def test_leiden_clustering():
graph = Graph(get_input("propertygraphs/rmat10_symmetric"))
leiden_clustering(graph, "value", "output")
leiden_clustering_assert_valid(graph, "value", "output")
LeidenClusteringStatistics(graph, "value", "output")
def test_triangle_count_presorted():
graph = Graph(get_input("propertygraphs/rmat15_cleaned_symmetric"))
sort_nodes_by_degree(graph)
sort_all_edges_by_dest(graph)
n = triangle_count(
graph,
TriangleCountPlan.node_iteration(relabeling=False, edges_sorted=True))
assert n == 282617
def test_k_truss_fail():
graph = Graph(get_input("propertygraphs/rmat10_symmetric"))
with raises(GaloisError):
k_truss(graph, 2, "output")
with raises(GaloisError):
k_truss(graph, 1, "output2")
def test_local_clustering_coefficient():
graph = Graph(get_input("propertygraphs/rmat15_cleaned_symmetric"))
local_clustering_coefficient(graph, "output")
graph: Graph
out = graph.get_node_property("output")
assert out[-1].as_py() == 0
assert not np.any(np.isnan(out))
def test_k_truss():
graph = Graph(get_input("propertygraphs/rmat10_symmetric"))
k_truss(graph, 10, "output")
stats = KTrussStatistics(graph, 10, "output")
assert stats.number_of_edges_left == 13338
k_truss_assert_valid(graph, 10, "output")
def test_k_core():
graph = Graph(get_input("propertygraphs/rmat10_symmetric"))
k_core(graph, 10, "output")
stats = KCoreStatistics(graph, 10, "output")
assert stats.number_of_nodes_in_kcore == 438
k_core_assert_valid(graph, 10, "output")
def test_connected_components():
graph = Graph(get_input("propertygraphs/rmat10_symmetric"))
connected_components(graph, "output")
stats = ConnectedComponentsStatistics(graph, "output")
assert stats.total_components == 69
assert stats.total_non_trivial_components == 1
assert stats.largest_component_size == 956
assert stats.largest_component_ratio == approx(0.933594)
connected_components_assert_valid(graph, "output")
def test_independent_set():
graph = Graph(get_input("propertygraphs/rmat10_symmetric"))
independent_set(graph, "output")
IndependentSetStatistics(graph, "output")
independent_set_assert_valid(graph, "output")
independent_set(graph, "output2", IndependentSetPlan.pull())
IndependentSetStatistics(graph, "output2")
independent_set_assert_valid(graph, "output2")
def get_default_args():
arguments = {
"json_output": "",
"input_dir": get_input("propertygraphs/"),
"graph": "rmat15",
"app": "all",
"source_nodes": "",
"trails": 1,
"num_sources": 4,
"thread_spin": False,
"threads": None,
}
return arguments
def test_subgraph_extraction():
graph = Graph(get_input("propertygraphs/rmat15_cleaned_symmetric"))
sort_all_edges_by_dest(graph)
nodes = [1, 3, 11, 120]
expected_edges = [[
nodes.index(graph.get_edge_dest(e)) for e in graph.edge_ids(i)
if graph.get_edge_dest(e) in nodes
] for i in nodes]
pg = subgraph_extraction(graph, nodes)
assert isinstance(pg, Graph)
assert len(pg) == len(nodes)
assert pg.num_edges() == 6
for i, _ in enumerate(expected_edges):
assert len(pg.edge_ids(i)) == len(expected_edges[i])
assert [pg.get_edge_dest(e)
for e in pg.edge_ids(i)] == expected_edges[i]
def test_triangle_count():
graph = Graph(get_input("propertygraphs/rmat15_cleaned_symmetric"))
original_first_edge_list = [
graph.get_edge_dest(e) for e in graph.edge_ids(0)
]
n = triangle_count(graph)
assert n == 282617
n = triangle_count(graph, TriangleCountPlan.node_iteration())
assert n == 282617
n = triangle_count(graph, TriangleCountPlan.edge_iteration())
assert n == 282617
assert [graph.get_edge_dest(e)
for e in graph.edge_ids(0)] == original_first_edge_list
sort_all_edges_by_dest(graph)
n = triangle_count(graph,
TriangleCountPlan.ordered_count(edges_sorted=True))
assert n == 282617
def pg_rmat15_cleaned_symmetric():
katana.local.initialize()
pg = Graph(get_input("propertygraphs/rmat15_cleaned_symmetric"))
return pg
def graph():
g = Graph(get_input("propertygraphs/ldbc_003"))
return g