def display_telescope(event, tel_id, display, geom_dict, pp, fig):
fig.clear()
cam_dimensions = (event.dl0.tel[tel_id].num_pixels,
event.meta.optical_foclen[tel_id])
fig.suptitle("EVENT {} {:.1e} @({:.1f},{:.1f}) @{:.1f}".format(
event.dl1.event_id, event.mc.energy, event.mc.alt, event.mc.az,
np.sqrt(pow(event.mc.core_x, 2) + pow(event.mc.core_y, 2))))
# Select number of pads to display (will depend on the integrator):
# charge and/or time of maximum.
# This last one is displayed only if the integrator calculates it
npads = 1
if not event.dl1.tel[tel_id].peakpos[0] is None:
npads = 2
# Only create two pads if there is timing information extracted
# from the calibration
ax1 = fig.add_subplot(1, npads, 1)
# If the geometery has not already been added to geom_dict, it will
# be added in CameraPlotter
plotter = CameraPlotter(event, geom_dict)
signals = event.dl1.tel[tel_id].pe_charge
camera1 = plotter.draw_camera(tel_id, signals, ax1)
cmaxmin = (max(signals) - min(signals))
cmap_charge = colors.LinearSegmentedColormap.from_list(
'cmap_c', [(0 / cmaxmin, 'darkblue'),
(np.abs(min(signals)) / cmaxmin, 'black'),
(2.0 * np.abs(min(signals)) / cmaxmin, 'blue'),
(2.5 * np.abs(min(signals)) / cmaxmin, 'green'),
(1, 'yellow')])
camera1.pixels.set_cmap(cmap_charge)
camera1.add_colorbar(ax=ax1, label=" [photo-electrons]")
ax1.set_title("CT {} ({}) - Mean pixel charge".format(
tel_id, geom_dict[cam_dimensions].cam_id))
if not event.dl1.tel[tel_id].peakpos[0] is None:
ax2 = fig.add_subplot(1, npads, npads)
times = event.dl1.tel[tel_id].peakpos
camera2 = plotter.draw_camera(tel_id, times, ax2)
tmaxmin = event.dl0.tel[tel_id].num_samples
t_chargemax = times[signals.argmax()]
if t_chargemax > 15:
t_chargemax = 7
cmap_time = colors.LinearSegmentedColormap.from_list(
'cmap_t', [(0 / tmaxmin, 'darkgreen'),
(0.6 * t_chargemax / tmaxmin, 'green'),
(t_chargemax / tmaxmin, 'yellow'),
(1.4 * t_chargemax / tmaxmin, 'blue'), (1, 'darkblue')])
camera2.pixels.set_cmap(cmap_time)
camera2.add_colorbar(ax=ax2, label="[time slice]")
ax2.set_title("CT {} ({}) - Pixel peak position".format(
tel_id, geom_dict[cam_dimensions].cam_id))
if display:
plt.pause(0.1)
if pp is not None:
pp.savefig(fig)
def test_eventplotter():
dataset = get_dataset("gamma_test.simtel.gz")
source = hessio_event_source(dataset, max_events=1)
event = next(source)
data = event.r0.tel[38].adc_samples[0]
plotter = CameraPlotter(event)
camera = plotter.draw_camera(38, data[:, 0])
assert camera is not None
np.testing.assert_array_equal(camera.image, data[:, 0])
plotter.draw_camera_pixel_ids(38, [0, 1, 2])
waveform = plotter.draw_waveform(data[0, :])
assert waveform is not None
np.testing.assert_array_equal(waveform.get_ydata(), data[0, :])
line = plotter.draw_waveform_positionline(0)
assert line is not None
np.testing.assert_array_equal(line.get_xdata(), [0, 0])
def test_eventplotter():
dataset = get_dataset_path("gamma_test_large.simtel.gz")
with event_source(dataset, max_events=1) as source:
event = next(iter(source))
telid = list(event.r0.tels_with_data)[0]
data = event.r0.tel[telid].waveform[0]
plotter = CameraPlotter(event)
camera = plotter.draw_camera(telid, data[:, 0])
assert camera is not None
np.testing.assert_array_equal(camera.image, data[:, 0])
plotter.draw_camera_pixel_ids(telid, [0, 1, 2])
waveform = plotter.draw_waveform(data[0, :])
assert waveform is not None
np.testing.assert_array_equal(waveform.get_ydata(), data[0, :])
line = plotter.draw_waveform_positionline(0)
assert line is not None
np.testing.assert_array_equal(line.get_xdata(), [0, 0])
def plot_muon_event(event, muonparams, args=None):
if muonparams['MuonRingParams'] is not None:
# Plot the muon event and overlay muon parameters
fig = plt.figure(figsize=(16, 7))
colorbar = None
colorbar2 = None
#for tel_id in event.dl0.tels_with_data:
for tel_id in muonparams['TelIds']:
idx = muonparams['TelIds'].index(tel_id)
if not muonparams['MuonRingParams'][idx]:
continue
#otherwise...
npads = 2
# Only create two pads if there is timing information extracted
# from the calibration
ax1 = fig.add_subplot(1, npads, 1)
plotter = CameraPlotter(event)
image = event.dl1.tel[tel_id].image[0]
geom = event.inst.subarray.tel[tel_id].camera
tailcuts = (5., 7.)
# Try a higher threshold for
if geom.cam_id == 'FlashCam':
tailcuts = (10., 12.)
clean_mask = tailcuts_clean(geom,
image,
picture_thresh=tailcuts[0],
boundary_thresh=tailcuts[1])
signals = image * clean_mask
#print("Ring Centre in Nominal Coords:",muonparams[0].ring_center_x,muonparams[0].ring_center_y)
muon_incl = np.sqrt(
muonparams['MuonRingParams'][idx].ring_center_x**2. +
muonparams['MuonRingParams'][idx].ring_center_y**2.)
muon_phi = np.arctan(
muonparams['MuonRingParams'][idx].ring_center_y /
muonparams['MuonRingParams'][idx].ring_center_x)
rotr_angle = geom.pix_rotation
# if event.inst.optical_foclen[tel_id] > 10.*u.m and
# event.dl0.tel[tel_id].num_pixels != 1764:
if geom.cam_id == 'LSTCam' or geom.cam_id == 'NectarCam':
#print("Resetting the rotation angle")
rotr_angle = 0. * u.deg
# Convert to camera frame (centre & radius)
altaz = HorizonFrame(alt=event.mc.alt, az=event.mc.az)
ring_nominal = NominalFrame(
x=muonparams['MuonRingParams'][idx].ring_center_x,
y=muonparams['MuonRingParams'][idx].ring_center_y,
array_direction=altaz,
pointing_direction=altaz)
# embed()
ring_camcoord = ring_nominal.transform_to(
CameraFrame(pointing_direction=altaz,
focal_length=event.inst.optical_foclen[tel_id],
rotation=rotr_angle))
centroid_rad = np.sqrt(ring_camcoord.y**2 + ring_camcoord.x**2)
centroid = (ring_camcoord.x.value, ring_camcoord.y.value)
ringrad_camcoord = muonparams['MuonRingParams'][idx].ring_radius.to(u.rad) \
* event.inst.optical_foclen[tel_id] * 2. # But not FC?
px, py = event.inst.pixel_pos[tel_id]
flen = event.inst.optical_foclen[tel_id]
camera_coord = CameraFrame(x=px,
y=py,
focal_length=flen,
rotation=geom.pix_rotation)
nom_coord = camera_coord.transform_to(
NominalFrame(array_direction=altaz, pointing_direction=altaz))
px = nom_coord.x.to(u.deg)
py = nom_coord.y.to(u.deg)
dist = np.sqrt(
np.power(px -
muonparams['MuonRingParams'][idx].ring_center_x, 2) +
np.power(py -
muonparams['MuonRingParams'][idx].ring_center_y, 2))
ring_dist = np.abs(dist -
muonparams['MuonRingParams'][idx].ring_radius)
pixRmask = ring_dist < muonparams['MuonRingParams'][
idx].ring_radius * 0.4
#if muonparams[1] is not None:
if muonparams['MuonIntensityParams'][idx] is not None:
signals *= muonparams['MuonIntensityParams'][idx].mask
camera1 = plotter.draw_camera(tel_id, signals, ax1)
cmaxmin = (max(signals) - min(signals))
cmin = min(signals)
if not cmin:
cmin = 1.
if not cmaxmin:
cmaxmin = 1.
cmap_charge = colors.LinearSegmentedColormap.from_list(
'cmap_c', [(0 / cmaxmin, 'darkblue'),
(np.abs(cmin) / cmaxmin, 'black'),
(2.0 * np.abs(cmin) / cmaxmin, 'blue'),
(2.5 * np.abs(cmin) / cmaxmin, 'green'),
(1, 'yellow')])
camera1.pixels.set_cmap(cmap_charge)
if not colorbar:
camera1.add_colorbar(ax=ax1, label=" [photo-electrons]")
colorbar = camera1.colorbar
else:
camera1.colorbar = colorbar
camera1.update(True)
camera1.add_ellipse(centroid,
ringrad_camcoord.value,
ringrad_camcoord.value,
0.,
0.,
color="red")
if muonparams['MuonIntensityParams'][idx] is not None:
# continue #Comment this...(should ringwidthfrac also be *0.5?)
ringwidthfrac = muonparams['MuonIntensityParams'][
idx].ring_width / muonparams['MuonRingParams'][
idx].ring_radius
ringrad_inner = ringrad_camcoord * (1. - ringwidthfrac)
ringrad_outer = ringrad_camcoord * (1. + ringwidthfrac)
camera1.add_ellipse(centroid,
ringrad_inner.value,
ringrad_inner.value,
0.,
0.,
color="magenta")
camera1.add_ellipse(centroid,
ringrad_outer.value,
ringrad_outer.value,
0.,
0.,
color="magenta")
npads = 2
ax2 = fig.add_subplot(1, npads, npads)
pred = muonparams['MuonIntensityParams'][idx].prediction
if len(pred) != np.sum(
muonparams['MuonIntensityParams'][idx].mask):
print("Warning! Lengths do not match...len(pred)=",
len(pred), "len(mask)=",
np.sum(muonparams['MuonIntensityParams'][idx].mask))
# Numpy broadcasting - fill in the shape
plotpred = np.zeros(image.shape)
plotpred[muonparams['MuonIntensityParams'][idx].mask ==
True] = pred
camera2 = plotter.draw_camera(tel_id, plotpred, ax2)
if np.isnan(max(plotpred)) or np.isnan(min(plotpred)):
print("nan prediction, skipping...")
