def remove_cycle_edges_heuristic(g, edges_score, nodetype=int):
from remove_self_loops import remove_self_loops_from_graph
self_loops = remove_self_loops_from_graph(g)
edges_to_be_removed = scc_based_to_remove_cycle_edges_iterately(g, edges_score)
edges_to_be_removed = list(set(edges_to_be_removed))
return edges_to_be_removed + self_loops
def remove_cycle_edges_heuristic(graph_file,edges_score,nodetype = int): g = nx.read_edgelist(graph_file,create_using = nx.DiGraph(),nodetype = nodetype) from remove_self_loops import remove_self_loops_from_graph self_loops = remove_self_loops_from_graph(g) edges_to_be_removed = scc_based_to_remove_cycle_edges_iterately(g,edges_score) edges_to_be_removed = list(set(edges_to_be_removed)) return edges_to_be_removed+self_loops
def remove_cycle_edges_BF_iterately(g,
players,
is_Forward=True,
score_name="socialagony"):
from remove_self_loops import remove_self_loops_from_graph
self_loops = remove_self_loops_from_graph(g)
edges_to_be_removed = scc_based_to_remove_cycle_edges_iterately(
g, players, is_Forward)
edges_to_be_removed = list(set(edges_to_be_removed))
return edges_to_be_removed + self_loops
def scc_based_to_remove_cycle_edges_iterately(g, nodes_score):
from remove_self_loops import remove_self_loops_from_graph
self_loops = remove_self_loops_from_graph(g)
big_sccs = get_big_sccs(g)
scc_nodes_score_dict = scores_of_nodes_in_scc(big_sccs, nodes_score)
edges_to_be_removed = []
if len(big_sccs) == 0:
print("After removal of self loop edgs: %s" % nx.is_directed_acyclic_graph(g))
return self_loops
remove_cycle_edges_by_agony_iterately(big_sccs, scc_nodes_score_dict, edges_to_be_removed)
# print(" # edges to be removed: %d" % len(edges_to_be_removed))
return edges_to_be_removed + self_loops
def remove_cycle_edges_by_mfas(graph_file):
g = nx.read_edgelist(graph_file,create_using = nx.DiGraph(),nodetype = int)
from remove_self_loops import remove_self_loops_from_graph
self_loops = remove_self_loops_from_graph(g)
scc_nodes,_,_,_ = scc_nodes_edges(g)
degree_dict = get_nodes_degree_dict(g,scc_nodes)
sccs = get_big_sccs(g)
if len(sccs) == 0:
print("After removal of self loop edgs: %s" % nx.is_directed_acyclic_graph(g))
return self_loops
edges_to_be_removed = []
import timeit
t1 = timeit.default_timer()
greedy_local_heuristic(sccs,degree_dict,edges_to_be_removed)
t2 = timeit.default_timer()
print("mfas time usage: %0.4f s" % (t2 - t1))
edges_to_be_removed = list(set(edges_to_be_removed))
g.remove_edges_from(edges_to_be_removed)
edges_to_be_removed += self_loops
edges_to_be_removed_file = graph_file[:len(graph_file)-6] + "_removed_by_mfas.edges"
write_pairs_to_file(edges_to_be_removed,edges_to_be_removed_file)
return edges_to_be_removed
