Here’s a simple script which is a good starting point for animating a plot using matplotlib’s animation package (which, by their own admission, is really in a beta status as of matplotlib 1.1.0). I find the code needed to perform the animation more cumbersome than I’d like, but importantly, it’s not too cumbersome. In line2 50-51 of the code, where the actual animation call is made, note that

animation.FuncAnimation(fig, simPoints, simData, blit=False,
   interval=10, repeat=True)

has the user function simData as the argument for the user function simPoints. These are two functions that the user has to provide. A little staring at the code, and I think you’ll quickly be able to adapt it to suit your needs.

I don’t think of this as a great example how I eventually want to construct this site, but I think I realize that I should at least start somewhere, and perhaps when I am on sabattical and have more time to devote to this, I’ll nail down some nice structures for archiving, searching and displaying code. For now, I’ll archive the code on PasteBin  (link: SimpleAnimatedPlot.py ), and provide a local copy here (double clicking on the code selects it all):

"""
This short code snippet utilizes the new animation package in
matplotlib 1.1.0; it's the shortest snippet that I know of that can
produce an animated plot in python. I'm still hoping that the
animate package's syntax can be simplified further. 
"""
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation

def simData():
# this function is called as the argument for
# the simPoints function. This function contains
# (or defines) and iterator---a device that computes
# a value, passes it back to the main program, and then
# returns to exactly where it left off in the function upon the
# next call. I believe that one has to use this method to animate
# a function using the matplotlib animation package.
#
    t_max = 10.0
    dt = 0.05
    x = 0.0
    t = 0.0
    while t < t_max:
        x = np.sin(np.pi*t)
        t = t + dt
        yield x, t

def simPoints(simData):
    x, t = simData[0], simData[1]
    time_text.set_text(time_template%(t))
    line.set_data(t, x)
    return line, time_text

##
##   set up figure for plotting:
##
fig = plt.figure()
ax = fig.add_subplot(111)
# I'm still unfamiliar with the following line of code:
line, = ax.plot([], [], 'bo', ms=10)
ax.set_ylim(-1, 1)
ax.set_xlim(0, 10)
##
time_template = 'Time = %.1f s'    # prints running simulation time
time_text = ax.text(0.05, 0.9, '', transform=ax.transAxes)
## Now call the animation package: (simData is the user function
## serving as the argument for simPoints):
ani = animation.FuncAnimation(fig, simPoints, simData, blit=False,\
     interval=10, repeat=True)
plt.show()