def plot_short_map(short_map, name):
data_top = short_map["top"]
data_bot = short_map["bottom"]
new_data = {}
for cell_num in data_top.keys():
if cell_num not in data_bot.keys():
# This shouldn't happen
raise ValueError
top = bool(data_top[cell_num])
bot = bool(data_bot[cell_num])
if top and bot:
new_data[cell_num] = 3
elif top and not bot:
new_data[cell_num] = 2
elif not top and bot:
new_data[cell_num] = 1
else:
new_data[cell_num] = 0
sn_tracker = sn.tracker("short_" + name, with_palette=True)
sn_tracker.draw_content = False
sn_tracker.draw_cellnum = False
sn_tracker.draw_cellid = False
for cell_num in new_data.keys():
# cell_num = side * 113 * 9 + row * 9 + layer
if cell_num == 0 * 113 * 9 + 108 * 9 + 4:
continue
elif cell_num == 0 * 113 * 9 + 89 * 9 + 1:
continue
sn_tracker.setcontent(cell_num, new_data[cell_num])
sn_tracker.draw()
sn_tracker.save("/Users/williamquinn/Desktop/tracksioning")
del sn_tracker
def plot_event_map(name: str, hits: list, output_directory):
sntracker = sn.tracker(name, with_palette=True)
sntracker.draw_cellid_label()
sntracker.draw_content_label('{:.2f}')
for i_cell in range(len(hits)):
if hits[i_cell] == 0:
continue
sntracker.setcontent(i_cell, hits[i_cell])
# sntracker.setrange(0, 35)
sntracker.draw()
sntracker.save(output_directory)
def draw_propagation_vs_time(run: int, events):
sn_tracker = sndisplay.tracker('tr_prop_vs_time_' + str(run))
sn_tracker.draw_cellid_label()
sn_tracker.draw_content_label('{:.0e}')
lower = 0
higher = 100
x = [[] for i in range(2034)]
y = [[] for i in range(2034)]
for event in events:
event_time = []
for calo_event in event[0]:
event_time.append(calo_event.time)
event_time = np.array(event_time)
if event_time.size == 0:
continue
event_time = np.min(event_time)
tracker_events = event[1]
for tracker_event in tracker_events:
if tracker_event.timestamp_r1 is None or tracker_event.timestamp_r2 is None \
or tracker_event.time_bottom_cathode is None or tracker_event.time_top_cathode is None:
continue
t5 = (tracker_event.time_bottom_cathode - event_time) * 1e6
t6 = (tracker_event.time_top_cathode - event_time) * 1e6
t1 = (tracker_event.timestamp_r1 * 1.25e-8 - event_time) * 1e6
t2 = (tracker_event.timestamp_r2 * 1.25e-8 - event_time) * 1e6
if t5 < 10 and t6 < 10:
continue
if lower < t1 < higher and lower < t2 < higher:
x[tracker_event.cell_num].append(event_time)
y[tracker_event.cell_num].append(t5 + t6)
for i_cell in range(len(x)):
try:
popt, pcov = curve_fit(xdata=x[i_cell], ydata=y[i_cell], f=linear)
m = popt[0]
c = popt[1]
sn_tracker.setcontent(i_cell, m)
except:
pass
sn_tracker.setrange(-0.001, 0.001)
sn_tracker.draw()
sn_tracker.save("/Users/williamquinn/Desktop/" + str(run))
def draw_bottom_cathode_events(run: int, events):
sn_tracker = sndisplay.tracker('tr_bottom_cathode_' + str(run))
sn_tracker.draw_cellid_label()
sn_tracker.draw_content_label('{}')
n_events = [0 for i in range(2034)]
for event in events:
tracker_events = event[1]
for i_tr in tracker_events:
if i_tr.time_bottom_cathode is not None:
n_events[i_tr.cell_num] += 1
for i in range(2034):
if n_events[i] > 0:
sn_tracker.setcontent(i, n_events[i])
sn_tracker.draw()
sn_tracker.save("/Users/williamquinn/Desktop/" + str(run))
def draw_normalised_anode_events(run: int, events):
sn_tracker = sndisplay.tracker('tr_anode_normalised_' + str(run))
sn_tracker.draw_cellid_label()
sn_tracker.draw_content_label('{:.3f}')
