smoothing function

code/spikes_analysis.py

@@ -53,11 +53,8 @@ for deltaf in df_map.keys():
 plot_trials = df_phase_time['-50Hz'][0.0]
 plot_trials_binary = np.mean(df_phase_binary['-50Hz'][0.0], axis=0)
 
-mu = 1
-sigma = 100
-time_gauss = np.arange(-4*sigma, 4*sigma, 1)
-gauss = gaussian(time_gauss, mu, sigma)
-smoothed_spikes = np.convolve(plot_trials_binary, gauss, 'same')
+window = 100
+smoothed_spikes = smooth(plot_trials_binary, window)
 time_axis = np.arange(-50, 50, 1/sampling_rate)
 
 fig, ax = plt.subplots()

code/utility.py

@@ -23,6 +23,16 @@ def gaussian(x, mu, sig):
 	y = np.exp(-np.power(x - mu, 2.) / (2 * np.power(sig, 2.)))
 	return y
 
+
+def smooth(data, window):
+	mu = 1
+	sigma = window
+	time_gauss = np.arange(-4 * sigma, 4 * sigma, 1)
+	gauss = gaussian(time_gauss, mu, sigma)
+	smoothed_data = np.convolve(data, gauss, 'same')
+	return smoothed_data
+
+
 def map_keys(input):
 	df_map = {} 
 	for k in input.keys():