def k_core(G,
k=None,
core_number=None):
"""
Compute the k-core of the graph G based on the out degree of its nodes. A
k-core of a graph is a maximal subgraph that contains nodes of degree k or
more. This call does not support a graph with self-loops and parallel
edges.
Parameters
----------
G : cuGraph.Graph
cuGraph graph descriptor with connectivity information. The graph
should contain undirected edges where undirected edges are represented
as directed edges in both directions. While this graph can contain edge
weights, they don't participate in the calculation of the k-core.
k : int, optional
Order of the core. This value must not be negative. If set to None, the
main core is returned.
core_number : cudf.DataFrame, optional
Precomputed core number of the nodes of the graph G containing two
cudf.Series of size V: the vertex identifiers and the corresponding
core number values. If set to None, the core numbers of the nodes are
calculated internally.
core_number['vertex'] : cudf.Series
Contains the vertex identifiers
core_number['values'] : cudf.Series
Contains the core number of vertices
Returns
-------
KCoreGraph : cuGraph.Graph
K Core of the input graph
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)
>>> KCoreGraph = cugraph.k_core(G)
"""
KCoreGraph = DiGraph()
if core_number is None:
core_number = core_number_wrapper.core_number(G)
core_number = core_number.rename(columns={"core_number": "values"})
if k is None:
k = core_number['values'].max()
k_core_wrapper.k_core(G,
KCoreGraph,
k,
core_number)
return KCoreGraph
def core_number(G):
"""
Compute the core numbers for the nodes of the graph G. A k-core of a graph
is a maximal subgraph that contains nodes of degree k or more.
A node has a core number of k if it belongs a k-core but not to k+1-core.
This call does not support a graph with self-loops and parallel
edges.
Parameters
----------
G : cuGraph.Graph or networkx.Graph
The graph should contain undirected edges where undirected edges are
represented as directed edges in both directions. While this graph
can contain edge weights, they don't participate in the calculation
of the core numbers.
Returns
-------
df : cudf.DataFrame or python dictionary (in NetworkX input)
GPU data frame containing two cudf.Series of size V: the vertex
identifiers and the corresponding core number values.
df['vertex'] : cudf.Series
Contains the vertex identifiers
df['core_number'] : cudf.Series
Contains the core number of vertices
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')
>>> cn = cugraph.core_number(G)
"""
G, isNx = ensure_cugraph_obj_for_nx(G)
df = core_number_wrapper.core_number(G)
if G.renumbered:
df = G.unrenumber(df, "vertex")
if isNx is True:
df = df_score_to_dictionary(df, 'core_number')
return df
def core_number(G):
"""
Compute the core numbers for the nodes of the graph G. A k-core of a graph
is a maximal subgraph that contains nodes of degree k or more.
A node has a core number of k if it belongs a k-core but not to k+1-core.
This call does not support a graph with self-loops and parallel
edges.
Parameters
----------
graph : cuGraph.Graph
cuGraph graph descriptor with connectivity information. The graph
should contain undirected edges where undirected edges are represented
as directed edges in both directions. While this graph can contain edge
weights, they don't participate in the calculation of the core numbers.
Returns
-------
df : cudf.DataFrame
GPU data frame containing two cudf.Series of size V: the vertex
identifiers and the corresponding core number values.
df['vertex'] : cudf.Series
Contains the vertex identifiers
df['core_number'] : cudf.Series
Contains the core number of vertices
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')
>>> cn = cugraph.core_number(G)
"""
df = core_number_wrapper.core_number(G)
if G.renumbered:
df = G.unrenumber(df, "vertex")
return df
def k_core(G, k=None, core_number=None):
"""
Compute the k-core of the graph G based on the out degree of its nodes. A
k-core of a graph is a maximal subgraph that contains nodes of degree k or
more. This call does not support a graph with self-loops and parallel
edges.
