\MhnNdZddlZdgZejdddZdS)z Spectral bipartivity measure. Nspectral_bipartivityweight) edge_attrsc xddl}t|}tj|||}|j|}|j| }d||zz}|Zt ||z Stt|tt|} i} |D]:} | | } | | | | | | z | | <;| S)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) rN)rg?)scipylistnxto_numpy_arraylinalgexpmfloatdiagonalsumdictziprangelenitem) GnodesrspnodelistAexpAexpmAcoshAindexsbnis f/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/networkx/algorithms/bipartite/spectral.pyrr sTAwwH !Xf555A 9>>!  D INNA2  E 4%< E }U^^%%))++dmmoo.A.A.C.CCDDDS5X#7#78899  7 7AaAJJq!$$tyyA6BqEE )Nr)__doc__networkxr __all__ _dispatchablerr"r!r(s` ! "X&&&:::'&:::r"