B ฒ๔`Aใ@sHdZddlZddlmZddlmZGdd„dejƒZ ej dddd Z e e  e กƒZ e กZe e  eกƒZe กZe e  eกƒZe e feefeefgZxReD]J\ZZd d „e eกDƒZd d „e eกDƒZxeD]Zeeksาt‚qาWqœWxVeD]N\ZZd d „e eกDƒZdd „e eกDƒZxeD]Zeeks&t‚q&Wq๐Wx๎eD]ๆ\ZZee กƒdZee กƒdd…Ze  eกe  eกksŽt‚e!dd„e  กDƒƒe!dd„e  กDƒƒksภt‚e!dd„e  กDƒƒe!dd„ej ddDƒƒks๖t‚e!dd„e  eกDƒƒe!dd„e  eกDƒƒksHt‚qHWe "e กe #กdS)a ========= Antigraph ========= Complement graph class for small footprint when working on dense graphs. This class allows you to add the edges that *do not exist* in the dense graph. However, when applying algorithms to this complement graph data structure, it behaves as if it were the dense version. So it can be used directly in several NetworkX algorithms. This subclass has only been tested for k-core, connected_components, and biconnected_components algorithms but might also work for other algorithms. ้N)ฺ NetworkXErrorc@sFeZdZdZddiZdd„ZeZdd„Zdd „Zdd d „Z d d„Z d S)ฺ AntiGraphaฅ Class for complement graphs. The main goal is to be able to work with big and dense graphs with a low memory footprint. In this class you add the edges that *do not exist* in the dense graph, the report methods of the class return the neighbors, the edges and the degree as if it was the dense graph. Thus it's possible to use an instance of this class with some of NetworkX functions. ฺweight้cCs|jS)N)ฺ all_edge_dict)ฺselfฉr๚o/home/dcms/DCMS/lib/python3.7/site-packages/../../../share/doc/networkx-2.5/examples/subclass/plot_antigraph.pyฺsingle_edge_dict&szAntiGraph.single_edge_dictcs,‡fdd„tˆjƒtˆj|ƒ|hDƒS)aReturn a dict of neighbors of node n in the dense graph. Parameters ---------- n : node A node in the graph. Returns ------- adj_dict : dictionary The adjacency dictionary for nodes connected to n. csi|] }ˆj|“qSr)r)ฺ.0ฺnode)rrr ๚ 9sz)AntiGraph.__getitem__..)ฺsetฺadj)rฺnr)rr ฺ __getitem__+s zAntiGraph.__getitem__c Cs\y"tt|jƒt|j|ƒ|hƒStk rV}ztd|›dƒ|‚Wdd}~XYnXdS)zXReturn an iterator over all neighbors of node n in the dense graph. z The node z is not in the graph.N)ฺiterrrฺKeyErrorr)rrฺerrr ฺ neighbors=s"zAntiGraph.neighborsNcs”|dkr ‡fdd„ˆ กDƒ}nH|ˆkrPtˆ กƒtˆj|ƒ|h}t|ƒS‡fdd„ˆ |กDƒ}ˆdkr~dd„|DƒS‡fdd„|DƒSdS)a๕Return an iterator for (node, degree) in the dense graph. The node degree is the number of edges adjacent to the node. Parameters ---------- nbunch : iterable container, optional (default=all nodes) A container of nodes. The container will be iterated through once. weight : string or None, optional (default=None) The edge attribute that holds the numerical value used as a weight. If None, then each edge has weight 1. The degree is the sum of the edge weights adjacent to the node. Returns ------- nd_iter : iterator The iterator returns two-tuples of (node, degree). See Also -------- degree Examples -------- >>> G = nx.path_graph(4) # or DiGraph, MultiGraph, MultiDiGraph, etc >>> list(G.degree(0)) # node 0 with degree 1 [(0, 1)] >>> list(G.degree([0, 1])) [(0, 1), (1, 2)] Nc3s>|]6}|‡fdd„tˆjƒtˆj|ƒ|hDƒfVqdS)csi|] }ˆj|“qSr)r)r ฺv)rrr r msz.AntiGraph.degree...N)rr)r r)rrr ๚ ksz#AntiGraph.degree..c3s@|]8}|‡fdd„tˆ กƒtˆj|ƒ|hDƒfVqdS)csi|] }ˆj|“qSr)r)r r)rrr r {sz.AntiGraph.degree...N)rฺnodesr)r r)rrr ryscss|]\}}|t|ƒfVqdS)N)ฺlen)r rฺnbrsrrr r„sc3s.|]&\}‰|t‡‡fdd„ˆDƒƒfVqdS)c3s|]}ˆ| ˆdกVqdS)rN)ฺget)r Znbr)rrrr rˆsz-AntiGraph.degree...N)ฺsum)r r)r)rr rˆs)rrrrZ nbunch_iter)rZnbunchrZ nodes_nbrsrr)rrr ฺdegreeGs"    zAntiGraph.degreeccs8x2|jD](}|t|jƒt|j|ƒ|hfVqWdS)azReturn an iterator of (node, adjacency set) tuples for all nodes in the dense graph. This is the fastest way to look at every edge. For directed graphs, only outgoing adjacencies are included. Returns ------- adj_iter : iterator An iterator of (node, adjacency set) for all nodes in the graph. N)rr)rrrrr ฺadjacency_iterŒs zAntiGraph.adjacency_iter)NN) ฺ__name__ฺ __module__ฺ __qualname__ฺ__doc__rr Zedge_attr_dict_factoryrrrrrrrr rs  Er้gš™™™™™้?้*)ฺseedcCsg|] }t|ƒ‘qSr)r)r ฺcrrr ๚ ชsr'cCsg|] }t|ƒ‘qSr)r)r r&rrr r'ซscCsg|] }t|ƒ‘qSr)r)r r&rrr r'ฐscCsg|] }t|ƒ‘qSr)r)r r&rrr r'ฑsr้ccs|]\}}|VqdS)Nr)r rฺdrrr rนsrccs|]\}}|VqdS)Nr)r rr)rrr rปsr)rccs|]\}}|VqdS)Nr)r rr)rrr rผs)$r"ZnetworkxZnxZnetworkx.exceptionrZmatplotlib.pyplotZpyplotZpltZGraphrZgnp_random_graphZGnpZ complementZAnpZdavis_southern_women_graphZGdZAdZkarate_club_graphZGkZAkฺpairsฺGฺAZconnected_componentsฺgcฺacฺcompฺAssertionErrorZbiconnected_componentsฺlistrr rrZdrawฺshowrrrr ฺs>     26<