prim_mst_edges(G, minimum, weight='weight', keys=True, data=True, ignore_nan=False)

Parameters

G : NetworkX Graph

The graph holding the tree of interest.

minimum : bool (default: True)

Find the minimum (True) or maximum (False) spanning tree.

weight : string (default: 'weight')

The name of the edge attribute holding the edge weights.

keys : bool (default: True)

If G is a multigraph, keys controls whether edge keys ar yielded. Otherwise keys is ignored.

data : bool (default: True)

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)`.

ignore_nan : bool (default: False)

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.

Iterate over edges of Prim's algorithm min/max spanning tree.

Examples

See :

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

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GitHub : /networkx/algorithms/tree/mst.py#249
type: <class 'function'>
Commit: