Gradio UI

flight_route_ui.py

@@ -0,0 +1,67 @@
+import gradio as gr
+import pandas as pd
+from optimizer import *
+from weather import *
+from flight_distance import *  # Assuming this function is defined in your aircraft capabilities module
+
+# Load airport data and aircraft data from CSV files
+airport_df = pd.read_csv(r'airport.csv')  # Adjust the path to your CSV file
+aircraft_df = pd.read_csv(r'aircraft.csv')  # Adjust the path to your CSV file
+
+# Create a combined option list with both IATA codes and airport names
+airport_options = [f"{row['IATA']} - {row['Airport_Name']}" for _, row in airport_df.iterrows()]
+
+# Ensure the correct column is used for aircraft types
+aircraft_type_column = 'Aircraft'  # Adjust if your column name is different
+if aircraft_type_column not in aircraft_df.columns:
+    raise ValueError(f"Column '{aircraft_type_column}' not found in aircraft_types.csv. Available columns: {aircraft_df.columns}")
+
+aircraft_options = aircraft_df[aircraft_type_column].tolist()
+
+# Function to determine if a route can be flown
+def check_route(airport_selections, aircraft_type):
+    # Extract IATA codes from the selected options
+    airports = [selection.split(" - ")[0] for selection in airport_selections]
+    
+    # Get coordinates for selected airports as a dictionary {IATA: (latitude, longitude)}
+    lat_long_dict = get_airport_lat_long(airports)  # Ensure this function returns a dictionary in the expected format
+    
+    # Pass only the required details in the expected format for the weather function
+    raw_weather = fetch_weather_for_all_routes(airports, lat_long_dict)  # This should receive the correct lat_long_dict
+    
+    # Extract route factors (e.g., conditions impacting the route)
+    route_factors = extract_route_factors(raw_weather)
+
+    # Calculate distances between selected airports
+    trip_distance = calculate_distances(airports)
+
+    # Ensure the graph is bidirectional
+    for (a, b), dist in list(trip_distance.items()):
+        trip_distance[(b, a)] = dist
+
+    # Find the optimal route
+    optimal_route, optimal_distance = find_optimal_route(airports, trip_distance, route_factors)
+
+    # Check if the aircraft can fly the route without refueling
+    result = can_fly_route(aircraft_type, airports)
+
+    # Convert all dictionary keys to strings for JSON compatibility
+    return {
+        "Optimal Route": " -> ".join(optimal_route) + f" -> {optimal_route[0]}",
+        "Total Adjusted Distance/Cost": str(optimal_distance),  # Convert to string if necessary
+        "Can Fly Route": str(result)  # Convert to string if necessary
+    }
+
+# Gradio Interface
+with gr.Blocks() as demo:
+    gr.Markdown("## Airport Route Feasibility Checker")
+    airport_selector = gr.Dropdown(airport_options, multiselect=True, label="Select Airports (IATA - Name)")
+    aircraft_selector = gr.Dropdown(aircraft_options, label="Select Aircraft Type")
+    check_button = gr.Button("Check Route Feasibility")
+    
+    result_output = gr.JSON(label="Result")
+
+    check_button.click(fn=check_route, inputs=[airport_selector, aircraft_selector], outputs=result_output)
+
+# Launch the Gradio app
+demo.launch()

main.py

@@ -29,3 +29,8 @@ optimal_route, optimal_distance = find_optimal_route(airport_identifiers, trip_d
 print("Optimal Route:", " -> ".join(optimal_route) + f" -> {optimal_route[0]}")
 print("Total Adjusted Distance/Cost:", optimal_distance)
 
+aircraft_type = input("Enter the aircraft type: ")
+
+# Check if the aircraft can fly the route without refuel
+result = can_fly_route(aircraft_type, airport_identifiers)
+print(result)

optimizer.py

@@ -95,7 +95,7 @@ def find_optimal_route(airports, distances, route_factors):
         try:
             current_distance = calculate_route_distance(route, distances, route_factors)
             if current_distance < min_distance:
-                min_distance = current_distance
+                min_distance = round(current_distance,2)
                 best_route = route
         except ValueError as e:
             print(e)  # Log the error to debug missing segments

weather.py

@@ -87,23 +87,3 @@ def fetch_weather_for_all_routes(airport_identifiers, airports):
 
     return route_factors
 
-# # Example usage
-# airports = {
-#     'SIN': (1.3644, 103.9915),  # Singapore Changi Airport
-#     'LAX': (33.9416, -118.4085),  # Los Angeles International Airport
-#     'JFK': (40.6413, -73.7781),  # John F. Kennedy International Airport
-#     'CDG': (49.0097, 2.5479),  # Charles de Gaulle Airport
-#     'LHR': (51.4700, -0.4543)   # London Heathrow Airport
-# }
-
-# airport_identifiers = ['SIN', 'LAX', 'JFK', 'CDG', 'LHR']  # Replace with actual identifiers
-
-# # Fetch the weather along all possible routes
-# route_weather = fetch_weather_for_all_routes(airport_identifiers, airports)
-
-# # Display the weather data for each route
-# for route, factors in route_weather.items():
-#     print(f"Route: {route}")
-#     for factor in factors:
-#         print(f"  Segment: {factor['segment']}, Weather: {factor['weather']}, Temperature: {factor['temperature']} °C")
-#     print()