50 lines
1.2 KiB
Python
50 lines
1.2 KiB
Python
import matplotlib.pyplot as plt
|
|
import numpy as np
|
|
import pylab
|
|
from IPython import embed
|
|
from scipy.optimize import curve_fit
|
|
from matplotlib.mlab import specgram
|
|
import os
|
|
from jar_functions import gain_curve_fit
|
|
|
|
identifier = ['2020lepto06']
|
|
|
|
tau = []
|
|
f_c = []
|
|
for ID in identifier:
|
|
predict = []
|
|
|
|
print(ID)
|
|
amf = np.load('amf_%s.npy' %ID)
|
|
gain = np.load('gain_%s.npy' %ID)
|
|
print(gain)
|
|
|
|
sinv, sinc = curve_fit(gain_curve_fit, amf, gain)
|
|
print('tau:', sinv[0])
|
|
tau.append(sinv[0])
|
|
f_cutoff = abs(1 / (2*np.pi*sinv[0]))
|
|
print('f_cutoff:', f_cutoff)
|
|
f_c.append(f_cutoff)
|
|
|
|
# predict of gain
|
|
for f in amf:
|
|
G = np.max(gain) / np.sqrt(1 + (2 * ((np.pi * f * sinv[0]) ** 2)))
|
|
predict.append(G)
|
|
print(np.max(gain))
|
|
|
|
fig = plt.figure()
|
|
ax = fig.add_subplot()
|
|
ax.plot(amf, gain,'o' , label = 'gain')
|
|
ax.plot(amf, predict, label = 'fit')
|
|
ax.axvline(x=f_cutoff, ymin=0, ymax=5, ls='-', alpha=0.5, label = 'cutoff frequency')
|
|
ax.set_xscale('log')
|
|
ax.set_yscale('log')
|
|
ax.set_ylabel('gain [Hz/(mV/cm)]')
|
|
ax.set_xlabel('envelope_frequency [Hz]')
|
|
ax.set_title('gaincurve %s' %ID)
|
|
plt.legend(loc = 'lower left')
|
|
plt.show()
|
|
|
|
|
|
#np.save('f_c', f_c)
|
|
#np.save('tau', tau) |