continue
c2maxmin = (max(plotpred) - min(plotpred))
if not c2maxmin:
c2maxmin = 1.
c2map_charge = colors.LinearSegmentedColormap.from_list(
'c2map_c',
[(0 / c2maxmin, 'darkblue'),
(np.abs(min(plotpred)) / c2maxmin, 'black'),
(2.0 * np.abs(min(plotpred)) / c2maxmin, 'blue'),
(2.5 * np.abs(min(plotpred)) / c2maxmin, 'green'),
(1, 'yellow')])
camera2.pixels.set_cmap(c2map_charge)
if not colorbar2:
camera2.add_colorbar(ax=ax2, label=" [photo-electrons]")
colorbar2 = camera2.colorbar
else:
camera2.colorbar = colorbar2
camera2.update(True)
plt.pause(1.) # make shorter
# plt.pause(0.1)
# if pp is not None:
# pp.savefig(fig)
#fig.savefig(str(args.output_path) + "_" +
# str(event.dl0.event_id) + '.png')
plt.close()
def plot_muon_event(event, muonparams, geom_dict=None, args=None):
if muonparams[0] is not None:
# Plot the muon event and overlay muon parameters
fig = plt.figure(figsize=(16, 7))
# if args.display:
# plt.show(block=False)
#pp = PdfPages(args.output_path) if args.output_path is not None else None
# pp = None #For now, need to correct this
colorbar = None
colorbar2 = None
for tel_id in event.dl0.tels_with_data:
npads = 2
# Only create two pads if there is timing information extracted
# from the calibration
ax1 = fig.add_subplot(1, npads, 1)
plotter = CameraPlotter(event, geom_dict)
#image = event.dl1.tel[tel_id].calibrated_image
image = event.dl1.tel[tel_id].image[0]
# Get geometry
geom = None
if geom_dict is not None and tel_id in geom_dict:
geom = geom_dict[tel_id]
else:
#log.debug("[calib] Guessing camera geometry")
geom = CameraGeometry.guess(*event.inst.pixel_pos[tel_id],
event.inst.optical_foclen[tel_id])
#log.debug("[calib] Camera geometry found")
if geom_dict is not None:
geom_dict[tel_id] = geom
tailcuts = (5., 7.)
# Try a higher threshold for
if geom.cam_id == 'FlashCam':
tailcuts = (10., 12.)
#print("Using Tail Cuts:",tailcuts)
clean_mask = tailcuts_clean(geom, image,
picture_thresh=tailcuts[0],
boundary_thresh=tailcuts[1])
signals = image * clean_mask
#print("Ring Centre in Nominal Coords:",muonparams[0].ring_center_x,muonparams[0].ring_center_y)
muon_incl = np.sqrt(muonparams[0].ring_center_x**2. +
muonparams[0].ring_center_y**2.)
muon_phi = np.arctan(muonparams[0].ring_center_y /
muonparams[0].ring_center_x)
rotr_angle = geom.pix_rotation
# if event.inst.optical_foclen[tel_id] > 10.*u.m and
# event.dl0.tel[tel_id].num_pixels != 1764:
if geom.cam_id == 'LSTCam' or geom.cam_id == 'NectarCam':
#print("Resetting the rotation angle")
rotr_angle = 0. * u.deg
# Convert to camera frame (centre & radius)
altaz = HorizonFrame(alt=event.mc.alt, az=event.mc.az)
ring_nominal = NominalFrame(x=muonparams[0].ring_center_x,
y=muonparams[0].ring_center_y,
array_direction=altaz,
pointing_direction=altaz)
# embed()
ring_camcoord = ring_nominal.transform_to(CameraFrame(
pointing_direction=altaz,
focal_length=event.inst.optical_foclen[tel_id],
rotation=rotr_angle))
centroid_rad = np.sqrt(ring_camcoord.y**2 + ring_camcoord.x**2)
centroid = (ring_camcoord.x.value, ring_camcoord.y.value)
ringrad_camcoord = muonparams[0].ring_radius.to(u.rad) \
* event.inst.optical_foclen[tel_id] * 2. # But not FC?
#rot_angle = 0.*u.deg
# if event.inst.optical_foclen[tel_id] > 10.*u.m and event.dl0.tel[tel_id].num_pixels != 1764:
#rot_angle = -100.14*u.deg
px, py = event.inst.pixel_pos[tel_id]
flen = event.inst.optical_foclen[tel_id]
camera_coord = CameraFrame(x=px, y=py,
z=np.zeros(px.shape) * u.m,
focal_length=flen,
rotation=geom.pix_rotation)
nom_coord = camera_coord.transform_to(
NominalFrame(array_direction=altaz,
pointing_direction=altaz)
)
#,focal_length = event.inst.optical_foclen[tel_id])) # tel['TelescopeTable_VersionFeb2016'][tel['TelescopeTable_VersionFeb2016']['TelID']==telid]['FL'][0]*u.m))
px = nom_coord.x.to(u.deg)
py = nom_coord.y.to(u.deg)
dist = np.sqrt(np.power( px - muonparams[0].ring_center_x, 2)
+ np.power(py - muonparams[0].ring_center_y, 2))
ring_dist = np.abs(dist - muonparams[0].ring_radius)
pixRmask = ring_dist < muonparams[0].ring_radius * 0.4
if muonparams[1] is not None:
signals *= muonparams[1].mask
camera1 = plotter.draw_camera(tel_id, signals, ax1)
cmaxmin = (max(signals) - min(signals))
if not cmaxmin:
cmaxmin = 1.
cmap_charge = colors.LinearSegmentedColormap.from_list(
'cmap_c', [(0 / cmaxmin, 'darkblue'),
(np.abs(min(signals)) / cmaxmin, 'black'),
(2.0 * np.abs(min(signals)) / cmaxmin, 'blue'),
(2.5 * np.abs(min(signals)) / cmaxmin, 'green'),
(1, 'yellow')]
)
camera1.pixels.set_cmap(cmap_charge)
if not colorbar:
camera1.add_colorbar(ax=ax1, label=" [photo-electrons]")
colorbar = camera1.colorbar
else:
camera1.colorbar = colorbar
camera1.update(True)
camera1.add_ellipse(centroid, ringrad_camcoord.value,
ringrad_camcoord.value, 0., 0., color="red")
# ax1.set_title("CT {} ({}) - Mean pixel charge"
# .format(tel_id, geom_dict[tel_id].cam_id))
if muonparams[1] is not None:
# continue #Comment this...(should ringwidthfrac also be *0.5?)
ringwidthfrac = muonparams[
1].ring_width / muonparams[0].ring_radius
ringrad_inner = ringrad_camcoord * (1. - ringwidthfrac)
ringrad_outer = ringrad_camcoord * (1. + ringwidthfrac)
camera1.add_ellipse(centroid, ringrad_inner.value,
ringrad_inner.value, 0., 0.,
color="magenta")
camera1.add_ellipse(centroid, ringrad_outer.value,
ringrad_outer.value, 0., 0., color="magenta")
npads = 2
ax2 = fig.add_subplot(1, npads, npads)
pred = muonparams[1].prediction
if len(pred) != np.sum(muonparams[1].mask):
print("Warning! Lengths do not match...len(pred)=",
len(pred), "len(mask)=", np.sum(muonparams[1].mask))
# Numpy broadcasting - fill in the shape
plotpred = np.zeros(image.shape)
plotpred[muonparams[1].mask == True] = pred
camera2 = plotter.draw_camera(tel_id, plotpred, ax2)
c2maxmin = (max(plotpred) - min(plotpred))
if not c2maxmin:
c2maxmin = 1.
