def valid_delete(self, x, y, H, na_y_x):
if self.knowledge is not None:
for h in H:
if self.knowledge.is_forbidden(x, h):
return False
if self.knowledge.is_forbidden(y, h):
return False
diff = set(na_y_x)
diff = diff - H
return graph_util.is_clique(self.graph, diff)
def valid_insert(self, x, y, T, na_y_x):
union = set(T)
if self.knowledge is not None:
if self.knowledge.is_forbidden(x, y):
return False
for node in union:
if self.knowledge.is_forbidden(node, y):
return False
if na_y_x != set([]):
union.update(na_y_x)
return graph_util.is_clique(self.graph, union) and \
not graph_util.exists_unblocked_semi_directed_path(
self.graph, y, x, union, self.cycle_bound)
def outer_loop():
previous_cliques = set() # set of sets of nodes
previous_cliques.add(frozenset())
new_cliques = set() # set of sets of nodes
for i in range(len_T + 1):
choices = itertools.combinations(range(len_T), i)
choices2 = itertools.combinations(range(len_T), i)
# print("All choices: ", list(choices2), " TNeighbors: ", t_neighbors)
for choice in choices:
T = frozenset([t_neighbors[k] for k in choice])
# print("Choice:", T)
union = set(na_y_x)
union.update(T)
found_a_previous_clique = False
for clique in previous_cliques:
# basically if clique is a subset of union
if union >= clique:
found_a_previous_clique = True
break
if not found_a_previous_clique:
# Break out of the outer for loop
return
if not graph_util.is_clique(self.graph, union):
continue
new_cliques.add(frozenset(union))
bump = self.insert_eval(a, b, T, na_y_x)
# print("Evaluated arrow " + str(a) + " -> " + str(b) + " with T: " + str(T) + " and bump: " + str(bump));
if bump > 0:
self.add_arrow(a, b, na_y_x, T, bump)
previous_cliques = new_cliques
new_cliques = set()
def calculate_arrows_forward(self, a, b):
# print("Calculate Arrows Forward: " + str(a) + " " + str(b))
if b not in self.effect_edges_graph[a] and self.mode == "heuristic":
print("Returning early...")
return
if self.knowledge is not None and self.knowledge.is_forbidden(a, b):
return
# print("Get neighbors for " + str(b) + " returns " + str(graph_util.neighbors(self.graph, b)))
self.stored_neighbors[b] = graph_util.neighbors(self.graph, b)
na_y_x = graph_util.get_na_y_x(self.graph, a, b)
_na_y_x = list(na_y_x)
if not graph_util.is_clique(self.graph, na_y_x):
return
t_neighbors = list(graph_util.get_t_neighbors(self.graph, a, b))
# print("tneighbors for " + str(a) + ", " + str(b) + " returns " + str(t_neighbors))
len_T = len(t_neighbors)
def outer_loop():
previous_cliques = set() # set of sets of nodes
previous_cliques.add(frozenset())
new_cliques = set() # set of sets of nodes
for i in range(len_T + 1):
choices = itertools.combinations(range(len_T), i)
choices2 = itertools.combinations(range(len_T), i)
# print("All choices: ", list(choices2), " TNeighbors: ", t_neighbors)
for choice in choices:
T = frozenset([t_neighbors[k] for k in choice])
# print("Choice:", T)
union = set(na_y_x)
union.update(T)
found_a_previous_clique = False
for clique in previous_cliques:
# basically if clique is a subset of union
if union >= clique:
found_a_previous_clique = True
break
if not found_a_previous_clique:
# Break out of the outer for loop
return
if not graph_util.is_clique(self.graph, union):
continue
new_cliques.add(frozenset(union))
bump = self.insert_eval(a, b, T, na_y_x)
# print("Evaluated arrow " + str(a) + " -> " + str(b) + " with T: " + str(T) + " and bump: " + str(bump));
if bump > 0:
self.add_arrow(a, b, na_y_x, T, bump)
previous_cliques = new_cliques
new_cliques = set()
outer_loop()