Open 84a8d5a7-8b56-4408-8526-3d1eb144bfdc opened 8 years ago
Description changed:
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+This is a new function that computes the probability that vertices in a simple undirected graph are connected.
+The input is a (symmetric) probability matrix that assigns a probability to each edge in the graph.
+
+The output is a matrix containing the probability that each pair of vertices will be connected in the graph given the edge probabilities in the input matrix.
+
+See the documentation in the file for more information.
Attachment: connectivity_probability.py.gz
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Best, Travis
Commit: d82e9d4
New commits:
d82e9d4 | Added the file connectivity_probability.py |
Author: James Rudzinski
There are no references provided in docstrings to the algorithms implemented.
I don't understand why this function does not take a weighted Sage graph as an input, but some matrix. E.g. it would be most natural apply it to the weighted adjacency matrix of a graph, e.g.
sage: h.add_edges([[0,1,1/2],[1,2,2/3]])
sage: h
Graph on 3 vertices
sage: h.weighted_adjacency_matrix()
[ 0 1/2 0]
[1/2 0 2/3]
[ 0 2/3 0]
This is a new function that computes the probability that vertices in a simple undirected graph are connected.
The input is a (symmetric) probability matrix that assigns a probability to each edge in the graph.
The output is a matrix containing the probability that each pair of vertices will be connected in the graph given the edge probabilities in the input matrix.
See the documentation in the file for more information.
CC: @dimpase
Component: graph theory
Author: James Rudzinski
Branch/Commit: u/jerudzin/graph_connectivity_probability @
d82e9d4
Issue created by migration from https://trac.sagemath.org/ticket/20186