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ALF/dioderata/spectrum_ta.py
2023-10-23 19:03:37 +02:00

71 lines
1.8 KiB
Python
Executable File

#!/usr/bin/env python
from time import sleep
from collections import deque
import numpy as np
from zoetrope import aniplot as plt
from scipy.stats.stats import pearsonr
from bstrd import BS, bsstream
plt.blit = False
plt.style.use('ggplot')
wav = np.linspace(409.914, 672.792, num=2048)
def unpumpedshots(pulseids, *arrays):
unpumped_shots = (pulseids%2 == 0)
return [a[unpumped_shots] for a in arrays]
def pumpedshots(pulseids, *arrays):
pumped_shots = (pulseids%2 == 1)
return [a[pumped_shots] for a in arrays]
chname_specsig = "SARES11-SPEC125-M2.projection_signal"
chname_specback = "SARES11-SPEC125-M2.projection_background"
chname_i0 = "SLAAR11-LSCP1-FNS:CH5:VAL_GET"
#chname_events = "SAR-CVME-TIFALL4:EvtSet"
chname_pids = "SATCB01-RLLE-STA:MASTER-EVRPULSEID"
# create channel
ch_spec1 = BS(chname_specsig)
ch_back1 = BS(chname_specback)
ch_i0 = BS(chname_i0)
ch_pids = BS(chname_pids)
n = 200
sigs1 = np.empty((n, 2048))
backs1 = np.empty((n, 2048))
i0s = np.empty(n)
pids = np.empty(n)
# create the empty plot
pd = plt.plot([0])
# some plot settings
plt.fig.set_figheight(6)
plt.fig.set_figwidth(7)
for counter, data in zip(plt.show(), bsstream):
print(counter)
for i in range(n):
sigs1[i] = ch_spec1.get()
backs1[i] = ch_back1.get()
i0s[i] = ch_i0.get()
pids[i] = int(ch_pids.get())
next(bsstream) # this gets the next set of data
pumpi0s, pumpsigs, pumpbacks = pumpedshots(pids, i0s, sigs1, backs1)
unpumpi0s, unpumpsigs, unpumpbacks = unpumpedshots(pids, i0s, sigs1, backs1)
diffa = np.mean((pumpsigs - pumpbacks), axis=0) / np.mean((unpumpsigs - unpumpbacks), axis=0)
plt.tight_layout()
plt.clf()
plt.xlim(450, 650)
plt.ylim(-0.05, 0.05)
plt.plot(wav, -np.log10(diffa))
plt.show()
bsstream.close()