upxo.netops.kchar module

Contains a list of definitions to enable charactyerizaion of networkx data.

Created on Fri Jun 7 11:38:09 2024

@author: Dr. Sunil Anandatheertha

upxo.netops.kchar.calculate_kdegrees(networks)[source]

Get degree distribution of every network graph in networks.

Parameters:

networks (list) – List of networkx network graphs.

Returns:

  • kd (list) – List of list of degree of every node in each network graph.

  • Data structures

  • —————

  • networks = [k1, k2, …, kp, … kP] – Where, kp: pth network graph

  • ks = [k1d, k2d, …, kid, …, knd] – Where, kid: degree distribution of ith network.

  • kid = [dn1, dn2, …, dnj,… dnJ] – Where, dnj: degree of node j.

upxo.netops.kchar.calculate_kdegrees_equalbinning(networks)[source]

Calculate the pairwise degree distributions, and equally bin them.

Parameters:
  • tgt_graph (networkx graph) – Target graon structure O(n) neighbour network graph.

  • smp_graph (networkx graph) – Sample graon structure O(n) neighbour network graph.

Returns:

  • kd_tgt (List of degree of every node in target network.)

  • kd_smp (List of degree of every node in sample network.)

  • Data structures

  • —————

  • networks = [k1, k2, …, kp, … kP] – Where, kp: pth network graph

  • ks = [k1d, k2d, …, kid, …, knd] – Where, kid: degree distribution of ith network.

  • kid = [dn1, dn2, …, dnj,… dnJ] – Where, dnj: degree of node j.

  • Explanations

  • ————

  • Some tests are sensitive to differences in the cumulative

  • distribution functions (CDFs) of the data. Directly using the raw

  • degree sequences can be misleading if the sample sizes

  • (number of nodes) differ significantly between the two networks.

  • Histograms normalize the data, providing a better representation of

  • the underlying probability distributions.