import random
initial = [(10,10),(20,20),(30,0),(30,40),(50,40)]
#X = (random.sample(range(1, 501), 200))
#Y = (random.sample(range(1, 501), 200))
#initial = []
#i = 0
#while i < len(X):
# initial.append((X[i],Y[i]))
# i+= 1
print("PointList = %s" %(initial))
initialState = AntennaState(initial,200,1,time.time())
#initialState = AntennaState([(10,10),(20,20)],200,1)
solution = astar_search(initialState)
print("Solution is %s " % (solution))
def shortest_path(self, graph, intial, goal):
self.goal_state = goal
self.start_state = intial
solution = astar_search(graph, self.hueristic_fn)
#print(str(solution.path) + "hello123")
return solution.path
for cell in row:
if cell == 0:
return False
return True
def heuristic(self):
a = self.emptyCells / 4
b = self.emptyCells % 4
if b == 0:
return a
elif b == 3:
return a+2
else:
return a+1
### Private methods ####
def _createGrid(self,dimX,dimY,obstacles):
grid = [ [0 for y in range(dimY)] for x in range(dimX) ]
for i in range(dimX):
for j in range(dimY):
if (i,j) in obstacles:
grid[i][j] = -1
return grid
solution = astar_search(TileState((3,4),[(1,2)]))
