Ë Ü›7inãóJ—dZddlZdgZejd¬«dd„«Zy)z Spectral bipartivity measure. éNÚspectral_bipartivityÚweight)Ú edge_attrsc ó—ddl}t|«}tj|||¬«}|jj |«}|jj | «}d||zz}|€Ft |j«j«|j«j«z «Stt|tt|««««} i} |D]/} | | } |j| | «|j| | «z | | <Œ1| 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)rgà?)ÚscipyÚlistÚnxÚto_numpy_arrayÚlinalgÚexpmÚfloatÚdiagonalÚsumÚdictÚzipÚrangeÚlenÚitem) ÚGÚnodesrÚspÚnodelistÚAÚexpAÚexpmAÚcoshAÚindexÚsbÚnÚis úc/home/rose/Desktop/poly/venv/lib/python3.12/site-packages/networkx/algorithms/bipartite/spectral.pyrr së€óTäA‹w€HÜ ×ј!˜X¨fÔ5€AØ 9‰9>‰>˜!Ó €DØ I‰IN‰N˜A˜2Ó €EØ 4˜%‘<Ñ €EØ €}äU—^‘^Ó%×)Ñ)Ó+¨d¯m©m«o×.AÑ.AÓ.CÑCÓDÐDô”S˜¤5¬¨X«Ó#7Ó8Ó9ˆØ ˆÛˆAØa‘ˆAØ—J‘J˜q !Ó$ t§y¡y°°A£Ñ6ˆBˆqŠEððˆ ó)Nr)Ú__doc__Únetworkxr Ú__all__Ú _dispatchabler©r"r!Úr(s8ðñóà !Ð "€ð€×јXÔ&ò:ó'ñ:r"