c2map_charge = colors.LinearSegmentedColormap.from_list(
'c2map_c', [(0 / c2maxmin, 'darkblue'),
(np.abs(min(plotpred)) / c2maxmin, 'black'),
(2.0 * np.abs(min(plotpred)) / c2maxmin, 'blue'),
(2.5 * np.abs(min(plotpred)) / c2maxmin, 'green'),
(1, 'yellow')]
)
camera2.pixels.set_cmap(c2map_charge)
if not colorbar2:
camera2.add_colorbar(ax=ax2, label=" [photo-electrons]")
colorbar2 = camera2.colorbar
else:
camera2.colorbar = colorbar2
camera2.update(True)
plt.pause(1.) # make shorter
# plt.pause(0.1)
# if pp is not None:
# pp.savefig(fig)
fig.savefig(str(args.output_path) + "_" +
str(event.dl0.event_id) + '.png')
plt.close()
def run(self, inputs):
self.log.debug("--- PrepareDisplayStep RUN ---")
calibrated_event, geom_dict = inputs
for tel_id in calibrated_event.dl0.tels_with_data:
self.fig.clear()
cam_dimensions = (calibrated_event.inst.num_pixels[tel_id],
calibrated_event.inst.optical_foclen[tel_id])
self.fig.suptitle(
"EVENT {} {:.1e} @({:.1f},{:.1f}) @{:.1f}".format(
calibrated_event.dl1.event_id, calibrated_event.mc.energy,
calibrated_event.mc.alt, calibrated_event.mc.az,
np.sqrt(
pow(calibrated_event.mc.core_x, 2) +
pow(calibrated_event.mc.core_y, 2))))
# Select number of pads to display (will depend on the integrator):
# charge and/or time of maximum.
# This last one is displayed only if the integrator calculates it
npads = 1
if not calibrated_event.dl1.tel[tel_id].peakpos[0] is None:
npads = 2
# Only create two pads if there is timing information extracted
# from the calibration
ax1 = self.fig.add_subplot(1, npads, 1)
# If the geometery has not already been added to geom_dict, it will
# be added in CameraPlotter
plotter = CameraPlotter(calibrated_event, geom_dict)
signals = calibrated_event.dl1.tel[tel_id].calibrated_image
camera1 = plotter.draw_camera(tel_id, signals, ax1)
cmaxmin = (max(signals) - min(signals))
color_list = [(0 / cmaxmin, 'darkblue'),
(np.abs(min(signals)) / cmaxmin, 'black'),
(2.0 * np.abs(min(signals)) / cmaxmin, 'blue'),
(2.5 * np.abs(min(signals)) / cmaxmin, 'green'),
(1, 'yellow')]
try:
cmap_charge = colors.LinearSegmentedColormap.from_list(
'cmap_c', color_list)
camera1.pixels.set_cmap(cmap_charge)
camera1.add_colorbar(ax=ax1, label=" [photo-electrons]")
except:
camera1.pixels.set_cmap('jet')
ax1.set_title("CT {} ({}) - Mean pixel charge".format(
tel_id, geom_dict[tel_id].cam_id))
if not calibrated_event.dl1.tel[tel_id].peakpos[0] is None:
ax2 = self.fig.add_subplot(1, npads, npads)
times = calibrated_event.dl1.tel[tel_id].peakpos
camera2 = plotter.draw_camera(tel_id, times, ax2)
tmaxmin = calibrated_event.dl0.tel[tel_id].num_samples
t_chargemax = times[signals.argmax()]
if t_chargemax > 15:
t_chargemax = 7
cmap_time = colors.LinearSegmentedColormap.from_list(
'cmap_t', [(0 / tmaxmin, 'darkgreen'),
(0.6 * t_chargemax / tmaxmin, 'green'),
(t_chargemax / tmaxmin, 'yellow'),
(1.4 * t_chargemax / tmaxmin, 'blue'),
(1, 'darkblue')])
try:
camera2.pixels.set_cmap(cmap_time)
camera2.add_colorbar(ax=ax2, label="[time slice]")
except:
camera2.pixels.set_cmap('jet')
ax2.set_title("CT {} ({}) - Pixel peak position".format(
tel_id, geom_dict[tel_id].cam_id))
yield self.fig
self.log.debug("--- PrepareDisplayStep END ---")
def plot_muon_event(event, muonparams):
if muonparams['MuonRingParams'] is not None:
# Plot the muon event and overlay muon parameters
fig = plt.figure(figsize=(16, 7))
colorbar = None
colorbar2 = None
subarray = event.inst.subarray
# for tel_id in event.dl0.tels_with_data:
for tel_id in muonparams['TelIds']:
idx = muonparams['TelIds'].index(tel_id)
if not muonparams['MuonRingParams'][idx]:
continue
# otherwise...
npads = 2
# Only create two pads if there is timing information extracted
# from the calibration
ax1 = fig.add_subplot(1, npads, 1)
plotter = CameraPlotter(event)
image = event.dl1.tel[tel_id].image[0]
geom = event.inst.subarray.tel[tel_id].camera
tailcuts = (5., 7.)
# Try a higher threshold for
if geom.cam_id == 'FlashCam':
tailcuts = (10., 12.)
clean_mask = tailcuts_clean(geom, image,
picture_thresh=tailcuts[0],
boundary_thresh=tailcuts[1])
signals = image * clean_mask
rotr_angle = geom.pix_rotation
# The following two lines have been commented out to avoid a rotation error.
# if geom.cam_id == 'LSTCam' or geom.cam_id == 'NectarCam':
# rotr_angle = 0. * u.deg
# Convert to camera frame (centre & radius)
altaz = HorizonFrame(alt=event.mc.alt, az=event.mc.az)
ring_nominal = SkyCoord(
delta_az=muonparams['MuonRingParams'][idx].ring_center_x,
delta_alt=muonparams['MuonRingParams'][idx].ring_center_y,
frame=NominalFrame(origin=altaz)
)
flen = subarray.tel[tel_id].optics.equivalent_focal_length
ring_camcoord = ring_nominal.transform_to(CameraFrame(
pointing_direction=altaz,
focal_length=flen,
rotation=rotr_angle))
centroid = (ring_camcoord.x.value, ring_camcoord.y.value)
radius = muonparams['MuonRingParams'][idx].ring_radius
ringrad_camcoord = 2 * radius.to(u.rad) * flen # But not FC?
px = subarray.tel[tel_id].camera.pix_x
py = subarray.tel[tel_id].camera.pix_y
camera_coord = SkyCoord(
x=px,
y=py,
frame=CameraFrame(
focal_length=flen,
rotation=geom.pix_rotation,
)
)
nom_coord = camera_coord.transform_to(
NominalFrame(origin=altaz)
)
px = nom_coord.delta_az.to(u.deg)
py = nom_coord.delta_alt.to(u.deg)
dist = np.sqrt(np.power(px - muonparams['MuonRingParams'][idx].ring_center_x,
2) + np.power(py - muonparams['MuonRingParams'][idx].
ring_center_y, 2))
ring_dist = np.abs(dist - muonparams['MuonRingParams'][idx].ring_radius)
pix_rmask = ring_dist < muonparams['MuonRingParams'][idx].ring_radius * 0.4
if muonparams['MuonIntensityParams'][idx] is not None:
signals *= muonparams['MuonIntensityParams'][idx].mask
elif muonparams['MuonIntensityParams'][idx] is None:
signals *= pix_rmask
camera1 = plotter.draw_camera(tel_id, signals, ax1)
cmaxmin = (max(signals) - min(signals))
cmin = min(signals)
if not cmin:
cmin = 1.
if not cmaxmin:
cmaxmin = 1.
cmap_charge = colors.LinearSegmentedColormap.from_list(
'cmap_c', [(0 / cmaxmin, 'darkblue'),
(np.abs(cmin) / cmaxmin, 'black'),
(2.0 * np.abs(cmin) / cmaxmin, 'blue'),
(2.5 * np.abs(cmin) / cmaxmin, 'green'),
(1, 'yellow')]
)
camera1.pixels.set_cmap(cmap_charge)
if not colorbar:
camera1.add_colorbar(ax=ax1, label=" [photo-electrons]")
colorbar = camera1.colorbar
else:
camera1.colorbar = colorbar
camera1.update(True)
camera1.add_ellipse(centroid, ringrad_camcoord.value,
ringrad_camcoord.value, 0., 0., color="red")
if muonparams['MuonIntensityParams'][idx] is not None:
ringwidthfrac = muonparams['MuonIntensityParams'][idx].ring_width / \
muonparams['MuonRingParams'][idx].ring_radius
ringrad_inner = ringrad_camcoord * (1. - ringwidthfrac)
ringrad_outer = ringrad_camcoord * (1. + ringwidthfrac)
camera1.add_ellipse(centroid, ringrad_inner.value,
ringrad_inner.value, 0., 0.,
color="magenta")
camera1.add_ellipse(centroid, ringrad_outer.value,
ringrad_outer.value, 0., 0.,
color="magenta")
npads = 2
ax2 = fig.add_subplot(1, npads, npads)
pred = muonparams['MuonIntensityParams'][idx].prediction
if len(pred) != np.sum(
muonparams['MuonIntensityParams'][idx].mask):
logger.warning("Lengths do not match...len(pred)=%s len("
"mask)=", len(pred),
np.sum(muonparams['MuonIntensityParams'][idx].mask))
# Numpy broadcasting - fill in the shape
plotpred = np.zeros(image.shape)
truelocs = np.where(muonparams['MuonIntensityParams'][idx].mask == True)
plotpred[truelocs] = pred
camera2 = plotter.draw_camera(tel_id, plotpred, ax2)
if np.isnan(max(plotpred)) or np.isnan(min(plotpred)):
logger.debug("nan prediction, skipping...")
continue
c2maxmin = (max(plotpred) - min(plotpred))
if not c2maxmin:
c2maxmin = 1.
c2map_charge = colors.LinearSegmentedColormap.from_list(
'c2map_c', [(0 / c2maxmin, 'darkblue'),
(np.abs(min(plotpred)) / c2maxmin, 'black'),
(
2.0 * np.abs(min(plotpred)) / c2maxmin, 'blue'),
(2.5 * np.abs(min(plotpred)) / c2maxmin,
'green'),
(1, 'yellow')]
)
camera2.pixels.set_cmap(c2map_charge)
if not colorbar2:
camera2.add_colorbar(ax=ax2, label=" [photo-electrons]")
colorbar2 = camera2.colorbar
else:
camera2.colorbar = colorbar2
camera2.update(True)
plt.pause(1.) # make shorter
# plt.pause(0.1)
# if pp is not None:
# pp.savefig(fig)
# fig.savefig(str(args.output_path) + "_" +
# str(event.dl0.event_id) + '.png')
plt.close()
def plot_muon_event(event, muonparams):
if muonparams['MuonRingParams'] is not None:
# Plot the muon event and overlay muon parameters
fig = plt.figure(figsize=(16, 7))
colorbar = None
colorbar2 = None
subarray = event.inst.subarray
# for tel_id in event.dl0.tels_with_data:
for tel_id in muonparams['TelIds']:
idx = muonparams['TelIds'].index(tel_id)
if not muonparams['MuonRingParams'][idx]:
continue
# otherwise...
npads = 2
# Only create two pads if there is timing information extracted
# from the calibration
ax1 = fig.add_subplot(1, npads, 1)
plotter = CameraPlotter(event)
image = event.dl1.tel[tel_id].image
geom = event.inst.subarray.tel[tel_id].camera
tailcuts = (5., 7.)
