diff --git a/read_arduino.py b/read_arduino.py
index 2b66669..1da243b 100644
--- a/read_arduino.py
+++ b/read_arduino.py
@@ -44,19 +44,9 @@ def read():
         writer.writerow(header)
         f.close()
         while True:
-            #dat_list = np.random.randint(0, v_in * 1000, SENSORS_MAX)  # create a randomized voltage data
+            dat_list = np.random.randint(0, v_in * 1000, SENSORS_MAX)  # create a randomized voltage data
             # take only the nonzero indices, and truncated to two decimal places to "filter" out some hardware errors
-            #dat_sel = np.trunc((np.take(dat_list, sensor_ports) / 1000) * 10**2) / 10**2
-            '''ser = serial.Serial(port)
-            ser.flushInput()
-            while True:
-                try:
-                    ser_bytes = ser.readline()
-                    decoded_bytes = float(ser_bytes[0:len(ser_bytes)-2].decode("utf-8"))
-                except:
-                    print("Keyboard Interrupt")
-                    break'''
-            #dat_sel = np.trunc((np.take(decoded_bytes, sensor_ports) / 1000) * 10**2) / 10**2
+            dat_sel = np.trunc((np.take(dat_list, sensor_ports) / 1000) * 10**2) / 10**2
             r_arr = np.take(refRes, sensor_ports) * (v_in / dat_sel - 1) # *2 <-- change with actual formula for ammonia concentration
             # created a new array to convert resistance values to sci notation
             r_arr2 = np.empty(len(r_arr), dtype=object)
@@ -91,17 +81,12 @@ def read():
     f.close()
     while controller.isOpen():
         try:
-            #controller.flushInput()
             read_data = controller.readline().decode("utf-8")
             # use numpy so it can make list calculations easier (and possibly faster)
             dat_list = np.asarray(json.loads(read_data), dtype=np.float32)[:SENSORS_MAX]
-            #ser_bytes = controller.readline()
-            #decoded_bytes = float(ser_bytes[0:len(ser_bytes)-2].decode("utf-8"))
-            #dat_sel = np.trunc((np.take(dat_list, sensor_ports) / 1000) * 10**2) / 10**2
             dat_sel = np.take(dat_list, sensor_ports)
             # if we decided to switch back to analogRead(), replace this line of comment to the algorithm to something like the commented line below
             # dat_sel = np.take(dat_list, sensor_ports) * v_in / resolution
-
             # take only the nonzero indices, and truncated to two decimal places to "filter" out some hardware errors
             #dat_sel = np.trunc((np.take(dat_list, sensor_ports) / 1000) * 10**2) / 10**2
             r_arr = np.take(refRes, sensor_ports) * (v_in / dat_sel - 1) # *2 <-- change with actual formula for ammonia concentration
diff --git a/serial_plotter.py b/serial_plotter.py
index d6be973..7705388 100644
--- a/serial_plotter.py
+++ b/serial_plotter.py
@@ -76,18 +76,23 @@ class SerialPlotter:
                     self.sensorsData[i].append(row[i])
                     # plot a line
                     # round the number to scientific notation
-                    self.axs.plot(self.timeStamps[i],self.sensorsData[i], color=self.colors[i],
+                    self.axs.plot(self.timeStamps[i], self.sensorsData[i], color=self.colors[i], 
                                   label=f'sensor {i + 1}, latest: {np.format_float_scientific(self.sensorsData[i][-1], precision = 2)} $\Omega$')
                     
-                    self.axs.set_xlabel('Time (seconds)')
-                    self.axs.set_ylabel(u'Resistance ($\Omega$)')
+                    # Make the font size of values placed on x-axis and y-aixs equal to 16 (large enough)
+                    plt.xticks(fontsize = 16)
+                    plt.yticks(fontsize = 16)
+                    
+                    # make the label of two axes large enough
+                    self.axs.set_xlabel('Time (seconds)', fontsize = 15)
+                    self.axs.set_ylabel(u'Resistance ($\Omega$)', fontsize = 15)
                     i += 1
             self.timeElapsed += 1  # increment time
 
             # Acknowledgement: https://stackoverflow.com/a/13589144
             handles, labels = self.axs.get_legend_handles_labels()
             by_label = dict(zip(labels, handles))
-            self.axs.legend(by_label.values(), by_label.keys(), loc='best')
+            self.axs.legend(by_label.values(), by_label.keys(), loc='best', fontsize = 15) # Make the legend on graph large enough
         except:
             traceback.print_exc()