upxo.netops.kcmp module

Created on Fri Jun 7 11:35:01 2024

@author: Dr. Sunil Anandatheertha

upxo.netops.kcmp.calculate_rkfield_js(G1, G2)[source]

Calculate Jaccard similarity between the node sets of two graphs.

Usage

from upxo.netops.kcmp import calculate_rkfield_js

upxo.netops.kcmp.calculate_rkfield_wd(kd_tgt, kd_smp)[source]

Calculate Wasserstein distance based R-Field.

Parameters:

  • kd_tgt (Netowrk Degrees of the target grain structure)

  • kd_smp (Netowrk Degrees of the sample grain structure)

Returns:

  • r

  • Usage

  • —–

  • from upxo.netops.kcmp import calculate_rkfield_wd

upxo.netops.kcmp.calculate_rkfield_ksp(kd_tgt, kd_smp)[source]

kd: Netowrk Degree

Usage

from upxo.netops.kcmp import calculate_rkfield_ksp

upxo.netops.kcmp.calculate_rkfield_ed(kd_tgt, kd_smp)[source]

kd: Netowrk Degree

Usage

from upxo.netops.kcmp import calculate_rkfield_ed

upxo.netops.kcmp.calculate_rkfield_nlsd(kd_tgt, kd_smp, timescales=numpy.logspace)[source]

Calculates NetLSD similarity between two networks.

Parameters:

  • G1 (nx.Graph) – The first network.

  • G2 (nx.Graph) – The second network.

  • timescales (int, optional) – Number of timescales to use (default: 10).

Returns:

The NetLSD distance (lower is more similar).

Return type:

float

Usage

from upxo.netops.kcmp import calculate_rkfield_nlsd