n_events = [0 for i in range(2034)]
for event in events:
tracker_events = event[1]
for i_tr in tracker_events:
if i_tr.time_anode is not None:
n_events[i_tr.cell_num] += 1
for i in range(2034):
if n_events[i] > 0:
sn_tracker.setcontent(i, n_events[i] / np.sum(n_events))
sn_tracker.setrange(0, 0.01)
sn_tracker.draw()
sn_tracker.save("/Users/williamquinn/Desktop/" + str(run))
def draw_av_propagation(run: int, events):
lower = -50
higher = 100
sn_tracker = sndisplay.tracker('tr_av_propagation_' + str(run))
sn_tracker.draw_cellid_label()
sn_tracker.draw_content_label('{:.2f}')
propagation_times = [[] for i in range(2034)]
for event in events:
event_time = []
for calo_event in event[0]:
event_time.append(calo_event.time)
event_time = np.array(event_time)
if event_time.size == 0:
continue
event_time = np.min(event_time)
tracker_events = event[1]
for tracker_event in tracker_events:
if tracker_event.time_bottom_cathode is None or tracker_event.time_top_cathode is None:
continue
t5 = (tracker_event.time_bottom_cathode - event_time) * 1e6
t6 = (tracker_event.time_top_cathode - event_time) * 1e6
# print(t5 + t6)
if t5 < 10 and t6 < 10:
continue
if lower < t5 < higher and lower < t6 < higher:
propagation_times[int(tracker_event.cell_num)].append(t5 + t6)
for i_cell in range(len(propagation_times)):
average = 0
if len(propagation_times[i_cell]) == 0:
continue
for i_propagation in range(len(propagation_times[i_cell])):
average += propagation_times[i_cell][i_propagation]
average = average / len(propagation_times[i_cell])
sn_tracker.setcontent(i_cell, average)
sn_tracker.draw()
sn_tracker.save("/Users/williamquinn/Desktop/" + str(run))
def draw_std_propagation(run: int, events):
lower = -50
higher = 100
sn_tracker = sndisplay.tracker('tr_std_propagation_' + str(run))
sn_tracker.draw_cellid_label()
sn_tracker.draw_content_label('{:.2f}')
propagation_times = [[] for i in range(2034)]
for event in events:
event_time = []
for calo_event in event[0]:
event_time.append(calo_event.time)
event_time = np.array(event_time)
if event_time.size == 0:
continue
event_time = np.min(event_time)
tracker_events = event[1]
for tracker_event in tracker_events:
if tracker_event.time_bottom_cathode is None or tracker_event.time_top_cathode is None:
continue
t5 = (tracker_event.time_bottom_cathode - event_time) * 1e6
t6 = (tracker_event.time_top_cathode - event_time) * 1e6
if t5 < 10 and t6 < 10:
continue
if lower < t5 < higher and lower < t6 < higher:
propagation_times[tracker_event.cell_num].append(t5 + t6)
for i_cell in range(2034):
temp_propagation = np.array(propagation_times[i_cell], dtype='float')
if temp_propagation.size == 0:
continue
std = np.std(temp_propagation)
sn_tracker.setcontent(i_cell, std)
sn_tracker.draw()
sn_tracker.save("/Users/williamquinn/Desktop/" + str(run))
def plot_event_map(data: dict, output_path):
sntracker = sn.tracker(new_name='tracker_event_map', with_palette=True)
sntracker.draw_cellid_label()
sntracker.draw_content_label('{}')
for event in data:
cell_info = data[event]["cells"]
for cell in cell_info:
sntracker.fill(cell, 1)
sntracker.draw()
sntracker.save(output_path)
del sntracker
sncalo = sn.calorimeter(new_name='calo_event_map', with_palette=True)
sncalo.draw_content_label('{}')
sncalo.draw_omid_label()
for event in data:
om_info = data[event]["oms"]
for om in om_info:
sncalo.fill(om)
sncalo.draw()
sncalo.save(output_path)