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import networkx as nx
import osmnx as ox
from src.generation.graph_generation import generate_graph
from src.helper.prune_maps import prune_verdun
from src.helper.display_graph import display_graph
from src.deneigeuses.directed_cpp import oriented_cpt, chinese_postman_greedy
from src.helper.export_to_kml import export_to_kml
def output_debug(G, paths, connections, debug_mode):
# debug_print("Calcule de la distance total :", debug_mode)
# distance_drone, unused_distance = distance_total(G, paths, connections)
# debug_print(f"Distance total du drone en kilometre = {distance_drone}", debug_mode)
# debug_print(f"Distance Manqué (routes hors arrondissement) du drone en kilometre = {unused_distance}", debug_mode)
# distance_opti = 4025.2333363147495 # distance_optimal(G)
# debug_print(f"Distance Optimal du drone en kilometre = {distance_opti}", debug_mode)
# G_undirected = G.to_undirected()
# distance_ref = 0
# for u, v, data in G_undirected.edges(data=True):
# distance_ref += data["length"]
# distance_ref /= 1000
# debug_print(f"Distance total de Montréal en kilomètres = {distance_ref}", debug_mode)
tmp = generate_graph("Verdun, Montréal, Québec, Canada", debug_mode)
print("Graph généré")
tmp = prune_verdun(tmp, debug_mode)
print("Verdun pruné, nb_nodes : ", len(tmp.nodes), ", nb_edges : ", len(tmp.edges()))
print("cpt")
path = chinese_postman_greedy(tmp, debug=True)
print("cpt fini")
display_graph(tmp, "Verdun, Québec, Canada", False, last_call=True, double_sens=True)
export_to_kml(path, [], tmp, debug_mode)
#for edg in tmp.edges:
#print(edg, " ", tmp.get_edge_data(edg[0], edg[1]))
return True
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