def paint(self):
""" Paints the player and its aim indicator on the screen.
Also paints the targets for the aimed at tile if it has any.
"""
super(Player, self).paint()
if self.removing_tile:
if g.in_map(*self.get_aim_tile()) and g.get_img(*self.get_aim_tile()).destroy is not None:
aim = "remove_aim"
else:
aim = "remove_aim_fail"
else:
aim = "aim"
x = ((self.last_aim_tile[0]*c.TILE_SIZE) +
(c.TILE_SIZE - g.images[aim].get_size()[0]) / 2)
y = ((self.last_aim_tile[1]*c.TILE_SIZE) +
(c.TILE_SIZE - g.images[aim].get_size()[1]) / 2)
g.screen.blit(g.images[aim].get(), (x, y))
# When you aim at a factory, display the set targets for that tile
if g.in_map(*self.last_aim_tile) and g.get_img(*self.last_aim_tile).factory_output:
x, y = self.last_aim_tile
if g.map[x][y].good_targets:
for good_target in list(g.map[x][y].good_targets.values()):
g.screen.blit(g.images["tile_target_aim"].get(),
(good_target[0]*c.TILE_SIZE +
(c.TILE_SIZE - g.images["tile_target_aim"].get_size()[0]) / 2,
good_target[1]*c.TILE_SIZE +
(c.TILE_SIZE - g.images["tile_target_aim"].get_size()[1]) / 2))
# Show the direction the selected launcher tile is shooting
if type(g.map[x][y]) == tiles.LauncherTile and g.map[x][y].shoot_direction != (0, 0):
g.screen.blit(g.images["tile_target_aim"].get(),
((g.map[x][y].shoot_direction[0]+x)*c.TILE_SIZE +
(c.TILE_SIZE - g.images["tile_target_aim"].get_size()[0]) / 2,
((g.map[x][y].shoot_direction[1]+y)*c.TILE_SIZE +
(c.TILE_SIZE - g.images["tile_target_aim"].get_size()[1]) / 2)))
def goods_pathfind(self, target_goods):
""" Finds a path from the start tile, (the current tile of the entity) to the nearest factory tile that
can recieve the passed-in goods type.
"goods" should be a string with the type of goods that the entity will be carrying.
returns True if a suitable tile was found and False if no suitable tile was found
"""
start = self.get_tile()
# The open_dict and closed_dict both follow the format:
# (key_x, key_y): [g, (came_from_x, came_from_y)]
# This is a simplified version of the pathfind function. It doesn't use heuristics because it doesn't
# know where to go yet. It only uses the G value, which is the distance to the tile it came from.
if type(start) != tuple:
raise Exception("Value given by self.get_tile() to PathingEntity.goods_pathfind() is not tuple")
# The open dictionary is a dictionary keeping the currently checkable tiles
# The starting tile is identified as not having a came_from-tuple.
open_dict = {start: [0]}
# The closed dictionary is a dicionary keeping the currently checked tiles
closed_dict = {}
current = None
while len(open_dict.keys()) > 0:
lowest_value = None
# Get the lowest value
for key in open_dict.keys():
value = open_dict[key][0]
if lowest_value is None:
lowest_value = value
current = key
elif value < lowest_value:
lowest_value = value
current = key
# Move current from the open dictionary to the closed one
closed_dict[current] = open_dict[current]
del open_dict[current]
# If we're done here
done = False
deliver_tiles = []
# This code block makes sure the items are delivered to the tile next to the tile instead of diagonally
if (g.in_map(current[0]+1, current[1]) and
g.get_img(current[0]+1, current[1]).factory_input):
deliver_tiles.append((current[0]+1, current[1]))
elif (g.in_map(current[0]-1, current[1]) and
g.get_img(current[0]-1, current[1]).factory_input):
deliver_tiles.append((current[0]-1, current[1]))
elif (g.in_map(current[0], current[1]+1) and
g.get_img(current[0], current[1]+1).factory_input):
deliver_tiles.append((current[0], current[1]+1))
elif (g.in_map(current[0], current[1]-1) and
g.get_img(current[0], current[1]-1).factory_input):
deliver_tiles.append((current[0], current[1]-1))
if deliver_tiles:
for deliver_tile in deliver_tiles:
try:
for good_name in list(g.map[deliver_tile[0]][deliver_tile[1]].requests.keys()):
if good_name == target_goods:
if g.map[deliver_tile[0]][deliver_tile[1]].requests[target_goods] > 0:
done = True
g.map[deliver_tile[0]][deliver_tile[1]].requests[target_goods] -= 1
break # Break out of the goods for loop, not the entire while loop
if done:
break
except AttributeError:
pass
if done is True:
full_path = []
self.deliver_tile = deliver_tile
try:
while current != start:
full_path.append(current)
current = closed_dict[current][1]
except:
print(closed_dict)
print(full_path)
# Trying to understand the heisenbug! D:
import pdb, sys
e, m, tb = sys.exc_info()
pdb.post_mortem(tb)
full_path.reverse()
self.path = full_path
self.next_target_tile()
self.home_tile = self.get_tile()
return True
# Move through all neighbours
for i in range(current[0]-1, current[0]+2):
for j in range(current[1]-1, current[1]+2):
neighbour = (i, j)
if 0 <= neighbour[0] < len(g.map) and 0 <= neighbour[1] < len(g.map[0]):
# Get the G score, the cost to go back to the start
if neighbour[0] == current[0]:
if neighbour[1] == current[1]:
continue
else:
g_score = closed_dict[current][0] + 10
else:
if neighbour[1] == current[1]:
g_score = closed_dict[current][0] + 10
else:
