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from gui import marker, marker_updated
import gui
import math
# A* code taken and adapted from https://gist.github.com/jamiees2/5531924
class Node:
def __init__(self,value,point,point_in_grid):
self.value = value
self.point = point
self.point_in_grid = point_in_grid
self.parent = None
self.H = 0
self.G = 0
def move_cost(self,other):
# assert other in siblings(self,grid). otherwise this makes no sense
# assert that siblings are only in horizontal or vertical directions. otherwise
# someone must replace the number "1" by appropriate distances
return distance(self, other) + (self.value + other.value)/2
def siblings(point,grid):
x,y = point.point_in_grid
links = [grid[d[0]][d[1]] for d in [(x-1, y),(x-1,y-1),(x,y - 1),(x+1,y-1),(x+1,y),(x+1,y+1),(x,y + 1),(x-1,y+1)]]
return [link for link in links if link.value != None]
def distance(point,point2):
return math.sqrt((point.point[0] - point2.point[0])**2 + (point.point[1]-point2.point[1])**2)
def aStar(start, goal, grid):
print("aStar("+str(start.point)+"="+str(start.point_in_grid)+", "+str(goal.point)+"="+str(goal.point_in_grid)+")")
openset = set()
closedset = set()
current = start
openset.add(current)
while openset:
#Find the item in the open set with the lowest G + H score
current = min(openset, key=lambda o:o.G + o.H)
#If it is the item we want, retrace the path and return it
if current == goal:
path = []
while current.parent:
path.append(current)
current = current.parent
path.append(current)
return path[::-1]
openset.remove(current)
closedset.add(current)
for node in siblings(current,grid):
if node in closedset:
continue
if node in openset:
#Check if we beat the G score
new_g = current.G + current.move_cost(node)
if node.G > new_g:
#If so, update the node to have a new parent
node.G = new_g
node.parent = current
else:
#If it isn't in the open set, calculate the G and H score for the node
node.G = current.G + current.move_cost(node)
node.H = distance(node, goal)
node.parent = current
openset.add(node)
raise ValueError('No Path Found')
grid_radius=int(1100/30)*30
grid_density=30
class PathfindingTesterStrategy:
def __init__(self, c):
self.c = c
self.path = None
def build_grid(self):
grid = [[None for x in range(int(2*grid_radius//grid_density+1))] for x in range(int(2*grid_radius//grid_density+1))]
interesting_cells = list(filter(lambda c : not (c.is_food or c in self.c.player.own_cells), self.c.player.world.cells.values()))
for x in range(-grid_radius,grid_radius+1,grid_density):
gridx = (x+grid_radius) // grid_density
for y in range(-grid_radius,grid_radius+1,grid_density):
gridy = (y+grid_radius) // grid_density
val = 0
for cell in interesting_cells:
relpos = (cell.pos.x - (x+self.c.player.center.x), cell.pos.y - (y+self.c.player.center.y))
dist_sq = relpos[0]**2 + relpos[1]**2
if dist_sq < cell.size**2 *3:
val += 100000000
if (gridx in [0,len(grid)-1] or gridy in [0, len(grid[gridx])-1]):
val = None
grid[gridx][gridy] = Node(val, (self.c.player.center[0]+x,self.c.player.center[1]+y), (gridx, gridy))
return grid
def plan_path(self):
goalx = int((marker[0][0] - self.c.player.center[0] + grid_radius)/grid_density)
goaly = int((marker[0][1] - self.c.player.center[1] + grid_radius)/grid_density)
grid = self.build_grid()
path = aStar(grid[int(grid_radius/grid_density)][int(grid_radius/grid_density)], grid[goalx][goaly], grid)
return path
def path_is_valid(self, path):
interesting_cells = list(filter(lambda c : not (c.is_food or c in self.c.player.own_cells), self.c.player.world.cells.values()))
for node in path:
for cell in interesting_cells:
relpos = (cell.pos.x - node.point[0], cell.pos.y - node.point[1])
dist_sq = relpos[0]**2 + relpos[1]**2
if dist_sq < cell.size**2 *2:
return False
return True
def process_frame(self):
if marker_updated[0]:
marker_updated[0]=False
self.path = self.plan_path()
for node in self.path:
print (node.point_in_grid)
print("="*10)
for (node1,node2) in zip(self.path,self.path[1:]):
gui.draw_line(node1.point, node2.point, (0,0,0))
if self.path:
relx, rely = self.path[0].point[0]-self.c.player.center.x, self.path[0].point[1]-self.c.player.center.y
if relx*relx + rely*rely < (2*grid_density)**2:
self.path=self.path[1:]
if self.path and not self.path_is_valid(self.path):
print("recalculating!")
self.path = self.plan_path()
if self.path:
return self.path[0].point
return marker[0]
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