def test_h_max_results():
"""
creating some planes pointing in different directions (two
north-south, two east-west) and that have a slight position errors (+-
0.1 m in one of the four cardinal directions """
horizon_frame = AltAz()
p1 = SkyCoord(alt=0 * u.deg, az=45 * u.deg, frame=horizon_frame)
p2 = SkyCoord(alt=0 * u.deg, az=45 * u.deg, frame=horizon_frame)
circle1 = HillasPlane(p1=p1, p2=p2, telescope_position=[0, 1, 0] * u.m)
p1 = SkyCoord(alt=0 * u.deg, az=90 * u.deg, frame=horizon_frame)
p2 = SkyCoord(alt=0 * u.deg, az=90 * u.deg, frame=horizon_frame)
circle2 = HillasPlane(p1=p1, p2=p2, telescope_position=[1, 0, 0] * u.m)
p1 = SkyCoord(alt=0 * u.deg, az=45 * u.deg, frame=horizon_frame)
p2 = SkyCoord(alt=0 * u.deg, az=45 * u.deg, frame=horizon_frame)
circle3 = HillasPlane(p1=p1, p2=p2, telescope_position=[0, -1, 0] * u.m)
p1 = SkyCoord(alt=0 * u.deg, az=90 * u.deg, frame=horizon_frame)
p2 = SkyCoord(alt=0 * u.deg, az=90 * u.deg, frame=horizon_frame)
circle4 = HillasPlane(p1=p1, p2=p2, telescope_position=[-1, 0, 0] * u.m)
# creating the fit class and setting the the great circle member
fit = HillasReconstructor()
fit.hillas_planes = {1: circle1, 2: circle2, 3: circle3, 4: circle4}
# performing the direction fit with the minimisation algorithm
# and a seed that is perpendicular to the up direction
h_max_reco = fit.estimate_h_max()
print("h max fit test minimise:", h_max_reco)
# the results should be close to the direction straight up
np.testing.assert_allclose(h_max_reco.value, 0, atol=1e-8)
def test_estimator_results():
"""
creating some planes pointing in different directions (two
north-south, two east-west) and that have a slight position errors (+-
0.1 m in one of the four cardinal directions """
horizon_frame = AltAz()
p1 = SkyCoord(alt=43 * u.deg, az=45 * u.deg, frame=horizon_frame)
p2 = SkyCoord(alt=47 * u.deg, az=45 * u.deg, frame=horizon_frame)
circle1 = HillasPlane(p1=p1, p2=p2, telescope_position=[0, 1, 0] * u.m)
p1 = SkyCoord(alt=44 * u.deg, az=90 * u.deg, frame=horizon_frame)
p2 = SkyCoord(alt=46 * u.deg, az=90 * u.deg, frame=horizon_frame)
circle2 = HillasPlane(p1=p1, p2=p2, telescope_position=[1, 0, 0] * u.m)
p1 = SkyCoord(alt=44.5 * u.deg, az=45 * u.deg, frame=horizon_frame)
p2 = SkyCoord(alt=46.5 * u.deg, az=45 * u.deg, frame=horizon_frame)
circle3 = HillasPlane(p1=p1, p2=p2, telescope_position=[0, -1, 0] * u.m)
p1 = SkyCoord(alt=43.5 * u.deg, az=90 * u.deg, frame=horizon_frame)
p2 = SkyCoord(alt=45.5 * u.deg, az=90 * u.deg, frame=horizon_frame)
circle4 = HillasPlane(p1=p1, p2=p2, telescope_position=[-1, 0, 0] * u.m)
# creating the fit class and setting the the great circle member
fit = HillasReconstructor()
fit.hillas_planes = {1: circle1, 2: circle2, 3: circle3, 4: circle4}
# performing the direction fit with the minimisation algorithm
# and a seed that is perpendicular to the up direction
dir_fit_minimise, _ = fit.estimate_direction()
print("direction fit test minimise:", dir_fit_minimise)
print()
def test_estimator_results():
"""
creating some planes pointing in different directions (two
north-south, two east-west) and that have a slight position errors (+-
0.1 m in one of the four cardinal directions """
horizon_frame = AltAz()
p1 = SkyCoord(alt=43 * u.deg, az=45 * u.deg, frame=horizon_frame)
p2 = SkyCoord(alt=47 * u.deg, az=45 * u.deg, frame=horizon_frame)
circle1 = HillasPlane(p1=p1, p2=p2, telescope_position=[0, 1, 0] * u.m)
p1 = SkyCoord(alt=44 * u.deg, az=90 * u.deg, frame=horizon_frame)
p2 = SkyCoord(alt=46 * u.deg, az=90 * u.deg, frame=horizon_frame)
circle2 = HillasPlane(p1=p1, p2=p2, telescope_position=[1, 0, 0] * u.m)
p1 = SkyCoord(alt=44.5 * u.deg, az=45 * u.deg, frame=horizon_frame)
