Source code for networkx.algorithms.assortativity.pairs

"""Generators of  x-y pairs of node data."""
__all__ = ["node_attribute_xy", "node_degree_xy"]


[docs]def node_attribute_xy(G, attribute, nodes=None): """Returns iterator of node-attribute pairs for all edges in G. Parameters ---------- G: NetworkX graph attribute: key The node attribute key. nodes: list or iterable (optional) Use only edges that are incident to specified nodes. The default is all nodes. Returns ------- (x, y): 2-tuple Generates 2-tuple of (attribute, attribute) values. Examples -------- >>> 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. """ if nodes is None: nodes = set(G) else: nodes = set(nodes) Gnodes = G.nodes for u, nbrsdict in G.adjacency(): if u not in nodes: continue uattr = Gnodes[u].get(attribute, None) if G.is_multigraph(): for v, keys in nbrsdict.items(): vattr = Gnodes[v].get(attribute, None) for _ in keys: yield (uattr, vattr) else: for v in nbrsdict: vattr = Gnodes[v].get(attribute, None) yield (uattr, vattr)
[docs]def node_degree_xy(G, x="out", y="in", weight=None, nodes=None): """Generate 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. """ nodes = set(G) if nodes is None else set(nodes) if G.is_directed(): direction = {"out": G.out_degree, "in": G.in_degree} xdeg = direction[x] ydeg = direction[y] else: xdeg = ydeg = G.degree for u, degu in xdeg(nodes, weight=weight): # use G.edges to treat multigraphs correctly neighbors = (nbr for _, nbr in G.edges(u) if nbr in nodes) for _, degv in ydeg(neighbors, weight=weight): yield degu, degv