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    9%e<                     @   s$   d Z ddlmZ dgZdddZdS )zBBasic algorithms for breadth-first searching the nodes of a graph.   )generic_bfs_edgesbfs_beam_edgesNc                 #   s6   dkrt   fdd}t ||E dH  dS )a[  Iterates over edges in a beam search.

    The beam search is a generalized breadth-first search in which only
    the "best" *w* neighbors of the current node are enqueued, where *w*
    is the beam width and "best" is an application-specific
    heuristic. In general, a beam search with a small beam width might
    not visit each node in the graph.

    Parameters
    ----------
    G : NetworkX graph

    source : node
        Starting node for the breadth-first search; this function
        iterates over only those edges in the component reachable from
        this node.

    value : function
        A function that takes a node of the graph as input and returns a
        real number indicating how "good" it is. A higher value means it
        is more likely to be visited sooner during the search. When
        visiting a new node, only the `width` neighbors with the highest
        `value` are enqueued (in decreasing order of `value`).

    width : int (default = None)
        The beam width for the search. This is the number of neighbors
        (ordered by `value`) to enqueue when visiting each new node.

    Yields
    ------
    edge
        Edges in the beam search starting from `source`, given as a pair
        of nodes.

    Examples
    --------
    To give nodes with, for example, a higher centrality precedence
    during the search, set the `value` function to return the centrality
    value of the node:

    >>> G = nx.karate_club_graph()
    >>> centrality = nx.eigenvector_centrality(G)
    >>> source = 0
    >>> width = 5
    >>> for u, v in nx.bfs_beam_edges(G, source, centrality.get, width):
    ...     print((u, v))
    ...
    (0, 2)
    (0, 1)
    (0, 8)
    (0, 13)
    (0, 3)
    (2, 32)
    (1, 30)
    (8, 33)
    (3, 7)
    (32, 31)
    (31, 28)
    (31, 25)
    (25, 23)
    (25, 24)
    (23, 29)
    (23, 27)
    (29, 26)
    Nc                    s    t t | ddd S )av  Returns a list of the best neighbors of a node.

        `v` is a node in the graph `G`.

        The "best" neighbors are chosen according to the `value`
        function (higher is better). Only the `width` best neighbors of
        `v` are returned.

        The list returned by this function is in decreasing value as
        measured by the `value` function.

        T)keyreverseN)itersortedZ	neighbors)vGvaluewidth g/var/www/html/Darija-Ai-API/env/lib/python3.8/site-packages/networkx/algorithms/traversal/beamsearch.py
successorsN   s    z"bfs_beam_edges.<locals>.successors)lenr   )r
   sourcer   r   r   r   r	   r   r      s    C)N)__doc__Zbreadth_first_searchr   __all__r   r   r   r   r   <module>   s   