Graph similarity algorithms based on NetworkX.
Project description
graphsim
Graph similarity algorithms based on NetworkX.
BSD License
Install
$ pip install -U graphsim
Usage
>>> import graphsim as gs
Supported algorithms
gs.ascos: Asymmetric network Structure COntext Similarity, by Hung-Hsuan Chen et al.
gs.nsim_bvd04: node-node similarity matrix, by Blondel et al.
gs.hits: the hub and authority scores for nodes, by Kleinberg.
gs.nsim_hs03: node-node similarity with mismatch penalty, by Heymans et al.
gs.simrank: A Measure of Structural-Context Similarity, by Jeh et al.
gs.simrank_bipartite: SimRank for bipartite graphs, by Jeh et al.
gs.tacsim: Topology-Attributes Coupling Simmilarity, by Xiaming Chen et al.
gs.tacsim_combined: A combined topology-attributes coupling simmilarity, by Xiaming Chen et al.
Supported utilities
gs.normalized: L2 normalization of vectors, matrices or arrays.
gs.node_edge_adjacency: Obtain node-edge adjacency matrices in source and dest directions.
