def generate(self):
print 'Generating...'
global size, heuristicNo
state = generateSlidingBlockGrid(size)
print 'Solving...'
global sb
sb = SlidingBlock(state)
global search
global lastAction
lastAction = None
if heuristicNo == 1:
search = astar_search(sb, lambda x: h1(x))
elif heuristicNo == 2:
search = astar_search(sb, lambda x: h2(x))
elif heuristicNo == 3:
search = astar_search(sb, lambda x: h3(x))
elif heuristicNo == 4:
search = astar_search(sb, lambda x: h4(x))
if search == None:
self.generate()
return
print "Actions to solution:", len(search.solution())
if (len(search.solution())):
lastAction = 0
else:
lastAction = None
grid.reset(state)
return
def step(self):
global lastAction, search, sb
if lastAction != None:
state = sb.result(grid.state, search.solution()[lastAction])
lastAction += 1
if (not lastAction < len(search.solution())):
lastAction = None
grid.reset(state)
return True
return False
def step(self):
global lastAction, search, sb
if lastAction != None:
state = sb.result(grid.state, search.solution()[lastAction])
lastAction += 1
if (not lastAction < len(search.solution())):
lastAction = None
grid.reset(state)
return True
return False
def generate(self):
print 'Generating...'
global size, heuristicNo
state = generateSlidingBlockGrid(size)
print 'Solving...'
global sb
sb = SlidingBlock(state)
global search
global lastAction
lastAction = None
if heuristicNo == 1:
search = astar_search(sb, lambda x : h1(x))
elif heuristicNo == 2:
search = astar_search(sb, lambda x : h2(x))
elif heuristicNo == 3:
search = astar_search(sb, lambda x : h3(x))
elif heuristicNo == 4:
search = astar_search(sb, lambda x : h4(x))
if search == None:
self.generate()
return
print "Actions to solution:", len(search.solution())
if (len(search.solution())):
lastAction = 0
else:
lastAction = None
grid.reset(state)
return
def solve(self):
for i in range(len(search.solution())):
self.after(i*500, self.step)
return
def solve(self):
for i in range(len(search.solution())):
self.after(i * 500, self.step)
return