Triangles and cliques

This notebook illustrates clique counting and evaluation of the clustering coefficient of a graph.

from IPython.display import SVG

import numpy as np

from sknetwork.data import karate_club
from sknetwork.topology import count_triangles, get_clustering_coefficient, count_cliques
from sknetwork.visualization import visualize_graph

Triangles

graph = karate_club(metadata=True)
adjacency = graph.adjacency
position = graph.position

# graph
image = visualize_graph(adjacency, position)
SVG(image)

# number of triangles
count_triangles(adjacency)

45

# coefficient of clustering
np.round(get_clustering_coefficient(adjacency), 2)

0.26

Cliques

# number of 4-cliques
count_cliques(adjacency, 4)

11