# Try a higher threshold for
if geom.cam_id == 'FlashCam':
tailcuts = (10., 12.)
clean_mask = tailcuts_clean(geom,
image,
picture_thresh=tailcuts[0],
boundary_thresh=tailcuts[1])
signals = image * clean_mask
rotr_angle = geom.pix_rotation
# The following two lines have been commented out to avoid a rotation error.
# if geom.cam_id == 'LSTCam' or geom.cam_id == 'NectarCam':
# rotr_angle = 0. * u.deg
# Convert to camera frame (centre & radius)
altaz = AltAz(alt=event.mc.alt, az=event.mc.az)
ring_nominal = SkyCoord(
delta_az=muonparams['MuonRingParams'][idx].ring_center_x,
delta_alt=muonparams['MuonRingParams'][idx].ring_center_y,
frame=NominalFrame(origin=altaz))
flen = subarray.tel[tel_id].optics.equivalent_focal_length
ring_camcoord = ring_nominal.transform_to(
CameraFrame(pointing_direction=altaz,
focal_length=flen,
rotation=rotr_angle))
centroid = (ring_camcoord.x.value, ring_camcoord.y.value)
radius = muonparams['MuonRingParams'][idx].ring_radius
ringrad_camcoord = 2 * radius.to(u.rad) * flen # But not FC?
px = subarray.tel[tel_id].camera.pix_x
py = subarray.tel[tel_id].camera.pix_y
camera_coord = SkyCoord(x=px,
y=py,
frame=CameraFrame(
focal_length=flen,
rotation=geom.pix_rotation,
))
nom_coord = camera_coord.transform_to(NominalFrame(origin=altaz))
px = nom_coord.delta_az.to(u.deg)
py = nom_coord.delta_alt.to(u.deg)
dist = np.sqrt(
np.power(px -
muonparams['MuonRingParams'][idx].ring_center_x, 2) +
np.power(py -
muonparams['MuonRingParams'][idx].ring_center_y, 2))
ring_dist = np.abs(dist -
muonparams['MuonRingParams'][idx].ring_radius)
pix_rmask = ring_dist < muonparams['MuonRingParams'][
idx].ring_radius * 0.4
if muonparams['MuonIntensityParams'][idx] is not None:
signals *= muonparams['MuonIntensityParams'][idx].mask
elif muonparams['MuonIntensityParams'][idx] is None:
signals *= pix_rmask
camera1 = plotter.draw_camera(tel_id, signals, ax1)
cmaxmin = (max(signals) - min(signals))
cmin = min(signals)
if not cmin:
cmin = 1.
if not cmaxmin:
cmaxmin = 1.
cmap_charge = colors.LinearSegmentedColormap.from_list(
'cmap_c', [(0 / cmaxmin, 'darkblue'),
(np.abs(cmin) / cmaxmin, 'black'),
(2.0 * np.abs(cmin) / cmaxmin, 'blue'),
(2.5 * np.abs(cmin) / cmaxmin, 'green'),
(1, 'yellow')])
camera1.pixels.set_cmap(cmap_charge)
if not colorbar:
camera1.add_colorbar(ax=ax1, label=" [photo-electrons]")
colorbar = camera1.colorbar
else:
camera1.colorbar = colorbar
camera1.update(True)
camera1.add_ellipse(centroid,
ringrad_camcoord.value,
ringrad_camcoord.value,
0.,
0.,
color="red")
if muonparams['MuonIntensityParams'][idx] is not None:
ringwidthfrac = muonparams['MuonIntensityParams'][idx].ring_width / \
muonparams['MuonRingParams'][idx].ring_radius
ringrad_inner = ringrad_camcoord * (1. - ringwidthfrac)
ringrad_outer = ringrad_camcoord * (1. + ringwidthfrac)
camera1.add_ellipse(centroid,
ringrad_inner.value,
ringrad_inner.value,
0.,
0.,
color="magenta")
camera1.add_ellipse(centroid,
ringrad_outer.value,
ringrad_outer.value,
0.,
0.,
color="magenta")
npads = 2
ax2 = fig.add_subplot(1, npads, npads)
pred = muonparams['MuonIntensityParams'][idx].prediction
if len(pred) != np.sum(
muonparams['MuonIntensityParams'][idx].mask):
logger.warning(
"Lengths do not match...len(pred)=%s len("
"mask)=", len(pred),
np.sum(muonparams['MuonIntensityParams'][idx].mask))
# Numpy broadcasting - fill in the shape
plotpred = np.zeros(image.shape)
truelocs = np.where(
muonparams['MuonIntensityParams'][idx].mask == True)
plotpred[truelocs] = pred
camera2 = plotter.draw_camera(tel_id, plotpred, ax2)
if np.isnan(max(plotpred)) or np.isnan(min(plotpred)):
logger.debug("nan prediction, skipping...")
continue
c2maxmin = (max(plotpred) - min(plotpred))
if not c2maxmin:
c2maxmin = 1.
c2map_charge = colors.LinearSegmentedColormap.from_list(
'c2map_c',
[(0 / c2maxmin, 'darkblue'),
(np.abs(min(plotpred)) / c2maxmin, 'black'),
(2.0 * np.abs(min(plotpred)) / c2maxmin, 'blue'),
(2.5 * np.abs(min(plotpred)) / c2maxmin, 'green'),
(1, 'yellow')])
camera2.pixels.set_cmap(c2map_charge)
if not colorbar2:
camera2.add_colorbar(ax=ax2, label=" [photo-electrons]")
colorbar2 = camera2.colorbar
else:
camera2.colorbar = colorbar2
camera2.update(True)
plt.pause(1.) # make shorter
# plt.pause(0.1)
# if pp is not None:
# pp.savefig(fig)
# fig.savefig(str(args.output_path) + "_" +
# str(event.dl0.event_id) + '.png')
plt.close()
def run(self,inputs):
self.log.debug("--- PrepareDisplayStep RUN ---")
calibrated_event, geom_dict = inputs
for tel_id in calibrated_event.dl0.tels_with_data:
self.fig.clear()
cam_dimensions = (calibrated_event.inst.num_pixels[tel_id],
calibrated_event.inst.optical_foclen[tel_id])
self.fig.suptitle("EVENT {} {:.1e} @({:.1f},{:.1f}) @{:.1f}"
.format(calibrated_event.dl1.event_id, calibrated_event.mc.energy,
calibrated_event.mc.alt,
calibrated_event.mc.az,
np.sqrt(pow(calibrated_event.mc.core_x, 2) +
pow(calibrated_event.mc.core_y, 2))))
# Select number of pads to display (will depend on the integrator):
# charge and/or time of maximum.
# This last one is displayed only if the integrator calculates it
npads = 1
if not calibrated_event.dl1.tel[tel_id].peakpos[0] is None:
npads = 2
# Only create two pads if there is timing information extracted
# from the calibration
ax1 = self.fig.add_subplot(1, npads, 1)
# If the geometery has not already been added to geom_dict, it will
# be added in CameraPlotter
plotter = CameraPlotter(calibrated_event, geom_dict)
signals = calibrated_event.dl1.tel[tel_id].calibrated_image
camera1 = plotter.draw_camera(tel_id, signals, ax1)
cmaxmin = (max(signals) - min(signals))
color_list = [(0 / cmaxmin, 'darkblue'),
(np.abs(min(signals)) / cmaxmin, 'black'),
(2.0 * np.abs(min(signals)) / cmaxmin, 'blue'),
(2.5 * np.abs(min(signals)) / cmaxmin, 'green'),
(1, 'yellow')]
try:
cmap_charge = colors.LinearSegmentedColormap.from_list('cmap_c',
color_list)
camera1.pixels.set_cmap(cmap_charge)
camera1.add_colorbar(ax=ax1, label=" [photo-electrons]")
except:
camera1.pixels.set_cmap('jet')
ax1.set_title("CT {} ({}) - Mean pixel charge"
.format(tel_id, geom_dict[tel_id].cam_id))
if not calibrated_event.dl1.tel[tel_id].peakpos[0] is None:
ax2 = self.fig.add_subplot(1, npads, npads)
times = calibrated_event.dl1.tel[tel_id].peakpos
camera2 = plotter.draw_camera(tel_id, times, ax2)
tmaxmin = calibrated_event.dl0.tel[tel_id].num_samples
t_chargemax = times[signals.argmax()]
if t_chargemax > 15:
t_chargemax = 7
cmap_time = colors.LinearSegmentedColormap.from_list(
'cmap_t', [(0 / tmaxmin, 'darkgreen'),
(0.6 * t_chargemax / tmaxmin, 'green'),
(t_chargemax / tmaxmin, 'yellow'),
(1.4 * t_chargemax / tmaxmin, 'blue'),
(1, 'darkblue')])
try:
camera2.pixels.set_cmap(cmap_time)
camera2.add_colorbar(ax=ax2, label="[time slice]")
except:
camera2.pixels.set_cmap('jet')
ax2.set_title("CT {} ({}) - Pixel peak position"
.format(tel_id, geom_dict[tel_id].cam_id))
yield self.fig
self.log.debug("--- PrepareDisplayStep END ---")
def main():
script = os.path.splitext(os.path.basename(__file__))[0]
log.info("[SCRIPT] {}".format(script))
parser = argparse.ArgumentParser(
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('-f',
'--file',
dest='input_path',
action='store',
default=get_path('gamma_test.simtel.gz'),
help='path to the input file')
parser.add_argument('-O',
'--origin',
dest='origin',
action='store',
choices=InputFile.origin_list(),
default='hessio',
help='origin of the file')
parser.add_argument('-o',
'--output',
dest='output_dir',
action='store',
default=None,
help='path of the output directory to store the '
'images (default = input file directory)')
parser.add_argument('-e',
'--event',
dest='event_req',
action='store',
default=0,
type=int,
help='event index to plot (not id!)')
