def setupGraph(): # set up the problem as a TSP
import itertools
import copy
import read_maze
import Astar
maze, visited, unavaiable, start, goal, rows, columns = read_maze.generate_maze(
)
goal_temp = copy.deepcopy(goal)
goal_temp.append(start)
print(len(goal))
paths = []
costs = []
pair = []
N = len(goal_temp)
csgraph = [[0 for x in range(N)] for y in range(N)]
for first, second in itertools.combinations(goal_temp, 2):
#print("copy")
#visited1= copy.deepcopy(visited)
#maze1 = copy.deepcopy(maze)
#unavaiable1 = copy.deepcopy(unavaiable)
#print("index")
N1 = goal_temp.index(first)
N2 = goal_temp.index(second)
#print(first)
#print(second)
cost = Astar2(maze, visited, unavaiable, first, second, rows, columns)
#cost = Astar.Astar(maze1, visited1, unavaiable1, first, second, rows, columns)
csgraph[N1][N2] = cost
costs.append(cost)
pair.append([first, second])
print("graph done")
print(pair)
return (csgraph, pair, costs, paths, maze, visited, unavaiable, start,
goal, rows, columns)
def setupGraph():
import itertools
import copy
maze, visited, unavaiable, start, pure_goal, rows, columns = read_maze.generate_maze(
)
goal = copy.deepcopy(pure_goal)
goal.insert(0, start)
print(len(goal))
paths = []
costs = []
pairs = []
graph = []
for first, second in itertools.combinations(goal, 2):
visited1 = copy.deepcopy(visited)
maze1 = copy.deepcopy(maze)
unavaiable1 = copy.deepcopy(unavaiable)
(maze1, cost, curridx, path) = Astar(maze1, visited1, unavaiable1,
first, second, rows, columns)
graph.append([cost, path, [first, second]])
pairs.append([first, second])
costs.append(cost)
paths.append(path)
return (graph, pairs, costs, paths, pure_goal, start, goal, maze1)
def setupGraph ():
import itertools
import copy
import read_maze
maze, visited, unavaiable, start, goal, rows, columns = read_maze.generate_maze()
goal.append(start)
print(len(goal))
paths = []
costs = []
pair = []
csgraph = [[0 for x in range(N)] for y in range(N)]
for first, second in itertools.combinations(goal,2):
visited1= copy.deepcopy(visited)
maze1 = copy.deepcopy(maze)
unavaiable1 = copy.deepcopy(unavaiable)
(maze1,cost,curridx,path) = Astar3(maze1,visited1,unavaiable1,first,second,rows,columns)
paths.append(path)
pair.append([first,second])
costs.append(cost)
print(len(costs))
return(costs)
def Astar():
import read_maze
import copy
maze,visited,unavaiable,start,goals,rows,columns = read_maze.generate_maze()
#costs = setupGraph()
points = len(goals)
#print(points)
#print(start,goals)
prev = [[[[-1, -1, -1] for x in range(2**points)] for y in range(columns)] for z in range(rows)] # record all the history
collected = '0' * points # collected is a vector that contains which dots have been collected
#print(collected)
collected_int = int(collected,2) # collected_int is the index of what the 3rd dimension value is
path = []
steps = 1
expanded = 0
goal = goals[0]
#print(goals)
heu_start = heuristic(start,goals)
mincost = [[[9999999 for x in range(2**points)] for y in range(columns)] for z in range(rows)]
frontier = [[start[0],start[1],heu_start,steps,collected]]
while(len(frontier)!=0):
node_now = min(frontier, key=lambda t: t[2])
#print(node_now)
steps = node_now[3]
#print(steps)
frontier.remove(node_now)
x = node_now[0]
y = node_now[1]
collected = node_now[4]
collected_int = int(collected,2)
#print(collected)
visited[x][y][collected_int] = 1
goal_here = copy.deepcopy(goals)
#print(goal_here)
for i in range(points):
if collected[i] == '1':
goal_here[i] = [-2,-2]
if ([x,y] in goal_here):
i = goal_here.index([x,y])
collected[i] = '1'
if collected == '1'*points:
print("solution found")
print(expanded)
pos_now = [x,y]
# print(pos_now)
# print(collected)
while ([pos_now,collected_int] != [start,0] ):
path.append(pos_now)
(pos_now,collected_int) = ([prev[pos_now[0]][pos_now[1]][collected_int][0],prev[pos_now[0]][pos_now[1]][collected_int][1]], prev[pos_now[0]][pos_now[1]][collected_int][2])
#print(pos_now)
maze[pos_now[0]][pos_now[1]] = '.'
