Animating Network Growth with NetworkX and Matplotlib

Question

I would like to animate a graph that grows over time.

This is what I have so far:

fig = plt.figure()
ims = []
graph = nx.Graph()
for i in range(50):
    // Code to modify Graph
    nx.draw(graph, pos=nx.get_node_attributes(graph,'Position'))
    im = plt.draw()
    self.ims.append([im])
ani = animation.ArtistAnimation(fig, ims, interval=50, blit=True,repeat_delay=1000)
ani.save('dynamic_images.mp4')
plt.show()

However, I get the following error message:

 File "main.py", line 204, in <module>
    repeat_delay=1000)
  File "/usr/lib/pymodules/python2.7/matplotlib/animation.py", line 356, in __init__
    TimedAnimation.__init__(self, fig, *args, **kwargs)
  File "/usr/lib/pymodules/python2.7/matplotlib/animation.py", line 304, in __init__
    Animation.__init__(self, fig, event_source=event_source, *args, **kwargs)
  File "/usr/lib/pymodules/python2.7/matplotlib/animation.py", line 53, in __init__
    self._init_draw()
  File "/usr/lib/pymodules/python2.7/matplotlib/animation.py", line 363, in _init_draw
    artist.set_visible(False)
AttributeError: 'NoneType' object has no attribute 'set_visible'
nicomoto@nicomoto-VirtualBox:~/Desktop/CS8903-SpecialProblem/Code/

What I want is an animation, where you can see the graph growing. I can save the graph at each stage, and might be able to create an animation outside matplotlib, but is there any way of getting it work like this?

Answer 1

An improved version of bretlance's. Hope it will be helpful. It will show animations but not picture after picture.

Still don't know how the owner of the question Animate drawing networkx edges made use of matplotlib's animation

#!/usr/bin/env python
import random
import pylab
from matplotlib.pyplot import pause
import networkx as nx
pylab.ion()

graph = nx.Graph()
node_number = 0
graph.add_node(node_number, Position=(random.randrange(0, 100), random.randrange(0, 100)))

def get_fig():
    global node_number
    node_number += 1
    graph.add_node(node_number, Position=(random.randrange(0, 100), random.randrange(0, 100)))
    graph.add_edge(node_number, random.choice(graph.nodes()))
    nx.draw(graph, pos=nx.get_node_attributes(graph,'Position'))

num_plots = 50;
pylab.show()

for i in range(num_plots):

    get_fig()
    pylab.draw()
    pause(2)