btjZdZddlmZddlZdgZejdddZdS) z Vitality measures. )partialNcloseness_vitalityweight) edge_attrsc|tj||}|?tj|t||hz |}||z St t |||fd|DS)aReturns the closeness vitality for nodes in the graph. The *closeness vitality* of a node, defined in Section 3.6.2 of [1], is the change in the sum of distances between all node pairs when excluding that node. Parameters ---------- G : NetworkX graph A strongly-connected graph. weight : string The name of the edge attribute used as weight. This is passed directly to the :func:`~networkx.wiener_index` function. node : object If specified, only the closeness vitality for this node will be returned. Otherwise, a dictionary mapping each node to its closeness vitality will be returned. Other parameters ---------------- wiener_index : number If you have already computed the Wiener index of the graph `G`, you can provide that value here. Otherwise, it will be computed for you. Returns ------- dictionary or float If `node` is None, this function returns a dictionary with nodes as keys and closeness vitality as the value. Otherwise, it returns only the closeness vitality for the specified `node`. The closeness vitality of a node may be negative infinity if removing that node would disconnect the graph. Examples -------- >>> G = nx.cycle_graph(3) >>> nx.closeness_vitality(G) {0: 2.0, 1: 2.0, 2: 2.0} See Also -------- closeness_centrality References ---------- .. [1] Ulrik Brandes, Thomas Erlebach (eds.). *Network Analysis: Methodological Foundations*. Springer, 2005. N)r)r wiener_indexc*i|]}||S))node).0vvitalitys Z/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/networkx/algorithms/vitality.py z&closeness_vitality..Ls( + + +AAxxQ + + +)nxrsubgraphsetrr)Gr rrafterrs @rrr stq888   3q66TF? ; ;FKKKe##)1V,WWWH + + + + + + ++r)NNN)__doc__ functoolsrnetworkxr__all__ _dispatchablerr rrrsr  X&&&?,?,?,'&?,?,?,r