kruskal_mst_edges(G, minimum, weight='weight', keys=True, data=True, ignore_nan=False, partition=None)
The graph holding the tree of interest.
Find the minimum (True) or maximum (False) spanning tree.
The name of the edge attribute holding the edge weights.
If G is a multigraph, keys
controls whether edge keys ar yielded. Otherwise keys
is ignored.
Flag for whether to yield edge attribute dicts. If True, yield edges :None:None:`(u, v, d)`, where d is the attribute dict. If False, yield edges :None:None:`(u, v)`.
If a NaN is found as an edge weight normally an exception is raised. If :None:None:`ignore_nan is True` then that edge is ignored instead.
The name of the edge attribute holding the partition data, if it exists. Partition data is written to the edges using the EdgePartition
enum. If a partition exists, all included edges and none of the excluded edges will appear in the final tree. Open edges may or may not be used.
Iterate over edge of a Kruskal's algorithm min/max spanning tree.
The edges as discovered by Kruskal's method. Each edge can take the following forms: :None:None:`(u, v)`, :None:None:`(u, v, d)` or :None:None:`(u, v, k, d)` depending on the :None:None:`key` and :None:None:`data` parameters
The following pages refer to to this document either explicitly or contain code examples using this.
networkx.algorithms.tree.mst.EdgePartition
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