pagerank_points_distribution_method.py

# -*- coding: utf-8 -*-
"""
Created on Sun Apr 11 22:13:39 2021

@author: DELL
"""

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

def add_edges():
    nodes=list(G.nodes())
    for s in nodes:
        for t in nodes:
            if s!=t:
                r=random.random()
                if r<=0.5:
                    G.add_edge(s,t)
    return G

def assign_points(G):
    nodes=list(G.nodes())
    p=[]
    for each in nodes:
        p.append(100)
    return p

def distribute_points(G, points):
    nodes=list(G.nodes())
    new_points=[]
    for i in range(len(nodes)):
        new_points.append(0) 
    for n in nodes:
        out=list(G.out_edges(n))
        if(len(out)==0):
            new_points=new_points[n]+points[n]
        else:
            share=points[n]/len(out)
            for (src,tgt) in out:
                new_points[tgt]=new_points[tgt]+share
    return new_points

def keep_distributing(points,G):
    while(1):
        new_points=distribute_points(G,points)
        print(new_points)
        points=new_points
        stop=input("Press # to stop or any other key to continue:  ")
        if stop=='#':
            break
    return new_points
def rank_by_points(final_points):
    d={}
    for i in range(len(final_points)):
        d[i]=final_points[i]
    print(sorted(d.items(),key=lambda f:f[1]))# 1 for value, 0 for key
    
#Created a directed graph
G=nx.DiGraph()
G.add_nodes_from([i for i in range(10)])
G=add_edges()

#Visualize the graph
nx.draw(G, with_labels=True)
plt.show()

#assign initial values
points=assign_points(G)
#keep distributing
final_points=keep_distributing(points, G)
rank_by_points(final_points)
#default network function
result=nx.pagerank(G)
print(sorted(result.items(),key=lambda f:f[1]))