graphsim 0.2.6.8

Graph similarity algorithms based on NetworkX.

graphsim

Graph similarity algorithms based on NetworkX.

BSD License

Install

First, install building tool:

$ yum install -y scons

On Mac OS:

$ brew install scons

Then install graphsim via PyPI:

$ 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 Similarity, by Xiaming Chen et al.

• gs.tacsim_combined: A combined topology-attributes coupling similarity, by Xiaming Chen et al.

• gs.tacsim_in_C: an efficient implementation of TACSim in pure C.

• gs.tacsim_combined_in_C: an efficient implementation of combined TACSim in pure C.

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.

Author

Xiaming Chen <[e-mail]>