Complement

Complement

This example shows how to generate the complement graph of a graph (sometimes known as the anti-graph) using complementer().

First we generate a random graph

import igraph as ig
import matplotlib.pyplot as plt
import random

# Create a random graph
random.seed(0)
g1 = ig.Graph.Erdos_Renyi(n=10, p=0.5)

To compute the complement graph:

# Generate complement
g2 = g1.complementer(loops=False)

Of course, the union of the original graph and its complement creates the full graph:

g_full = g1 | g2

And the complement is a graph with the same number of vertices and no edges:

g_empty = g_full.complementer(loops=False)

To appreciate these results, we can easily plot the four graphs:

fig, axs = plt.subplots(2, 2)
ig.plot(
    g1,
    target=axs[0, 0],
    layout="circle",
    vertex_color="black",
)
axs[0, 0].set_title('Original graph')
ig.plot(
    g2,
    target=axs[0, 1],
    layout="circle",
    vertex_color="black",
)
axs[0, 1].set_title('Complement graph')

ig.plot(
    g_full,
    target=axs[1, 0],
    layout="circle",
    vertex_color="black",
)
axs[1, 0].set_title('Union graph')
ig.plot(
    g_empty,
    target=axs[1, 1],
    layout="circle",
    vertex_color="black",
)
axs[1, 1].set_title('Complement of union graph')
plt.show()

The original graph (top left), its complement (top right), their union (bottom left) and its complement (bottom right).