o ]ZŽh6ã@s^dZddlZddlmZgd¢Zejdd„ƒZedƒejdd „ƒƒZedƒejd d „ƒƒZ dS) zDegree centrality measures.éN)Únot_implemented_for)Údegree_centralityÚin_degree_centralityÚout_degree_centralitycóDt|ƒdkr dd„|DƒSdt|ƒd‰‡fdd„| ¡Dƒ}|S)a¥Compute the degree centrality for nodes. The degree centrality for a node v is the fraction of nodes it is connected to. Parameters ---------- G : graph A networkx graph Returns ------- nodes : dictionary Dictionary of nodes with degree centrality as the value. Examples -------- >>> G = nx.Graph([(0, 1), (0, 2), (0, 3), (1, 2), (1, 3)]) >>> nx.degree_centrality(G) {0: 1.0, 1: 1.0, 2: 0.6666666666666666, 3: 0.6666666666666666} See Also -------- betweenness_centrality, load_centrality, eigenvector_centrality Notes ----- The degree centrality values are normalized by dividing by the maximum possible degree in a simple graph n-1 where n is the number of nodes in G. For multigraphs or graphs with self loops the maximum degree might be higher than n-1 and values of degree centrality greater than 1 are possible. écSói|]}|d“qS©r©©Ú.0Únr r úX/var/www/auris/lib/python3.10/site-packages/networkx/algorithms/centrality/degree_alg.pyÚ .óz%degree_centrality..çð?cói|] \}}||ˆ“qSr r ©r r Úd©Úsr rr1ó)ÚlenZdegree©ÚGZ centralityr rrr s $rZ undirectedcr)a Compute the in-degree centrality for nodes. The in-degree centrality for a node v is the fraction of nodes its incoming edges are connected to. Parameters ---------- G : graph A NetworkX graph Returns ------- nodes : dictionary Dictionary of nodes with in-degree centrality as values. Raises ------ NetworkXNotImplemented If G is undirected. Examples -------- >>> G = nx.DiGraph([(0, 1), (0, 2), (0, 3), (1, 2), (1, 3)]) >>> nx.in_degree_centrality(G) {0: 0.0, 1: 0.3333333333333333, 2: 0.6666666666666666, 3: 0.6666666666666666} See Also -------- degree_centrality, out_degree_centrality Notes ----- The degree centrality values are normalized by dividing by the maximum possible degree in a simple graph n-1 where n is the number of nodes in G. For multigraphs or graphs with self loops the maximum degree might be higher than n-1 and values of degree centrality greater than 1 are possible. rcSrr r r r r rr`rz(in_degree_centrality..rcrr r rrr rrcr)rZ in_degreerr rrr5ó *rcr)aïCompute the out-degree centrality for nodes. The out-degree centrality for a node v is the fraction of nodes its outgoing edges are connected to. Parameters ---------- G : graph A NetworkX graph Returns ------- nodes : dictionary Dictionary of nodes with out-degree centrality as values. Raises ------ NetworkXNotImplemented If G is undirected. Examples -------- >>> G = nx.DiGraph([(0, 1), (0, 2), (0, 3), (1, 2), (1, 3)]) >>> nx.out_degree_centrality(G) {0: 1.0, 1: 0.6666666666666666, 2: 0.0, 3: 0.0} See Also -------- degree_centrality, in_degree_centrality Notes ----- The degree centrality values are normalized by dividing by the maximum possible degree in a simple graph n-1 where n is the number of nodes in G. For multigraphs or graphs with self loops the maximum degree might be higher than n-1 and values of degree centrality greater than 1 are possible. rcSrr r r r r rr’rz)out_degree_centrality..rcrr r rrr rr•r)rZ out_degreerr rrrgrr) Ú__doc__ZnetworkxÚnxZnetworkx.utils.decoratorsrÚ__all__Z _dispatchablerrrr r r rÚs  + 0