73 lines
1.6 KiB
Python
Executable File
73 lines
1.6 KiB
Python
Executable File
#!/usr/bin/env python
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from time import sleep
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from collections import deque
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import numpy as np
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import scipy.signal
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from zoetrope import aniplot as plt
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from scipy.stats.stats import pearsonr
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from bstrd import BS, bsstream
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plt.blit = False
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plt.style.use('ggplot')
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def pumpedshots(events, *arrays):
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laser = events[:, 18]
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darkShot = events[:, 21]
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pumped_shots = np.logical_and.reduce((laser, np.logical_not(darkShot)))
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return [a[pumped_shots] for a in arrays]
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chname_tt1 = "SARES11-SPEC125-M1.edge_amplitude"
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chname_tt2 = "SARES11-SPEC125-M1.edge_amplitude2"
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chname_i0 = "SAROP11-PBPS110:INTENSITY"
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chname_events = "SAR-CVME-TIFALL4:EvtSet"
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length = 500
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# create channel
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ch_tt1 = BS(chname_tt1)
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ch_tt2 = BS(chname_tt2)
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ch_i0 = BS(chname_i0)
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ch_events = BS(chname_events)
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n = 200
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tt1 = np.empty(n)
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tt2 = np.empty(n)
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i0s = np.empty(n)
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evts = np.empty((n, 256))
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# create a buffer for the plotting
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pp_sigs = deque(maxlen=length)
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# create the empty plot
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pd = plt.plot([0])
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# some plot settings
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plt.suptitle("{}, {}".format(chname_tt1, chname_tt2))
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plt.fig.set_figheight(5)
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plt.fig.set_figwidth(5)
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plt.tight_layout()
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for counter, data in zip(plt.show(), bsstream):
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print(counter)
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for i in range(n):
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tt1[i] = ch_tt1.get()
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tt2[i] = ch_tt2.get()
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i0s[i] = ch_i0.get()
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evts[i] = ch_events.get()
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next(bsstream) # this gets the next set of data
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pumptt1, pumptt2 = pumpedshots(evts, tt1, tt2)
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pearscoeff1, _ = pearsonr(pumptt1, pumptt2)
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#xs = np.arange(len(pp_sigs))
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plt.clf()
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plt.scatter(pumptt1, pumptt2)
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plt.title("{}".format(round(pearscoeff1, 4)))
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plt.show()
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bsstream.close()
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