ó
    …~iî  ã                   ó`   • S r SSKrSSKJrJr  S/r\" S5      \R                  S 5       5       rg)zSemiconnectedness.é    N)Únot_implemented_forÚpairwiseÚis_semiconnectedÚ
undirectedc                 ó  ^• [        U 5      S:X  a  [        R                  " S5      e[        R                  " U 5      (       d  g[        R                  " U 5      m[        U4S j[        [        R                  " T5      5       5       5      $ )a=  Returns True if the graph is semiconnected, False otherwise.

A graph is semiconnected if and only if for any pair of nodes, either one
is reachable from the other, or they are mutually reachable.

This function uses a theorem that states that a DAG is semiconnected
if for any topological sort, for node $v_n$ in that sort, there is an
edge $(v_i, v_{i+1})$. That allows us to check if a non-DAG `G` is
semiconnected by condensing the graph: i.e. constructing a new graph `H`
with nodes being the strongly connected components of `G`, and edges
(scc_1, scc_2) if there is a edge $(v_1, v_2)$ in `G` for some
$v_1 \in scc_1$ and $v_2 \in scc_2$. That results in a DAG, so we compute
the topological sort of `H` and check if for every $n$ there is an edge
$(scc_n, scc_{n+1})$.

Parameters
----------
G : NetworkX graph
    A directed graph.

Returns
-------
semiconnected : bool
    True if the graph is semiconnected, False otherwise.

Raises
------
NetworkXNotImplemented
    If the input graph is undirected.

NetworkXPointlessConcept
    If the graph is empty.

Examples
--------
>>> G = nx.path_graph(4, create_using=nx.DiGraph())
>>> print(nx.is_semiconnected(G))
True
>>> G = nx.DiGraph([(1, 2), (3, 2)])
>>> print(nx.is_semiconnected(G))
False

See Also
--------
is_strongly_connected
is_weakly_connected
is_connected
is_biconnected
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