44 lines
1.1 KiB
Python
44 lines
1.1 KiB
Python
from scipy import signal
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import matplotlib.pyplot as plt
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import numpy as np
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import pylab
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from IPython import embed
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from scipy.optimize import curve_fit
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from jar_functions import gain_curve_fit
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identifier = ['2018lepto1',
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'2018lepto4',
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'2018lepto5',
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'2018lepto76',
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'2018lepto98',
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'2019lepto03',
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'2019lepto24',
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'2019lepto27',
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'2019lepto30',
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'2020lepto04',
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'2020lepto06',
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'2020lepto16',
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'2020lepto19',
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'2020lepto20'
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]
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tau = []
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f_c = []
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for ID in identifier:
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print(ID)
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amf = np.load('amf_%s.npy' %ID)
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gain = np.load('gain_%s.npy' %ID)
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'''fig = plt.figure()
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ax = fig.add_subplot(111)
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ax.plot(amf, gain, 'o')
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ax.set_yscale('log')
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ax.set_xscale('log')
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plt.show()
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'''
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sinv, sinc = curve_fit(gain_curve_fit, amf, gain)
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print('tau:', sinv[0])
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tau.append(sinv[0])
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f_cutoff = 1 / (2*np.pi*sinv[0])
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print('f_cutoff:', f_cutoff)
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f_c.append(f_cutoff)
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#welche zeitkonstante ist das? was ist mit der zweiten? |