Spaces:
Sleeping
Sleeping
import pandas as pd | |
from flight_distance import * | |
from optimizer import * | |
from weather import * | |
airport_identifiers = ['BOM', 'CCU', 'DEL'] # Replace with actual identifiers | |
#Get Airport Coordinates | |
lat_long_dict = get_airport_lat_long(airport_identifiers) | |
print("Coordinates: \n",lat_long_dict) | |
#Get Distance between each node (airports) | |
trip_distance = calculate_distances(airport_identifiers) | |
print("Distance b/w Airports: \n",trip_distance) | |
#Get onroute weather | |
raw_weather = fetch_weather_for_all_routes(airport_identifiers, lat_long_dict) | |
route_factors = extract_route_factors(raw_weather) | |
print("On Route weather: \n", raw_weather) | |
# # Ensure the graph is bidirectional (undirected) | |
# for (a, b), dist in list(trip_distance.items()): | |
# trip_distance[(b, a)] = dist | |
# # Find the optimal route with the new cost metric | |
# Ensure the graph is bidirectional (undirected) | |
for (a, b), dist in list(trip_distance.items()): | |
trip_distance[(b, a)] = dist | |
# Find the optimal route with the new cost metric | |
optimal_route, optimal_distance = find_optimal_route(airport_identifiers, trip_distance, route_factors) | |
# Display the optimal route and the total adjusted distance/cost | |
print("Optimal Route:", " -> ".join(optimal_route) + f" -> {optimal_route[0]}") | |
print("Total Adjusted Distance/Cost:", optimal_distance) | |
# print("Optimal Route:", " -> ".join(optimal_route) + f" -> {optimal_route[0]}") | |
# print("Total Adjusted Distance/Cost:", optimal_distance) | |