times
aeff = self.aeff
if aeff is not None and aeff.is_pointlike:
self._rad_max = RadMax2D.from_irf(aeff)
return self._rad_max
edisp = self.edisp
if edisp is not None and edisp.is_pointlike:
self._rad_max = RadMax2D.from_irf(self.edisp)
return self._rad_max
def test_rad_max_from_irf():
e_bins = 3
o_bins = 2
energy_axis = MapAxis.from_energy_bounds(1 * u.TeV,
10 * u.TeV,
nbin=e_bins,
name='energy_true')
offset_axis = MapAxis.from_bounds(0 * u.deg,
3 * u.deg,
nbin=o_bins,
name='offset')
aeff = EffectiveAreaTable2D(
data=u.Quantity(np.ones((e_bins, o_bins)), u.m**2, copy=False),
axes=[energy_axis, offset_axis],
is_pointlike=True,
)
with pytest.raises(ValueError):
# not a point-like IRF
RadMax2D.from_irf(aeff)
with pytest.raises(ValueError):
# missing rad_max
RadMax2D.from_irf(aeff)
aeff.meta['RAD_MAX'] = '0.2 deg'
with pytest.raises(ValueError):
# invalid format
RadMax2D.from_irf(aeff)
aeff.meta['RAD_MAX'] = 0.2
rad_max = RadMax2D.from_irf(aeff)
assert rad_max.axes['energy'].nbin == 1
assert rad_max.axes['offset'].nbin == 1
assert rad_max.axes['energy'].edges[0] == aeff.axes['energy_true'].edges[0]
assert rad_max.axes['energy'].edges[1] == aeff.axes['energy_true'].edges[
-1]
assert rad_max.axes['offset'].edges[0] == aeff.axes['offset'].edges[0]
assert rad_max.axes['offset'].edges[1] == aeff.axes['offset'].edges[-1]
assert rad_max.quantity.shape == (1, 1)
assert rad_max.quantity[0, 0] == 0.2 * u.deg
def test_rad_max_single_bin():
energy_axis = MapAxis.from_energy_bounds(0.01, 100, 1, unit="TeV")
offset_axis = MapAxis.from_bounds(
0.,
5,
1,
unit="deg",
name="offset",
)
rad_max = RadMax2D(data=[[0.1]] * u.deg,
axes=[energy_axis, offset_axis],
interp_kwargs={
"method": "nearest",
"fill_value": None
})
value = rad_max.evaluate(energy=1 * u.TeV, offset=1 * u.deg)
assert_allclose(value, 0.1 * u.deg)
value = rad_max.evaluate(energy=[1, 2, 3] * u.TeV, offset=[[1]] * u.deg)
assert value.shape == (1, 3)
assert_allclose(value, 0.1 * u.deg)