wgkdZddlZddlmZddlmZgdZedejdZ edejd Z edejd Z edejd Z d Z y) zConnected components.N)not_implemented_for)arbitrary_element)number_connected_componentsconnected_components is_connectednode_connected_componentdirectedc#Kt}t|}|D])}||vst|||}|j||+yw)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)setlen _plain_bfsupdate)Gseennvcs m/home/mcse/projects/flask/flask-venv/lib/python3.12/site-packages/networkx/algorithms/components/connected.pyrrsM` 5D AA  D=1a#A KKNG s A%Ac8tdt|DS)aYReturns the number of connected components. Parameters ---------- G : NetworkX graph An undirected graph. Returns ------- n : integer Number of connected components Raises ------ NetworkXNotImplemented If G is directed. 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. c3 K|]}dywN).0ccs r z.number_connected_components..ns3Rq3 )sumr)rs rrrIsJ 3/23 33c t|}|dk(rtjdtdt ||t |Dt|k(S)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. rz-Connectivity is undefined for the null graph.c3 K|]}dywrr)rnodes rrzis_connected..sDTqDr)r nxNetworkXPointlessConceptrrrrrs rrrqsVN AAAv)) ;   DZ1.?.BCD DA NNr c.t|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. )rr r&s rr r sL aQ ##r c|j}|h}|g}|rQ|}g}|D]E}||D])}||vs|j||j|+t||k(sC|cS|rQ|S)zA fast BFS node generator)_adjaddappendr ) rrsourceadjr nextlevel thislevelrws rrrs &&C 8DI    AV (D=HHQK$$Q' (4yA~    Kr )__doc__networkxr$networkx.utils.decoratorsrutilsr__all__ _dispatchablerrrr rrr rr7s9& Z 4!4nZ #4!#4LZ *O!*OZZ $$!$$Nr