This script finds the the clique with the clique with the largest weight

max_weight_clique_finder.py

import matplotlib.pyplot as plt
import numpy as np
import networkx as nx

nodes = ["1", "2", "3", "4", "5"]

P = nx.Graph()
P.add_nodes_from(nodes)

weighted_edges = [
    ("1", "2", 0.11),
    ("1", "3", 3.1),
    ("1", "5", 2.25),
    ("4", "5", 0.25),
    ("2", "5", 0.2),
    ("2", "4", 0.22),
    ("2", "3", 0.2),
]

P.add_weighted_edges_from(weighted_edges)

#set up the graph layout
pos = nx.spring_layout(P, seed=1)  # Add the seed here
labels = nx.get_edge_attributes(P, "weight")

nx.draw(P, pos=pos, with_labels=True)  # add the position argument

# get edge labels
edge_labels = dict(
    [
        (
            (u, v),
            d["weight"],
        )
        for u, v, d in P.edges(data=True)
    ]
)
nx.draw_networkx_edge_labels(P, pos, edge_labels=edge_labels, font_weight="normal")


max_weight_clique=nx.max_weight_clique(P)