| 123456789101112131415161718192021222324252627282930313233343536373839 |
- import networkx as nx
- __all__ = ["s_metric"]
- @nx._dispatch
- def s_metric(G, normalized=True):
- """Returns the s-metric of graph.
- The s-metric is defined as the sum of the products deg(u)*deg(v)
- for every edge (u,v) in G. If norm is provided construct the
- s-max graph and compute it's s_metric, and return the normalized
- s value
- Parameters
- ----------
- G : graph
- The graph used to compute the s-metric.
- normalized : bool (optional)
- Normalize the value.
- Returns
- -------
- s : float
- The s-metric of the graph.
- References
- ----------
- .. [1] Lun Li, David Alderson, John C. Doyle, and Walter Willinger,
- Towards a Theory of Scale-Free Graphs:
- Definition, Properties, and Implications (Extended Version), 2005.
- https://arxiv.org/abs/cond-mat/0501169
- """
- if normalized:
- raise nx.NetworkXError("Normalization not implemented")
- # Gmax = li_smax_graph(list(G.degree().values()))
- # return s_metric(G,normalized=False)/s_metric(Gmax,normalized=False)
- # else:
- return float(sum(G.degree(u) * G.degree(v) for (u, v) in G.edges()))
|
