def graphbased_trueskill(g,iter_times = 15,n_sigma = 3,threshold = 0.95):
from s_c_c import scc_nodes_edges
relative_scores = trueskill_ratings(list(g.edges()),iter_times = iter_times,n_sigma = n_sigma,threshold = threshold)
scc_nodes,scc_edges,nonscc_nodes,nonscc_edges = scc_nodes_edges(g)
print("scc")
scc_accu = measure_pairs_agreement(scc_edges,relative_scores)
print("non-scc")
nonscc_accu = measure_pairs_agreement(nonscc_edges,relative_scores)
print("scc accu: %0.4f, nonscc accu: %0.4f" % (scc_accu,nonscc_accu))
return relative_scores
def trueskill_ratings(pairs,iter_times = 15,n_sigma = 3,threshold = 0.85):
start = datetime.now()
players = {}
for i in xrange(iter_times):
#print("========= Trueskill iteration times: %d =========" % (i + 1))
players = compute_trueskill(pairs,players)
relative_scores = get_players_score(players,n_sigma = n_sigma)
accu = measure_pairs_agreement(pairs,relative_scores)
#print("agreement of pairs: %0.4f" % accu)
if accu >= threshold:
return relative_scores
end = datetime.now()
time_used = end - start
print("time used in computing true skill: %0.4f s, iteration time is: %i" % ((time_used.seconds),(i+1)))
return relative_scores