In [1]:

    

%matplotlib inline

# Imports
import networkx as nx
import numpy
import matplotlib.pyplot as plt
import pandas

import seaborn; seaborn.set()
seaborn.set_style("darkgrid")

# Import widget methods
from IPython.html.widgets import *


    

    




:0: FutureWarning: IPython widgets are experimental and may change in the future.

In [2]:

    

g = nx.Graph()
print((g.number_of_nodes(), g.number_of_edges()))


    

    




(0, 0)

In [3]:

    

g.add_node("alice")
print((g.number_of_nodes(), g.number_of_edges()))


    

    




(1, 0)

In [4]:

    

g.add_node("bob")
print((g.number_of_nodes(), g.number_of_edges()))


    

    




(2, 0)

In [5]:

    

g.add_edge("alice", "bob")
print((g.number_of_nodes(), g.number_of_edges()))


    

    




(2, 1)

In [6]:

    

# Draw the random graph
g_layout = nx.spring_layout(g, iterations=1000)
nx.draw_networkx(g, pos=g_layout, node_color='#dddddd')


    

    




/data/workspace/env/local/lib/python2.7/site-packages/matplotlib/collections.py:650: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
  if self._edgecolors_original != str('face'):
/data/workspace/env/local/lib/python2.7/site-packages/matplotlib/collections.py:590: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
  if self._edgecolors == str('face'):






    

In [22]:

    

# Create a new graph
g = nx.Graph()
num_steps = 10
prob_triad = 0.1

# Iterate through time
for t in range(num_steps):
    # Draw a random number of nodes to add
    num_nodes_add = numpy.random.binomial(10, 0.25)
    num_edges_add = 0
    
    for i in range(g.number_of_nodes(), g.number_of_nodes() + num_nodes_add):
        print("adding node {0} at time step {1}".format(i, t))
        g.add_node(i)
        
        if i > 0:
            print("adding edge from {0} to {1} at time step {2}".format(i, i-1, t))
            g.add_edge(i, i-1)
            
        if i > 3:
            if numpy.random.random() < prob_triad:
                print("adding edge from {0} to {1} at time step {2}".format(i, i-1, t))
                g.add_edge(i, i-4)
    
    print((num_nodes_add, num_edges_add))


    

    




adding node 0 at time step 0
adding node 1 at time step 0
adding edge from 1 to 0 at time step 0
adding node 2 at time step 0
adding edge from 2 to 1 at time step 0
(3, 0)
adding node 3 at time step 1
adding edge from 3 to 2 at time step 1
adding node 4 at time step 1
adding edge from 4 to 3 at time step 1
adding edge from 4 to 3 at time step 1
(2, 0)
adding node 5 at time step 2
adding edge from 5 to 4 at time step 2
adding node 6 at time step 2
adding edge from 6 to 5 at time step 2
(2, 0)
adding node 7 at time step 3
adding edge from 7 to 6 at time step 3
(1, 0)
adding node 8 at time step 4
adding edge from 8 to 7 at time step 4
adding node 9 at time step 4
adding edge from 9 to 8 at time step 4
adding edge from 9 to 8 at time step 4
(2, 0)
adding node 10 at time step 5
adding edge from 10 to 9 at time step 5
adding node 11 at time step 5
adding edge from 11 to 10 at time step 5
adding node 12 at time step 5
adding edge from 12 to 11 at time step 5
adding node 13 at time step 5
adding edge from 13 to 12 at time step 5
(4, 0)
adding node 14 at time step 6
adding edge from 14 to 13 at time step 6
adding node 15 at time step 6
adding edge from 15 to 14 at time step 6
(2, 0)
adding node 16 at time step 7
adding edge from 16 to 15 at time step 7
adding node 17 at time step 7
adding edge from 17 to 16 at time step 7
adding node 18 at time step 7
adding edge from 18 to 17 at time step 7
adding node 19 at time step 7
adding edge from 19 to 18 at time step 7
adding edge from 19 to 18 at time step 7
adding node 20 at time step 7
adding edge from 20 to 19 at time step 7
(5, 0)
adding node 21 at time step 8
adding edge from 21 to 20 at time step 8
adding node 22 at time step 8
adding edge from 22 to 21 at time step 8
adding node 23 at time step 8
adding edge from 23 to 22 at time step 8
adding node 24 at time step 8
adding edge from 24 to 23 at time step 8
(4, 0)
adding node 25 at time step 9
adding edge from 25 to 24 at time step 9
adding node 26 at time step 9
adding edge from 26 to 25 at time step 9
(2, 0)

In [23]:

    

# Draw the random graph
g_layout = nx.spring_layout(g, iterations=100)
nx.draw_networkx(g, pos=g_layout, node_color='#dddddd')


    

In [24]:

    

# Get the giant component
giant_component = g.subgraph(sorted(nx.connected_components(g), key = len, reverse=True)[0])

# Draw the giant component
g_layout = nx.spring_layout(giant_component, iterations=1000)
nx.draw_networkx(giant_component, pos=g_layout, node_color='#dddddd')


    

In [32]:

    

# Create a new graph
g = nx.Graph()
num_steps = 10
prob_triad = 1.0
num_node_n = 10
num_node_p = 0.5
num_edge_p = 0.1

# Iterate through time
for t in range(num_steps):
    # Draw a random number of nodes to add
    num_nodes_add = numpy.random.binomial(n=num_node_n, p=num_node_p)
    
    for i in range(g.number_of_nodes(), g.number_of_nodes() + num_nodes_add):
        # Add the new node
        g.add_node(i)
        
        # Determine number of edges to sample
        num_edges_add = numpy.random.binomial(n=g.number_of_nodes(), p=num_edge_p)
        target_nodes = numpy.random.choice(g.nodes(), size=num_edges_add)
        
        for target_node in target_nodes:
            g.add_edge(i, target_node)
            
    print(((t, g.number_of_nodes(), g.number_of_edges())))
    
# Draw the random graph
g_layout = nx.spring_layout(g, iterations=100)
nx.draw_networkx(g, pos=g_layout, node_color='#dddddd')


    

    




(0, 7, 3)
(1, 13, 13)
(2, 19, 20)
(3, 21, 25)
(4, 27, 38)
(5, 31, 53)
(6, 35, 67)
(7, 42, 89)
(8, 50, 125)
(9, 55, 161)






    

In [34]:

    

print(len(list(nx.connected_components(g))))

# Get the giant component
giant_component = g.subgraph(sorted(nx.connected_components(g), key = len, reverse=True)[0])

# Draw the giant component
g_layout = nx.spring_layout(giant_component, iterations=1000)
nx.draw_networkx(giant_component, pos=g_layout, node_color='#dddddd')


    

    




1






    

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