def cycles_compatible(left, right): if left[1] == right[1]: # same cycle, different inputs, this cannot be part of a consistent mapping return False elif len(set(cycles[left[1]]).intersection(set(cycles[right[1]]))) == 0: # disjoint cycles are always locally compatible return True elif left[0] == right[0]: # this is an adjoint cycle, it can only be compatible if the intersection of states is empty # therefore it is not compatible return False else: # there is some overlap, we need to evaluate pairwise consistency explicitly decider = InequalityDecider() decider.add_cycle(problem_def, left[0], cycles[left[1]]) decider.add_cycle(problem_def, right[0], cycles[right[1]]) return decider.satisfiable()
all_states = set(map(lambda s: string.join(s, ""), itertools.permutations(["a","a","b","b","c"]))) other_states = all_states-set(itertools.chain(*my_cycles)) for input in inputs: graphs[input] = (decider.build_transition_graph(my_cycles, other_states, input), my_cycles[0][0]) return graphs result = list() for i in xrange(len(cliques)): 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)