Animated graphs in ipython notebook - plot

Question

Is there a way of creating animated graphs. For example showing the same graph, with different parameters.
For example is SAGE notebook, one can write:
a = animate([circle((i,i), 1-1/(i+1), hue=i/10) for i in srange(0,2,0.2)],
xmin=0,ymin=0,xmax=2,ymax=2,figsize=[2,2])
a.show()

Answer 1

This has horrible flickering, but at least this creates a plot that animates for me. It is based on Aron's, but Aron's does not work as-is.
import time, sys
from IPython.core.display import clear_output
f, ax = plt.subplots()
n = 30
x = array([i/10.0 for i in range(n)])
y = array([sin(i) for i in x])
for i in range(5,n):
ax.plot(x[:i],y[:i])
time.sleep(0.1)
clear_output()
display(f)
ax.cla() # turn this off if you'd like to "build up" plots
plt.close()

Answer 2

Update: January 2014
Jake Vanderplas has created a Javascript-based package for matplotlib animations available here. Using it is as simple as:
# https://github.com/jakevdp/JSAnimation
from JSAnimation import examples
examples.basic_animation()
See his blog post for a more complete description and examples.
Historical answer (see goger for a correction)
Yes, the Javascript update does not correctly hold the image frame yet, so there is flicker, but you can do something quite simple using this technique:
import time, sys
from IPython.display import clear_output
f, ax = plt.subplots()
for i in range(10):
y = i/10*sin(x)
ax.plot(x,y)
time.sleep(0.5)
clear_output()
display(f)
ax.cla() # turn this off if you'd like to "build up" plots
plt.close()

Answer 3

IPython widgets let you manipulate Python objects in the kernel with GUI objects in the Notebook. You might also like Sage hosted IPython Notebooks. One problem you might have with sharing widgets or interactivity in Notebooks is that if someone else doesn't have IPython, they can't run your work. To solve that, you can use Domino to share Notebooks with widgets that others can run.
Below are three examples of widgets you can build in a Notebook using pandas to filter data, fractals, and a slider for a 3D plot. Learn more and see the code and Notebooks here.
If you want to live-stream data or set up a simulation to run as a loop, you can also stream data into plots in a Notebook. Disclaimer: I work for Plotly.

Answer 4

If you use IPython notebook, v2.0 and above support interactive widgets. You can find a good example notebook here (n.b. you need to download and run from your own machine to see the sliders).
It essentially boils down to importing interact, and then passing it a function, along with ranges for the paramters. e.g., from the second link:
In [8]:
def pltsin(f, a):
plot(x,a*sin(2*pi*x*f))
ylim(-10,10)
In [9]:
interact(pltsin, f=(1,10,0.1), a=(1,10,1));
This will produce a plot with two sliders, for f and a.

Answer 5

If you want 3D scatter plot animations, the Ipyvolume Jupyter widget is very impressive.
http://ipyvolume.readthedocs.io/en/latest/animation.html#

Answer 6

bqplot is a really good option to do this now. its built specifically for animation through python in the notebook
https://github.com/bloomberg/bqplot

Answer 7

On #goger's comment of 'horrible flickering', I found that calling clear_output(wait=True) solved my problem. The flag tells clear_output to wait to render till it has something new to render.

Answer 8

matplotlib has an animation module to do just that. However, examples provided on the site will not run as is in a notebook; you need to make a few tweaks to make it work.
Here is the example of the page below modified to work in a notebook (modifications in bold).
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
from matplotlib import rc
from IPython.display import HTML
fig, ax = plt.subplots()
xdata, ydata = [], []
ln, = plt.plot([], [], 'ro', animated=True)
def init():
ax.set_xlim(0, 2*np.pi)
ax.set_ylim(-1, 1)
return ln,
def update(frame):
xdata.append(frame)
ydata.append(np.sin(frame))
ln.set_data(xdata, ydata)
return ln,
ani = FuncAnimation(fig, update, frames=np.linspace(0, 2*np.pi, 128),
init_func=init, blit=True)
rc('animation', html='html5')
ani
# plt.show() # not needed anymore
Note that the animation in the notebook is made via a movie and that you need to have ffmpeg installed and matplotlib configured to use it.