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