cugraph.tree.minimum_spanning_tree.minimum_spanning_tree#

cugraph.tree.minimum_spanning_tree.minimum_spanning_tree(G, weight=None, algorithm='boruvka', ignore_nan=False)[source]#

Returns a minimum spanning tree (MST) or forest (MSF) on an undirected graph

Parameters:

GcuGraph.Graph or networkx.Graph: cuGraph graph descriptor with connectivity information.

Deprecated since version 24.12: Accepting a networkx.Graph is deprecated and will be removed in a future version. For networkx.Graph use networkx directly with the nx-cugraph backend. See: https://rapids.ai/nx-cugraph/
weightstring: default to the weights in the graph, if the graph edges do not have a weight attribute a default weight of 1 will be used.
algorithmstring: Default to ‘boruvka’. The parallel algorithm to use when finding a minimum spanning tree.
ignore_nanbool: Default to False

Returns:

G_mstcuGraph.Graph or networkx.Graph: A graph descriptor with a minimum spanning tree or forest. The networkx graph will not have all attributes copied over

Examples

>>> from cugraph.datasets import netscience
>>> G = netscience.get_graph(download=True)
>>> G_mst = cugraph.minimum_spanning_tree(G)