def subgraph(G, vertices):
"""
Compute a subgraph of the existing graph including only the specified
vertices. This algorithm works for both directed and undirected graphs,
it does not actually traverse the edges, simply pulls out any edges that
are incident on vertices that are both contained in the vertices list.
Parameters
----------
G : cugraph.Graph
cuGraph graph descriptor
vertices : cudf.Series
Specifies the vertices of the induced subgraph
Returns
-------
Sg : cugraph.Graph
A graph object containing the subgraph induced by the given vertex set.
Examples
--------
>>> gdf = cudf.read_csv('datasets/karate.csv',
delimiter = ' ',
dtype=['int32', 'int32', 'float32'],
header=None)
>>> G = cugraph.Graph()
>>> G.from_cudf_edgelist(gdf, source='0', destination='1')
>>> verts = numpy.zeros(3, dtype=numpy.int32)
>>> verts[0] = 0
>>> verts[1] = 1
>>> verts[2] = 2
>>> sverts = cudf.Series(verts)
>>> Sg = cugraph.subgraph(G, sverts)
"""
null_check(vertices)
if G.renumbered:
vertices = G.lookup_internal_vertex_id(vertices)
result_graph = type(G)()
df = subgraph_extraction_wrapper.subgraph(G, vertices)
if G.renumbered:
df = G.unrenumber(df, "src")
df = G.unrenumber(df, "dst")
if G.edgelist.weights:
result_graph.from_cudf_edgelist(df,
source="src",
destination="dst",
edge_attr="weight")
else:
result_graph.from_cudf_edgelist(df, source="src", destination="dst")
return result_graph
def subgraph(G, vertices):
"""
Compute a subgraph of the existing graph including only the specified
vertices. This algorithm works for both directed and undirected graphs,
it does not actually traverse the edges, simply pulls out any edges that
are incident on vertices that are both contained in the vertices list.
Parameters
----------
G : cugraph.Graph
cuGraph graph descriptor
vertices : cudf.Series
Specifies the vertices of the induced subgraph
Returns
-------
Sg : cugraph.Graph
A graph object containing the subgraph induced by the given vertex set.
Examples
--------
>>> M = cudf.read_csv('datasets/karate.csv', delimiter=' ',
>>> dtype=['int32', 'int32', 'float32'], header=None)
>>> sources = cudf.Series(M['0'])
>>> destinations = cudf.Series(M['1'])
>>> G = cugraph.Graph()
>>> G.add_edge_list(sources, destinations, None)
>>> verts = numpy.zeros(3, dtype=numpy.int32)
>>> verts[0] = 0
>>> verts[1] = 1
>>> verts[2] = 2
>>> sverts = cudf.Series(verts)
>>> Sg = cugraph.subgraph(G, sverts)
"""
null_check(vertices)
result_graph = Graph()
subgraph_extraction_wrapper.subgraph(G.graph_ptr, vertices,
result_graph.graph_ptr)
return result_graph
def subgraph(G, vertices):
"""
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.
Parameters
----------
G : cugraph.Graph
cuGraph graph descriptor
vertices : cudf.Series or cudf.DataFrame
Specifies the vertices of the induced subgraph. For multi-column
vertices, vertices should be provided as a cudf.DataFrame
Returns
-------
Sg : cugraph.Graph
A graph object containing the subgraph induced by the given vertex set.
Examples
--------
>>> gdf = cudf.read_csv(datasets_path / 'karate.csv',
... delimiter = ' ',
... dtype=['int32', 'int32', 'float32'],
... header=None)
>>> G = cugraph.Graph()
>>> G.from_cudf_edgelist(gdf, source='0', destination='1')
>>> verts = np.zeros(3, dtype=np.int32)
>>> verts[0] = 0
>>> verts[1] = 1
>>> verts[2] = 2
>>> sverts = cudf.Series(verts)
>>> Sg = cugraph.subgraph(G, sverts)
"""
G, isNx = ensure_cugraph_obj_for_nx(G)
if G.renumbered:
if isinstance(vertices, cudf.DataFrame):
vertices = G.lookup_internal_vertex_id(vertices, vertices.columns)
else:
vertices = G.lookup_internal_vertex_id(vertices)
result_graph = type(G)()
df = subgraph_extraction_wrapper.subgraph(G, vertices)
src_names = "src"
dst_names = "dst"
if G.renumbered:
df, src_names = G.unrenumber(df, src_names, get_column_names=True)
df, dst_names = G.unrenumber(df, dst_names, get_column_names=True)
if G.edgelist.weights:
result_graph.from_cudf_edgelist(df,
source=src_names,
destination=dst_names,
edge_attr="weight")
else:
result_graph.from_cudf_edgelist(df,
source=src_names,
destination=dst_names)
if isNx is True:
result_graph = cugraph_to_nx(result_graph)
return result_graph