131 lines
4.0 KiB
Python
131 lines
4.0 KiB
Python
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 scipy.optimize import curve_fit
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from matplotlib.mlab import specgram
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import os
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from jar_functions import import_data
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from jar_functions import import_amfreq
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from jar_functions import sin_response
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from jar_functions import mean_noise_cut
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from jar_functions import gain_curve_fit
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plt.rcParams.update({'font.size': 10})
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def take_second(elem): # function for taking the names out of files
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return elem[1]
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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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for ident in identifier:
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times = []
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jars = []
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jms = []
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amfreq = []
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times1 = []
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jars1 = []
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jms1 = []
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amfreq1 = []
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amf = [0.001, 0.002, 0.005, 0.01, 0.02, 0.05, 0.1, 0.2, 0.5, 1]
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data = sorted(np.load('%s files.npy' %ident), key = take_second) # list with filenames in it
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for i, d in enumerate(data):
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dd = list(d)
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if dd[1] == '1' or dd[1] == '0.2' or dd[1] == '0.05' or dd[1] == '0.01' or dd[1] == '0.005' or dd[1] == '0.001':
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jar = np.load('%s.npy' %dd) # load data for every file name
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jm = jar - np.mean(jar) # low-pass filtering by subtracting mean
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time = np.load('%s time.npy' %dd) # time file
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dt = time[1] - time[0]
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n = int(1/float(d[1])/dt)
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cutf = mean_noise_cut(jm, n = n)
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cutt = time
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if dd[1] == '0.001':
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amfreq1.append(dd[1])
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jars1.append(jm - cutf)
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jms1.append(jm)
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times1.append(time)
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if dd[1] not in amfreq:
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print(dd)
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amfreq.append(dd[1])
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jars.append(jm - cutf)
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jms.append(jm)
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times.append(time)
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else:
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print('1:', dd)
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amfreq1.append(dd[1])
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jars1.append(jm - cutf)
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jms1.append(jm)
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times1.append(time)
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if len(jars) != 6:
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continue
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fig = plt.figure(figsize=(8.27,11.69))
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fig.suptitle('%s' %ident)
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fig.text(0.06, 0.5, 'frequency [Hz]', ha='center', va='center', rotation='vertical')
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fig.text(0.5, 0.04, 'time [s]', ha='center', va='center')
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ax0 = fig.add_subplot(611)
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ax0.plot(times[0], jms[0])
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#ax0.plot(times[0], jars[0])
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ax0.set_ylim(-12, 12)
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#plt.text(-0.1, 1.05, "A)", fontweight=550, transform=ax0.transAxes)
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ax1 = fig.add_subplot(612)
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ax1.plot(times[1], jms[1])
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#ax1.plot(times[1], jars[1])
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ax1.set_ylim(-12, 12)
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#plt.text(-0.1, 1.05, "B)", fontweight=550, transform=ax1.transAxes)
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ax2 = fig.add_subplot(613)
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ax2.plot(times[2], jms[2])
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#ax2.plot(times[2], jars[2])
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ax2.set_ylim(-12, 12)
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#plt.text(-0.1, 1.05, "C)", fontweight=550, transform=ax2.transAxes)
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ax3 = fig.add_subplot(614)
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ax3.plot(times[3], jms[3])
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#ax3.plot(times[3], jars[3])
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ax3.set_ylim(-12, 12)
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#plt.text(-0.1, 1.05, "D)", fontweight=550, transform=ax3.transAxes)
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ax4 = fig.add_subplot(615)
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ax4.plot(times[4], jms[4])
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#ax4.plot(times[4], jars[4])
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ax4.set_ylim(-12, 12)
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# plt.text(-0.1, 1.05, "E)", fontweight=550, transform=ax4.transAxes)
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ax5 = fig.add_subplot(616)
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ax5.plot(times[5], jms[5])
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#ax5.plot(times[5], jars[5])
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ax5.set_ylim(-12, 12)
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#plt.text(-0.1, 1.05, "F)", fontweight=550, transform=ax5.transAxes)
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plt.subplots_adjust(left=0.125,
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bottom=0.1,
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right=0.9,
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top=0.9,
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wspace=0.2,
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hspace=0.35)
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plt.show() |