def test_import_and_export(self):
g = DGraph.read_dot(join(project_root(), "./dot/example.dot"))
self.assertIsNotNone(g, "import of example.dot failed")
g.write_dot(join(project_root(), "./tests/dot_export/example.dot"))
g2 = DGraph.read_dot(
join(project_root(), "./tests/dot_export/example.dot"))
self.assertIsNotNone(g2, "import of exported example.dot failed")
self.assertEqual(len(g2.nodes()), 24,
"wrong number of nodes after export")
assert nx.algorithms.is_isomorphic(g.dgraph, g2.dgraph)
def test_minimum_cut(self):
print("Testing MinimumCut")
g2 = DGraph.read_dot(join(project_root(), "dot/g2.dot"))
algo_result = minimum_cut.MinimumCut().cluster(g2)
self.assertIsClusterRepresentation(
algo_result,
"MinimumCut result is not a lists of clusters when testing g2.dot")
def test_labeling(self):
g = DGraph.read_dot(join(project_root(),
"dot/java.util.Formatter.dot"))
den = partition.partition(g, SpectralCluster.SpectralCluster(),
stop_criteria.SizeCriteria(4))
labeler = RandomWalkLabeler.RandomWalkLabeler(g, den, 'Both')
labeler.label()
def test_labeling(self):
g = DGraph.read_dot(join(project_root(), "dot/large/ktails4.dot"))
den = partition.partition(g, SpectralCluster.SpectralCluster(),
stop_criteria.SizeCriteria(4))
labeler = PathLabeler.PathLabeler(g, den, labeling_on_type.EDGES)
labeler.label()
def test_import_zip(self):
g = DGraph.read_dot(join(project_root(), "./dot/zip.dot"))
self.assertIsNotNone(g.dgraph, "import of zip.dot failed")
self.assertEqual(len(g.nodes()), 5,
"wrong number of nodes after import")
self.assertEqual(len(g.edges()), 9,
"wrong number of edges after import")
def test_kerningham_lin(self):
g = DGraph.read_dot(
os.path.join(project_root(), "dot/cvs.net.mutated.dot"))
KL = KernighanLinCluster()
dendrogram = partition(g,
clustering_algo=KL,
stop_criterion=SizeCriteria(3))
print("foo")
def test_branch_and_bound(self):
print("Testing Branch and Bound")
g2 = DGraph.read_dot(join(project_root(), "dot/g2.dot"))
algo_result = BranchAndBound.BranchAndBoundCluster().cluster(g2)
self.assertIsClusterRepresentation(
algo_result,
"BnB result is not a lists of clusters when testing g2.dot")
expected = clusters_to_set([['1', '2', '3', '4'], ['5', '6', '7']])
assert clusters_to_set(
algo_result) == expected, "BnB did not work as expected on g2.dot"
def test_partition():
den = None
g = DGraph.read_dot(os.path.join(project_root(), "dot/weighted_g2.dot"))
print("testing partition on g2.dot for threshold=4:")
den = partition(g, SpectralCluster.SpectralCluster(), SizeCriteria(4))
assert len(den.node_list) == 10
print("testing partition on g2.dot for threshold=2:")
den = partition(g, SpectralCluster.SpectralCluster(), SizeCriteria(2))
print('expected:', len(den.node_list))
assert len(den.node_list) == 13
def test_Kmeans(self):
print("Testing Kmeans")
g2 = DGraph.read_dot(join(project_root(), "dot/g2.dot"))
algo_result = KMeans.KMeansClustering().cluster(g2)
self.assertIsClusterRepresentation(
algo_result,
"Kmeans result is not a lists of clusters when testing g2.dot")
expected = clusters_to_set([['1', '2', '3', '4'], ['5', '6', '7']])
assert clusters_to_set(
algo_result
) == expected, "Kmeans did not work as expected on g2.dot"
def test_spectral(self):
print("Testing Spectral Clustering")
g2 = DGraph.read_dot(join(project_root(), "dot/g2.dot"))
algo_result = SpectralCluster.SpectralCluster().cluster(g2)
self.assertIsClusterRepresentation(
algo_result,
"SpectralCluster result is not a lists of clusters when testing g2.dot"
)
expected = clusters_to_set([['1', '2', '3'], ['4', '5', '6', '7']])
assert clusters_to_set(
algo_result
) == expected, "SpectralCluster did not work as expected on g2.dot"
def test_builtgraph_export(self):
g = DGraph()
g.add_node('1', label='kekek')
g.add_node('2')
g.add_node('3')
g.add_node('4')
g.add_edge('1', '2', weight=2)
g.add_edge('3', '2', weight=2)
g.write_dot(join(project_root(), "./tests/dot_export/g.dot"))
g2 = DGraph.read_dot(join(project_root(), "./tests/dot_export/g.dot"))
assert g2.dgraph is not None
self.assertEqual(len(g.nodes()), 4,
"wrong number of nodes after export")
self.assertEqual(len(g.edges()), 2,
"wrong number of edges after export")
assert nx.algorithms.is_isomorphic(g.dgraph, g2.dgraph)
def test_labeling(self):
g = DGraph.read_dot(os.path.join(project_root(), "dot/ssh.net.dot"))
den = partition.partition(g, SpectralCluster.SpectralCluster(), stop_criteria.SizeCriteria(4))
labeler = TfIdfLabeler.TfIdfLabeler(g, den, 'Both')
labeler.label()
def open(self, model_id):
model_path = os.path.join(self.base_dir,
_model_name_to_filename(model_id))
return DGraph.read_dot(model_path)
def test_import_example(self):
g = DGraph.read_dot(join(project_root(), "./dot/example.dot"))
self.assertIsNotNone(g.dgraph, "import of example.dot failed")
self.assertEqual(len(g.nodes()), 24,
"wrong number of nodes after import")