def generic_solver_multi(maze_num):
maze_map = mazes[maze_num]
selected_type = request.args.get('search_type')
# change string to enum
selected_type = search_type.A_Star if selected_type == "a_star" else selected_type
selected_type = search_type.DFS if selected_type == "dfs" else selected_type
selected_type = search_type.BFS if selected_type == "bfs" else selected_type
selected_type = search_type.GFS if selected_type == "gfs" else selected_type
s = search(selected_type, maze_map)
targets_dict = s.get_path()
distance = s.get_cost()
targets_ordered = list(targets_dict.keys())
path = multi_point_path(targets_dict)
# points = path_id_to_points(maze_map, path)
for k in targets_dict.keys():
path_ids = targets_dict[k]
path = [maze_map.graph.nodes[id_] for id_ in path_ids]
points = path_to_points(path)
targets_dict[k] = points
return json.dumps({"points": targets_dict, "order": targets_ordered, "cost": distance}, cls=EnhancedJSONEncoder)
def map_sol_a_star(maze_num):
maze_map = mazes[maze_num]
start_node = maze_map.get_node_by_map_point(maze_map.player)
target_node = maze_map.get_node_by_map_point(maze_map.traget[0])
path, cost = a_star_one_target(start_node, target_node)
points = path_to_points(path)
distance = path_to_distance(path)
return json.dumps({"points": points, "cost": distance}, cls=EnhancedJSONEncoder)
def map_sol_bfs(maze_num):
maze_map = mazes[maze_num]
starting_point = maze_map.get_node_by_map_point(maze_map.player).id
sol = BFS_Solver(starting_point, maze_map.graph, maze_map)
BFS(maze_map.graph, starting_point, sol.solver, sol.steps_counter)
path_dict = sol.get_result()
path_ids = path_dict[next(iter(path_dict))]
path = [maze_map.graph.nodes[id_] for id_ in path_ids]
distance = path_to_distance(path)
points = path_to_points(path)
return json.dumps({"points":points,"cost":distance}, cls=EnhancedJSONEncoder)
def map_sol_gfs(maze_num):
maze_map = mazes[maze_num]
starting_point = maze_map.get_node_by_map_point(maze_map.player).id
graph = maze_map.graph
sol = GFS_Solver(graph, starting_point)
informed_multi_target_solver(
GFS, graph, starting_point, maze_map, sol.solve, sol.steps_counter)
path_dict = sol.get_path()
path_ids = path_dict[next(iter(path_dict))]
path = [maze_map.graph.nodes[id_] for id_ in path_ids]
distance = path_to_distance(path)
points = path_to_points(path)
return json.dumps({"points": points, "cost": distance}, cls=EnhancedJSONEncoder)
def map_sol_dfs(maze_num):
maze_map = mazes[maze_num]
adjc_dict = maze_map.graph.get_adjacency_dict()
start_node = maze_map.get_node_by_map_point(maze_map.player)
target_node = maze_map.get_node_by_map_point(maze_map.traget[0])
path_ids = dfs_single_target(start_node.id, target_node.id, adjc_dict)
path = [maze_map.graph.nodes[id_] for id_ in path_ids]
# cost = path_to_distance(path)
route = path_to_points(path)
distance = path_to_distance(path)
points = route
return json.dumps({"points": points, "cost": distance}, cls=EnhancedJSONEncoder)
def map_sol_multi_a_star(maze_num):
maze_map = mazes[maze_num]
starting_point = maze_map.get_node_by_map_point(maze_map.player).id
targets_dict = a_star_multi_target(maze_map, maze_map.player.node_id)
targets_ordered = list(targets_dict.keys())
path = multi_point_path(targets_dict)
res_nodes = [maze_map.graph.nodes[id_] for id_ in path]
distance = path_to_distance(res_nodes)
#convert to points
for k in targets_dict.keys():
path_ids = targets_dict[k]
path = [maze_map.graph.nodes[id_] for id_ in path_ids]
points = path_to_points(path)
targets_dict[k] = points
return json.dumps({"points": targets_dict, "order": targets_ordered, "cost": distance}, cls=EnhancedJSONEncoder)
def map_sol_multi(maze_num):
maze_map = mazes[maze_num]
starting_point = maze_map.get_node_by_map_point(maze_map.player).id
graph = maze_map.graph
sol = GFS_Solver(graph, starting_point)
informed_multi_target_solver(
GFS, graph, starting_point, maze_map, sol.solve, sol.steps_counter)
targets_dict = sol.get_path()
# targets_dict.keys()
targets_ordered = list(targets_dict.keys())
distance = sol.res_path_cost()
#convert to points
for k in targets_dict.keys():
path_ids = targets_dict[k]
path = [maze_map.graph.nodes[id_] for id_ in path_ids]
points = path_to_points(path)
targets_dict[k] = points
return json.dumps({"points": targets_dict,"order":targets_ordered, "cost": distance}, cls=EnhancedJSONEncoder)