def compute_path(labyrinth):
children_gen = lab_module.NeighborsGeneratorJPS(labyrinth)
heur_goal = lab_module.heur_diag(labyrinth.goal, labyrinth.start)
eq_to_goal = lambda p: p == labyrinth.goal
cur_time = time.perf_counter()
path, *_, info = searching.a_star(labyrinth.start, eq_to_goal,
heur_goal, children_gen)
cur_time = time.perf_counter() - cur_time
if path:
path = reconstruct_path(path, labyrinth)
return path, cur_time, info
def compute(self):
if not self.labyrinth.start or not self.labyrinth.goal:
raise ValueError("Start or goal not found")
self.children_gen = NeighborsGeneratorJPS(self.labyrinth)
self.heur = heur_diag
self.heur_goal = self.heur(self.labyrinth.goal, self.labyrinth.start)
self.max_heur = int(self.heur_goal(self.labyrinth.start))
print("Start detected:\t{}".format(self.labyrinth.start))
print("Goal detected:\t{}".format(self.labyrinth.goal))
print("Starting search...")
eq_to_goal = lambda p: np.array_equal(p, self.labyrinth.goal)
c_time = time.perf_counter()
path, *_, info = a_star(self.labyrinth.start,
eq_to_goal,
self.heur_goal, self.children_gen,
self.gui_callback)
c_time = (time.perf_counter() - c_time)
if path:
path, cost = self.reconstruct_path(path)
else:
cost = float("inf")
# print(path)
print("Search ended")
print("Time:", round(c_time, 2), "s")
print("Nodes searched:", info.nodes)
print("Maximum list size:", info.maxl)
print("Path cost:", cost)
if path is None:
print("Path not found")
else:
print("Found path of", len(path), "nodes")
print("Path generation completed")
print("*" * 100)
if PATH_DELAY_TIME:
for i in range(len(path)):
self.gui_callback(None, path[:i])
time.sleep(PATH_DELAY_TIME)
else:
self.gui_callback(None, path)
def test_a_star(self):
"""Test and visualize A* search"""
start = 'a'
goal = 'u'
node_positions = {
n: self.romania.node[n]['pos']
for n in self.romania.node.keys()
}
self.romania.reset_search()
path = a_star(self.romania, start, goal)
self.draw_graph(self.romania,
node_positions=node_positions,
start=start,
goal=goal,
path=path)
