diff --git a/code/eod_frequency_normal.py b/code/eod_freq_normal.py
similarity index 100%
rename from code/eod_frequency_normal.py
rename to code/eod_freq_normal.py
diff --git a/code/eod_frequency_chirp.py b/code/eod_frequency_chirp.py
deleted file mode 100644
index a495601..0000000
--- a/code/eod_frequency_chirp.py
+++ /dev/null
@@ -1,39 +0,0 @@
-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()
-
-
-
-