graph.markov_cluster — Markov Clustering Algorithm¶
The graph.markov_cluster module implements a markov based walk method to compute graph clusters.
New in version 0.1.0.
- autocnet.graph.markov_cluster.mcl(g, expand_factor=2, inflate_factor=2, max_loop=10, mult_factor=1)[source]¶
Markov Cluster Algorithm
Implementation modified from: https://github.com/koteth/python_mcl Originally released under the MIT license (https://opensource.org/licenses/MIT)
- Parameters
g (object or ndarray) – NetworkX graph object or adjacency matrix
inflate_factor (float) – Parameter to strengthen and weaken flow between nodes. The larger the value the more granular the resultant clusters are.
expand_factor (int) – Parameter to manage flow connection between different regions of the graph.
mult_factor (int) – Value to set for self loops. That is, the flow between a node and itself.
max_loop (int) – Number of iterations to perform before terminating (or convergence).
- Returns
arr (ndarray) – arr normalized flow matrix computed after convergence or max_loop is exceeded.
clusters (dict) – of clusters where the key is an arbitrary cluster identifier and the value is a list of node identifiers.
References