chore: import upstream snapshot with attribution

2026-07-13 12:36:30 +08:00
commit 55ab4e4a73
473 changed files with 72932 additions and 0 deletions
@@ -0,0 +1,89 @@
+import easygraph as eg
+
+
+__all__ = ["s_betweenness", "s_closeness", "s_eccentricity"]
+
+
+def s_betweenness(H, s=1, weight=False, n_workers=None):
+    """Computes the betweenness centrality for each edge in the hypergraph.
+
+    Computes the betweenness centrality for each edge in the hypergraph.
+
+    Parameters
+    ----------
+    H : eg.Hypergraph.
+        The hypergraph to compute
+
+    s : int, optional.
+
+    Returns
+    ----------
+    dict
+    The keys are the edges and the values are the betweenness centrality.
+    The betweenness centrality for each edge in the hypergraph.
+
+
+    """
+
+    linegraph = H.get_linegraph(s=s, weight=weight)
+    results = eg.betweenness_centrality(linegraph, n_workers=n_workers)
+    return results
+
+
+def s_closeness(H, s=1, weight=False, n_workers=None):
+    """
+    Compute the closeness centrality for each edge in the hypergraph.
+
+    Parameters
+    ----------
+    H : eg.Hypergraph.
+    s : int, optional
+
+    Returns
+    -------
+    dict. The closeness centrality for each edge in the hypergraph. The keys are the edges and the values are the closeness centrality.
+    """
+    linegraph = H.get_linegraph(s=s, weight=weight)
+    results = eg.closeness_centrality(linegraph, n_workers=n_workers)
+    return results
+
+
+def s_eccentricity(H, s=1, edges=True, source=None):
+    r"""
+    The length of the longest shortest path from a vertex $u$ to every other vertex in
+    the s-linegraph.
+    $V$ = set of vertices in the s-linegraph
+    $d$ = shortest path distance
+
+    .. math::
+
+        \text{s-ecc}(u) = \text{max}\{d(u,v): v \in V\}
+
+    Parameters
+    ----------
+    H : eg.Hypergraph
+
+    s : int, optional
+
+    edges : bool, optional
+        Indicates if method should compute edge linegraph (default) or node linegraph.
+
+    source : str, optional
+        Identifier of node or edge of interest for computing centrality
+
+    Returns
+    -------
+    dict or float
+        returns the s-eccentricity value of the edges(nodes).
+        If source=None a dictionary of values for each s-edge in H is returned.
+        If source then a single value is returned.
+        If the s-linegraph is disconnected, np.inf is returned.
+
+    """
+
+    g = H.get_linegraph(s=s)
+    result = eg.eccentricity(g)
+    if source:
+        return result[source]
+    else:
+        return result