matplotlib.animation
Table of Contents
The easiest way to make a live animation in matplotlib is to use one of the Animation classes.
FuncAnimation ArtistAnimation
In both cases it is critical to keep a reference to the instance object. The animation is advanced by a timer (typically from the host GUI framework) which the Animation object holds the only reference to. If you do not hold a reference to the Animation object, it (and hence the timers), will be garbage collected which will stop the animation.
To save an animation to disk use Animation.save or Animation.to_html5_video
See ani_writer_classes below for details about what movie formats are supported.
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 old 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 using 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', 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)
plt.show()The second method is to us 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.
../gallery/animation/bayes_update ../gallery/animation/double_pendulum_sgskip ../gallery/animation/dynamic_image ../gallery/animation/histogram ../gallery/animation/rain ../gallery/animation/random_walk ../gallery/animation/simple_anim ../gallery/animation/strip_chart ../gallery/animation/unchained
../gallery/animation/dynamic_image2
The provided writers fall into two broad categories: pipe-based and file-based. The pipe-based writers stream the captured frames over a pipe to an external process. The pipe-based variants tend to be more performant, but may not work on all systems.
FFMpegWriter ImageMagickFileWriter AVConvWriter
Alternatively the file-based writers save temporary files for each frame which are stitched into a single file at the end. Although slower, these writers can be easier to debug.
FFMpegFileWriter ImageMagickWriter AVConvFileWriter
Fundamentally, a MovieWriter provides a way to grab sequential frames from the same underlying ~matplotlib.figure.Figure object. The base class MovieWriter implements 3 methods and a context manager. The only difference between the pipe-based and file-based writers is in the arguments to their respective setup methods.
The setup() method is used to prepare the writer (possibly opening a pipe), successive calls to grab_frame() capture a single frame at a time and finish() finalizes the movie and writes the output file to disk. For example :
moviewriter = MovieWriter(...)
moviewriter.setup(fig=fig, 'my_movie.ext', dpi=100)
for j in range(n):
update_figure(n)
moviewriter.grab_frame()
moviewriter.finish()If using the writer classes directly (not through Animation.save), it is strongly encouraged to use the ~MovieWriter.saving context manager :
with moviewriter.saving(fig, 'myfile.mp4', dpi=100):
for j in range(n):
update_figure(n)
moviewriter.grab_frame()to ensures that setup and cleanup are performed as necessary.
../gallery/animation/frame_grabbing_sgskip
Animation TimedAnimation
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.
MovieWriterRegistry
To reduce code duplication base classes
AbstractMovieWriter MovieWriter FileMovieWriter
and mixins
AVConvBase FFMpegBase ImageMagickBase
are provided.
See the source code for how to easily implement new MovieWriter classes.
matplotlib.animation.FuncAnimation matplotlib.animation.ArtistAnimation
matplotlib.animation.AVConvFileWriter matplotlib.animation.AVConvWriter matplotlib.animation.FFMpegFileWriter matplotlib.animation.FFMpegWriter matplotlib.animation.ImageMagickFileWriter matplotlib.animation.ImageMagickWriter