freq_chirp

code/eod_freq_chirp.py

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+from read_chirp_data import *
+import os
+from IPython import embed
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+data_dir = "../data"
+dataset = "2018-11-14-ak-invivo-1"
+stim = read_chirp_stimulus(os.path.join(data_dir, dataset))
+
+s = stim[(1, 675.0, 100.0)][0]
+eod = s[1]
+time = s[0]
+
+eod_norm = eod - np.mean(eod)
+# calculate chirp times and indices by zero crossings
+threshold = 0
+shift_eod = np.roll(eod_norm, 1)
+eod_times = time[(eod_norm >= threshold) & (shift_eod < threshold)]
+
+eod_freq_chirp = 1/np.diff(eod_times)
+kernel = np.ones(11)/11
+smooth_eod_freq_chirp = np.convolve(eod_freq_chirp, kernel, mode = 'valid')
+time_axis = np.arange(len(smooth_eod_freq_chirp))
+
+
+fig = plt.plot(time_axis, smooth_eod_freq_chirp)
+plt.xlabel("time [ms]", fontsize = 14)
+plt.xticks(fontsize = 12)
+plt.ylabel("eod frequency [mV]", fontsize = 14)
+plt.yticks(fontsize = 12)
+plt.axis([0, len(time_axis), 0, 2000])
+
+plt.show()
+
+
+
+