Matplotlib in Python - Drawing shapes and animating them

So I'm representing a token ring network (doing the simulation in SimPy), I'm a totally newbie to matplotlib, but I was told that it'd be really good for representing my simulation visually.

So I googled around and found out how to draw shapes and lines - using add_patch and add_line respectively to the axes (I believe). So now I have this output which is absolutely fine:

(can't post images yet!!) http://img137.imageshack.us/img137/7822/screenshot20100121at120.png

But I'm getting this using the pylab.show() function, and what I think I want is to achieve this using the pyl开发者_StackOverflow中文版ab.plot() function so that I can then update it as my simulation progresses using pylab.draw() afterward.

My code is as follows:

plab.ion()

plab.axes()

for circ in self.circleList:
    plab.gca().add_patch(circ)

for line in self.lineList:
    plab.gca().add_line(line)

plab.axis('scaled')
plab.show()

Where circleList and lineList are lists containing the circles and lines on the diagram

I'm probably misunderstanding something simple here, but I can't actually find any examples that aren't overtly graph based that use the plot() function.

Clarification:

How can I get that same output, using pylab.plot() instead of pylab.show() ?

Replicating your image using the plot method:

from pylab import *

points = []
points.append((-0.25, -1.0))
points.append((0.7, -0.7))
points.append((1,0))
points.append((0.7,1))
points.append((-0.25,1.2))
points.append((-1,0.5))
points.append((-1,-0.5))
points.append((-0.25, -1.0))

a_line = plot(*zip(*points))[0]
a_line.set_color('g')
a_line.set_marker('o')
a_line.set_markerfacecolor('b')
a_line.set_markersize(30)
axis([-1.5,1.5,-1.5,1.5])

show()

EDIT BASED ON COMMENTS

This uses python multiprocessing library to run the matplotlib animation in a separate process. The main process uses a queue to pass data to it which then updates the plot image.

# general imports
import random, time
from multiprocessing import Process, Queue

# for matplotlib
import random
import numpy as np
import matplotlib
matplotlib.use('GTKAgg') # do this before importing pylab

import matplotlib.pyplot as plt
from matplotlib.patches import Circle


def matplotLibAnimate(q,points):

    # set up initial plot
    fig = plt.figure()
    ax = fig.add_subplot(111)


    circles = []
    for point in points:
        ax.add_patch(Circle(point,0.1))

    a_line, = ax.plot(*zip(*points))
    a_line.set_color('g')
    a_line.set_lw(2)

    currentNode = None  
    def animate(currentNode = currentNode):
        while 1:
            newNode = q.get()
            if currentNode: currentNode.remove()
            circle = Circle(newNode,0.1)
            currentNode = ax.add_patch(circle)
            circle.set_fc('r')
            fig.canvas.draw()

    # start the animation
    import gobject
    gobject.idle_add(animate)
    plt.show()

#initial points
points = ((-0.25, -1.0),(0.7, -0.7),(1,0),(0.7,1),(-0.25,1.2),(-1,0.5),(-1,-0.5),(-0.25, -1.0))
q = Queue()
p = Process(target = matplotLibAnimate, args=(q,points,))
p.start()

# feed animation data
while 1:
    time.sleep(random.randrange(4))
    q.put(random.sample(points,1)[0])

Of course, after doing this I think you'll be better served with whatnick's image solution. I'd create my own GUI and not use matplotlibs built in widget. I'd then "animate" my GUI by generating PNGs and swapping them.

It sounds like Mark has the answer you were looking for, but if you decide to go with whatnick's approach and build an animation from individual pngs, here is the code to implement Amit's suggestion to use mencoder (from http://en.wikibooks.org/wiki/Mplayer):

mencoder mf://*.png -mf w=400:h=400 -ovc lavc -lavcopts vcodec=xvid -of avi -o output.avi

The core technique is to update the data of the elements being rendered using set_data. Then call draw(). See if your circle and line elements have set_data functions. Otherwise you can use pyvtk. The other option is to render and save the plots to png files and later build an animation from those.