a h@sdZddlZddlmZddlmZgdZedejdd Z ejd d Z edejd d Z edejddZ ddZ dS)zConnected components.N)not_implemented_for)arbitrary_element)number_connected_componentsconnected_components is_connectednode_connected_componentZdirectedccs6t}|D]&}||vr t||}|||Vq dS)aGenerate connected components. Parameters ---------- G : NetworkX graph An undirected graph Returns ------- comp : generator of sets A generator of sets of nodes, one for each component of G. Raises ------ NetworkXNotImplemented If G is directed. Examples -------- Generate a sorted list of connected components, largest first. >>> G = nx.path_graph(4) >>> nx.add_path(G, [10, 11, 12]) >>> [len(c) for c in sorted(nx.connected_components(G), key=len, reverse=True)] [4, 3] If you only want the largest connected component, it's more efficient to use max instead of sort. >>> largest_cc = max(nx.connected_components(G), key=len) To create the induced subgraph of each component use: >>> S = [G.subgraph(c).copy() for c in nx.connected_components(G)] See Also -------- strongly_connected_components weakly_connected_components Notes ----- For undirected graphs only. N)set _plain_bfsupdate)GseenvcrV/var/www/auris/lib/python3.9/site-packages/networkx/algorithms/components/connected.pyrs 0  rcCstddt|DS)a Returns the number of connected components. Parameters ---------- G : NetworkX graph An undirected graph. Returns ------- n : integer Number of connected components Examples -------- >>> G = nx.Graph([(0, 1), (1, 2), (5, 6), (3, 4)]) >>> nx.number_connected_components(G) 3 See Also -------- connected_components number_weakly_connected_components number_strongly_connected_components Notes ----- For undirected graphs only. css|] }dVqdSNr).0ccrrr fz.number_connected_components..)sumrr rrrrGsrcCs<t|dkrtddtddt|t|Dt|kS)agReturns True if the graph is connected, False otherwise. Parameters ---------- G : NetworkX Graph An undirected graph. Returns ------- connected : bool True if the graph is connected, false otherwise. Raises ------ NetworkXNotImplemented If G is directed. Examples -------- >>> G = nx.path_graph(4) >>> print(nx.is_connected(G)) True See Also -------- is_strongly_connected is_weakly_connected is_semiconnected is_biconnected connected_components Notes ----- For undirected graphs only. rzConnectivity is undefined zfor the null graph.css|] }dVqdSrr)rnoderrrrrzis_connected..)lennxZNetworkXPointlessConceptrr rrrrrris ' rcCs t||S)aReturns the set of nodes in the component of graph containing node n. Parameters ---------- G : NetworkX Graph An undirected graph. n : node label A node in G Returns ------- comp : set A set of nodes in the component of G containing node n. Raises ------ NetworkXNotImplemented If G is directed. Examples -------- >>> G = nx.Graph([(0, 1), (1, 2), (5, 6), (3, 4)]) >>> nx.node_connected_component(G, 0) # nodes of component that contains node 0 {0, 1, 2} See Also -------- connected_components Notes ----- For undirected graphs only. )r )r nrrrrs&rc Cst|j}t|}|h}|g}|rp|}g}|D]B}||D] }||vr6||||q6t||kr*|Sq*q|S)zA fast BFS node generator)Z_adjraddappend) r sourceZadjrr Z nextlevelZ thislevelrwrrrr s     r )__doc__ZnetworkxrZnetworkx.utils.decoratorsrutilsr__all__ _dispatchrrrrr rrrrs    6 ! , '