maze[start[0]][start[1]] = "P"
path.reverse()
print(path)
length = len(path)
print("Total length of the path is " + str(length))
print("Number of expanded nodes is " + str(expanded))
# write it
with open('test_file.csv', 'w') as csvfile:
writer = csv.writer(csvfile)
for r in maze:
r = ''.join(str(word) for word in r)
print(r)
writer.writerow(r)
return
# loop over all possible nodes
if (unavaiable[x+1][y] == 0):
if [x + 1, y] in goal_here:
idx = goal_here.index([x+1,y])
collected_temp = copy.deepcopy(collected)
temp = list(collected_temp)
temp[idx] = '1'
collected_temp = "".join(temp)
collected_int_temp = int(collected_temp,2)
goal_temp = copy.deepcopy(goal_here)
goal_temp[idx] = [-2,-2]
if (steps + 1 < mincost[x+1][y][collected_int_temp]): # right
mincost[x+1][y][collected_int_temp] = steps+1
heu = heuristic([x+1,y],goal_temp)
prev[x+1][y][collected_int_temp] = [x,y,collected_int]
frontier.append([x+1,y,heu+steps+1,steps+1,collected_temp])
else:
if (steps + 1 < mincost[x+1][y ][collected_int]) : # right
mincost[x + 1][y][collected_int] = steps + 1
heu = heuristic([x + 1, y], goal_here)
prev[x+1][y][collected_int] = [x,y,collected_int]
frontier.append([x+1,y,heu+steps+1,steps+1,collected])
if (unavaiable[x-1][y] == 0):
if [x - 1, y] in goal_here:
idx = goal_here.index([x-1,y])
collected_temp = copy.deepcopy(collected)
temp = list(collected_temp)
temp[idx] = '1'
collected_temp = "".join(temp)
collected_int_temp = int(collected_temp,2)
goal_temp = copy.deepcopy(goal_here)
goal_temp[idx] = [-2, -2]
if (steps + 1 < mincost[x-1][y][collected_int_temp]): # left
mincost[x-1][y][collected_int_temp] = steps+1
heu = heuristic([x-1,y],goal_temp)
prev[x-1][y][collected_int_temp] = [x,y,collected_int]
frontier.append([x-1,y,heu+steps+1,steps+1,collected_temp])
else:
if (steps + 1 < mincost[x-1][y ][collected_int]) : # left
mincost[x - 1][y][collected_int] = steps + 1
heu = heuristic([x - 1, y], goal_here)
prev[x-1][y][collected_int] = [x,y,collected_int]
frontier.append([x-1,y,heu+steps+1,steps+1,collected])
if (unavaiable[x][y-1] == 0):
if [x, y-1] in goal_here:
idx = goal_here.index([x, y-1])
collected_temp = copy.deepcopy(collected)
temp = list(collected_temp)
temp[idx] = '1'
collected_temp = "".join(temp)
collected_int_temp = int(collected_temp,2)
goal_temp = copy.deepcopy(goal_here)
goal_temp[idx] = [-2, -2]
if (steps + 1 < mincost[x ][y-1][collected_int_temp]): # down
mincost[x][y-1][collected_int_temp] = steps + 1
heu = heuristic([x, y-1], goal_temp)
prev[x][y-1][collected_int_temp] = [x, y, collected_int]
frontier.append([x, y-1, heu + steps + 1, steps + 1, collected_temp])
else:
if (steps + 1 < mincost[x][y-1][collected_int]): # down
mincost[x][y-1][collected_int] = steps + 1
heu = heuristic([x, y-1], goal_here)
prev[x][y-1][collected_int] = [x, y, collected_int]
frontier.append([x, y-1, heu + steps + 1, steps + 1, collected])
if (unavaiable[x][y +1] == 0):
if [x, y + 1] in goal_here:
idx = goal_here.index([x, y + 1])