parser.add_argument('--id',
dest='event_id_f',
action='store_true',
default=False,
help='-e will specify event_id instead '
'of index')
parser.add_argument('-t',
'--telescope',
dest='tel',
action='store',
type=int,
default=None,
help='telecope to view')
parser.add_argument('-c',
'--channel',
dest='chan',
action='store',
type=int,
default=0,
help='channel to view (default = 0 (HG))')
parser.add_argument('--calib-help',
dest='calib_help',
action='store_true',
default=False,
help='display the arguments used for the camera '
'calibration')
logger_detail = parser.add_mutually_exclusive_group()
logger_detail.add_argument('-q',
'--quiet',
dest='quiet',
action='store_true',
default=False,
help='Quiet mode')
logger_detail.add_argument('-v',
'--verbose',
dest='verbose',
action='store_true',
default=False,
help='Verbose mode')
logger_detail.add_argument('-d',
'--debug',
dest='debug',
action='store_true',
default=False,
help='Debug mode')
args, excess_args = parser.parse_known_args()
if args.quiet:
log.setLevel(40)
if args.verbose:
log.setLevel(20)
if args.debug:
log.setLevel(10)
telid = args.tel
chan = args.chan
log.debug("[file] Reading file")
input_file = InputFile(args.input_path, args.origin)
event = input_file.get_event(args.event_req, args.event_id_f)
# Print event/args values
log.info("[event_index] {}".format(event.count))
log.info("[event_id] {}".format(event.dl0.event_id))
log.info("[telescope] {}".format(telid))
log.info("[channel] {}".format(chan))
params, unknown_args = calibration_parameters(excess_args, args.origin,
args.calib_help)
if unknown_args:
parser.print_help()
calibration_parameters(unknown_args, args.origin, True)
msg = 'unrecognized arguments: %s'
parser.error(msg % ' '.join(unknown_args))
# Create a dictionary to store any geoms in
geom = CameraGeometry.guess(*event.meta.pixel_pos[telid],
event.meta.optical_foclen[telid])
geom_dict = {telid: geom}
calibrated_event = calibrate_event(event, params, geom_dict)
# Select telescope
tels = list(calibrated_event.dl0.tels_with_data)
if telid is None or telid not in tels:
log.error("[event] please specify one of the following telescopes "
"for this event: {}".format(tels))
exit()
# Extract required images
data_ped = calibrated_event.dl1.tel[telid].pedestal_subtracted_adc[chan]
true_pe = calibrated_event.mc.tel[telid].photo_electrons
measured_pe = calibrated_event.dl1.tel[telid].pe_charge
max_time = np.unravel_index(np.argmax(data_ped), data_ped.shape)[1]
max_charges = np.max(data_ped, axis=1)
max_pixel = int(np.argmax(max_charges))
min_pixel = int(np.argmin(max_charges))
# Get Neighbours
max_pixel_nei = geom.neighbors[max_pixel]
min_pixel_nei = geom.neighbors[min_pixel]
# Get Windows
windows = calibrated_event.dl1.tel[telid].integration_window[chan]
length = np.sum(windows, axis=1)
start = np.argmax(windows, axis=1)
end = start + length - 1
# Draw figures
ax_max_nei = {}
ax_min_nei = {}
fig_waveforms = plt.figure(figsize=(18, 9))
fig_waveforms.subplots_adjust(hspace=.5)
fig_camera = plt.figure(figsize=(15, 12))
ax_max_pix = fig_waveforms.add_subplot(4, 2, 1)
ax_min_pix = fig_waveforms.add_subplot(4, 2, 2)
ax_max_nei[0] = fig_waveforms.add_subplot(4, 2, 3)
ax_min_nei[0] = fig_waveforms.add_subplot(4, 2, 4)
ax_max_nei[1] = fig_waveforms.add_subplot(4, 2, 5)
ax_min_nei[1] = fig_waveforms.add_subplot(4, 2, 6)
ax_max_nei[2] = fig_waveforms.add_subplot(4, 2, 7)
ax_min_nei[2] = fig_waveforms.add_subplot(4, 2, 8)
ax_img_nei = fig_camera.add_subplot(2, 2, 1)
ax_img_max = fig_camera.add_subplot(2, 2, 2)
ax_img_true = fig_camera.add_subplot(2, 2, 3)
ax_img_cal = fig_camera.add_subplot(2, 2, 4)
plotter = CameraPlotter(event, geom_dict)
# Draw max pixel traces
plotter.draw_waveform(data_ped[max_pixel], ax_max_pix)
ax_max_pix.set_title("(Max) Pixel: {}, "
"True: {}, "
"Measured = {:.3f}".format(max_pixel,
true_pe[max_pixel],
measured_pe[max_pixel]))
ax_max_pix.set_ylabel("Amplitude-Ped (ADC)")
max_ylim = ax_max_pix.get_ylim()
plotter.draw_waveform_positionline(start[max_pixel], ax_max_pix)
plotter.draw_waveform_positionline(end[max_pixel], ax_max_pix)
for i, ax in ax_max_nei.items():
if len(max_pixel_nei) > i:
pix = max_pixel_nei[i]
plotter.draw_waveform(data_ped[pix], ax)
ax.set_title("(Max Nei) Pixel: {}, "
"True: {}, "
"Measured = {:.3f}".format(pix, true_pe[pix],
measured_pe[pix]))
ax.set_ylabel("Amplitude-Ped (ADC)")
ax.set_ylim(max_ylim)
plotter.draw_waveform_positionline(start[pix], ax)
plotter.draw_waveform_positionline(end[pix], ax)
# Draw min pixel traces
plotter.draw_waveform(data_ped[min_pixel], ax_min_pix)
ax_min_pix.set_title("(Min) Pixel: {}, "
"True: {}, "
"Measured = {:.3f}".format(min_pixel,
true_pe[min_pixel],
measured_pe[min_pixel]))
ax_min_pix.set_ylabel("Amplitude-Ped (ADC)")
ax_min_pix.set_ylim(max_ylim)
plotter.draw_waveform_positionline(start[min_pixel], ax_min_pix)
plotter.draw_waveform_positionline(end[min_pixel], ax_min_pix)
for i, ax in ax_min_nei.items():
if len(min_pixel_nei) > i:
pix = min_pixel_nei[i]
plotter.draw_waveform(data_ped[pix], ax)
ax.set_title("(Min Nei) Pixel: {}, "
"True: {}, "
"Measured = {:.3f}".format(pix, true_pe[pix],
measured_pe[pix]))
ax.set_ylabel("Amplitude-Ped (ADC)")
ax.set_ylim(max_ylim)
plotter.draw_waveform_positionline(start[pix], ax)
plotter.draw_waveform_positionline(end[pix], ax)
# Draw cameras
nei_camera = np.zeros_like(max_charges, dtype=np.int)
nei_camera[min_pixel_nei] = 2
nei_camera[min_pixel] = 1
nei_camera[max_pixel_nei] = 3
nei_camera[max_pixel] = 4
camera = plotter.draw_camera(telid, nei_camera, ax_img_nei)
camera.cmap = plt.cm.viridis
ax_img_nei.set_title("Neighbour Map")
plotter.draw_camera_pixel_annotation(telid, max_pixel, min_pixel,
ax_img_nei)
camera = plotter.draw_camera(telid, data_ped[:, max_time], ax_img_max)
camera.add_colorbar(ax=ax_img_max, label="Amplitude-Ped (ADC)")
ax_img_max.set_title("Max Timeslice (T = {})".format(max_time))
plotter.draw_camera_pixel_annotation(telid, max_pixel, min_pixel,
ax_img_max)
camera = plotter.draw_camera(telid, true_pe, ax_img_true)
camera.add_colorbar(ax=ax_img_true, label="True Charge (Photo-electrons)")
ax_img_true.set_title("True Charge")
plotter.draw_camera_pixel_annotation(telid, max_pixel, min_pixel,
ax_img_true)
int_dict, inverted = integrator_dict()
integrator_name = '' if 'integrator' not in params else \
params['integrator']
camera = plotter.draw_camera(telid, measured_pe, ax_img_cal)
camera.add_colorbar(ax=ax_img_cal, label="Calib Charge (Photo-electrons)")
ax_img_cal.set_title("Charge (integrator={})".format(integrator_name))
plotter.draw_camera_pixel_annotation(telid, max_pixel, min_pixel,
ax_img_cal)
fig_waveforms.suptitle("Integrator = {}".format(integrator_name))
fig_camera.suptitle("Camera = {}".format(geom.cam_id))
waveform_output_name = "{}_e{}_t{}_c{}_integrator{}_waveform.pdf"\
.format(input_file.filename, event.count, telid, chan,
inverted[params['integrator']])
camera_output_name = "{}_e{}_t{}_c{}_integrator{}_camera.pdf"\
.format(input_file.filename, event.count, telid, chan,
inverted[params['integrator']])
output_dir = args.output_dir if args.output_dir is not None else \
input_file.output_directory
output_dir = os.path.join(output_dir, script)
if not os.path.exists(output_dir):
log.info("[output] Creating directory: {}".format(output_dir))
os.makedirs(output_dir)
waveform_output_path = os.path.join(output_dir, waveform_output_name)
log.info("[output] {}".format(waveform_output_path))
fig_waveforms.savefig(waveform_output_path,
format='pdf',
bbox_inches='tight')
camera_output_path = os.path.join(output_dir, camera_output_name)
log.info("[output] {}".format(camera_output_path))
fig_camera.savefig(camera_output_path, format='pdf', bbox_inches='tight')
log.info("[COMPLETE]")
def plot_muon_event(event, muonparams, args=None):
if muonparams['MuonRingParams'] is not None:
# Plot the muon event and overlay muon parameters
fig = plt.figure(figsize=(16, 7))
colorbar = None
colorbar2 = None
#for tel_id in event.dl0.tels_with_data:
for tel_id in muonparams['TelIds']:
idx = muonparams['TelIds'].index(tel_id)
if not muonparams['MuonRingParams'][idx]:
continue
#otherwise...
