How to Use FuncAnimation in Matplotlib for Animations

Use FuncAnimation from matplotlib.animation to create animations by repeatedly calling an update function that modifies the plot. You provide the figure, update function, and number of frames to animate smoothly.

Syntax

The basic syntax of FuncAnimation is:

• fig: The Matplotlib figure object to animate.
• func: The update function called for each frame. It changes the plot elements.
• frames: Number of frames or an iterable of frame values.
• interval: Delay between frames in milliseconds.
• repeat: Whether to repeat the animation after the last frame.

python

FuncAnimation(fig, func, frames=None, init_func=None, fargs=None, save_count=None, interval=200, repeat=True, blit=False)

Example

This example shows a simple animation of a sine wave moving horizontally. The update function changes the y-data of the line for each frame.

python

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

fig, ax = plt.subplots()
x = np.linspace(0, 2 * np.pi, 200)
line, = ax.plot(x, np.sin(x))

# Update function for animation
def update(frame):
    line.set_ydata(np.sin(x + frame / 10))  # Shift sine wave
    return line,

ani = FuncAnimation(fig, update, frames=100, interval=50, blit=True)
plt.show()

Output

A window opens showing a sine wave smoothly moving to the left.

Common Pitfalls

• Not returning the updated artists (plot elements) from the update function can cause the animation not to update properly.
• For better performance, use blit=True and return the updated artists.
• For animations in Jupyter notebooks, use %matplotlib notebook or save the animation to a file.
• For infinite animations, set repeat=True. Otherwise, the animation stops after the last frame.

python

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

fig, ax = plt.subplots()
line, = ax.plot([0, 1], [0, 1])

def update(frame):
    line.set_ydata([frame, frame + 1])
    # Missing return statement here causes no update when blit=True

# Wrong: blit=True but update does not return artists
ani_wrong = FuncAnimation(fig, update, frames=10, blit=True)

# Right: return updated line

def update_correct(frame):
    line.set_ydata([frame, frame + 1])
    return line,

ani_right = FuncAnimation(fig, update_correct, frames=10, blit=True)

Quick Reference

Parameter	Description
fig	Matplotlib figure object to animate
func	Function called at each frame to update plot elements
frames	Number of frames or iterable of frame values
interval	Delay between frames in milliseconds
repeat	Whether to repeat animation after last frame
blit	Optimize drawing by only re-drawing changed parts

Key Takeaways

Use FuncAnimation with a figure and an update function to create animations.

Always return updated plot elements from the update function when using blit=True.

Set interval to control animation speed and repeat to loop the animation.

Use blit=True for better performance but ensure correct return values.

In Jupyter notebooks, use appropriate backends or save animations to files.