collected_temp = copy.deepcopy(collected)
temp = list(collected_temp)
#print(temp)
temp[idx] = '1'
collected_temp = "".join(temp)
collected_int_temp = int(collected_temp,2)
goal_temp = copy.deepcopy(goal_here)
goal_temp[idx] = [-2, -2]
if (steps + 1 < mincost[x][y + 1][collected_int_temp]): # up
mincost[x][y + 1][collected_int_temp] = steps + 1
heu = heuristic([x, y + 1], goal_temp)
prev[x][y + 1][collected_int_temp] = [x, y, collected_int]
frontier.append([x, y + 1, heu + steps + 1, steps + 1, collected_temp])
else:
if (steps + 1 < mincost[x][y +1][collected_int]): # up
mincost[x][y + 1][collected_int] = steps + 1
heu = heuristic([x, y + 1], goal_here)
prev[x][y + 1][collected_int] = [x, y, collected_int]
frontier.append([x, y + 1, heu + steps + 1, steps + 1, collected])
expanded += 1
def Greedy():
maze,visited,unavaiable,start,goals,rows,columns = read_maze.generate_maze()
points = len(goals)
prev = [[[[-1, -1, -1] for x in range(2**points)] for y in range(columns)] for z in range(rows)] # record all the history
collected = '0' * points # collected is a vector that contains which dots have been collected
collected_int = int(collected,2) # collected_int is the index of what the 3rd dimension value is
goal = goals[0]
print(start,goal)
path = []
steps = 1
expanded = 0
heu_start = heuristic(start,goals)
mincost = [[[9999999 for x in range(2**points)] for y in range(columns)] for z in range(rows)]
frontier = [[start[0],start[1],heu_start,steps,collected]]
explored = 0
while(len(frontier)!=0):
node_now = min(frontier, key=lambda t: t[2])
#print(node_now)
steps = node_now[3]
#print(steps)
frontier.remove(node_now)
x = node_now[0]
y = node_now[1]
collected = node_now[4]
collected_int = int(collected,2)
#print(collected)
#visited[x][y][collected_int] = 1
goal_here = copy.deepcopy(goals)
heu_now = heuristic([x,y],goals)
#print(goal_here)
for i in range(points):
if collected[i] == '1':
goal_here[i] = [-2,-2]
if ([x,y] in goal_here):
i = goal_here.index([x,y])
collected[i] = '1'
if collected == '1'*points:
print("solution found")
print(expanded)
pos_now = [x,y]
# print(pos_now)
# print(collected)
goalnames = ['0','1','2','3','4','5','6','7','8','9']
goalnames.extend(['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t'])
goalnames.extend(['u','v','w','x','y','z'])
goalnames.extend(['A','B','C','D','E','F','G','H','I','J','K','L','M','N','O','P','Q','R','S','T','U','V','W'])
goalnames.extend(['X','Y','Z'])
goalcounter = 1
while ([pos_now,collected_int] != [start,0] ):
path.append(pos_now)
print(pos_now)
(pos_now,collected_int) = ([prev[pos_now[0]][pos_now[1]][collected_int][0],prev[pos_now[0]][pos_now[1]][collected_int][1]], prev[pos_now[0]][pos_now[1]][collected_int][2])
#print(pos_now)
if pos_now in goals:
if not maze[pos_now[0]][pos_now[1]] in goalnames:
maze[pos_now[0]][pos_now[1]] = goalnames[points-goalcounter]
goalcounter += 1
else:
if points == 1:
maze[pos_now[0]][pos_now[1]] = '.'
