{ "info": { "author": "Charles-Abner DADI @Ekimetrics", "author_email": "charles-abner.dadi@ekimetrics.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 1 - Planning", "License :: OSI Approved", "Natural Language :: French", "Operating System :: OS Independent", "Programming Language :: Python", "Programming Language :: Python :: 2.7", "Topic :: Communications" ], "description": "##EkiNetworkX - Custom functions to compute networkX graph\n\n\n========================================================\n### INSTALL\nInstall with pip:\n\n pip install ekiNx\n\nExample of usage:\n\n >>> from ekiNx import core\n >>> core.proclamer()\n========================================================\n\n### This module provides complement functions for lib NetworkX\n_Function to compute bipartite graph and project to one set of nodes_\n#### __FromDataFrame__ :\n* _INPUT:_\n\n * data is a pandas dataframe\n * u is the name of column for node 'projected'\n * v is the name of column for node to project\n * w is the name of column for weight\n * alpha is a threshold to map or not a edge \n* _OUTPUT:_\n\n\t* compute numpy array (dim 2 N) \n\t* U: are nodes projected\n\t* V: are node to project\n\t* E: edges with weight attributes if weight columns filled \n\n#### __mapBipartite__ :\n- create biGraph and map nodes/edges\n* _INPUT:_\n * U nodes 'projected'\n * V nodes to project\n * E: edges with weight attributes if weight columns filled \n* _OUTPUT:_\n * g: networkX biGraph \n\n#### __projectGraph__ :\n- create biGraph and map nodes/edges\n* _INPUT:_\n * U biGraph a bigraph networkX object \n * V is the set on\n\t* weight_function to compute edges weight ( for instance jaccard)\n* _OUTPUT:_\n * g: networkX object representing a undirected graph\n\n\n\n#### __graphFromPandasAdjancyMatrix__ :\n- map nodes and edges from adjancy matrix:\n* _INPUT:_\n * data is a pandas object representing an adjacency matrix\n* _OUTPUT:_\n * g: anetworkX object representing a undirected 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