Bridges

• Bridges
  • Advanced: Cutting Effect

Bridges

This example shows how to compute and visualize the bridges in a graph using bridges_method(). For an example on articulation points instead, see Articulation Points.

import igraph as ig
import matplotlib.pyplot as plt

# Construct graph
g = ig.Graph(14, [(0, 1), (1, 2), (2, 3), (0, 3), (0, 2), (1, 3), (3, 4),
        (4, 5), (5, 6), (6, 4), (6, 7), (7, 8), (7, 9), (9, 10), (10 ,11),
        (11 ,7), (7, 10), (8, 9), (8, 10), (5, 12), (12, 13)])

# Find and color bridges
bridges = g.bridges()
g.es["color"] = "gray"
g.es[bridges]["color"] = "red"
g.es["width"] = 0.8
g.es[bridges]["width"] = 1.2

# Plot graph
fig, ax = plt.subplots()
ig.plot(
    g,
    target=ax,
    vertex_size=0.3,
    vertex_color="lightblue",
    vertex_label=range(g.vcount())
)
plt.show()

The plot looks like this:

Bridge edges are marked in red.

Advanced: Cutting Effect

Bridges are edges that when removed, will separate the graph into more components then they started with. To emphasise the removal of edges from the graph, we can add small “x” effect to each of the bridges by using edge labels. We add the following code to define the edge labels only for bridges:

g.es["label"] = ""
g.es[bridges]["label"] = "x"

And then when we plot…

# Plot graph
fig, ax = plt.subplots()
ig.plot(
    g,
    target=ax,
    vertex_size=0.3,
    vertex_color="lightblue",
    vertex_label=range(g.vcount()),
    edge_background="#FFF0",    # transparent background color
    edge_align_label=True,      # make sure labels are aligned with the edge
    edge_label=g.es["label"],
    edge_label_color="red"
)
plt.show()

As a result, we get:

Bridges marked with an additional “x” effect.