npads = 2
# Only create two pads if there is timing information extracted
# from the calibration
ax1 = fig.add_subplot(1, npads, 1)
plotter = CameraPlotter(event)
image = event.dl1.tel[tel_id].image[0]
geom = event.inst.subarray.tel[tel_id].camera
tailcuts = (5., 7.)
# Try a higher threshold for
if geom.cam_id == 'FlashCam':
tailcuts = (10., 12.)
clean_mask = tailcuts_clean(geom, image,
picture_thresh=tailcuts[0],
boundary_thresh=tailcuts[1])
signals = image * clean_mask
#print("Ring Centre in Nominal Coords:",muonparams[0].ring_center_x,muonparams[0].ring_center_y)
muon_incl = np.sqrt(muonparams['MuonRingParams'][idx].ring_center_x**2. +
muonparams['MuonRingParams'][idx].ring_center_y**2.)
muon_phi = np.arctan(muonparams['MuonRingParams'][idx].ring_center_y /
muonparams['MuonRingParams'][idx].ring_center_x)
rotr_angle = geom.pix_rotation
# if event.inst.optical_foclen[tel_id] > 10.*u.m and
# event.dl0.tel[tel_id].num_pixels != 1764:
if geom.cam_id == 'LSTCam' or geom.cam_id == 'NectarCam':
#print("Resetting the rotation angle")
rotr_angle = 0. * u.deg
# Convert to camera frame (centre & radius)
altaz = HorizonFrame(alt=event.mc.alt, az=event.mc.az)
ring_nominal = NominalFrame(x=muonparams['MuonRingParams'][idx].ring_center_x,
y=muonparams['MuonRingParams'][idx].ring_center_y,
array_direction=altaz,
pointing_direction=altaz)
# embed()
ring_camcoord = ring_nominal.transform_to(CameraFrame(
pointing_direction=altaz,
focal_length=event.inst.optical_foclen[tel_id],
rotation=rotr_angle))
centroid_rad = np.sqrt(ring_camcoord.y**2 + ring_camcoord.x**2)
centroid = (ring_camcoord.x.value, ring_camcoord.y.value)
ringrad_camcoord = muonparams['MuonRingParams'][idx].ring_radius.to(u.rad) \
* event.inst.optical_foclen[tel_id] * 2. # But not FC?
px, py = event.inst.pixel_pos[tel_id]
flen = event.inst.optical_foclen[tel_id]
camera_coord = CameraFrame(x=px, y=py,
z=np.zeros(px.shape) * u.m,
focal_length=flen,
rotation=geom.pix_rotation)
nom_coord = camera_coord.transform_to(
NominalFrame(array_direction=altaz,
pointing_direction=altaz)
)
px = nom_coord.x.to(u.deg)
py = nom_coord.y.to(u.deg)
dist = np.sqrt(np.power( px - muonparams['MuonRingParams'][idx].ring_center_x, 2)
+ np.power(py - muonparams['MuonRingParams'][idx].ring_center_y, 2))
ring_dist = np.abs(dist - muonparams['MuonRingParams'][idx].ring_radius)
pixRmask = ring_dist < muonparams['MuonRingParams'][idx].ring_radius * 0.4
#if muonparams[1] is not None:
if muonparams['MuonIntensityParams'][idx] is not None:
signals *= muonparams['MuonIntensityParams'][idx].mask
camera1 = plotter.draw_camera(tel_id, signals, ax1)
cmaxmin = (max(signals) - min(signals))
cmin = min(signals)
if not cmin:
cmin = 1.
if not cmaxmin:
cmaxmin = 1.
cmap_charge = colors.LinearSegmentedColormap.from_list(
'cmap_c', [(0 / cmaxmin, 'darkblue'),
(np.abs(cmin) / cmaxmin, 'black'),
(2.0 * np.abs(cmin) / cmaxmin, 'blue'),
(2.5 * np.abs(cmin) / cmaxmin, 'green'),
(1, 'yellow')]
)
camera1.pixels.set_cmap(cmap_charge)
if not colorbar:
camera1.add_colorbar(ax=ax1, label=" [photo-electrons]")
colorbar = camera1.colorbar
else:
camera1.colorbar = colorbar
camera1.update(True)
camera1.add_ellipse(centroid, ringrad_camcoord.value,
ringrad_camcoord.value, 0., 0., color="red")
if muonparams['MuonIntensityParams'][idx] is not None:
# continue #Comment this...(should ringwidthfrac also be *0.5?)
ringwidthfrac = muonparams['MuonIntensityParams'][idx].ring_width / muonparams['MuonRingParams'][idx].ring_radius
ringrad_inner = ringrad_camcoord * (1. - ringwidthfrac)
ringrad_outer = ringrad_camcoord * (1. + ringwidthfrac)
camera1.add_ellipse(centroid, ringrad_inner.value,
ringrad_inner.value, 0., 0.,
color="magenta")
camera1.add_ellipse(centroid, ringrad_outer.value,
ringrad_outer.value, 0., 0., color="magenta")
npads = 2
ax2 = fig.add_subplot(1, npads, npads)
pred = muonparams['MuonIntensityParams'][idx].prediction
if len(pred) != np.sum(muonparams['MuonIntensityParams'][idx].mask):
print("Warning! Lengths do not match...len(pred)=",
len(pred), "len(mask)=", np.sum(muonparams['MuonIntensityParams'][idx].mask))
# Numpy broadcasting - fill in the shape
plotpred = np.zeros(image.shape)
plotpred[muonparams['MuonIntensityParams'][idx].mask == True] = pred
camera2 = plotter.draw_camera(tel_id, plotpred, ax2)
if np.isnan(max(plotpred)) or np.isnan(min(plotpred)):
print("nan prediction, skipping...")
continue
c2maxmin = (max(plotpred) - min(plotpred))
if not c2maxmin:
c2maxmin = 1.
c2map_charge = colors.LinearSegmentedColormap.from_list(
'c2map_c', [(0 / c2maxmin, 'darkblue'),
(np.abs(min(plotpred)) / c2maxmin, 'black'),
(2.0 * np.abs(min(plotpred)) / c2maxmin, 'blue'),
(2.5 * np.abs(min(plotpred)) / c2maxmin, 'green'),
(1, 'yellow')]
)
camera2.pixels.set_cmap(c2map_charge)
if not colorbar2:
camera2.add_colorbar(ax=ax2, label=" [photo-electrons]")
colorbar2 = camera2.colorbar
else:
camera2.colorbar = colorbar2
camera2.update(True)
plt.pause(1.) # make shorter
# plt.pause(0.1)
# if pp is not None:
# pp.savefig(fig)
#fig.savefig(str(args.output_path) + "_" +
# str(event.dl0.event_id) + '.png')
plt.close()
def display_telescope(event, tel_id, display, geom_dict, pp, fig):
fig.clear()
cam_dimensions = (event.dl0.tel[tel_id].num_pixels,
event.meta.optical_foclen[tel_id])
fig.suptitle("EVENT {} {:.1e} @({:.1f},{:.1f}) @{:.1f}"
.format(event.dl1.event_id, event.mc.energy,
event.mc.alt,
event.mc.az,
np.sqrt(pow(event.mc.core_x, 2) +
pow(event.mc.core_y, 2))))
