def test_wrong_sizes(self):
nodes = [4, 4, 16, 32, 32, 64, 64, 256, 64, 256, 256]
try:
gc.MultiResGraphClustering(self.G, nodes, k=4)
self.fail()
except:
pass
def test_cont_nodes(self):
self.G_params['type_z'] = ds.RAND
G = ds.create_graph(self.G_params, seed=SEED)
cluster = gc.MultiResGraphClustering(G, self.nodes_enc, k=4)
out = np.unique(cluster.labels[0])
for U in cluster.Us:
out = U.dot(out)
self.assertTrue(np.array_equal(out, cluster.labels[0]))
def compute_clusters(G, alg, k):
sizes = []
Us = []
hier_As = []
for i in range(N_EXPS):
cluster = gc.MultiResGraphClustering(G, EXPS[i]['nodes'], k, alg)
sizes.append(cluster.sizes)
Us.append(cluster.Us)
hier_As.append(cluster.As)
return sizes, Us, hier_As
def setUp(self):
np.random.seed(SEED)
G_params = {}
G_params['type'] = ds.SBM
G_params['N'] = 256
G_params['k'] = 4
G_params['p'] = 0.15
G_params['q'] = 0.01 / 4
G_params['type_z'] = ds.RAND
G = ds.create_graph(G_params, seed=SEED)
nodes_dec = [4, 16, 32, 64, 256]
self.N = nodes_dec[-1]
self.k = nodes_dec[0]
self.cluster = gc.MultiResGraphClustering(G, nodes_dec, k=4)
self.model = Sequential()
for i, U in enumerate(self.cluster.Us):
self.add_layer(MeanUps(U, self.cluster.As[i], gamma=1))
def compute_clusters(G, root_clust):
sizes = []
Us = []
As = []
for exp in EXPERIMENTS:
if not isinstance(exp, dict):
sizes.append(None)
Us.append(None)
As.append(None)
continue
exp['t'][-1] = G.N
cluster = gc.MultiResGraphClustering(G, exp['t'], root_clust)
sizes.append(cluster.sizes)
Us.append(cluster.Us)
As.append(cluster.As)
return sizes, Us, As
def compute_clusters(k):
sizes = []
Us = []
hier_As = []
for i in range(N_SCENARIOS):
if EXPS[i][0] is None:
nodes = [t[-1]] * len(t)
else:
nodes = t
cluster = gc.MultiResGraphClustering(G,
nodes,
k,
alg,
method=c_method,
up_method=EXPS[i][0])
sizes.append(cluster.sizes)
Us.append(cluster.Us)
hier_As.append(cluster.As)
return sizes, Us, hier_As
def setUp(self):
G_params = {}
G_params['type'] = ds.SBM
G_params['N'] = 256
G_params['k'] = 4
G_params['p'] = 0.15
G_params['q'] = 0.01 / 4
G_params['type_z'] = ds.RAND
G = ds.create_graph(G_params, seed=SEED)
nodes = [4, 16, 32, 256]
self.K = 3
cluster = gc.MultiResGraphClustering(G, nodes, k=4)
self.ups = []
self.As = []
self.Us = []
for i in range(len(cluster.Us)):
self.ups.append(GFUps(cluster.Us[i], cluster.As[i], self.K))
self.As.append(Tensor(cluster.As[i]))
self.Us.append(Tensor(cluster.Us[i]))
def test_all_sizes_repeated(self):
nodes = [256, 256, 256]
cluster = gc.MultiResGraphClustering(self.G, nodes, k=4)
self.assertEqual(len(nodes), len(cluster.sizes))
for U in cluster.Us:
self.assertEqual(U, None)
def test_repeated_sizes(self):
nodes = [4, 4, 16, 32, 32, 64, 256, 256, 256]
cluster = gc.MultiResGraphClustering(self.G, nodes, k=4)
self.assertEqual(len(nodes), len(cluster.sizes))
self.assertEqual(len(nodes) - 1, len(cluster.Us))