U
    A·f)  ã                   @   s`   d Z ddlZddlmZ dddgZejdd„ ƒZejedƒd	d„ ƒƒZejedƒd
d„ ƒƒZ	dS )zDegree centrality measures.é    N)Únot_implemented_forÚdegree_centralityÚin_degree_centralityÚout_degree_centralityc                    sD   t | ƒdkrdd„ | D ƒS dt | ƒd  ‰ ‡ fdd„|  ¡ D ƒ}|S )a¥  Compute the degree centrality for nodes.

    The degree centrality for a node v is the fraction of nodes it
    is connected to.

    Parameters
    ----------
    G : graph
      A networkx graph

    Returns
    -------
    nodes : dictionary
       Dictionary of nodes with degree centrality as the value.

    Examples
    --------
    >>> G = nx.Graph([(0, 1), (0, 2), (0, 3), (1, 2), (1, 3)])
    >>> nx.degree_centrality(G)
    {0: 1.0, 1: 1.0, 2: 0.6666666666666666, 3: 0.6666666666666666}

    See Also
    --------
    betweenness_centrality, load_centrality, eigenvector_centrality

    Notes
    -----
    The degree centrality values are normalized by dividing by the maximum
    possible degree in a simple graph n-1 where n is the number of nodes in G.

    For multigraphs or graphs with self loops the maximum degree might
    be higher than n-1 and values of degree centrality greater than 1
    are possible.
    é   c                 S   s   i | ]
}|d “qS ©r   © ©Ú.0Únr   r   úM/tmp/pip-unpacked-wheel-0wvcsx6h/networkx/algorithms/centrality/degree_alg.pyÚ
<dictcomp>-   s      z%degree_centrality.<locals>.<dictcomp>ç      ð?c                    s   i | ]\}}||ˆ  “qS r   r   ©r
   r   Úd©Úsr   r   r   0   s      )ÚlenZdegree©ÚGZ
centralityr   r   r   r      s
    $Z
undirectedc                    sD   t | ƒdkrdd„ | D ƒS dt | ƒd  ‰ ‡ fdd„|  ¡ D ƒ}|S )a
  Compute the in-degree centrality for nodes.

    The in-degree centrality for a node v is the fraction of nodes its
    incoming edges are connected to.

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

    Returns
    -------
    nodes : dictionary
        Dictionary of nodes with in-degree centrality as values.

    Raises
    ------
    NetworkXNotImplemented
        If G is undirected.

    Examples
    --------
    >>> G = nx.DiGraph([(0, 1), (0, 2), (0, 3), (1, 2), (1, 3)])
    >>> nx.in_degree_centrality(G)
    {0: 0.0, 1: 0.3333333333333333, 2: 0.6666666666666666, 3: 0.6666666666666666}

    See Also
    --------
    degree_centrality, out_degree_centrality

    Notes
    -----
    The degree centrality values are normalized by dividing by the maximum
    possible degree in a simple graph n-1 where n is the number of nodes in G.

    For multigraphs or graphs with self loops the maximum degree might
    be higher than n-1 and values of degree centrality greater than 1
    are possible.
    r   c                 S   s   i | ]
}|d “qS r   r   r	   r   r   r   r   _   s      z(in_degree_centrality.<locals>.<dictcomp>r   c                    s   i | ]\}}||ˆ  “qS r   r   r   r   r   r   r   b   s      )r   Z	in_degreer   r   r   r   r   4   s
    *c                    sD   t | ƒdkrdd„ | D ƒS dt | ƒd  ‰ ‡ fdd„|  ¡ D ƒ}|S )aï  Compute the out-degree centrality for nodes.

    The out-degree centrality for a node v is the fraction of nodes its
    outgoing edges are connected to.

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

    Returns
    -------
    nodes : dictionary
        Dictionary of nodes with out-degree centrality as values.

    Raises
    ------
    NetworkXNotImplemented
        If G is undirected.

    Examples
    --------
    >>> G = nx.DiGraph([(0, 1), (0, 2), (0, 3), (1, 2), (1, 3)])
    >>> nx.out_degree_centrality(G)
    {0: 1.0, 1: 0.6666666666666666, 2: 0.0, 3: 0.0}

    See Also
    --------
    degree_centrality, in_degree_centrality

    Notes
    -----
    The degree centrality values are normalized by dividing by the maximum
    possible degree in a simple graph n-1 where n is the number of nodes in G.

    For multigraphs or graphs with self loops the maximum degree might
    be higher than n-1 and values of degree centrality greater than 1
    are possible.
    r   c                 S   s   i | ]
}|d “qS r   r   r	   r   r   r   r   ‘   s      z)out_degree_centrality.<locals>.<dictcomp>r   c                    s   i | ]\}}||ˆ  “qS r   r   r   r   r   r   r   ”   s      )r   Z
out_degreer   r   r   r   r   f   s
    *)
Ú__doc__ZnetworkxZnxZnetworkx.utils.decoratorsr   Ú__all__Ú	_dispatchr   r   r   r   r   r   r   Ú<module>   s   

+0