FuncAnimation

The inner workings of FuncAnimation is more-or-less:

for d in frames:
   artists = func(d, *fargs)
   fig.canvas.draw_idle()
   fig.canvas.start_event_loop(interval)

with details to handle 'blitting' (to dramatically improve the live performance), to be non-blocking, not repeatedly start/stop the GUI event loop, handle repeats, multiple animated axes, and easily save the animation to a movie file.

'Blitting' is a standard technique in computer graphics. The general gist is to take an existing bit map (in our case a mostly rasterized figure) and then 'blit' one more artist on top. Thus, by managing a saved 'clean' bitmap, we can only re-draw the few artists that are changing at each frame and possibly save significant amounts of time. When we use blitting (by passing blit=True), the core loop of FuncAnimation gets a bit more complicated:

ax = fig.gca()

def update_blit(artists):
    fig.canvas.restore_region(bg_cache)
    for a in artists:
        a.axes.draw_artist(a)

    ax.figure.canvas.blit(ax.bbox)

artists = init_func()

for a in artists:
   a.set_animated(True)

fig.canvas.draw()
bg_cache = fig.canvas.copy_from_bbox(ax.bbox)

for f in frames:
    artists = func(f, *fargs)
    update_blit(artists)
    fig.canvas.start_event_loop(interval)

This is of course leaving out many details (such as updating the background when the figure is resized or fully re-drawn). However, this hopefully minimalist example gives a sense of how init_func and func are used inside of FuncAnimation and the theory of how 'blitting' works.

The expected signature on func and init_func is very simple to keep FuncAnimation out of your book keeping and plotting logic, but this means that the callable objects you pass in must know what artists they should be working on. There are several approaches to handling this, of varying complexity and encapsulation. The simplest approach, which works quite well in the case of a script, is to define the artist at a global scope and let Python sort things out. For example

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation

fig, ax = plt.subplots()
xdata, ydata = [], []
ln, = plt.plot([], [], 'ro')

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)
plt.show()

The second method is to use functools.partial to 'bind' artists to function. A third method is to use closures to build up the required artists and functions. A fourth method is to create a class.

ArtistAnimation

Examples

• Frame grabbing

Animation Base Classes

Writer Registry

A module-level registry is provided to map between the name of the writer and the class to allow a string to be passed to Animation.save instead of a writer instance.

Writer Base Classes

To reduce code duplication base classes

and mixins

are provided.

See the source code for how to easily implement new MovieWriter classes.