<gh_stars>0
import networkx as nx
import matplotlib.pyplot as plt
import random

def create_graph():
	G = nx.Graph()
	G.add_nodes_from(range(1, 101)
	return G

def visualize(G, labeldict, nodesize, color):
	nx.draw(G, labels = labeldict, node_size = nodesize, node_color = color)
	plt.show()

def assign_bmi(G):
	for each in G.nodes():
		G.node[each]['name'] = random.randint(15, 40)
		G.node[each]['type'] = 'person'

def get_labels(G):
	dict1 = {}
	for each in G.nodes():
		dict1[each] = G.node[each]['name']
	return dict1

def get_size(G):
	array1 = []
	for each in G.nodes():
		if G.node[each]['type'] == 'person':
			array1.append(G.node[each]['name']*20)
		else:
			array1.append(1000)
	return array1

def add_foci_nodes(G):
	n = G.number_of_nodes()
	i = n+1
	foci_nodes = ['gym', 'eatout', 'movie_club', 'karate_club', 'yoga_club']
	for j in range(0, 5):
		G.add_node(1)
		G.node[i]['name'] = foci_nodes[j]
		G.node[i]['type'] = 'foci'
		i = i+1

def get_colors(G):
	c = []
	for each in G.nodes():
		if G.node[each]['type'] == 'person':
			if G.node[each]['name'] == 15:
				c.append('green')
			elif G.node[each]['name'] == 40:
				c.append('yellow')
			else:
				c.append('blue')
		else:
			c.append('red')
	return c

def get_persons_nodes():
	p = []
	for each in G.nodes():
		if G.node[each]['type'] == 'person':
			p.append(each)
	return p

def get_foci_nodes():
	f = []
	for each in G.nodes():
		if G.node[each]['type'] == 'foci':
			f.append(each)
	return f

def add_foci_edges():
	foci_nodes = get_foci_nodes()
	person_nodes = get_persons_nodes()
	for each in person_nodes:
		r = random.choice(foci_nodes)
		G.add_edge(each, r)

def homophily(G):
	pnodes = get_persons_nodes()
	for u in pnodes:
		for v in pnodes:
			if u != v:
				diff = abs(G.node[u]['name'] - G.node[v]['name'])
				p = float(1/(diff + 1000))
				r = random.uniform(0, 1)
				if r < p:
					G.add_edge(u, v)

G = create_graph()
assign_bmi(G)
add_foci_nodes(G)
labeldict = get_labels(G)
nodesize = get_size(G)
color_array = get_colors(G)
add_foci_edges()

visualize(G, labeldict, nodesize, color)

homophily(G)

visualize(G, labeldict, nodesize, color)

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

def create_graph():
	G = nx.Graph()
	G.add_nodes_from(range(1, 101)
	return G

def visualize(G, labeldict, nodesize, color):
	nx.draw(G, labels = labeldict, node_size = nodesize, node_color = color)
	plt.show()

def assign_bmi(G):
	for each in G.nodes():
		G.node[each]['name'] = random.randint(15, 40)
		G.node[each]['type'] = 'person'

def get_labels(G):
	dict1 = {}
	for each in G.nodes():
		dict1[each] = G.node[each]['name']
	return dict1

def get_size(G):
	array1 = []
	for each in G.nodes():
		if G.node[each]['type'] == 'person':
			array1.append(G.node[each]['name']*20)
		else:
			array1.append(1000)
	return array1

def add_foci_nodes(G):
	n = G.number_of_nodes()
	i = n+1
	foci_nodes = ['gym', 'eatout', 'movie_club', 'karate_club', 'yoga_club']
	for j in range(0, 5):
		G.add_node(1)
		G.node[i]['name'] = foci_nodes[j]
		G.node[i]['type'] = 'foci'
		i = i+1

def get_colors(G):
	c = []
	for each in G.nodes():
		if G.node[each]['type'] == 'person':
			if G.node[each]['name'] == 15:
				c.append('green')
			elif G.node[each]['name'] == 40:
				c.append('yellow')
			else:
				c.append('blue')
		else:
			c.append('red')
	return c

def get_persons_nodes():
	p = []
	for each in G.nodes():
		if G.node[each]['type'] == 'person':
			p.append(each)
	return p

def get_foci_nodes():
	f = []
	for each in G.nodes():
		if G.node[each]['type'] == 'foci':
			f.append(each)
	return f

def add_foci_edges():
	foci_nodes = get_foci_nodes()
	person_nodes = get_persons_nodes()
	for each in person_nodes:
		r = random.choice(foci_nodes)
		G.add_edge(each, r)

def homophily(G):
	pnodes = get_persons_nodes()
	for u in pnodes:
		for v in pnodes:
			if u != v:
				diff = abs(G.node[u]['name'] - G.node[v]['name'])
				p = float(1/(diff + 1000))
				r = random.uniform(0, 1)
				if r < p:
					G.add_edge(u, v)

G = create_graph()
assign_bmi(G)
add_foci_nodes(G)
labeldict = get_labels(G)
nodesize = get_size(G)
color_array = get_colors(G)
add_foci_edges()

visualize(G, labeldict, nodesize, color)

homophily(G)

visualize(G, labeldict, nodesize, color)