def test_calc_pedestals_from_traces():
""" test calc_pedestals_from_traces """
from ctapipe.calib.camera.pedestals import calc_pedestals_from_traces
# create some test data (all ones, but with a 2 stuck in for good measure):
npix = 1000
nsamp = 32
traces = np.ones(shape=(npix, nsamp), dtype=np.int32)
traces[:, 2] = 2
# calculate pedestals over samples 0-10
peds, pedvars = calc_pedestals_from_traces(traces, 0, 10)
# check the results. All pedestals should be 1.1 and vars 0.09:
assert np.all(peds == 1.1)
assert np.all(pedvars == 0.09)
assert peds.shape[0] == npix
assert pedvars.shape[0] == npix
# try another sample range, where there should be no variances and
# all 1.0 peds:
peds, pedvars = calc_pedestals_from_traces(traces, 12, 32)
assert np.all(peds == 1.0)
assert np.all(pedvars == 0)
# loop over all events, all telescopes and all channels and call
# the calc_peds function defined above to do some work:
for event in EventSource(filename):
for telid in event.r0.tel.keys():
for chan in range(event.r0.tel[telid].waveform.shape[0]):
print(f"CT{telid} chan {chan}:")
traces = event.r0.tel[telid].waveform[chan, ...]
# skip telescopes without timeseries data
if traces.shape[1] == 1:
continue
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()
# note with the sample data you'll get a warning about "Wrong