89 lines
2.3 KiB
Python
Executable File
89 lines
2.3 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 scipy.special import erf
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from scipy.optimize import curve_fit
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from zoetrope import aniplot as plt
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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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# config
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#chname_diode = "SLAAR11-LSCP1-FNS:CH0:VAL_GET"
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chname_diode = "SARES11-GES1:CH1_VAL_GET"
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chname_i0 = "SAROP11-PBPS110:INTENSITY"
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chname_xhuber = "SARES11-XSAM125:ENC_X1_BS"
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chname_yhuber = "SARES11-XSAM125:ENC_Y1_BS"
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chname_events = "SAR-CVME-TIFALL4:EvtSet"
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length = 5000
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# create channel
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ch_diode = BS(chname_diode)
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ch_i0 = BS(chname_i0)
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ch_xhuber = BS(chname_xhuber)
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ch_yhuber = BS(chname_yhuber)
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ch_evts = BS(chname_events)
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n = 100
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sigs = np.empty(n)
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i0s = np.empty(n)
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x_pos = np.empty(n)
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y_pos = 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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#ke_sigs = deque(maxlen=length)
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#x_poses = deque(maxlen=length)
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#y_poses = deque(maxlen=length)
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ke_sigs = []
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x_poses = []
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y_poses = []
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i_zeroes = []
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# fit stuff for knife edge scans
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def errfunc_fwhm(x, x0, amplitude, width, offset):
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return offset + amplitude*erf((x0-x)*2*np.sqrt(np.log(2))/(np.abs(width))) #d is fwhm
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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(chname_diode)
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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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# sigs[i] = ch_diode.get()
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# i0s[i] = ch_i0.get()
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# x_pos[i] = ch_xhuber.get()
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# y_pos[i] = ch_yhuber.get()
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ke_sigs.append(ch_diode.get())
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x_poses.append(ch_xhuber.get())
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y_poses.append(ch_yhuber.get())
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i_zeroes.append(ch_i0.get())
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next(bsstream) # this gets the next set of data
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# sig_norm = sigs#/np.asarray(i0s)
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# ke_sigs.append(sig_norm)
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pd.set(x_poses, np.asarray(ke_sigs)/(i_zeroes))
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# popt, pcov = curve_fit(errfunc_fwhm, np.asarray(x_poses), np.asarray(ke_sigs)/(i_zeroes), p0=[np.mean(x_poses), (np.max(ke_sigs)-np.min(ke_sigs)), 10, 0])
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# pd.set(x_poses, errfunc_fwhm(x_poses, *popt))
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print(np.shape(x_poses))
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# this, I need to move into the library
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pd.ax.relim()
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pd.ax.autoscale_view()
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# pd.ax.suptitle("{}, {}".format(popt[0], popt[2]))
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bsstream.close()
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