end_time + bin_width,
bin_width)
# compare len(time_window_positron) with len(number_pe_per_bin_positron):
missing_zeros = len(time_window_positron) - len(
number_pe_per_bin_positron)
# append the missing_zeros to number_pe_per_bin_positron:
number_pe_per_bin_positron = np.pad(number_pe_per_bin_positron,
(0, missing_zeros),
'constant',
constant_values=(0.0, 0.0))
# analyze the hittime distribution of these event:
tot_ratio_positron, npe_norm_positron = pulse_shape(
time_window_positron, number_pe_per_bin_positron,
start_tail[index], stop_tail[index1])
# append tail-to-total ratio to array:
array_tot_ratio_positron.append(tot_ratio_positron)
# append zeros to npe_norm_positron to get a average length of the hittimes:
npe_norm_positron = np.pad(
npe_norm_positron,
(0, length_average_hittime - len(npe_norm_positron)),
'constant',
constant_values=(0.0, 0.0))
# add the normalized hittime distribution (npe_norm_positron) to the average hittime distribution
# (hittime_average_positron):
hittime_average_positron = hittime_average_positron + npe_norm_positron
time_window_neutron = np.arange(min_time_neutron,
end_time + bin_width, bin_width)
# compare len(time_window_neutron) with len(number_pe_per_bin_neutron):
missing_zeros = len(time_window_neutron) - len(
number_pe_per_bin_neutron)
# append the missing_zeros to number_pe_per_bin_neutron:
number_pe_per_bin_neutron = np.pad(number_pe_per_bin_neutron,
(0, missing_zeros),
'constant',
constant_values=(0.0, 0.0))
# analyze the hittime distribution of these event:
tot_ratio_neutron, npe_norm_neutron = pulse_shape(
time_window_neutron, number_pe_per_bin_neutron,
start_tail[index], stop_tail[index])
# check if tot-value is not 0:
if tot_ratio_neutron == 0:
continue
# increment number of analyzed events:
num_events_analyzed_neutron += 1
# append tail-to-total ratio to array:
array_tot_ratio_neutron.append(tot_ratio_neutron)
# append zeros to npe_norm_neutron to get a average length of the hittimes:
npe_norm_neutron = np.pad(
npe_norm_neutron,
"ERROR: set binwidth ({0:.1f} ns) != binwidth from pulse shape file ({1:.1f} ns)"
.format(binwidth, bin_width_IBD))
# the rest of pulse_shape_data_IBD is the hittime distribution histogram in nPE per bin. Take only the
# prompt signal defined by start_time and end_time:
nPE_per_bin_IBD = pulse_shape_data_IBD[6:(int(
(end_time + binwidth + np.abs(min_time_IBD)) / binwidth) +
3)]
# set the time window corresponding to nPE_per_bin_IBD:
time_window_IBD = np.arange(min_time_IBD, end_time + binwidth,
binwidth)
# analyze pulse shape of this event:
ttr_IBD, npe_norm_IBD = pulse_shape(time_window_IBD,
nPE_per_bin_IBD,
start_tail[index],
stop_tail[index1])
# append tail-to-total ratio to array:
array_TTR_IBD.append(ttr_IBD)
# append filenumber and eventID to arrays:
filenumber_IBD.append(filenumber)
evtID_IBD.append(event)
# append zeros to npe_norm_IBD to get a average length of the hittimes:
npe_norm_IBD = np.pad(
npe_norm_IBD,
(0, length_average_hittime - len(npe_norm_IBD)),
'constant',
constant_values=(0.0, 0.0))