# create a clean mask of pixels above the threshold
cleanmask = tailcuts_clean(camgeom,
image,
picture_thresh=10,
boundary_thresh=5)
if np.count_nonzero(cleanmask) < 10:
continue
# set all rejected pixels to zero
cleaned_image[~cleanmask] = 0
# Calculate hillas parameters
try:
hillas_dict[tel_id] = hillas_parameters(camgeom, cleaned_image)
except HillasParameterizationError:
continue # skip failed parameterization (normally no signal)
timing_dict[tel_id] = timing_parameters(camgeom, image, time,
hillas_dict[tel_id],
cleanmask).slope.value
array_disp.set_vector_hillas(hillas_dict,
500,
timing_dict,
angle_offset=0 * u.deg)
plt.pause(0.1) # allow matplotlib to redraw the display
if len(hillas_dict) < 2:
continue
continue
stereo = reco.predict(
hillas_containers,
event.inst,
pointing_alt=pointing_altitude,
pointing_az=pointing_azimuth
)
plt.figure()
angle_offset = event.mcheader.run_array_direction[0]
disp = ArrayDisplay(event.inst.subarray)
disp.set_vector_hillas(
hillas_containers,
time_gradient=time_gradients,
angle_offset=angle_offset,
length=500
)
plt.scatter(
event.mc.core_x, event.mc.core_y,
s=200, c='k', marker='x', label='True Impact',
)
plt.scatter(
stereo.core_x, stereo.core_y,
s=200, c='r', marker='x', label='Estimated Impact',
)
plt.legend()
plt.show()
continue
array_pointing = SkyCoord(az=event.mcheader.run_array_direction[0],
alt=event.mcheader.run_array_direction[1],
frame=horizon_frame)
stereo = reco.predict(
hillas_containers,
event_source.subarray,
array_pointing,
)
plt.figure()
angle_offset = event.mcheader.run_array_direction[0]
disp = ArrayDisplay(event_source.subarray)
disp.set_vector_hillas(hillas_containers,
time_gradient=time_gradients,
angle_offset=angle_offset,
length=500)
plt.scatter(
event.mc.core_x,
event.mc.core_y,
s=200,
c='k',
marker='x',
label='True Impact',
)
plt.scatter(
stereo.core_x,
stereo.core_y,
s=200,
c='r',
marker='x',
for tel_id in event.dl0.tels_with_data:
# Camera Geometry required for hillas parametrization
camgeom = subarray.tel[tel_id].camera
# note the [0] is for channel 0 which is high-gain channel
image = event.dl1.tel[tel_id].image[0]
# Cleaning of the image
cleaned_image = image.copy()
# create a clean mask of pixels above the threshold
cleanmask = tailcuts_clean(
camgeom, image, picture_thresh=10, boundary_thresh=5
)
# set all rejected pixels to zero
cleaned_image[~cleanmask] = 0
# Calculate hillas parameters
try:
hillas_dict[tel_id] = hillas_parameters(camgeom, cleaned_image)
except HillasParameterizationError:
pass # skip failed parameterization (normally no signal)
array_disp.set_vector_hillas(hillas_dict, angle_offset=0 * u.deg)
plt.pause(0.1) # allow matplotlib to redraw the display
if len(hillas_dict) < 2:
continue
