diff --git a/code/spikes_analysis.py b/code/spikes_analysis.py
index ea11eb8..7284cff 100644
--- a/code/spikes_analysis.py
+++ b/code/spikes_analysis.py
@@ -62,14 +62,22 @@ for deltaf in df_map.keys():
                         df_phase_binary[deltaf][idx] = binary_spikes
 
 
+# make dictionaries for csi
+csi_trains = {}
+csi_rates = {}
 # for plotting and calculating iterate over delta f and phases
 for df in df_phase_time.keys():
+    csi_trains[df] = []
+    csi_rates[df] = []
     beat_duration = int(abs(1/df*1000)) #ms
     beat_window = 0
     while beat_window+beat_duration <= cut_window:
         beat_window = beat_window+beat_duration
     for phase in df_phase_time[df].keys():
 
+        # csi calculation
+        # trains for synchronity and rate
+
         trials_binary = df_phase_binary[df][phase]
 
         train_chirp = []
@@ -99,18 +107,23 @@ for df in df_phase_time.keys():
         r_train_beat = np.mean(rbs)
 
         csi_train = (r_train_chirp - r_train_beat) / (r_train_chirp + r_train_beat)
-        print(csi_train)
         csi_rate = (np.std(spikerate_chirp) - np.std(spikerate_beat)) / (np.std(spikerate_chirp) + np.std(spikerate_beat))
-        print(csi_rate)
 
+        # add the csi to the dictionaries with the correct df and phase
+        #csi_trains[df][phase] = csi_train
+        #csi_rates[df][phase] = csi_rate
+
+        csi_trains[df].append(csi_train)
+        csi_rates[df].append(csi_rate)
+
+        '''
         # plot
-        #plot_trials = df_phase_time[df][phase]
-        #plot_trials_binary = np.mean(df_phase_binary[df][phase], axis=0)
+        plot_trials = df_phase_time[df][phase]
+        plot_trials_binary = np.mean(df_phase_binary[df][phase], axis=0)
 
         # calculation
         #overall_spikerate = (np.sum(plot_trials_binary)/len(plot_trials_binary))*sampling_rate*1000
 
-        '''
         smoothed_spikes = smooth(plot_trials_binary, window, 1./sampling_rate)
 
         fig, ax = plt.subplots(2, 1, sharex=True)
@@ -125,15 +138,9 @@ for df in df_phase_time.keys():
         ax[1].set_ylabel('firing rate [Hz]', fontsize=12)
         plt.show()
         '''
-
-
-'''
-for trial in range(len(trials_binary)):
-spike_rate = np.zeros(len(spike_bins)-1)
-for idx in range(len(spike_bins)-1):
-bin_start = spike_bins[idx]*sampling_rate
-bin_end = spike_bins[idx+1]*sampling_rate
-spike_rate[idx] = np.sum(trials_binary[trial][bin_start:bin_end])
 embed()
 exit()
-'''
\ No newline at end of file
+for i, k in enumerate(sorted(csi_rates.keys())):
+    print(csi_rates[k])
+
+