maze[start[0]][start[1]] = "P"
path.reverse()
print(path)
length = len(path)
print("Total length of the path is " + str(length))
print("Number of expanded nodes is " + str(expanded))
# write it
with open('test_file.csv', 'w') as csvfile:
writer = csv.writer(csvfile)
for r in maze:
r = ''.join(str(word) for word in r)
print(r)
writer.writerow(r)
return
# loop over all possible nodes
if (unavaiable[x+1][y] == 0):
if [x + 1, y] in goal_here:
idx = goal_here.index([x+1,y])
collected_temp = copy.deepcopy(collected)
temp = list(collected_temp)
temp[idx] = '1'
collected_temp = "".join(temp)
collected_int_temp = int(collected_temp,2)
goal_temp = copy.deepcopy(goal_here)
goal_temp[idx] = [-2,-2]
if (steps + 1 < mincost[x+1][y][collected_int_temp]): # right
mincost[x+1][y][collected_int_temp] = steps+1
heu = heuristic([x+1,y],goal_temp)
prev[x+1][y][collected_int_temp] = [x,y,collected_int]
frontier.append([x+1,y,heu,steps+1,collected_temp])
else:
if (steps + 1 < mincost[x+1][y ][collected_int]) : # right
mincost[x + 1][y][collected_int] = steps + 1
heu = heuristic([x + 1, y], goal_here)
prev[x+1][y][collected_int] = [x,y,collected_int]
frontier.append([x+1,y,heu,steps+1,collected])
if (unavaiable[x-1][y] == 0):
if [x - 1, y] in goal_here:
idx = goal_here.index([x-1,y])
collected_temp = copy.deepcopy(collected)
temp = list(collected_temp)
temp[idx] = '1'
collected_temp = "".join(temp)
collected_int_temp = int(collected_temp,2)
goal_temp = copy.deepcopy(goal_here)
goal_temp[idx] = [-2, -2]
if (steps + 1 < mincost[x-1][y][collected_int_temp]): # left
mincost[x-1][y][collected_int_temp] = steps+1
heu = heuristic([x-1,y],goal_temp)
prev[x-1][y][collected_int_temp] = [x,y,collected_int]
frontier.append([x-1,y,heu,steps+1,collected_temp])
else:
if (steps + 1 < mincost[x-1][y ][collected_int]) : # left
mincost[x - 1][y][collected_int] = steps + 1
heu = heuristic([x - 1, y], goal_here)
prev[x-1][y][collected_int] = [x,y,collected_int]
frontier.append([x-1,y,heu,steps+1,collected])
if (unavaiable[x][y-1] == 0):
if [x, y-1] in goal_here:
idx = goal_here.index([x, y-1])
collected_temp = copy.deepcopy(collected)
temp = list(collected_temp)
temp[idx] = '1'
collected_temp = "".join(temp)
collected_int_temp = int(collected_temp,2)
goal_temp = copy.deepcopy(goal_here)
goal_temp[idx] = [-2, -2]
if (steps + 1 < mincost[x ][y-1][collected_int_temp]): # down
mincost[x][y-1][collected_int_temp] = steps + 1
heu = heuristic([x, y-1], goal_temp)
prev[x][y-1][collected_int_temp] = [x, y, collected_int]
frontier.append([x, y-1, heu, steps + 1, collected_temp])
else:
if (steps + 1 < mincost[x][y-1][collected_int]): # down
mincost[x][y-1][collected_int] = steps + 1
heu = heuristic([x, y-1], goal_here)
prev[x][y-1][collected_int] = [x, y, collected_int]
frontier.append([x, y-1, heu, steps + 1, collected])
if (unavaiable[x][y +1] == 0):
if [x, y + 1] in goal_here:
idx = goal_here.index([x, y + 1])
collected_temp = copy.deepcopy(collected)
temp = list(collected_temp)
#print(temp)
temp[idx] = '1'
collected_temp = "".join(temp)
collected_int_temp = int(collected_temp,2)
goal_temp = copy.deepcopy(goal_here)
goal_temp[idx] = [-2, -2]
if (steps + 1 < mincost[x][y + 1][collected_int_temp]): # up
mincost[x][y + 1][collected_int_temp] = steps + 1
heu = heuristic([x, y + 1], goal_temp)
prev[x][y + 1][collected_int_temp] = [x, y, collected_int]
frontier.append([x, y + 1, heu, steps + 1, collected_temp])
else:
if (steps + 1 < mincost[x][y +1][collected_int]): # up
mincost[x][y + 1][collected_int] = steps + 1
heu = heuristic([x, y + 1], goal_here)
prev[x][y + 1][collected_int] = [x, y, collected_int]
frontier.append([x, y + 1, heu, steps + 1, collected])
expanded += 1
explored += 1