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Matplotlib animation

Programming / python / matplotlib

FuncAnimation is Matplotlib’s built-in way to make animations. You give it:

  • a Figure to draw on,
  • an update function that changes existing artists (lines, scatters, images) for each frame,
  • an optional init function to set the starting state,
  • and frames (how many frames or an iterable of frame values).

It repeatedly calls your update function and redraws.

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

# Data & figure
x = np.linspace(0, 2*np.pi, 400)
fig, ax = plt.subplots()
(line,) = ax.plot([], [], lw=2)   # artist to update
ax.set_xlim(0, 2*np.pi)
ax.set_ylim(-1.2, 1.2)
ax.grid(True)

def init():
    line.set_data([], [])
    return (line,)       # return a tuple/list of artists

def update(frame):
    # frame is an int (0..N-1) or any object from your frames iterable
    print(f"Frame {frame}")  # for debugging
    y = np.sin(x + 0.05*frame)
    line.set_data(x, y)  # mutate existing artist
    return (line,)

anim = FuncAnimation(
    fig, update, 
    init_func=init,
    frames=200,          # or frames=range(200) or any iterable/generator
    interval=20,         # milliseconds between frames
    blit=True            # only re-draw changed artists (faster on many backends)
)

plt.show()

Note

The callable update must return an iterable of artist when blit=True

Demo: Dynamic graph - Moving x axis

Code 
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# Source - https://stackoverflow.com/a/17903145
# Posted by tacaswell, modified by community. See post 'Timeline' for change history
# Retrieved 2026-04-13, License - CC BY-SA 3.0

import matplotlib.pylab as plt
import matplotlib.animation as animation
import numpy as np

#create image with format (time,x,y)
image = np.random.rand(100,10,10)

#setup figure
fig = plt.figure()
ax1 = fig.add_subplot(1,2,1)
ax2 = fig.add_subplot(1,2,2)
#set up viewing window (in this case the 25 most recent values)
repeat_length = (np.shape(image)[0]+1)/4
ax2.set_xlim([0,repeat_length])
#ax2.autoscale_view()
ax2.set_ylim([np.amin(image[:,5,5]),np.amax(image[:,5,5])])

#set up list of images for animation


im = ax1.imshow(image[0,:,:])
im2, = ax2.plot([], [], color=(0,0,1))

def func(n):
    im.set_data(image[n,:,:])

    im2.set_xdata(np.arange(n))
    im2.set_ydata(image[0:n, 5, 5])
    if n>repeat_length:
        lim = ax2.set_xlim(n-repeat_length, n)
    else:
        # makes it look ok when the animation loops
        lim = ax2.set_xlim(0, repeat_length)
    return im, im2

ani = animation.FuncAnimation(fig, func, frames=image.shape[0], interval=30, blit=False)

plt.show()