frame=tiltedframe,
).transform_to(array_disp.frame)
markers = ax.plot([core_coord.x.value], [core_coord.y.value],
"r+",
markersize=10)
# plot the hit pattern (triggered tels).
# first expand the tel.keys() list into a fixed-length vector,
# then set the value so that the ArrayDisplay shows it as color per
# telescope.
tel_idx = source.subarray.tel_indices
hit_pattern[:] = 0
mask = [tel_idx[t] for t in event.r0.tel.keys()]
hit_pattern[mask] = 10.0
array_disp.values = hit_pattern
# calculate and plot the hillas params
for tel_id in event.dl0.tel.keys():
# Camera Geometry required for hillas parametrization
camgeom = subarray.tel[tel_id].camera.geometry
# note the [0] is for channel 0 which is high-gain channel
image = event.dl1.tel[tel_id].image
time = event.dl1.tel[tel_id].peak_time
# Cleaning of the image
cleaned_image = image.copy()
from matplotlib import pyplot as plt
if __name__ == '__main__':
plt.style.use("ggplot")
plt.figure(figsize=(10, 8))
arrayfile = datasets.get_path("PROD2_telconfig.fits.gz")
tels = Table.read(arrayfile, hdu="TELESCOPE_LEVEL0")
adisp = ArrayDisplay(tels['TelX'], tels['TelY'], tels['MirrorArea'] * 2,
title='PROD2 telescopes', autoupdate=True)
plt.tight_layout()
values = np.zeros(len(tels))
# do a small animation to show various trigger patterns:
for ii in range(20):
# generate a random trigger pattern and integrated intensity:
ntrig = np.random.poisson(10)
trigmask = np.random.random_integers(len(tels) - 1, size=ntrig)
values[:] = 0
values[trigmask] = np.random.uniform(0, 100, size=ntrig)
# update the display:
adisp.values = values
plt.pause(0.5)
# display the array
subarray = event.inst.subarray
ad = ArrayDisplay(subarray, tel_scale=3.0)
print("Now setting vectors")
plt.pause(1.0)
plt.tight_layout()
for phi in np.linspace(0, 360, 30) * u.deg:
r = np.cos(phi / 2)
ad.set_vector_rho_phi(r, phi)
plt.pause(0.01)
ad.set_vector_rho_phi(0, 0 * u.deg)
plt.pause(1.0)
print("Now setting values")
ad.telescopes.set_linewidth(0)
for ii in range(50):
vals = np.random.uniform(100.0, size=subarray.num_tels)
ad.values = vals
plt.pause(0.01)
print("Setting labels")
for ii in range(3):
ad.add_labels()
plt.pause(0.5)
ad.remove_labels()
plt.pause(0.5)
from numpy import ones_like
import matplotlib.pylab as plt
if __name__ == '__main__':
plt.style.use("ggplot")
plt.figure(figsize=(9.5, 8.5))
# load up an example table that has the telescope positions and
# mirror areas in it:
arrayfile = datasets.get_path("PROD2_telconfig.fits.gz")
tels = Table.read(arrayfile, hdu="TELESCOPE_LEVEL0")
X = tels['TelX']
Y = tels['TelY']
A = tels['MirrorArea'] * 2 # exaggerate scale a bit
# display the array, and set the color value to 50
ad = ArrayDisplay(X, Y, A, title="Prod 2 Full Array")
ad.values = ones_like(X) * 50
# label them
for tel in tels:
name = "CT{tid}".format(tid=tel['TelID'])
plt.text(tel['TelX'], tel['TelY'], name, fontsize=8)
ad.axes.set_xlim(-1000, 1000)
ad.axes.set_ylim(-1000, 1000)
plt.tight_layout()
plt.show()
y=event.mc.core_y,
frame=tiltedframe
).transform_to(array_disp.frame)
markers = ax.plot([core_coord.x.value, ], [core_coord.y.value, ],
"r+", markersize=10)
# plot the hit pattern (triggered tels).
# first expand the tels_with_data list into a fixed-length vector,
# then set the value so that the ArrayDisplay shows it as color per
# telescope.
tel_idx = event.inst.subarray.tel_indices
hit_pattern[:] = 0
mask = [tel_idx[t] for t in event.r0.tels_with_data]
hit_pattern[mask] = 10.0
array_disp.values = hit_pattern
# calculate and plot the hillas params
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
if __name__ == '__main__':
plt.style.use("ggplot")
plt.figure(figsize=(10, 8))
arrayfile = datasets.get_path("PROD2_telconfig.fits.gz")
tels = Table.read(arrayfile, hdu="TELESCOPE_LEVEL0")
adisp = ArrayDisplay(tels['TelX'],
tels['TelY'],
tels['MirrorArea'] * 2,
title='PROD2 telescopes',
autoupdate=True)
plt.tight_layout()
values = np.zeros(len(tels))
# do a small animation to show various trigger patterns:
for ii in range(20):
# generate a random trigger pattern and integrated intensity:
ntrig = np.random.poisson(10)
trigmask = np.random.random_integers(len(tels) - 1, size=ntrig)
values[:] = 0
values[trigmask] = np.random.uniform(0, 100, size=ntrig)
# update the display:
adisp.values = values
plt.pause(0.5)
