import matplotlib.pyplot as plt
import random, time
from libs.clustering import split_tour_across_clusters
from libs.simulated_annealing import SimulatedAnnealing, total_distance

random.seed(42)

def generate_cities(nb, max_coords=1000):
    return [random.sample(range(max_coords), 2) for _ in range(nb)]

nb_ville = 150
max_coords = 1000
nb_truck = 3
temperature = 10000
cooling_rate = 0.9999
temperature_ok = 0.001

start_time_generate = time.time()
cities = generate_cities(nb_ville, max_coords)      
cities[0] = [max_coords/2, max_coords/2]
stop_time_generate = time.time()

start_time_split = time.time()
clusters = split_tour_across_clusters(cities, nb_truck)
stop_time_split = time.time()

for cluster in clusters.values():
    print(len(cluster))
print("\n---- TIME ----")
print("generate cities time: ", stop_time_generate - start_time_generate)
print("split cities time: ", stop_time_split - start_time_split)

# create new figure for annealing paths
plt.figure()
colors = [
    '#1f77b4',  # Bleu moyen
    '#ff7f0e',  # Orange
    '#2ca02c',  # Vert
    '#d62728',  # Rouge
    '#9467bd',  # Violet
    '#8c564b',  # Marron
    '#e377c2',  # Rose
    '#7f7f7f',  # Gris
    '#bcbd22',  # Vert olive
    '#17becf',  # Turquoise
    '#1b9e77',  # Vert Teal
    '#d95f02',  # Orange foncé
    '#7570b3',  # Violet moyen
    '#e7298a',  # Fuchsia
    '#66a61e',  # Vert pomme
    '#e6ab02',  # Jaune or
    '#a6761d',  # Bronze
    '#666666',  # Gris foncé
    '#f781bf',  # Rose clair
    '#999999',  # Gris moyen
]

best_routes = []

for i, cluster_indices in enumerate(clusters.values()):
    # Sélection d'une couleur pour le cluster
    color = colors[i % len(colors)]
    
    # Récupération des coordonnées de la ville
    cluster_cities = [cities[index] for index in cluster_indices]

    # Appel de la fonction simulated_annealing
    simulated_annealing = SimulatedAnnealing(cluster_cities, temperature=10000, cooling_rate=0.999, temperature_ok=0.01)
    best_route = simulated_annealing.run()
    best_routes.append((best_route, color))

    print("Final solution for cluster ", i, ":", best_route)
    print("Total distance: ", total_distance(best_route))

for i, (route, color) in enumerate(best_routes):
    x = [city[0] for city in route]
    y = [city[1] for city in route]
    x.append(x[0])
    y.append(y[0])
    plt.plot(x, y, color=color, marker='x', linestyle='-', label=f"Cluster {i}")
plt.legend(loc="best")
plt.show()