How to animate a pcolormesh in Matplotlib?

To animate a pcolormesh in Matplotlib, you create a pseudocolor plot and update its data over time using the FuncAnimation class. This technique is useful for visualizing time-varying 2D data like wave propagation or heat distribution.

Basic Steps

The animation process involves these key steps ?

• Create a figure and subplot

• Generate coordinate data using numpy.meshgrid()

• Create initial pcolormesh plot

• Define animation function to update data

• Use FuncAnimation to create the animation

Example

Here's a complete example animating a ripple wave pattern ?

import numpy as np
from matplotlib import pyplot as plt, animation

plt.rcParams["figure.figsize"] = [7.00, 3.50]
plt.rcParams["figure.autolayout"] = True

# Create figure and axis
fig, ax = plt.subplots()

# Create coordinate arrays
x = np.linspace(-3, 3, 91)
y = np.linspace(-3, 3, 91)
t = np.linspace(0, 25, 30)

# Create 3D meshgrid
X3, Y3, T3 = np.meshgrid(x, y, t)

# Generate time-varying wave data
sinT3 = np.sin(2 * np.pi * T3 / T3.max(axis=2)[..., np.newaxis])
G = (X3 ** 2 + Y3 ** 2) * sinT3

# Create initial pcolormesh
cax = ax.pcolormesh(x, y, G[:-1, :-1, 0], vmin=-1, vmax=1, cmap='Blues')
fig.colorbar(cax)

# Animation function
def animate(frame):
    cax.set_array(G[:-1, :-1, frame].flatten())
    return [cax]

# Create animation
anim = animation.FuncAnimation(fig, animate, interval=100, frames=len(t) - 1)
plt.show()

How It Works

Data Generation: The code creates a 3D array where the first two dimensions represent spatial coordinates and the third represents time. The wave pattern is generated using (X² + Y²) * sin(2?t/t_max).

Animation Function: The animate() function updates the pcolormesh data for each frame by calling set_array() with flattened 2D data from the current time slice.

Frame Updates: FuncAnimation calls the animate function repeatedly, passing the current frame number, which corresponds to the time index in our 3D array.

Key Parameters

Output

Conclusion

Animating a pcolormesh requires creating time-varying 2D data and using FuncAnimation to update the plot. The key is using set_array() to efficiently update data without recreating the entire plot each frame.