from scipy import signal
import matplotlib.pyplot as plt
import numpy as np
import pylab
from IPython import embed
from scipy.optimize import curve_fit
from jar_functions import gain_curve_fit

identifier = ['2018lepto1',
              '2018lepto4',
              '2018lepto5',
              '2018lepto76',
              '2018lepto98',
              '2019lepto03',
              '2019lepto24',
              '2019lepto27',
              '2019lepto30',
              '2020lepto04',
              '2020lepto06',
              '2020lepto16',
              '2020lepto19',
              '2020lepto20'
              ]

for ID in identifier:
    amf = np.load('amf_%s.npy' %ID)
    gain = np.load('gain_%s.npy' %ID)
    rms = np.load('rms_%s.npy' %ID)
    thresh = np.load('thresh_%s.npy' % ID)

    idx_arr = (rms < thresh) | (rms < np.mean(rms))

    embed()
    sinv, sinc = curve_fit(gain_curve_fit, amf[idx_arr], gain[idx_arr])
    print(sinv[0])
    f_cutoff = 1 / (2*np.pi*sinv[0])
    print(f_cutoff)