def calc_pedestals(self):
start = 15
end = None
for event in hessio_event_source(self.filename):
for telid in event.r0.tels_with_data:
for chan in range(event.r0.tel[telid].adc_samples.shape[0]):
traces = event.r0.tel[telid].adc_samples[chan, ...]
peds, pedvars = pedestals.calc_pedestals_from_traces(
traces, start, end)
print("Number of samples: {}".format(traces.shape[1]))
print("Calculate over window:({},{})".format(start, end))
print("PEDS:", peds)
print("VARS:", pedvars)
print("-----")
self.plot_peds(event, peds, pedvars)
plt.show()
start = 15
end = None # None means through sample
# loop over all events, all telescopes and all channels and call
# the calc_peds function defined above to do some work:
for event in event_source(filename):
for telid in event.r0.tels_with_data:
for chan in range(event.r0.tel[telid].waveform.shape[0]):
print(f"CT{telid} chan {chan}:")
traces = event.r0.tel[telid].waveform[chan, ...]
peds, pedvars = pedestals.calc_pedestals_from_traces(
traces, start, end
)
print("Number of samples: {}".format(traces.shape[1]))
print(f"Calculate over window:({start},{end})")
print("PEDS:", peds)
print("VARS:", pedvars)
print("-----")
# as an example, for the final event, let's plot the pedestals and
# variances: (you could also move this into the for-loop, but
# would then have tons of plots)
plot_peds(peds, pedvars)
plt.show()
# sample windows:
start = 15
end = None # None means through sample
# loop over all events, all telescopes and all channels and call
# the calc_peds function defined above to do some work:
for event in hessio_event_source(filename):
for telid in event.dl0.tels_with_data:
for chan in event.dl0.tel[telid].adc_samples.keys():
print("CT{} chan {}:".format(telid, chan))
traces = event.dl0.tel[telid].adc_samples[chan]
peds, pedvars = pedestals.calc_pedestals_from_traces(traces,
start,
end)
print("Number of samples: {}".format(traces.shape[1]))
print("Calculate over window:({},{})".format(start, end))
print("PEDS:", peds)
print("VARS:", pedvars)
print("-----")
# as an example, for the final event, let's plot the pedestals and
# variances: (you could also move this into the for-loop, but
# would then have tons of plots)
plot_peds(peds, pedvars)
plt.show()
neigh_mask = generate_neighbourg_masks()
hollow_neigh_mask = generate_hollow_neighbourg_masks()
min_evtcounter = 3383 - 3018
best_pix = -1
h, h1 = [], []
evt_counter = 0
cnt = 0
for event in inputfile_reader:
evt_counter += 1
if evt_counter < min_evtcounter: continue
for telid in event.r1.tels_with_data:
data = np.array(list(event.r1.tel[telid].adc_samples.values()))
# pedestal subtraction
peds, pedvars = pedestals.calc_pedestals_from_traces(data, 0, 50)
nsamples = event.r1.tel[telid].num_samples
# data_ped = np.array([data_ped[0], data_ped[0]]) # Test LG functionality
params = {
"integrator": "nb_peak_integration",
"integration_window": [50, 0],
"integration_sigamp": [2, 4],
"integration_lwt": 0
}
data = np.array([data])
integration, window, peakpos = integrators.simple_integration(
data, params)
integration[0] = integration[0] / 50.
integration_sub = integration[0] - np.ones(1296) * np.median(
np.extract(good_pixels, integration[0]))