ó ú£Õ\c@sPdZddlmZddlZdjddgƒZdgZdd„Z dS( s%Node redundancy for bipartite graphs.iÿÿÿÿ(t combinationsNs s%Jordi Torrents sAric Hagberg (hagberg@lanl.gov)tnode_redundancyc Csã|dkr|}ni}xÁ|D]¹}d}xet||dƒD]P\}}tt||ƒt||ƒ@t|gƒƒdkrB|d7}qBqBW|dkrÇt||ƒ}d||d}nd}||||>> from networkx.algorithms import bipartite >>> G = nx.cycle_graph(4) >>> rc = bipartite.node_redundancy(G) >>> rc[0] 1.0 Compute the average redundancy for the graph: >>> sum(rc.values())/len(G) 1.0 Compute the average redundancy for a set of nodes: >>> nodes = [0, 2] >>> sum(rc[n] for n in nodes)/len(nodes) 1.0 References ---------- .. [1] Latapy, Matthieu, Clémence Magnien, and Nathalie Del Vecchio (2008). Basic notions for the analysis of large two-mode networks. Social Networks 30(1), 31--48. giiig@gð?N(tNoneRtlentset( tGtnodestrctvtoverlaptutwtntnorm((s`/Users/dxp/prism/prism-games/prism-examples/smgs/car/networkx/algorithms/bipartite/redundancy.pyRs6    7 ( t__doc__t itertoolsRtnetworkxtnxtjoint __author__t__all__RR(((s`/Users/dxp/prism/prism-games/prism-examples/smgs/car/networkx/algorithms/bipartite/redundancy.pyts