mf_entropy#
- graph_tool.inference.mf_entropy(g, p)[source]#
Compute the “mean field” entropy given the vertex block membership marginals.
- Parameters:
- g
Graph The graph.
- p
VertexPropertyMap Vertex property map with vector-type values, storing the accumulated block membership counts.
- g
- Returns:
- Hmf
float The “mean field” entropy value (in nats).
- Hmf
Notes
The “mean field” entropy is defined as,
\[H = - \sum_{i,r}\pi_i(r)\ln\pi_i(r),\]where \(\pi_i(r)\) is the marginal probability that vertex \(i\) belongs to block \(r\).
References
[mezard-information-2009]Marc Mézard, Andrea Montanari, “Information, Physics, and Computation”, Oxford Univ Press, 2009. DOI: 10.1093/acprof:oso/9780198570837.001.0001 [sci-hub, @tor]