def test_zero_clusters(self):
io_graph = DenGraphIO(base_graph=DistanceGraph(
nodes=[1, 2, 3, 4], distance=DeltaDistance(), symmetric=True),
cluster_distance=1,
core_neighbours=5)
with self.assertRaises(ValueError):
davies_bouldin_score(io_graph.clusters, io_graph.graph)
def test_two_cluster(self):
io_graph = DenGraphIO(base_graph=DistanceGraph(
nodes=[1, 2, 3, 4, 5, 6, 13, 14, 15, 16, 17, 18],
distance=DeltaDistance(),
symmetric=True),
cluster_distance=5,
core_neighbours=5)
self.assertEqual(
.25, davies_bouldin_score(io_graph.clusters, io_graph.graph))
def test_one_cluster(self):
io_graph = DenGraphIO(
base_graph=DistanceGraph(
nodes=[1, 2, 3, 4, 5, 6],
distance=DeltaDistance(),
symmetric=True),
cluster_distance=5,
core_neighbours=5
)
self.assertEqual(-1, silhouette_score(io_graph.clusters, io_graph.graph))
def test_two_cluster(self):
io_graph = DenGraphIO(
base_graph=DistanceGraph(
nodes=[1, 2, 3, 4, 5, 6, 13, 14, 15, 16, 17, 18],
distance=DeltaDistance(),
symmetric=True),
cluster_distance=5,
core_neighbours=5
)
self.assertAlmostEqual(123.4, calinski_harabasz_score(io_graph.clusters, io_graph.graph), 1)
def test_one_cluster(self):
io_graph = DenGraphIO(
base_graph=DistanceGraph(
nodes=[1, 2, 3, 4, 5, 6],
distance=DeltaDistance(),
symmetric=True),
cluster_distance=5,
core_neighbours=5
)
with self.assertRaises(ValueError):
calinski_harabasz_score(io_graph.clusters, io_graph.graph)
def test_get(self):
cluster = DenGraphCluster(graph=DistanceGraph(
nodes=[1, 2, 3, 4], distance=DeltaDistance(), symmetric=True))
with self.assertRaises(dengraph.graph.NoSuchEdge):
cluster[1:2]
cluster.categorize_node(1, cluster.CORE_NODE)
with self.assertRaises(dengraph.graph.NoSuchEdge):
cluster[1:2]
cluster.categorize_node(2, cluster.BORDER_NODE)
self.assertEqual(1, cluster[1:2])
with self.assertRaises(dengraph.graph.NoSuchEdge):
cluster[3:2]
def setUp(self):
self.io_graph = DenGraphIO(base_graph=DistanceGraph(
nodes=[1, 2, 3, 4], distance=DeltaDistance(), symmetric=True),
cluster_distance=1,
core_neighbours=5)
self.one_cluster_graph = DenGraphIO(base_graph=DistanceGraph(
nodes=[(1, 1), (1, 2), (1, 3), (1, 4), (1, 5), (1, 6), (2, 1),
(2, 2), (2, 3), (2, 4), (2, 5), (2, 6)],
distance=ListDistance(),
symmetric=True),
cluster_distance=.1,
core_neighbours=5)
def test_simple(self):
io_graph = DenGraphVIO(
base_graph=DistanceGraph(nodes=[1, 2, 3, 4, 5, 6],
distance=DeltaDistance(),
symmetric=True),
cluster_distance=5,
core_neighbours=5)
cluster, distance = next(io_graph.probe(1))
self.assertEqual(2.5, distance)
io_graph[7] = {}
cluster, distance = next(io_graph.probe(1))
# expecting that algorithm uses cached mean
self.assertEqual(2.5, distance)
def test_creation(self):
io_graph = DenGraphVIO(
base_graph=DistanceGraph(nodes=[1, 2, 3, 4, 5, 6],
distance=DeltaDistance(),
symmetric=True),
cluster_distance=5,
core_neighbours=5)
self.assertIsNotNone(io_graph)
literal = textwrap.dedent("""
1,2,3,4,5,6
0,1,1,1,1,1
1,0,1,1,1,1
1,1,0,1,1,1
1,1,1,0,1,1
1,1,1,1,0,1
1,1,1,1,1,0
""".strip())
with self.assertRaises(dengraph.distance.NoDistanceSupport):
io_graph = DenGraphVIO(
base_graph=dengraph.graphs.graph_io.csv_graph_reader(
literal.splitlines(), symmetric=True),
cluster_distance=5,
core_neighbours=5)
def test_mean_iterator(self):
distance = DeltaDistance()
self.assertEqual(4.5, distance.mean(range(10)))
def test_median_exception_with_default(self):
distance = DeltaDistance()
self.assertIsNone(distance.median(default=None))
def test_median_exception(self):
distance = DeltaDistance()
with self.assertRaises(ValueError):
distance.median()
def test_median_args(self):
distance = DeltaDistance()
self.assertEqual(6, distance.median(10, 9, 8, 7, 6, 5, 4, 3, 2, 1))
self.assertEqual(6, distance.median(10, 9, 8, 7, 6, 5, 4, 3, 2))
def test_median_iterator(self):
distance = DeltaDistance()
self.assertEqual(6, distance.median(range(10, 0, -1)))
self.assertEqual(6, distance.median(range(10, 1, -1)))
def test_mean_args(self):
distance = DeltaDistance()
self.assertEqual(4.5, distance.mean(0, 1, 2, 3, 4, 5, 6, 7, 8, 9))