def __init__(self, size):
self.size = size
self.neighbors_i = {}
+ self.directions = self.get_directions()
def get_directions(self):
directions = []
def get_neighbors_yxyx(self, yxyx):
neighbors = {}
- for direction in self.get_directions():
+ for direction in self.directions:
neighbors[direction] = self.move_yxyx(yxyx, direction)
return neighbors
def get_neighbors_yx(self, pos):
neighbors = {}
- for direction in self.get_directions():
+ for direction in self.directions:
neighbors[direction] = self.move_yx(pos, direction)
return neighbors
if yxyx[0] not in obstacles:
obstacles[yxyx[0]] = []
obstacles[yxyx[0]] += [yxyx[1]]
- for yx in self:
+ for yx in self: # TODO: iter and source_yxyx expensive, cache earlier?
big_yx, little_yx = self.source_yxyx(yx)
if big_yx in obstacles and little_yx in obstacles[big_yx]:
self.source_map_segment += 'X'
class DijkstraMap(SourcedMap):
def __init__(self, *args, **kwargs):
+ # TODO: check potential optimizations:
+ # - do a first pass circling out from the center
+ # - somehow ignore tiles that have the lowest possible value (we can
+ # compare with a precalculated map for given starting position)
+ # - check if Python offers more efficient data structures to use here
+ # - shorten radius to nearest possible target
super().__init__(*args, **kwargs)
self.terrain = [255] * self.size_i
self[self.center] = 0