diff --git a/EStiMo_GUI_0123.py b/EStiMo_GUI_0123_alt.py
similarity index 98%
rename from EStiMo_GUI_0123.py
rename to EStiMo_GUI_0123_alt.py
index 43b493b..0fca16e 100644
--- a/EStiMo_GUI_0123.py
+++ b/EStiMo_GUI_0123_alt.py
@@ -394,7 +394,8 @@ class AppForm(QMainWindow):
         self.log_file.flush() #flushing is applying changes we made to the file
         self.Fs = 1000 #5000 
         self.size_of_up = 2*self.Fs #5000 how much data we get from NeurOne function
-        
+        self.plot_par = 0
+        self.baseline_reg = 0
         #file with settings and assigning variables to them
         settings_file = pd.read_csv('TMS_protocol.txt',sep=':', header=None)
         
@@ -786,16 +787,16 @@ class AppForm(QMainWindow):
         self.loaded_full = self.loaded.copy() #keeps it for the next second
         step2 = time.time()-time_start
         # ZeroDivisionError means that data is not yet loaded
-        try:
-            # [A,B] = ss.butter(2, 0.1/(self.Fs/2), 'highpass')
-            # self.loaded[:self.num_of_ch,-4*self.Fs:] = ss.filtfilt(A, B, self.loaded[:self.num_of_ch, -4*self.Fs:])
-            # self.loaded[:self.num_of_ch,-4*self.Fs:] = self.loaded[:self.num_of_ch,-4*self.Fs:] - np.mean(self.loaded[:self.num_of_ch,-4*self.Fs:],1, keepdims=True)
-            self.loaded[:self.num_of_ch,-4*self.Fs:] = ss.detrend(self.loaded[:self.num_of_ch,-4*self.Fs:])
-        except ZeroDivisionError: # This error means that buffer is still not full
-            if self.qmbx == None:
-                self.qmbx = Waiting_window() # Small window with a message to wait
-            print('Waiting for data (should take up to few seconds)')
-            return(0) # Stop function here, because in this case rest of update is not needed
+        # try:
+        #     # [A,B] = ss.butter(2, 0.1/(self.Fs/2), 'highpass')
+        #     # self.loaded[:self.num_of_ch,-4*self.Fs:] = ss.filtfilt(A, B, self.loaded[:self.num_of_ch, -4*self.Fs:])
+        #     # self.loaded[:self.num_of_ch,-4*self.Fs:] = self.loaded[:self.num_of_ch,-4*self.Fs:] - np.mean(self.loaded[:self.num_of_ch,-4*self.Fs:],1, keepdims=True)
+        #     self.loaded[:self.num_of_ch,-4*self.Fs:] = ss.detrend(self.loaded[:self.num_of_ch,-4*self.Fs:])
+        # except ZeroDivisionError: # This error means that buffer is still not full
+        #     if self.qmbx == None:
+        #         self.qmbx = Waiting_window() # Small window with a message to wait
+        #     print('Waiting for data (should take up to few seconds)')
+        #     return(0) # Stop function here, because in this case rest of update is not needed
         
         # Getting to this point of the code means there were no exception before
         # So the waiting window can be destroyed
@@ -837,7 +838,9 @@ class AppForm(QMainWindow):
                 #         self.loaded[i,min(od+ind-int(int_from*self.Fs),30000-1)], 
                 #         self.loaded[i,max(od+ind+int(int_to*self.Fs),30000-1)], 
                 #         od+ind+int(int_to*self.Fs)-(od+ind-int(int_from*self.Fs)))
-                
+        if self.plot_par%4==0:
+            self.baseline_reg = np.mean(self.loaded[:self.num_of_ch,-5*self.Fs:-4*self.Fs], 1)
+        self.loaded[:self.num_of_ch,-4*self.Fs:] = (self.loaded[:self.num_of_ch,-4*self.Fs:].T - self.baseline_reg).T
         step6 = time.time()-time_start
         # Eye regression for visualisation
         #plt.figure()
@@ -947,8 +950,13 @@ class AppForm(QMainWindow):
             
             else:
                 plot_data = plot_data/self.plot_dividing_factor + self.num_of_ch - i
+            if self.plot_par%4!=0:
+                plot_data_c = plot_data.copy()
+                plot_data[:self.Fs*(self.plot_par%4)], plot_data[self.Fs*(self.plot_par%4):] = plot_data_c[4000-self.Fs*(self.plot_par%4):], plot_data_c[:4000-self.Fs*(self.plot_par%4)]
+                plot_data[self.Fs*(self.plot_par%4)-100:self.Fs*(self.plot_par%4)+100] = np.nan
             # plot_data = plot_data/(3.5*np.max(np.abs(plot_data))) + self.num_of_ch - i
             self.line[i].set_data(np.arange(0,self.plot_len*self.Fs), plot_data)
+        self.plot_par+=1
         self.axes.set_ylim(0, self.num_of_ch+1)
         #self.axes.set_ylim(0,np.max(self.data[:,-self.plot_len*self.Fs:])+dif) #set ylim to fit everything on the plot
         if len(stim)>0: