def evaluate(self, action, zones, graph):
scenario = Scenario_Generator(
self.width,
self.height,
self.immobile_objs,
self.mobile_objs,
self.manipulatable_obj,
self.target_obj,
showRender=False,
)
game_objects = scenario.getGameObjects()
end_position, shape = scenario.evaluate(action)
radius = shape.radius
end_position = Point(end_position)
circular_region_ball = end_position.buffer(radius)
occupied_zones = []
for i in xrange(len(zones)):
if zones[i].intersects(circular_region_ball):
occupied_zones.append(i)
if len(occupied_zones) == 0:
return len(zones) # set to the maximum length
min_d = 9999
for occupied_zone in occupied_zones:
length = nx.shortest_path_length(graph, source=occupied_zone, target=self.target_zone)
if length < min_d:
min_d = length
return min_d
def test_old_evaluate(self, action):
scenario = Scenario_Generator(self.width, self.height, self.immobile_objs, self.mobile_objs, self.manipulatable_obj, self.target_obj, showRender=False)
game_objects = scenario.getGameObjects()
graph, zones = triangulate(game_objects, self.width, self.height)
end_position, shape = scenario.evaluate(action)
end_position = Point(end_position)
last_zone = -1
for i in xrange(len(zones)):
if zones[i].contains(end_position):
last_zone = i
break
if last_zone == -1:
return len(zones) # set to the maximum length
score = nx.shortest_path_length(graph, source=i, target=self.target_zone)
return score