Supported Algorithms#
The nx-cugraph backend to NetworkX connects pylibcugraph (cuGraph’s low-level Python interface to its CUDA-based graph analytics library) and CuPy (a GPU-accelerated array library) to NetworkX’s familiar and easy-to-use API.
Below is the list of algorithms that are currently supported in nx-cugraph.
Algorithms#
Centrality |
|---|
betweenness_centrality |
edge_betweenness_centrality |
degree_centrality |
in_degree_centrality |
out_degree_centrality |
eigenvector_centrality |
katz_centrality |
Cluster |
|---|
average_clustering |
clustering |
transitivity |
triangles |
Community |
|---|
louvain_communities |
Bipartite |
|---|
complete_bipartite_graph |
Components |
|---|
connected_components |
is_connected |
node_connected_component |
number_connected_components |
weakly_connected |
is_weakly_connected |
number_weakly_connected_components |
weakly_connected_components |
Core |
|---|
core_number |
k_truss |
DAG |
|---|
ancestors |
descendants |
Isolate |
|---|
is_isolate |
isolates |
number_of_isolates |
Link analysis |
|---|
hits |
pagerank |
Operators |
|---|
complement |
reverse |
Reciprocity |
|---|
overall_reciprocity |
reciprocity |
Shortest Paths |
|---|
has_path |
shortest_path |
shortest_path_length |
all_pairs_shortest_path |
all_pairs_shortest_path_length |
bidirectional_shortest_path |
single_source_shortest_path |
single_source_shortest_path_length |
single_target_shortest_path |
single_target_shortest_path_length |
all_pairs_bellman_ford_path |
all_pairs_bellman_ford_path_length |
all_pairs_dijkstra |
all_pairs_dijkstra_path |
all_pairs_dijkstra_path_length |
bellman_ford_path |
bellman_ford_path_length |
dijkstra_path |
dijkstra_path_length |
single_source_bellman_ford |
single_source_bellman_ford_path |
single_source_bellman_ford_path_length |
single_source_dijkstra |
single_source_dijkstra_path |
single_source_dijkstra_path_length |
Tree |
|---|
is_arborescence |
is_branching |
is_forest |
is_tree |
Utilities#
Classes |
|---|
is_negatively_weighted |
Convert |
|---|
from_dict_of_lists |
to_dict_of_lists |
Convert Matrix |
|---|
from_pandas_edgelist |
from_scipy_sparse_array |
Relabel |
|---|
convert_node_labels_to_integers |
relabel_nodes |
Generators#
Classic |
|---|
barbell_graph |
circular_ladder_graph |
complete_graph |
complete_multipartite_graph |
cycle_graph |
empty_graph |
ladder_graph |
lollipop_graph |
null_graph |
path_graph |
star_graph |
tadpole_graph |
trivial_graph |
turan_graph |
wheel_graph |
Classic |
|---|
caveman_graph |
Ego |
|---|
ego_graph |
small |
|---|
bull_graph |
chvatal_graph |
cubical_graph |
desargues_graph |
diamond_graph |
dodecahedral_graph |
frucht_graph |
heawood_graph |
house_graph |
house_x_graph |
icosahedral_graph |
krackhardt_kite_graph |
moebius_kantor_graph |
octahedral_graph |
pappus_graph |
petersen_graph |
sedgewick_maze_graph |
tetrahedral_graph |
truncated_cube_graph |
truncated_tetrahedron_graph |
tutte_graph |
Social |
|---|
davis_southern_women_graph |
florentine_families_graph |
karate_club_graph |
les_miserables_graph |
To request nx-cugraph backend support for a NetworkX API that is not listed above, visit the nx-cugraph GitHub repo.