cugraph.induced_subgraph

cugraph.induced_subgraph(G: Graph, vertices: Series | DataFrame, offsets: list | Series = None) → Tuple[Graph, Series]

Compute a subgraph of the existing graph including only the specified vertices. This algorithm works with both directed and undirected graphs and does not actually traverse the edges, but instead simply pulls out any edges that are incident on vertices that are both contained in the vertices list.

If no subgraph can be extracted from the vertices provided, a ‘None’ value will be returned.

Parameters:

Gcugraph.Graph

The current implementation only supports weighted graphs.

verticescudf.Series or cudf.DataFrame

Specifies the vertices of the induced subgraph. For multi-column vertices, vertices should be provided as a cudf.DataFrame

offsetslist or cudf.Series, optional

Specifies the subgraph offsets into the subgraph vertices. If no offsets array is provided, a default array [0, len(vertices)] will be used.

Returns:

Sgcugraph.Graph

A graph object containing the subgraph induced by the given vertex set.

seeds_offsets: cudf.Series

A cudf Series containing the starting offset in the returned edge list for each seed.

Examples

>>> from cugraph.datasets import karate
>>> G = karate.get_graph(download=True)
>>> verts = np.zeros(3, dtype=np.int32)
>>> verts[0] = 0
>>> verts[1] = 1
>>> verts[2] = 2
>>> sverts = cudf.Series(verts)
>>> Sg, seeds_offsets = cugraph.induced_subgraph(G, sverts)