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Project Description

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 <chen@xiaming.me>

Release History

Release History

0.2.6.8

This version

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0.2.6.7

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0.2.6.6

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0.2.6.5

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0.2.6.4

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0.2.6.3

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0.2.6.2

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0.2.6.1

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0.2.6

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0.2.5.3

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0.2.5.2

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0.2.5

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0.2.4

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0.2.3

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Download Files

Download Files

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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
graphsim-0.2.6.8.tar.gz (15.1 kB) Copy SHA256 Checksum SHA256 Source Dec 22, 2015

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