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a.py
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a.py
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import sys
from optparse import OptionParser
import math
from struct import pack
import heapq
class Solver:
def __init__(self, n):
self.N = n
self.L = n * n
self.GOAL = range(1, self.L)
self.GOAL.append(0)
# slide rules
self.SR = {}
for i in range(self.L):
s = []
if i - self.N >= 0:
s.append(i - self.N)
if (i % self.N) - 1 >= 0:
s.append(i - 1)
if (i % self.N) + 1 < self.N:
s.append(i + 1)
if i + self.N < self.L:
s.append(i + self.N)
self.SR[i] = s
# queue
self.queue = []
self.enqueued = {}
# verbose
#self.verbose = 104999
self.verbose = 8963
# h
self.w = 1
self.h = self.heuristics
def is_solvable(self, tiles):
x = 0
for p in range(len(tiles)):
a = tiles[p]
if a < 2 :
continue
for b in tiles[p:]:
if b == 0:
continue
if a > b:
x = x + 1
return (x & 1) == 0
def neighbors(self, tiles):
n = []
a = tiles.index(0)
for b in self.SR[a]:
n.append(self.swap(list(tiles), a, b))
return n
def swap(self, tiles, a, b):
tiles[a], tiles[b] = tiles[b], tiles[a]
return tiles
def display(self, tiles):
for i in range(self.L):
if tiles[i]:
print '%(n)#2d' % {'n': tiles[i]},
else:
print ' ',
if i % self.N == self.N - 1:
print
def enqueue(self, state):
(tiles, parent, h, g) = state
if self.verbose > 0 and len(self.enqueued) % self.verbose == self.verbose - 1:
print " -->", len(self.enqueued), g
f = h * self.w + g;
heapq.heappush(self.queue, (f, state))
def dequeue(self):
if len(self.queue) <= 0:
return None
(f, state) = heapq.heappop(self.queue)
return state
def heuristics(self, tiles):
return 0;
def manhattan(self, tiles):
h = 0
for i in range(self.L):
n = tiles[i]
if n == 0:
continue
h += int(abs(n - 1 - i) / self.N) + (abs(n - 1 - i) % self.N)
return h
def hamming(self, tiles):
h = 0
for i in range(self.L):
n = tiles[i]
if n > 0 and n - 1 != i:
h += 1
return h
def solve(self, initial):
if not self.is_solvable(initial):
return None
state = (initial, None, self.h(initial), 0);
if initial == self.GOAL:
return state
self.enqueue(state)
while True:
state = self.dequeue()
if (not state):
break
(tiles, parent, h, g) = state
neighbors = self.neighbors(tiles)
for n_tiles in neighbors:
if n_tiles == self.GOAL:
return (n_tiles, state, 0, g + 1)
packed = pack(self.L*'B', *n_tiles)
if (packed in self.enqueued):
continue;
self.enqueued[packed] = True
n_state = (n_tiles, state, self.h(n_tiles), g + 1)
self.enqueue(n_state)
def main(options, args):
initial = []
if args:
for n in args:
initial.append(int(n))
else:
initial = [8,7,6,5,4,3,2,1,0]
solver = Solver(int(math.sqrt(len(initial))))
solver.verbose = int(options.verbose)
solver.w = float(options.weight)
if int(options.function) == 1:
solver.h = solver.hamming
elif int(options.function) == 2:
solver.h = solver.manhattan
state = solver.solve(initial)
if not state:
print "No solution possible"
return 1
solution = []
while state:
(tiles, parent, h, g) = state
solution.insert(0, tiles)
state = parent
n = 0
for tiles in solution:
print "#", n
solver.display(tiles)
print
n += 1
print "Number of states enqueued =", len(solver.enqueued)
return 0
if __name__ == '__main__':
parser = OptionParser(usage="usage: %prog [options] [tile] [tile] [tiles ...]")
parser.add_option("-v", "--verbose", metavar="<level>",
default=8963)
parser.add_option("-f", "--function", metavar="<fid>",
help="heuristics function. 1 for hamming, 2 for manhattan [default: None as breadth first]",
default=0)
parser.add_option("-w", "--weight", metavar="<n>",
help="weighting of the heuristics function [default: 1]",
default=1)
(options, args) = parser.parse_args()
sys.exit(main(options, args))