Update app.py

app.py

@@ -105,6 +105,8 @@ def predict_and_plot(velocity, temperature, precipitation, humidity):
                         cleaning_time = t1 + (threshold - c1) * (t2 - t1) / (c2 - c1)
                         cleaning_times.append(cleaning_time)
                         break
+                else:
+                    cleaning_times.append(time_intervals[-1])  # If threshold is not reached
             return cleaning_times
 
         # Calculate cleaning times for all 6 lidars
@@ -114,22 +116,22 @@ def predict_and_plot(velocity, temperature, precipitation, humidity):
         lidar_names = ['F/L', 'F/R', 'Left', 'Right', 'Roof', 'Rear']
 
         # Plot the graph
-        plt.figure(figsize=(12, 8))
+        fig, ax = plt.subplots(figsize=(12, 8))
 
         for i in range(simulated_contamination_levels.shape[1]):
-            plt.plot(time_intervals, simulated_contamination_levels[:, i], label=f'{lidar_names[i]}')
-            plt.axhline(y=0.4, color='r', linestyle='--', label='Contamination Threshold' if i == 0 else "")
+            ax.plot(time_intervals, simulated_contamination_levels[:, i], label=f'{lidar_names[i]}')
+            ax.axhline(y=0.4, color='r', linestyle='--', label='Contamination Threshold' if i == 0 else "")
             if i < len(cleaning_times):
-                plt.scatter(cleaning_times[i], 0.4, color='k')  # Mark the cleaning time point
+                ax.scatter(cleaning_times[i], 0.4, color='k')  # Mark the cleaning time point
 
-        plt.title('Contamination Levels Over Time for Each Lidar')
-        plt.xlabel('Time (seconds)')
-        plt.ylabel('Contamination Level')
-        plt.legend()
-        plt.grid(True)
+        ax.set_title('Contamination Levels Over Time for Each Lidar')
+        ax.set_xlabel('Time (seconds)')
+        ax.set_ylabel('Contamination Level')
+        ax.legend()
+        ax.grid(True)
         
         # Flatten the results into a single list of 13 outputs
-        plot_output = plt
+        plot_output = fig
         contamination_output = [f"{val * 100:.2f}%" for val in contamination_levels[0]]
         cleaning_time_output = [f"{val:.2f}" for val in cleaning_times]