LISN#

cosasi.source_inference.multiple_source.lisn.fast_multisource_lisn(I, G, t, number_sources=None)#

Greedily runs single-source LISN algorithm on each estimated infection subgraph attributable to each of the hypothesized number of sources.

Parameters
  • I (NetworkX Graph) – The infection subgraph observed at a particular time step

  • G (NetworkX Graph) – The original graph the infection process was run on. I is a subgraph of G induced by infected vertices at observation time.

  • t (int) – the observation timestep corresponding to I

  • number_sources (int or None (optional)) – if int, this is the hypothesized number of infection sources if None, estimates the number of sources

Notes

The Jordan infection center is the vertex with minimum infection eccentricity. This is described in [1] and [2].

Examples

>>> result = cosasi.multiple_source.fast_multisource_jordan_centrality(I, G)

References

1

L. Ying and K. Zhu, “On the Universality of Jordan Centers for Estimating Infection Sources in Tree Networks” IEEE Transactions of Information Theory, 2017

2

L. Ying and K. Zhu, “Diffusion Source Localization in Large Networks” Synthesis Lectures on Communication Networks, 2018