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| author | Harri Nieminen <moiman@posteo.net> | 2023-04-04 16:45:17 +0000 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2023-04-04 09:45:17 -0700 |
| commit | 7297ae8a37dd3356b64d383cb0c55735a6364bcc (patch) | |
| tree | 60cf106958ceaf2f111413965f476cffd922efdf /networkx/algorithms/tree/mst.py | |
| parent | c55f87045edb25b033854f40eefab092ab9df6eb (diff) | |
| download | networkx-7297ae8a37dd3356b64d383cb0c55735a6364bcc.tar.gz | |
Fix typos (#6620)
Diffstat (limited to 'networkx/algorithms/tree/mst.py')
| -rw-r--r-- | networkx/algorithms/tree/mst.py | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/networkx/algorithms/tree/mst.py b/networkx/algorithms/tree/mst.py index 8ec693d6..d36f411b 100644 --- a/networkx/algorithms/tree/mst.py +++ b/networkx/algorithms/tree/mst.py @@ -613,7 +613,7 @@ def partition_spanning_tree( """ Find a spanning tree while respecting a partition of edges. - Edges can be flagged as either `INLCUDED` which are required to be in the + Edges can be flagged as either `INCLUDED` which are required to be in the returned tree, `EXCLUDED`, which cannot be in the returned tree and `OPEN`. This is used in the SpanningTreeIterator to create new partitions following @@ -742,7 +742,7 @@ def random_spanning_tree(G, weight=None, *, multiplicative=True, seed=None): is based on the product of edge weights, and if ``multiplicative=False`` it is based on the sum of the edge weight. However, since it is easier to determine the total weight of all spanning trees for the - multiplicative verison, that is significantly faster and should be used if + multiplicative version, that is significantly faster and should be used if possible. Additionally, setting `weight` to `None` will cause a spanning tree to be selected with uniform probability. |