How to make multipartite graphs using networkx and Matplotlib?

A multipartite graph is a graph where nodes are divided into multiple disjoint sets, with edges only connecting nodes from different sets. NetworkX provides tools to create and visualize these structures using multipartite_layout() for positioning nodes in distinct layers.

Steps to Create a Multipartite Graph

• Set the figure size and adjust the padding between and around the subplots

• Create a list of subset sizes and colors for each layer

• Define a method for multilayered graph that returns a graph object

• Assign colors to nodes based on their layers

• Position the nodes in layers using multipartite_layout()

• Draw the graph with Matplotlib

• Display the figure using show() method

Example

Here's how to create a multipartite graph with 8 layers of varying sizes ?

import itertools
import matplotlib.pyplot as plt
import networkx as nx

plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True

subset_sizes = [5, 5, 4, 3, 2, 4, 4, 3]
subset_color = [
    "gold",
    "violet", 
    "violet",
    "violet",
    "violet",
    "limegreen",
    "limegreen",
    "darkorange",
]

def multilayered_graph(*subset_sizes):
    extents = nx.utils.pairwise(itertools.accumulate((0,) + subset_sizes))
    layers = [range(start, end) for start, end in extents]
    G = nx.Graph()
    for (i, layer) in enumerate(layers):
        G.add_nodes_from(layer, layer=i)
    for layer1, layer2 in nx.utils.pairwise(layers):
        G.add_edges_from(itertools.product(layer1, layer2))
    return G

G = multilayered_graph(*subset_sizes)
color = [subset_color[data["layer"]] for v, data in G.nodes(data=True)]
pos = nx.multipartite_layout(G, subset_key="layer")
nx.draw(G, pos, node_color=color, with_labels=False)

plt.axis("equal")
plt.show()

Output

How It Works

The multilayered_graph() function creates nodes in sequential ranges for each layer and connects every node in one layer to every node in adjacent layers. The multipartite_layout() arranges nodes vertically by their layer attribute, creating the characteristic layered appearance.

Key Components

• subset_sizes − Defines number of nodes in each layer

• subset_color − Assigns colors to distinguish layers

• layer attribute − Tags each node with its layer number

• itertools.product() − Creates edges between all nodes in adjacent layers

Conclusion

Multipartite graphs are useful for modeling relationships between distinct groups. Use multipartite_layout() to position nodes in layers and assign colors to distinguish different partitions visually.