Source code for easygraph.functions.centrality.ego_betweenness

__all__ = ["ego_betweenness"]
import numpy as np

from easygraph.utils import *


@not_implemented_for("multigraph")
def ego_betweenness(G, node):
    """
    ego networks are networks consisting of a single actor (ego) together with the actors they are connected to (alters) and all the links among those alters.[1]
    Burt (1992), in his book Structural Holes, provides ample evidence that having high betweenness centrality, which is highly correlated with having many structural holes, can bring benefits to ego.[1]
    Returns the betweenness centrality of a ego network whose ego is set

    Parameters
    ----------
    G : graph
    node : int

    Returns
    -------
    sum : float
        the betweenness centrality of a ego network whose ego is set

    Examples
    --------
    Returns the betwenness centrality of node 1.

    >>> ego_betweenness(G,node=1)

    Reference
    ---------
    .. [1] Martin Everett, Stephen P. Borgatti. "Ego network betweenness." Social Networks, Volume 27, Issue 1, Pages 31-38, 2005.

    """
    g = G.ego_subgraph(node)
    n = len(g) + 1
    A = np.matlib.zeros((n, n))
    for i in range(n):
        for j in range(n):
            if g.has_edge(i, j):
                A[i, j] = 1
    B = A * A
    C = 1 - A
    sum = 0
    flag = G.is_directed()
    for i in range(n):
        for j in range(n):
            if i != j and C[i, j] == 1 and B[i, j] != 0:
                sum += 1.0 / B[i, j]
    if flag == False:
        sum /= 2
    return sum