wgnJdZddlZdgZejdddZy)z Spectral bipartivity measure. Nspectral_bipartivityweight) edge_attrsc ddl}t|}tj|||}|jj |}|jj | }d||zz}|Ft |jj|jjz Stt|tt|} i} |D]/} | | } |j| | |j| | z | | <1| 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 k/home/mcse/projects/flask/flask-venv/lib/python3.12/site-packages/networkx/algorithms/bipartite/spectral.pyrr sTAwH !Xf5A 99>>! D IINNA2 E 4%< E }U^^%))+dmmo.A.A.CCDDS5X#789  7AaAJJq!$tyyA6BqE 7 )Nr)__doc__networkxr __all__ _dispatchablerr"r!r(s8 ! "X&:':r"