def on_sample_chosen(self):
size = self.sample_radio_id.get()
logging.info('Loading sample of size ' + str(size))
self.grid_size, self.pipe_ends = Samples.get_puzzle(str(size))
self.on_grid_size_changed()
self.grid_manager.load_maze(self.grid_size, self.pipe_ends)
self.ready_for_run = True
self.init_run()
wall_nb = max(start_walls, target_walls)
score += wall_nb * 10
# increase score if the distance between the start and target is high
distance = self.shortest_path(start, target, self.original_id(i))
if distance > self.grid_size / 2:
score += distance * 2
if score > best_score:
best_pipe = i
best_score = score
logging.debug("Choosing next pipe {0}".format(
self.original_id(best_pipe)))
# flip the next pipe with the one we want to process
if best_pipe != self.curr_pipe:
original_best_pipe_id = self.pipes_mapping[best_pipe]
self.pipes_mapping[best_pipe] = self.pipes_mapping[self.curr_pipe]
self.pipes_mapping[self.curr_pipe] = original_best_pipe_id
if __name__ == "__main__":
setup_logging()
(size, pipes) = Samples.get_puzzle("12")
engine = ShortestPathEngine(size, pipes)
while not engine.solved:
for next_move in engine.next_moves():
logging.debug(next_move)
logging.info(engine.display())
