How to draw a bipartite graph

Question

if i want to simulate my network like this picture but Bipartite = 4 and increase my nodes to 600 node (n=150 l =150 s=150 and m=150) and also have 685 edges randomly...how can write simulation coding to make this network? can anyone help me ? enter code herethank you so much for your attention

also this picture coding here

import networkx as nx
import matplotlib.pyplot as plt
import random
from networkx.algorithms import bipartite
B = nx.Graph()
n = [1,2,3,4]
l = [*'abc']
B.add_nodes_from(n, bipartite=0)
B.add_nodes_from(l, bipartite=1)
B.add_edges_from([(1, "a"), (1, "b"), (2, "b"), (2, "c"), (3, "c"), (4, "a")])
pos = dict()
pos.update( (n, (1, i)) for i, n in enumerate(n) ) 
pos.update( (n, (2, i)) for i, n in enumerate(l) ) 

nx.draw_networkx(B, pos=pos)
nx.draw_networkx_nodes(B, pos=pos, nodelist=n)

plt.axis('off')
plt.show()

Answer 1

You want to draw a 4-partite graph. You can generalize your code above to draw a k-partite graph, where k=4 here, as shown below, using the following code (you can change the node color, type and font color if you want).

B = nx.Graph()

nodes = {}
k = 4
n = 150
ne = 685
e = 229 # since you want total 685 edges, you can have ~229 edges in between two 
        # adjacent sets of nodes

for i in range(k):
    nodes[i] = list(range(n*i, n*(i+1)))

for i in range(k):
    B.add_nodes_from(nodes[i], bipartite=k)

edges = []
for j in range(k-1):
    for i in range(e):
        edges.append((random.choice(nodes[j]), random.choice(nodes[j+1])))

B.add_edges_from(edges[:ne])

pos = dict()
for j in range(k):
    pos.update( (n, (j, i)) for i, n in enumerate(nodes[j]) ) 

plt.figure(figsize=(20,40))
nx.draw_networkx(B, pos=pos)

plt.axis('off')
plt.show()