Parameters
----------
G : cuGraph.Graph
cuGraph graph descriptor with connectivity information. The graph
should contain undirected edges where undirected edges are represented
as directed edges in both directions. While this graph can contain edge
weights, they don't participate in the calculation of the k-core.
k : int, optional
Order of the core. This value must not be negative. If set to None, the
main core is returned.
core_number : cudf.DataFrame, optional
Precomputed core number of the nodes of the graph G containing two
cudf.Series of size V: the vertex identifiers and the corresponding
core number values. If set to None, the core numbers of the nodes are
calculated internally.
core_number['vertex'] : cudf.Series
Contains the vertex identifiers
core_number['values'] : cudf.Series
Contains the core number of vertices
Returns
-------
KCoreGraph : cuGraph.Graph
K Core of the input graph
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')
>>> KCoreGraph = cugraph.k_core(G)
"""
mytype = type(G)
KCoreGraph = mytype()
if core_number is not None:
if G.renumbered is True:
core_number = G.add_internal_vertex_id(core_number,
"vertex",
"vertex",
drop=True)
else:
core_number = core_number_wrapper.core_number(G)
core_number = core_number.rename(columns={"core_number": "values"},
copy=False)
if k is None:
k = core_number["values"].max()
k_core_df = k_core_wrapper.k_core(G, k, core_number)
if G.renumbered:
k_core_df = G.unrenumber(k_core_df, "src")
k_core_df = G.unrenumber(k_core_df, "dst")
if G.edgelist.weights:
KCoreGraph.from_cudf_edgelist(k_core_df,
source="src",
destination="dst",
edge_attr="weight")
else:
KCoreGraph.from_cudf_edgelist(k_core_df,
source="src",
destination="dst")
return KCoreGraph
def k_core(G, k=None, core_number=None):
"""
Compute the k-core of the graph G based on the out degree of its nodes. A
k-core of a graph is a maximal subgraph that contains nodes of degree k or
more. This call does not support a graph with self-loops and parallel
edges.
Parameters
----------
G : cuGraph.Graph or networkx.Graph
cuGraph graph descriptor with connectivity information. The graph
should contain undirected edges where undirected edges are represented
as directed edges in both directions. While this graph can contain edge
weights, they don't participate in the calculation of the k-core.
k : int, optional (default=None)
Order of the core. This value must not be negative. If set to None, the
main core is returned.
core_number : cudf.DataFrame, optional (default=None)
Precomputed core number of the nodes of the graph G containing two
cudf.Series of size V: the vertex identifiers and the corresponding
core number values. If set to None, the core numbers of the nodes are
calculated internally.
core_number['vertex'] : cudf.Series
Contains the vertex identifiers
core_number['values'] : cudf.Series
Contains the core number of vertices
Returns
-------
KCoreGraph : cuGraph.Graph
K Core of the input graph
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')
>>> KCoreGraph = cugraph.k_core(G)
"""
G, isNx = ensure_cugraph_obj_for_nx(G)
mytype = type(G)
KCoreGraph = mytype()
if mytype is not Graph:
raise Exception("directed graph not supported")
if core_number is not None:
if G.renumbered is True:
if len(G.renumber_map.implementation.col_names) > 1:
cols = core_number.columns[:-1].to_list()
else:
cols = 'vertex'
core_number = G.add_internal_vertex_id(core_number, 'vertex', cols)
else:
core_number = core_number_wrapper.core_number(G)
core_number = core_number.rename(columns={"core_number": "values"},
copy=False)
if k is None:
k = core_number["values"].max()
k_core_df = k_core_wrapper.k_core(G, k, core_number)
if G.renumbered:
k_core_df, src_names = G.unrenumber(k_core_df,
"src",
get_column_names=True)
k_core_df, dst_names = G.unrenumber(k_core_df,
"dst",
get_column_names=True)
if G.edgelist.weights:
KCoreGraph.from_cudf_edgelist(k_core_df,
source=src_names,
destination=dst_names,
edge_attr="weight")
else:
KCoreGraph.from_cudf_edgelist(
k_core_df,
source=src_names,
destination=dst_names,
)
if isNx is True:
KCoreGraph = cugraph_to_nx(KCoreGraph)
return KCoreGraph