65 lines
1.6 KiB
Python
Executable File
65 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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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_diode = "SLAAR11-LSCP1-FNS:CH0:VAL_GET"
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#chname_diode1 = "SARES11-GES1:CH1_VAL_GET"
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chname_diode1 = "SARES12-GES1:PR1_CH2_VAL_GET"
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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_diode1 = BS(chname_diode1)
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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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sigs1 = 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 the empty plot
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pd = plt.plot([0])
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# some plot settings
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plt.fig.set_figheight(6)
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plt.fig.set_figwidth(7)
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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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sigs1[i] = ch_diode1.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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pearscoeff1, _ = pearsonr(i0s, sigs1)
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pumpi0s, pumpsigs = pumpedshots(evts, i0s, sigs1)
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#xs = np.arange(len(pp_sigs))
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plt.tight_layout()
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plt.clf()
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plt.scatter(i0s, sigs1)
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plt.scatter(pumpi0s, pumpsigs)
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plt.title("{}".format(round(pearscoeff1, 4)))
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plt.xlabel('sarop11-pbps110:intensity')
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plt.ylabel('tfy, sares11-ges1:ch1_val_get')
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plt.show()
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bsstream.close()
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