cugraph.Graph#

class cugraph.Graph(m_graph=None, directed=False)[source]#

A GPU Graph Object (Base class of other graph types)

Parameters:

m_graphcuGraph.MultiGraph object or None (default=None): Initialize the graph from a cugraph.MultiGraph object
directedboolean, optional (default=False): Indicated is the graph is directed.

Examples

>>> # undirected graph
>>> G = cugraph.Graph()
>>> # directed graph
>>> G = cugraph.Graph(directed=True)

Methods

`add_internal_vertex_id`(df, ...[, drop, ...])	Given a DataFrame containing external vertex ids in the identified columns, return a DataFrame containing the internal vertex ids as the specified column name.
`add_nodes_from`(nodes)	Add nodes information to the Graph.
`clear`()	Empty the graph.
`density`()	Compute the density of the graph.
`from_cudf_adjlist`(offset_col, index_col[, ...])	Initialize a graph from the adjacency list.
`from_cudf_edgelist`(input_df[, source, ...])	Initialize a graph from the edge list.
`from_dask_cudf_edgelist`(input_ddf[, source, ...])	Initializes the distributed graph from the dask_cudf.DataFrame edgelist.
`from_numpy_array`(np_array[, nodes])	Initializes the graph from numpy array containing adjacency matrix.
`from_numpy_matrix`(np_matrix)	Initializes the graph from numpy matrix containing adjacency matrix.
`from_pandas_adjacency`(pdf)	Initializes the graph from pandas adjacency matrix.
`from_pandas_edgelist`(pdf[, source, ...])	Initialize a graph from the edge list.
`has_isolated_vertices`()	Returns True if the graph has isolated vertices.
`is_bipartite`()	Checks if Graph is bipartite.
`is_directed`()	Returns True if the graph is a directed graph.
`is_multi_gpu`()	Returns True if the graph is a multi-gpu graph; otherwise returns False.
`is_multigraph`()	Returns True if the graph is a multigraph.
`is_multipartite`()	Checks if Graph is multipartite.
`is_remote`()	Returns True if the graph is remote; otherwise returns False.
`is_renumbered`()	Returns True if the graph is renumbered.
`is_weighted`()	Returns True if the graph has edge weights.
`lookup_internal_vertex_id`(df[, column_name])	Given a DataFrame containing external vertex ids in the identified columns, or a Series containing external vertex ids, return a Series with the internal vertex ids.
`to_directed`()	Return a directed representation of the graph.
`to_undirected`()	Return an undirected copy of the graph.
`unrenumber`(df, column_name[, ...])	Given a DataFrame containing internal vertex ids in the identified column, replace this with external vertex ids.

Properties

__init__(m_graph=None, directed=False)[source]#

Methods

`__init__`([m_graph, directed])
`add_internal_vertex_id`(df, ...[, drop, ...])	Given a DataFrame containing external vertex ids in the identified columns, return a DataFrame containing the internal vertex ids as the specified column name.
`add_nodes_from`(nodes)	Add nodes information to the Graph.
`clear`()	Empty the graph.
`density`()	Compute the density of the graph.
`from_cudf_adjlist`(offset_col, index_col[, ...])	Initialize a graph from the adjacency list.
`from_cudf_edgelist`(input_df[, source, ...])	Initialize a graph from the edge list.
`from_dask_cudf_edgelist`(input_ddf[, source, ...])	Initializes the distributed graph from the dask_cudf.DataFrame edgelist.
`from_numpy_array`(np_array[, nodes])	Initializes the graph from numpy array containing adjacency matrix.
`from_numpy_matrix`(np_matrix)	Initializes the graph from numpy matrix containing adjacency matrix.
`from_pandas_adjacency`(pdf)	Initializes the graph from pandas adjacency matrix.
`from_pandas_edgelist`(pdf[, source, ...])	Initialize a graph from the edge list.
`has_isolated_vertices`()	Returns True if the graph has isolated vertices.
`is_bipartite`()	Checks if Graph is bipartite.
`is_directed`()	Returns True if the graph is a directed graph.
`is_multi_gpu`()	Returns True if the graph is a multi-gpu graph; otherwise returns False.
`is_multigraph`()	Returns True if the graph is a multigraph.
`is_multipartite`()	Checks if Graph is multipartite.
`is_remote`()	Returns True if the graph is remote; otherwise returns False.
`is_renumbered`()	Returns True if the graph is renumbered.
`is_weighted`()	Returns True if the graph has edge weights.
`lookup_internal_vertex_id`(df[, column_name])	Given a DataFrame containing external vertex ids in the identified columns, or a Series containing external vertex ids, return a Series with the internal vertex ids.
`to_directed`()	Return a directed representation of the graph.
`to_undirected`()	Return an undirected copy of the graph.
`unrenumber`(df, column_name[, ...])	Given a DataFrame containing internal vertex ids in the identified column, replace this with external vertex ids.