RoleMagnet is a method of role clustering for flow networks.
-
rolemagnet/ Source code folder
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experiment_*.ipynb Experiments mentioned in the paper. You can learn how to use Role Magnet by reading them.
- Python 3
- Python libraries: numpy scipy sklearn networkx
Copy source code folder rolemagnet/ to your project.
Make a graph G by networkx, a list b representing balance of flow (or anything else you want to use as weight of nodes), then run:
import rolemagnet as rm
vec,role,label=rm.role_magnet(G, balance=b)vec is representations of nodes , label is a list consisting of role labels of nodes, vec and label are both arranged in same order as G.nodes(). role is a dict whose key is a role name and value is a list containing center of cluster and nodes in the cluster.
balance is optional. If node weight is insignificant in your network, just run:
vec,role,label=rm.role_magnet(G)Other optional parameters:
- shape The shape of competitive layer in SOM. If not provided, Role Magnet will compute according to the distribution of data.
- sample Evenly spaced sampling points. Default is
np.linspace(0,100,25).
We would like to thank the authors of struc2vec, RolX and GraphWave for the open access of the implementation of their method.
This project is licensed under the MIT License - see the LICENSE file for details.