if i % total_slices == my_slice:
clique = cliques[i]
print "starting %d %s"%(i, str(clique))
cycle_mapping = map(lambda c: (c[0], tuple(cycles[c[1]])), clique)
decider = InequalityDecider()
decider.add_cycle_mapping(problem_def, cycle_mapping)
if decider.satisfiable():
print " satisfiable"
graphs = build_potential_graphs(cycle_mapping)
good_states = list()
for state in set(map(lambda s: string.join(s, ""), itertools.permutations(["a","a","b","b","c"]))):
try:
decider = InequalityDecider()
decider.add_cycle_mapping(problem_def, cycle_mapping)
for input, graph_plus in graphs.iteritems():
path = nx.shortest_path(graph_plus[0], state, graph_plus[1])
for f, t in zip(path[:-1], path[1:]):
decider.add_transition(f, t, input)
if decider.satisfiable():
good_states.append(state)
except nx.exception.NetworkXNoPath:
pass
if len(good_states) > 0:
print " have one"
result.append( (clique, good_states) )
with open("%s/initializable_cliques/%d/%d.pickle"%(basedir, clique_size, my_slice), "w") as f:
pickle.dump(result, f)
def build_decider(prefix):
basedecider = InequalityDecider()
basedecider.add_cycle_mapping(problem_def, cycle_mapping)
for transition in prefix:
basedecider.add_transition(*transition)
return basedecider.freeze()
