def __init__(self, input_dict):
self.search = aStarSearch()
''' Create a new FeatureExtractor from a dict object.'''
new_type = input_dict['_type']
if new_type == BasicFeatures.type_name:
self.__class__ = BasicFeatures
elif new_type == QualifyingFeatures.type_name:
self.__class__ = QualifyingFeatures
elif new_type == CompositingFeatures.type_name:
self.__class__ = CompositingFeatures
elif new_type == AdvancedFeatures.type_name:
self.__class__ = AdvancedFeatures
else:
raise Exception("Invalid feature class %s" + new_type)
self.feature_names = []
self.feature_id = {}
# Call class-specific initialization.
self.init_from_dict(input_dict)
fid = 0
for name in self.feature_names:
self.feature_id[name] = fid
fid += 1
def moving_towards_on_astar(self, world, loc, new_loc, target, state):
""" Returns true, if the new_loc is the next step to go towards the target on an aStar Path. """
if self.pathfinder is None:
self.pathfinder = aStarSearch(world, use_cache=self.use_astar_cache)
if self.pathfinder.lookup(loc, target) and self.pathfinder.lookup(new_loc, target):
return self.pathfinder.lookup(loc, target)
elif state.a_star_counter < 0:
state.a_star_counter += 1
# Generate an a*-path
cur_path_len = self.pathfinder.get_path(loc, target)
next_path_len = self.pathfinder.get_path(new_loc,target)
if cur_path_len:
return next_path_len and next_path_len < cur_path_len
else:
# Food not near enough for this ant
return False
else:
# Fall back to greedy approximation
return self.moving_towards(world, loc, new_loc, target, state)
def __init__(self):
FeatureExtractor.__init__(self, {'_type': AdvancedFeatures.type_name})
self.search = aStarSearch()
