o ßË·eöã@s ddlmZdgZddd„ZdS) é)ÚcombinationsÚ dispersionNTçð?çc sÜ‡‡‡‡fdd„}|durI|dur0dd„|Dƒ}|D]}||D]}||||ƒ|||<q q|St ||i¡}||D] }||||ƒ||<q<|S|durft ||i¡}||D] }||||ƒ||<qY|S||||ƒ}|S)aŽCalculate dispersion between `u` and `v` in `G`. A link between two actors (`u` and `v`) has a high dispersion when their mutual ties (`s` and `t`) are not well connected with each other. Parameters ---------- G : graph A NetworkX graph. u : node, optional The source for the dispersion score (e.g. ego node of the network). v : node, optional The target of the dispersion score if specified. normalized : bool If True (default) normalize by the embededness of the nodes (u and v). Returns ------- nodes : dictionary If u (v) is specified, returns a dictionary of nodes with dispersion score for all "target" ("source") nodes. If neither u nor v is specified, returns a dictionary of dictionaries for all nodes 'u' in the graph with a dispersion score for each node 'v'. Notes ----- This implementation follows Lars Backstrom and Jon Kleinberg [1]_. Typical usage would be to run dispersion on the ego network $G_u$ if $u$ were specified. Running :func:`dispersion` with neither $u$ nor $v$ specified can take some time to complete. References ---------- .. [1] Romantic Partnerships and the Dispersion of Social Ties: A Network Analysis of Relationship Status on Facebook. Lars Backstrom, Jon Kleinberg. https://arxiv.org/pdf/1310.6753v1.pdf cs®t||ƒ‰‡fdd„||Dƒ}||h}t|dƒ}d}|D]\}}ˆ ||¡|} || vr:| ||¡r:|d7}qt|ƒ} |}ˆrU|ˆˆ}| ˆdkrU|| ˆ}|S)z=dispersion for all nodes 'v' in a ego network G_u of node 'u'csh|]}|ˆvr|’qS©r©Ú.0Ún©Úu_nbrsrú`/var/www/ideatree/venv/lib/python3.10/site-packages/networkx/algorithms/centrality/dispersion.pyÚ 2sz2dispersion.._dispersion..éré)ÚsetrÚintersectionÚ isdisjointÚlen)ÚG_uÚuÚvÚSTÚset_uvÚpossibÚtotalÚsÚtÚnbrs_sÚembedednessÚdispersion_val©ÚalphaÚbÚcÚ normalizedr rÚ_dispersion/s$ €zdispersion.._dispersionNcSsi|]}|i“qSrrrrrrÚ Nszdispersion..)ÚdictÚfromkeys) ÚGrrr$r!r"r#r%Úresultsrr rrs()ÿóøþ)NNTrrr)Ú itertoolsrÚ__all__rrrrrÚs