p2 = SkyCoord(alt=46.5 * u.deg, az=45 * u.deg, frame=horizon_frame)
circle3 = HillasPlane(p1=p1, p2=p2, telescope_position=[0, -1, 0] * u.m)
p1 = SkyCoord(alt=43.5 * u.deg, az=90 * u.deg, frame=horizon_frame)
p2 = SkyCoord(alt=45.5 * u.deg, az=90 * u.deg, frame=horizon_frame)
circle4 = HillasPlane(p1=p1, p2=p2, telescope_position=[-1, 0, 0] * u.m)
# Create a dummy subarray
# (not used here, but required to initialize the reconstructor)
subarray = SubarrayDescription(
"test array",
tel_positions={1: np.zeros(3) * u.m},
tel_descriptions={
1:
TelescopeDescription.from_name(optics_name="SST-ASTRI",
camera_name="CHEC")
},
)
# creating the fit class and setting the the great circle member
fit = HillasReconstructor(subarray)
hillas_planes = {1: circle1, 2: circle2, 3: circle3, 4: circle4}
# performing the direction fit with the minimisation algorithm
# and a seed that is perpendicular to the up direction
dir_fit_minimise, _ = fit.estimate_direction(hillas_planes)
print("direction fit test minimise:", dir_fit_minimise)
def initialize_hillas_planes(self, hillas_dict, subarray,
telescopes_pointings, array_pointing):
"""
Creates a dictionary of :class:`.HillasPlane` from a dictionary of
hillas parameters
Parameters
----------
hillas_dict : dictionary
dictionary of hillas moments
subarray : ctapipe.instrument.SubarrayDescription
subarray information
telescopes_pointings: dictionary
dictionary of pointing direction per each telescope
array_pointing: SkyCoord[AltAz]
pointing direction of the array
"""
self.hillas_planes = {}
k = next(iter(telescopes_pointings))
horizon_frame = telescopes_pointings[k].frame
for tel_id, moments in hillas_dict.items():
pointing = SkyCoord(
alt=telescopes_pointings[tel_id].alt,
az=telescopes_pointings[tel_id].az,
frame=horizon_frame,
)
if moments.x.unit == u.Unit(
"m"): # Image parameters are in CameraFrame
# we just need any point on the main shower axis a bit away from the cog
p2_x = moments.x + 0.1 * u.m * np.cos(moments.psi)
p2_y = moments.y + 0.1 * u.m * np.sin(moments.psi)
focal_length = subarray.tel[
tel_id].optics.equivalent_focal_length
camera_frame = CameraFrame(focal_length=focal_length,
telescope_pointing=pointing)
cog_coord = SkyCoord(
x=moments.x,
y=moments.y,
frame=camera_frame,
)
p2_coord = SkyCoord(x=p2_x, y=p2_y, frame=camera_frame)
# ============
# DIVERGENT
# re-project from sky to a "fake"-parallel-pointing telescope
# then recalculate the psi angle
# WARNING: this part will need to be reproduced accordingly in the TelescopeFrame case!
if self.divergent_mode:
camera_frame_parallel = CameraFrame(
focal_length=focal_length,
telescope_pointing=array_pointing)
cog_sky_to_parallel = cog_coord.transform_to(
camera_frame_parallel)
p2_sky_to_parallel = p2_coord.transform_to(
camera_frame_parallel)
angle_psi_corr = np.arctan2(
cog_sky_to_parallel.y - p2_sky_to_parallel.y,
cog_sky_to_parallel.x - p2_sky_to_parallel.x,
)
self.corrected_angle_dict[tel_id] = angle_psi_corr
# ============
else: # Image parameters are already in TelescopeFrame
# we just need any point on the main shower axis a bit away from the cog
p2_x = moments.x + 0.1 * u.deg * np.cos(moments.psi)
p2_y = moments.y + 0.1 * u.deg * np.sin(moments.psi)
telescope_frame = TelescopeFrame(telescope_pointing=pointing)
cog_coord = SkyCoord(
fov_lon=moments.x,
fov_lat=moments.y,
frame=telescope_frame,
)
p2_coord = SkyCoord(fov_lon=p2_x,
fov_lat=p2_y,
frame=telescope_frame)
cog_coord = cog_coord.transform_to(horizon_frame)
p2_coord = p2_coord.transform_to(horizon_frame)
circle = HillasPlane(
p1=cog_coord,
p2=p2_coord,
telescope_position=subarray.positions[tel_id],
weight=moments.intensity * (moments.length / moments.width),
)
self.hillas_planes[tel_id] = circle