return None
with open(datafile, 'r') as f:
T = Ensemble()
for line in f:
line = line.strip()
timestamp, v1, v2 = line.split('\t', 2)
if v1 != v2:
T.add_edge(timestamp, int(v1), int(v2))
else:
T.add_node(int(v1))
with open(results_folder + '/' + datafile + '.summary', 'w+') as f:
edges = [g.size() for g in T.get_all_static_graphs()]
summary = '%d\t%d\t%d\t%d\t%d' % (T.get_num_of_timestamps(), T.order(),
min(edges), max(edges), T.size())
print('Graph Summary: %s' % summary)
f.write(summary)
ssd_hyperedges_in_sigma_range = []
for sigma in sigma_range:
print('Computing %s-sigma-hyperedges' % sigma)
hyperedges = T.maximal_lam_sigma_ssd_ucs(sigma)
ssd_hyperedges = []
for hyperedge in hyperedges:
if (len(hyperedge) > 2):
hyperedge = sorted(hyperedge)
hyperedge.append(
T.compute_scaled_subgraph_divergence(list(hyperedge)))
ssd_hyperedges.append(tuple(hyperedge))
print('Updated top %d hyperedges' % k)
return None
with open(datafile, 'r') as f:
T = Ensemble()
for line in f:
line = line.strip()
timestamp, v1, v2 = line.split('\t', 2)
if v1 != v2:
T.add_edge(timestamp, int(v1), int(v2))
else:
T.add_node(int(v1))
with open(results_folder + '/' + datafile + '.summary', 'w+') as f:
edges = [g.size() for g in T.get_all_static_graphs()]
summary = '%d\t%d\t%d\t%d\t%d' % (T.get_num_of_timestamps(), T.order(), min(edges), max(edges), T.size())
print('Graph Summary: %s' % summary)
f.write(summary)
ssd_hyperedges_in_sigma_range = []
for sigma in sigma_range:
print('Computing %s-sigma-hyperedges' % sigma)
hyperedges = T.maximal_sigma_ssd_ucs(sigma)
ssd_hyperedges = []
for hyperedge in hyperedges:
if (len(hyperedge)>2):
hyperedge = sorted(hyperedge)
hyperedge.append(T.compute_scaled_subgraph_divergence(list(hyperedge)))
ssd_hyperedges.append(tuple(hyperedge))
ssd_hyperedges = sorted(ssd_hyperedges, key=lambda x: x[-1])
print('Found %d %s-sigma-hyperedges' % (len(ssd_hyperedges), sigma))
