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