diff --git a/code/plot_eodform_spikehist.py b/code/plot_eodform_spikehist.py
index 7c6be52..1983d46 100644
--- a/code/plot_eodform_spikehist.py
+++ b/code/plot_eodform_spikehist.py
@@ -14,21 +14,19 @@ dataset = '2018-11-14-al-invivo-1'
 # read eod and time of baseline
 time, eod = read_baseline_eod(os.path.join(data_dir, dataset))
 
-<<<<<<< HEAD
+
 eod_norm = eod - np.mean(eod)
 
 # calculate eod 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_times = time[(eod_norm >= threshold) & (shift_eod < threshold)]*40000
 
 
 
 eod_duration = eod_times[2]- eod_times[1]
 
 
-=======
->>>>>>> 5cd62554fa5af12a6a50661f0a60cd2b0457e702
 # read spikes during baseline activity
 spikes = read_baseline_spikes(os.path.join(data_dir, dataset))
 # calculate interpike intervals and plot them
diff --git a/code/stimulus_chirp.py b/code/stimulus_chirp.py
index f45827c..ad9336b 100644
--- a/code/stimulus_chirp.py
+++ b/code/stimulus_chirp.py
@@ -40,8 +40,8 @@ ax1 = fig.add_subplot(211)
 plt.yticks(fontsize=18)
 ax2 = fig.add_subplot(212, sharex=ax1)
 plt.setp(ax1.get_xticklabels(), visible=False)
-ax1.plot(time*1000, signal, color = 'midnightblue', lw = 1)
-ax2.plot(time*1000, freq, color = 'midnightblue', lw = 3)
+ax1.plot(time*1000, signal, color = 'royalblue', lw = 1)
+ax2.plot(time*1000, freq, color = 'royalblue', lw = 3)
 
 ax1.set_ylabel("field [mV]", fontsize = 22)