graphsim 0.2.12

Creator: bigcodingguy24

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graphsim 0.2.12

graphsim--------Graph similarity algorithms based on NetworkX.**BSD Licensed** [![Build Status](https://travis-ci.org/caesar0301/graphsim.svg?branch=master)](https://travis-ci.org/caesar0301/graphsim)[![PyPI](https://img.shields.io/pypi/l/graphsim.svg)](https://pypi.python.org/pypi/graphsim)[![PyPI](https://img.shields.io/pypi/pyversions/graphsim.svg)](https://pypi.python.org/pypi/graphsim)[![PyPI](https://img.shields.io/pypi/status/graphsim.svg)](https://pypi.python.org/pypi/graphsim)Install-------First, install building tool: yuminstall−ysconsOnMacOS: brew install sconsThen install graphsim via PyPI: pipinstall−UgraphsimPermissionIssues−−−−−−−−−−−−−−−−−−Bydefault,‘sudo‘isrequiredtogivepermissiontoinstallcppmodulesintosystem‘/usr/local/lib,include‘.Ifyoupreferlocalinstallation,followinginstructionsmayhelpyou:‘‘‘bashexportLIBTACSIMLIBDIR= /usr/lib/exportLIBTACSIMINCDIR= /usr/include/pipinstall−Ugraphsim‘‘‘MakesurethatthelocaldirectoriesareawareforClinkers:‘‘‘bashexportLDLIBRARYPATH= /usr/lib:LD_LIBRARY_PATHexport C_INCLUDE_PATH=~/usr/include:CINCLUDEPATHexportCPLUSINCLUDEPATH= /usr/include:CPLUS_INCLUDE_PATH```Coverage---------**NOTE**: `libtacsim` was tested on Ubuntu 12.04, Ubuntu 16.04, CentOS 6.5 and Mac OS 10.11.2, 10.13.2.Usage----- >>> import graphsim as gsSupported 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.Citation----------```tex@article{Chen2017, title = "Discovering and modeling meta-structures in human behavior from city-scale cellular data", journal = "Pervasive and Mobile Computing ", year = "2017", issn = "1574-1192", doi = "http://dx.doi.org/10.1016/j.pmcj.2017.02.001", author = "Xiaming Chen and Haiyang Wang and Siwei Qiang and Yongkun Wang and Yaohui Jin"}```Author------Xiaming Chen <chenxm35@gmail.com>

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