168 lines
5.4 KiB
Python
168 lines
5.4 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 = ['2015eigen8',
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'2015eigen15',
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'2015eigen16',
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'2015eigen17',
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'2015eigen19'
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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('eigen_%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('eigen_%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('eigen_%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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ssample = 100000
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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, 'fish frequency [Hz]', ha='center', va='center', rotation='vertical', color='C0')
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fig.text(0.97, 0.5, 'stimulus amplitude [mV/cm]', ha='center', va='center', rotation='vertical', color='red')
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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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print('absolute frequency shift 0.001Hz:', np.max(jars[0]) - np.min(jars[0]))
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ax0.plot(times[0], jars[0], zorder=20)
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# ax0.set_zorder(1)
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ax0.set_ylim(-12, 12)
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lower0 = 0
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upper0 = 2000
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x0 = np.linspace(lower0, upper0, sample)
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y0 = (sin_response(np.linspace(lower0, upper0, sample), 0.001, np.pi / 2, .35) + 0.5)
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ax0_0 = ax0.twinx()
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ax0_0.set_ylim(-0.2, 1.2)
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ax0_0.plot(x0, y0, color='red', zorder=1, alpha=0.5)
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# ax0_0.set_zorder(2)
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ax1 = fig.add_subplot(612)
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print('absolute frequency shift 0.005 Hz:', np.max(jars[1]) - np.min(jars[1]))
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ax1.plot(times[1], jars[1])
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ax1.set_ylim(-12, 12)
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lower1 = 0
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upper1 = 400
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x1 = np.linspace(lower1, upper1, sample)
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y1 = (sin_response(np.linspace(lower1, upper1, sample), 0.005, np.pi / 2, .35) + 0.5)
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ax1_0 = ax1.twinx()
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ax1_0.set_ylim(-0.2, 1.2)
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ax1_0.plot(x1, y1, color='red', alpha=0.5)
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ax2 = fig.add_subplot(613)
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print('absolute frequency shift 0.01 Hz:', np.max(jars[2]) - np.min(jars[2]))
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ax2.plot(times[2], jars[2])
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ax2.set_ylim(-12, 12)
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lower2 = 0
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upper2 = 400
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x2 = np.linspace(lower2, upper2, sample)
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y2 = (sin_response(np.linspace(lower2, upper2, sample), 0.01, np.pi / 2, 0.35) + 0.5)
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ax2_0 = ax2.twinx()
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ax2_0.set_ylim(-0.2, 1.2)
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ax2_0.plot(x2, y2, color='red', alpha=0.5)
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ax3 = fig.add_subplot(614)
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print('absolute frequency shift 0.02 Hz:', np.max(jars[3]) - np.min(jars[3]))
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ax3.plot(times[3], jars[3])
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ax3.set_ylim(-12, 12)
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lower3 = 0
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upper3 = 200
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x3 = np.linspace(lower3, upper3, sample)
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y3 = (sin_response(np.linspace(lower3, upper3, sample), 0.05, np.pi / 2, 0.35) + 0.5)
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ax3_0 = ax3.twinx()
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ax3_0.set_ylim(-0.2, 1.2)
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ax3_0.plot(x3, y3, color='red', alpha=0.5)
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ax4 = fig.add_subplot(615)
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print('absolute frequency shift 0.5 Hz:', np.max(jars[4]) - np.min(jars[4]))
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ax4.plot(times[4], jars[4])
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ax4.set_ylim(-12, 12)
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lower4 = 0
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upper4 = 200
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x4 = np.linspace(lower4, upper4, sample)
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y4 = (sin_response(np.linspace(lower4, upper4, sample), 0.2, np.pi / 2, 0.35) + 0.5)
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ax4_0 = ax4.twinx()
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ax4_0.set_ylim(-0.2, 1.2)
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ax4_0.plot(x4, y4, color='red', alpha=0.5)
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ax5 = fig.add_subplot(616)
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print('absolute frequency shift 1 Hz:', np.max(jars[5]) - np.min(jars[5]))
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ax5.plot(times[5], jars[5])
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ax5.set_ylim(-12, 12)
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lower5 = 0
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upper5 = 200
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x5 = np.linspace(lower5, upper5, sample)
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y5 = (sin_response(np.linspace(lower5, upper5, sample), 1, np.pi / 2, 0.35) + 0.5)
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ax5_0 = ax5.twinx()
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ax5_0.plot(x5, y5, color='red', lw=0.5, alpha=0.5)
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ax5_0.set_ylim(-0.2, 1.2)
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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=0.1,
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hspace=0.35)
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plt.show() |