#!/usr/bin/env python3
from perseus.client import ModuleClient

import sys, time, numpy, scipy.signal
import os
import sys

#
#   This is the  de-test  version of  waveform-stats.py    23-Dec-2025
#               ------------------
#
# Run in a pylab environment. Does not save plots, but will show them.
# Run e.g. as ipython --pylab -i waveform-stats.py discokraken_XXXXXX.local
#
# Shows a snapshot of the waveforms, power spectra, cross-correlation, and
# noise statistics. The trigger rates shown probe non-Gaussianity beyond
# the quoted noise levels.
# 
# An optional set of channels to plot can follow the hostname, e.g.
# ipython --pylab -i waveform-stats.py discokraken_XXXXXX.local 0 3 6
# will show data for channels 0, 3, and 6 only

m = ModuleClient(sys.argv[1])
m.tuber_resolve()

channels = list(range(16))
if len(sys.argv) > 2:
    channels = [int(i) for i in sys.argv[2:]]

t = m.trigger
print('Running for %.2f seconds' % (t.current_sample()/208.3333333e6))
print('Mean: ', t.channel_means(100))
print('RMS: ', t.channel_rms(100))
print(t.timecode_sync_data())

t.set_thresholds([int(i + 3) for i in t.channel_means()])
t.enable_scalers()
print('Rates at +3 counts trigger (Hz): ', [('%.1f' % i) for i in t.trigger_rates(3)])

t.set_thresholds([int(i + 5) for i in t.channel_means()])
t.enable_scalers()
print('Rates at +5 counts trigger (Hz): ', [('%.1f' % i) for i in t.trigger_rates(3)])

wf = numpy.asarray(m.trigger.get_waveforms(2048))

fig, p = pylab.subplots(1, 1)

for i in channels:
    p.plot(wf[i], label='Channel %d' % i)
p.set_xlabel('Sample Index (4.8 ns)')
p.set_ylabel('ADC Counts')
p.set_title('Sample Waveforms')
p.legend(ncols=4)

fig.show()