# Make sure the pathfinding doesn't try to go through blocks diagonally.
if (g.get_img(neighbour[0], current[1]).collides and
g.get_img(current[0], neighbour[1]).collides):
# If the blocks on either side of the diagonal walk is collidable, skip this one
if neighbour not in closed_dict:
closed_dict[neighbour] = None
continue
# If it can travel diagonally, give it a cost of the square root of two.
g_score = closed_dict[current][0] + 14
if c.IMAGES[g.map[neighbour[0]][neighbour[1]].type].collides is False or neighbour == start:
# Check if this neighbour can be added the the open_dict and do so if so
if neighbour not in closed_dict.keys():
if neighbour not in open_dict.keys() or g_score < open_dict[neighbour][0]:
open_dict[neighbour] = [g_score, current]
else:
if neighbour not in closed_dict.keys() and neighbour not in open_dict.keys():
closed_dict[neighbour] = None
self.path = []
self.stop_moving()
return False
def pathfind(self, end):
""" Finds a path from start to end tiles using A* algorithm
"start" and "end" are tuples with x and y coordinates of a tile
returns True if it succeded and False if it couldn't find a path
"""
start = self.get_tile()
# The open_dict and closed_dict both follow the format:
# (key_x, key_y): [f, g, h, (came_from_x, came_from_y)]
# F, G and H. G is the length to the start tile, H is the Heuristics
# estimate of the distance to the end tile and F = G + H
if type(start) != tuple or type(end) != tuple:
raise Exception("Value passed to PathingEntity.pathfind() is not tuple")
# The open dictionary is a dictionary keeping the currently checkable tiles
# The starting tile is identified as not having a came_from-tuple.
open_dict = {start: [self._heuristic_cost_estimate(start, end), 0,
self._heuristic_cost_estimate(start, end)]}
# The closed dictionary is a dicionary keeping the currently checked tiles
closed_dict = {}
current = None
while len(open_dict.keys()) > 0:
lowest_value = None
# Get the lowest value
for key in open_dict.keys():
value = open_dict[key][0]
if lowest_value is None:
lowest_value = value
current = key
else:
if value < lowest_value:
lowest_value = value
current = key
# Move current from the open dictionary to the closed one
closed_dict[current] = open_dict[current]
del open_dict[current]
# If we're done here
deliver_tile = None
if g.get_img(*end).collides and current != end:
# Find a tile next to the target tile to stand on if it collides
if (g.in_map(current[0] + 1, current[1]) and
(current[0] + 1, current[1]) == end):
deliver_tile = (current[0] + 1, current[1])
elif (g.in_map(current[0] - 1, current[1]) and
(current[0] - 1, current[1]) == end):
deliver_tile = (current[0] - 1, current[1])
elif (g.in_map(current[0], current[1] + 1) and
(current[0], current[1] + 1) == end):
deliver_tile = (current[0], current[1] + 1)
elif (g.in_map(current[0], current[1] - 1) and
(current[0], current[1] - 1) == end):
deliver_tile = (current[0], current[1] - 1)
elif current == end:
deliver_tile = current
if deliver_tile is not None:
# closed_dict[current]
full_path = []
while current != start:
full_path.append(current)
current = closed_dict[current][3]
full_path.reverse()
self.deliver_tile = deliver_tile
self.path = full_path
self.next_target_tile()
return True
# # Old version
# if done is True:
# full_path = []
# self.deliver_tile = deliver_tile
# while len(closed_dict[current]) > 1:
# full_path.append(current)
# current = closed_dict[current][1]
# full_path.reverse()
# self.path = full_path
# self.next_target_tile()
# self.home_tile = self.get_tile()
# return
# Move through all neighbours
for i in range(current[0]-1, current[0]+2):
for j in range(current[1]-1, current[1]+2):
neighbour = (i, j)
if 0 <= neighbour[0] < len(g.map) and 0 <= neighbour[1] < len(g.map[0]):
# Get the G score, the cost to go back to the start
if neighbour[0] == current[0]:
if neighbour[1] == current[1]:
continue
else:
g_score = closed_dict[current][1] + 10
else:
if neighbour[1] == current[1]:
g_score = closed_dict[current][1] + 10
else:
# Make sure the pathfinding doesn't try to go through blocks diagonally.
if (g.get_img(neighbour[0], current[1]).collides and
g.get_img(current[0], neighbour[1]).collides):
# If the blocks on either side of the diagonal walk is collidable, skip this one
closed_dict[neighbour] = None
continue
# If it can travel diagonally, give it a cost of the square root of two.
g_score = closed_dict[current][1] + 14
if c.IMAGES[g.map[neighbour[0]][neighbour[1]].type].collides is False:
# Check if this neighbour can be added the the open_dict and do so if so
if neighbour not in closed_dict.keys():
if neighbour not in open_dict.keys() or g_score < open_dict[neighbour][1]:
h_score = self._heuristic_cost_estimate(neighbour, end)
f_score = g_score + h_score
open_dict[neighbour] = [f_score, g_score, h_score, current]
else:
closed_dict[neighbour] = None
self.path = []
self.stop_moving()
return False