# Select number of pads to display (will depend on the integrator):
# charge and/or time of maximum.
# This last one is displayed only if the integrator calculates it
npads = 1
if not event.dl1.tel[tel_id].peakpos[0] is None:
npads = 2
# Only create two pads if there is timing information extracted
# from the calibration
ax1 = fig.add_subplot(1, npads, 1)
# If the geometery has not already been added to geom_dict, it will
# be added in CameraPlotter
plotter = CameraPlotter(event, geom_dict)
signals = event.dl1.tel[tel_id].pe_charge
camera1 = plotter.draw_camera(tel_id, signals, ax1)
cmaxmin = (max(signals) - min(signals))
cmap_charge = colors.LinearSegmentedColormap.from_list(
'cmap_c', [(0 / cmaxmin, 'darkblue'),
(np.abs(min(signals)) / cmaxmin, 'black'),
(2.0 * np.abs(min(signals)) / cmaxmin, 'blue'),
(2.5 * np.abs(min(signals)) / cmaxmin, 'green'),
(1, 'yellow')])
camera1.pixels.set_cmap(cmap_charge)
camera1.add_colorbar(ax=ax1, label=" [photo-electrons]")
ax1.set_title("CT {} ({}) - Mean pixel charge"
.format(tel_id, geom_dict[cam_dimensions].cam_id))
if not event.dl1.tel[tel_id].peakpos[0] is None:
ax2 = fig.add_subplot(1, npads, npads)
times = event.dl1.tel[tel_id].peakpos
camera2 = plotter.draw_camera(tel_id, times, ax2)
tmaxmin = event.dl0.tel[tel_id].num_samples
t_chargemax = times[signals.argmax()]
if t_chargemax > 15:
t_chargemax = 7
cmap_time = colors.LinearSegmentedColormap.from_list(
'cmap_t', [(0 / tmaxmin, 'darkgreen'),
(0.6 * t_chargemax / tmaxmin, 'green'),
(t_chargemax / tmaxmin, 'yellow'),
(1.4 * t_chargemax / tmaxmin, 'blue'),
(1, 'darkblue')])
camera2.pixels.set_cmap(cmap_time)
camera2.add_colorbar(ax=ax2, label="[time slice]")
ax2.set_title("CT {} ({}) - Pixel peak position"
.format(tel_id, geom_dict[cam_dimensions].cam_id))
if display:
plt.pause(0.1)
if pp is not None:
pp.savefig(fig)
def main():
script = os.path.splitext(os.path.basename(__file__))[0]
log.info("[SCRIPT] {}".format(script))
parser = argparse.ArgumentParser(description='Create a gif of an event')
parser.add_argument('-f', '--file', dest='input_path', action='store',
required=True, help='path to the input file')
parser.add_argument('-O', '--origin', dest='origin', action='store',
required=True, help='origin of the file: {}'
.format(origin_list()))
parser.add_argument('-o', '--output', dest='output_dir', action='store',
default=None,
help='path of the output directory to store the '
'images (default = input file directory)')
parser.add_argument('-e', '--event', dest='event_req', action='store',
required=True, type=int,
help='event index to plot (not id!)')
parser.add_argument('--id', dest='event_id_f', action='store_true',
default=False, help='-e will specify event_id instead '
'of index')
parser.add_argument('-t', '--telescope', dest='tel', action='store',
type=int, default=None, help='telecope to view')
parser.add_argument('-c', '--channel', dest='chan', action='store',
type=int, default=0,
help='channel to view (default = 0 (HG))')
calibration_arguments(parser)
logger_detail = parser.add_mutually_exclusive_group()
logger_detail.add_argument('-q', '--quiet', dest='quiet',
action='store_true', default=False,
help='Quiet mode')
logger_detail.add_argument('-v', '--verbose', dest='verbose',
action='store_true', default=False,
help='Verbose mode')
logger_detail.add_argument('-d', '--debug', dest='debug',
action='store_true', default=False,
help='Debug mode')
args = parser.parse_args()
if args.quiet:
log.setLevel(40)
if args.verbose:
log.setLevel(20)
if args.debug:
log.setLevel(10)
telid = args.tel
chan = args.chan
log.debug("[file] Reading file")
input_file = InputFile(args.input_path, args.origin)
event = input_file.get_event(args.event_req, args.event_id_f)
# Print event/args values
log.info("[event_index] {}".format(event.count))
log.info("[event_id] {}".format(event.dl0.event_id))
log.info("[telescope] {}".format(telid))
log.info("[channel] {}".format(chan))
params = calibration_parameters(args)
# Create a dictionary to store any geoms in
geom = CameraGeometry.guess(*event.meta.pixel_pos[telid],
event.meta.optical_foclen[telid])
geom_dict = {telid: geom}
calibrated_event = calibrate_event(event, params, geom_dict)
# Select telescope
tels = list(calibrated_event.dl0.tels_with_data)
if telid is None or telid not in tels:
log.error("[event] please specify one of the following telescopes "
"for this event: {}".format(tels))
exit()
# Extract required images
data_ped = calibrated_event.dl1.tel[telid].pedestal_subtracted_adc[chan]
true_pe = calibrated_event.mc.tel[telid].photo_electrons
measured_pe = calibrated_event.dl1.tel[telid].pe_charge
max_time = np.unravel_index(np.argmax(data_ped), data_ped.shape)[1]
max_charges = np.max(data_ped, axis=1)
max_pixel = int(np.argmax(max_charges))
min_pixel = int(np.argmin(max_charges))
# Get Neighbours
max_pixel_nei = geom.neighbors[max_pixel]
min_pixel_nei = geom.neighbors[min_pixel]
# Get Windows
windows = calibrated_event.dl1.tel[telid].integration_window[chan]
length = np.sum(windows, axis=1)
start = np.argmax(windows, axis=1)
end = start + length - 1
# Draw figures
ax_max_nei = {}
ax_min_nei = {}
fig_waveforms = plt.figure(figsize=(24, 10))
fig_waveforms.subplots_adjust(hspace=.5)
fig_camera = plt.figure(figsize=(30, 24))
ax_max_pix = fig_waveforms.add_subplot(4, 2, 1)
ax_min_pix = fig_waveforms.add_subplot(4, 2, 2)
ax_max_nei[0] = fig_waveforms.add_subplot(4, 2, 3)
ax_min_nei[0] = fig_waveforms.add_subplot(4, 2, 4)
ax_max_nei[1] = fig_waveforms.add_subplot(4, 2, 5)
ax_min_nei[1] = fig_waveforms.add_subplot(4, 2, 6)
ax_max_nei[2] = fig_waveforms.add_subplot(4, 2, 7)
ax_min_nei[2] = fig_waveforms.add_subplot(4, 2, 8)
ax_img_nei = fig_camera.add_subplot(2, 2, 1)
ax_img_max = fig_camera.add_subplot(2, 2, 2)
ax_img_true = fig_camera.add_subplot(2, 2, 3)
ax_img_cal = fig_camera.add_subplot(2, 2, 4)
plotter = CameraPlotter(event, geom_dict)
# Draw max pixel traces
plotter.draw_waveform(data_ped[max_pixel], ax_max_pix)
ax_max_pix.set_title("(Max) Pixel: {}, "
"True: {}, "
"Measured = {}".format(max_pixel, true_pe[max_pixel],
measured_pe[max_pixel]))
ax_max_pix.set_ylabel("Amplitude-Ped (ADC)")
max_ylim = ax_max_pix.get_ylim()
plotter.draw_waveform_positionline(start[max_pixel], ax_max_pix)
plotter.draw_waveform_positionline(end[max_pixel], ax_max_pix)
for i, ax in ax_max_nei.items():
if len(max_pixel_nei) > i:
pix = max_pixel_nei[i]
plotter.draw_waveform(data_ped[pix], ax)
ax.set_title("(Max Nei) Pixel: {}, "
"True: {}, "
"Measured = {}".format(pix, true_pe[pix],
measured_pe[pix]))
ax.set_ylabel("Amplitude-Ped (ADC)")
ax.set_ylim(max_ylim)
plotter.draw_waveform_positionline(start[pix], ax)
plotter.draw_waveform_positionline(end[pix], ax)
# Draw min pixel traces
plotter.draw_waveform(data_ped[min_pixel], ax_min_pix)
ax_min_pix.set_title("(Min) Pixel: {}, "
"True: {}, "
"Measured = {}".format(min_pixel, true_pe[min_pixel],
measured_pe[min_pixel]))
ax_min_pix.set_ylabel("Amplitude-Ped (ADC)")
ax_min_pix.set_ylim(max_ylim)
plotter.draw_waveform_positionline(start[min_pixel], ax_min_pix)
plotter.draw_waveform_positionline(end[min_pixel], ax_min_pix)
for i, ax in ax_min_nei.items():
if len(min_pixel_nei) > i:
pix = min_pixel_nei[i]
plotter.draw_waveform(data_ped[pix], ax)
ax.set_title("(Min Nei) Pixel: {}, "
"True: {}, "
"Measured = {}".format(pix, true_pe[pix],
measured_pe[pix]))
ax.set_ylabel("Amplitude-Ped (ADC)")
ax.set_ylim(max_ylim)
plotter.draw_waveform_positionline(start[pix], ax)
plotter.draw_waveform_positionline(end[pix], ax)
# Draw cameras
nei_camera = np.zeros_like(max_charges, dtype=np.int)
nei_camera[min_pixel_nei] = 2
nei_camera[min_pixel] = 1
nei_camera[max_pixel_nei] = 3
nei_camera[max_pixel] = 4
camera = plotter.draw_camera(telid, nei_camera, ax_img_nei)
camera.cmap = plt.cm.viridis
