3 Md@s dZddlZdgZdddZdS)z Spectral bipartivity measure. Nspectral_bipartivityweightcCsy ddl}Wn.tk r:}ztdd|WYdd}~XnXt|}tj|||d}|jj|}|jj| }d||} |dkr| jj|jjSt t |t t |} i} x0|D](} | | } | | | f|| | f| | <qW| SdS)u9Returns the spectral bipartivity. Parameters ---------- G : NetworkX graph nodes : list or container optional(default is all nodes) Nodes to return value of spectral bipartivity contribution. weight : string or None optional (default = 'weight') Edge data key to use for edge weights. If None, weights set to 1. Returns ------- sb : float or dict A single number if the keyword nodes is not specified, or a dictionary keyed by node with the spectral bipartivity contribution of that node as the value. Examples -------- >>> from networkx.algorithms import bipartite >>> G = nx.path_graph(4) >>> bipartite.spectral_bipartivity(G) 1.0 Notes ----- This implementation uses Numpy (dense) matrices which are not efficient for storing large sparse graphs. See Also -------- color References ---------- .. [1] E. Estrada and J. A. Rodríguez-Velázquez, "Spectral measures of bipartivity in complex networks", PhysRev E 72, 046105 (2005) rNz'spectral_bipartivity() requires SciPy: zhttp://scipy.org/)rg?) Z scipy.linalg ImportErrorlistnxZto_numpy_arrayZlinalgZexpmZdiagonalsumdictziprangelen)GZnodesrZscipyeZnodelistAZexpAZexpmAZcoshAindexZsbnirX/var/www/html/virt/lib/python3.6/site-packages/networkx/algorithms/bipartite/spectral.pyr s&)     )Nr)__doc__Znetworkxr__all__rrrrrs