o 3ήc @s$dZddgZdddZd ddZdS) z&Generators of x-y pairs of node data.node_attribute_xynode_degree_xyNc cs|dur t|}nt|}|j}|D]C\}}||vrq|||d}|rF|D]\}}|||d} |D]} || fVq>> G = nx.DiGraph() >>> G.add_node(1, color="red") >>> G.add_node(2, color="blue") >>> G.add_edge(1, 2) >>> list(nx.node_attribute_xy(G, "color")) [('red', 'blue')] Notes ----- For undirected graphs each edge is produced twice, once for each edge representation (u, v) and (v, u), with the exception of self-loop edges which only appear once. N)setnodes adjacencyget is_multigraphitems) G attributerGnodesunbrsdictuattrvkeysvattr_rN/tmp/pip-target-vg8gfxp4/lib/python/networkx/algorithms/assortativity/pairs.pyrs*"   outinc #sdur t|nt|r!|j|jd}||}||}n|j}}||dD] \}} fdd||D} || |dD] \} } | | fVqBq,dS)aGenerate node degree-degree pairs for edges in G. Parameters ---------- G: NetworkX graph x: string ('in','out') The degree type for source node (directed graphs only). y: string ('in','out') The degree type for target node (directed graphs only). 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. nodes: list or iterable (optional) Use only edges that are adjacency to specified nodes. The default is all nodes. Returns ------- (x, y): 2-tuple Generates 2-tuple of (degree, degree) values. Examples -------- >>> G = nx.DiGraph() >>> G.add_edge(1, 2) >>> list(nx.node_degree_xy(G, x="out", y="in")) [(1, 1)] >>> list(nx.node_degree_xy(G, x="in", y="out")) [(0, 0)] Notes ----- For undirected graphs each edge is produced twice, once for each edge representation (u, v) and (v, u), with the exception of self-loop edges which only appear once. N)rr)weightc3s |] \}}|vr|VqdSNr).0rnbrrrr psz!node_degree_xy..)r is_directed out_degree in_degreedegreeedges) r xyrr directionxdegydegr degu neighborsrdegvrrrr;s+   r)rrNN)__doc____all__rrrrrrs 6