ax_img_nei.set_title("Neighbour Map")
plotter.draw_camera_pixel_annotation(telid, max_pixel, min_pixel,
ax_img_nei)
camera = plotter.draw_camera(telid, data_ped[:, max_time], ax_img_max)
camera.add_colorbar(ax=ax_img_max, label="Amplitude-Ped (ADC)")
ax_img_max.set_title("Max Timeslice (T = {})".format(max_time))
plotter.draw_camera_pixel_annotation(telid, max_pixel, min_pixel,
ax_img_max)
camera = plotter.draw_camera(telid, true_pe, ax_img_true)
camera.add_colorbar(ax=ax_img_true, label="True Charge (Photo-electrons)")
ax_img_true.set_title("True Charge")
plotter.draw_camera_pixel_annotation(telid, max_pixel, min_pixel,
ax_img_true)
camera = plotter.draw_camera(telid, measured_pe, ax_img_cal)
camera.add_colorbar(ax=ax_img_cal, label="Calib Charge (Photo-electrons)")
ax_img_cal.set_title("Charge (integrator={})".format(params['integrator']))
plotter.draw_camera_pixel_annotation(telid, max_pixel, min_pixel,
ax_img_cal)
fig_waveforms.suptitle("Integrator = {}".format(params['integrator']))
fig_camera.suptitle("Camera = {}".format(geom.cam_id))
# TODO: another figure of all waveforms that have non-zero true charge
waveform_output_name = "{}_e{}_t{}_c{}_integrator{}_waveform.pdf"\
.format(input_file.filename, event.count, telid, chan, args.integrator)
camera_output_name = "{}_e{}_t{}_c{}_integrator{}_camera.pdf"\
.format(input_file.filename, event.count, telid, chan, args.integrator)
output_dir = args.output_dir if args.output_dir is not None else \
input_file.output_directory
output_dir = os.path.join(output_dir, script)
if not os.path.exists(output_dir):
log.info("[output] Creating directory: {}".format(output_dir))
os.makedirs(output_dir)
waveform_output_path = os.path.join(output_dir, waveform_output_name)
log.info("[output] {}".format(waveform_output_path))
fig_waveforms.savefig(waveform_output_path, format='pdf')
camera_output_path = os.path.join(output_dir, camera_output_name)
log.info("[output] {}".format(camera_output_path))
fig_camera.savefig(camera_output_path, format='pdf')
log.info("[COMPLETE]")
def plot_muon_event(event, muonparams, geom_dict=None, args=None):
if muonparams[0] is not None:
# Plot the muon event and overlay muon parameters
fig = plt.figure(figsize=(16, 7))
# if args.display:
# plt.show(block=False)
#pp = PdfPages(args.output_path) if args.output_path is not None else None
# pp = None #For now, need to correct this
colorbar = None
colorbar2 = None
for tel_id in event.dl0.tels_with_data:
npads = 2
# Only create two pads if there is timing information extracted
# from the calibration
ax1 = fig.add_subplot(1, npads, 1)
plotter = CameraPlotter(event, geom_dict)
#image = event.dl1.tel[tel_id].calibrated_image
image = event.dl1.tel[tel_id].image[0]
# Get geometry
geom = None
if geom_dict is not None and tel_id in geom_dict:
geom = geom_dict[tel_id]
else:
#log.debug("[calib] Guessing camera geometry")
geom = CameraGeometry.guess(*event.inst.pixel_pos[tel_id],
event.inst.optical_foclen[tel_id])
#log.debug("[calib] Camera geometry found")
if geom_dict is not None:
geom_dict[tel_id] = geom
tailcuts = (5., 7.)
# Try a higher threshold for
if geom.cam_id == 'FlashCam':
tailcuts = (10., 12.)
#print("Using Tail Cuts:",tailcuts)
clean_mask = tailcuts_clean(geom,
image,
picture_thresh=tailcuts[0],
boundary_thresh=tailcuts[1])
signals = image * clean_mask
#print("Ring Centre in Nominal Coords:",muonparams[0].ring_center_x,muonparams[0].ring_center_y)
muon_incl = np.sqrt(muonparams[0].ring_center_x**2. +
muonparams[0].ring_center_y**2.)
muon_phi = np.arctan(muonparams[0].ring_center_y /
muonparams[0].ring_center_x)
rotr_angle = geom.pix_rotation
# if event.inst.optical_foclen[tel_id] > 10.*u.m and
# event.dl0.tel[tel_id].num_pixels != 1764:
if geom.cam_id == 'LSTCam' or geom.cam_id == 'NectarCam':
#print("Resetting the rotation angle")
rotr_angle = 0. * u.deg
# Convert to camera frame (centre & radius)
altaz = HorizonFrame(alt=event.mc.alt, az=event.mc.az)
ring_nominal = NominalFrame(x=muonparams[0].ring_center_x,
y=muonparams[0].ring_center_y,
array_direction=altaz,
pointing_direction=altaz)
# embed()
ring_camcoord = ring_nominal.transform_to(
CameraFrame(pointing_direction=altaz,
focal_length=event.inst.optical_foclen[tel_id],
rotation=rotr_angle))
centroid_rad = np.sqrt(ring_camcoord.y**2 + ring_camcoord.x**2)
centroid = (ring_camcoord.x.value, ring_camcoord.y.value)
ringrad_camcoord = muonparams[0].ring_radius.to(u.rad) \
* event.inst.optical_foclen[tel_id] * 2. # But not FC?
#rot_angle = 0.*u.deg
# if event.inst.optical_foclen[tel_id] > 10.*u.m and event.dl0.tel[tel_id].num_pixels != 1764:
#rot_angle = -100.14*u.deg
px, py = event.inst.pixel_pos[tel_id]
flen = event.inst.optical_foclen[tel_id]
camera_coord = CameraFrame(x=px,
y=py,
z=np.zeros(px.shape) * u.m,
focal_length=flen,
rotation=geom.pix_rotation)
nom_coord = camera_coord.transform_to(
NominalFrame(array_direction=altaz, pointing_direction=altaz))
#,focal_length = event.inst.optical_foclen[tel_id])) # tel['TelescopeTable_VersionFeb2016'][tel['TelescopeTable_VersionFeb2016']['TelID']==telid]['FL'][0]*u.m))
px = nom_coord.x.to(u.deg)
py = nom_coord.y.to(u.deg)
dist = np.sqrt(
np.power(px - muonparams[0].ring_center_x, 2) +
np.power(py - muonparams[0].ring_center_y, 2))
ring_dist = np.abs(dist - muonparams[0].ring_radius)
pixRmask = ring_dist < muonparams[0].ring_radius * 0.4
if muonparams[1] is not None:
signals *= muonparams[1].mask
camera1 = plotter.draw_camera(tel_id, signals, ax1)
cmaxmin = (max(signals) - min(signals))
if not cmaxmin:
cmaxmin = 1.
cmap_charge = colors.LinearSegmentedColormap.from_list(
'cmap_c', [(0 / cmaxmin, 'darkblue'),
(np.abs(min(signals)) / cmaxmin, 'black'),
(2.0 * np.abs(min(signals)) / cmaxmin, 'blue'),
(2.5 * np.abs(min(signals)) / cmaxmin, 'green'),
(1, 'yellow')])
camera1.pixels.set_cmap(cmap_charge)
if not colorbar:
camera1.add_colorbar(ax=ax1, label=" [photo-electrons]")
colorbar = camera1.colorbar
else:
camera1.colorbar = colorbar
camera1.update(True)
camera1.add_ellipse(centroid,
ringrad_camcoord.value,
ringrad_camcoord.value,
0.,
0.,
color="red")
# ax1.set_title("CT {} ({}) - Mean pixel charge"
# .format(tel_id, geom_dict[tel_id].cam_id))
if muonparams[1] is not None:
# continue #Comment this...(should ringwidthfrac also be *0.5?)
ringwidthfrac = muonparams[1].ring_width / muonparams[
0].ring_radius
ringrad_inner = ringrad_camcoord * (1. - ringwidthfrac)
ringrad_outer = ringrad_camcoord * (1. + ringwidthfrac)
camera1.add_ellipse(centroid,
ringrad_inner.value,
ringrad_inner.value,
0.,
0.,
color="magenta")
camera1.add_ellipse(centroid,
ringrad_outer.value,
ringrad_outer.value,
0.,
0.,
color="magenta")
npads = 2
ax2 = fig.add_subplot(1, npads, npads)
pred = muonparams[1].prediction
if len(pred) != np.sum(muonparams[1].mask):
print("Warning! Lengths do not match...len(pred)=",
len(pred), "len(mask)=", np.sum(muonparams[1].mask))
# Numpy broadcasting - fill in the shape
plotpred = np.zeros(image.shape)
plotpred[muonparams[1].mask == True] = pred
camera2 = plotter.draw_camera(tel_id, plotpred, ax2)
c2maxmin = (max(plotpred) - min(plotpred))
if not c2maxmin:
c2maxmin = 1.
c2map_charge = colors.LinearSegmentedColormap.from_list(
'c2map_c',
[(0 / c2maxmin, 'darkblue'),
(np.abs(min(plotpred)) / c2maxmin, 'black'),
(2.0 * np.abs(min(plotpred)) / c2maxmin, 'blue'),
(2.5 * np.abs(min(plotpred)) / c2maxmin, 'green'),
(1, 'yellow')])
camera2.pixels.set_cmap(c2map_charge)
if not colorbar2:
camera2.add_colorbar(ax=ax2, label=" [photo-electrons]")
colorbar2 = camera2.colorbar
else:
camera2.colorbar = colorbar2
camera2.update(True)
plt.pause(1.) # make shorter
# plt.pause(0.1)
# if pp is not None:
# pp.savefig(fig)
fig.savefig(
str(args.output_path) + "_" + str(event.dl0.event_id) + '.png')
plt.close()