:movie_camera: Matplotlib animations made easy
Easy Matplotlib Animation
Creating animations should be easy. This module makes it easy to adapt your existing visualization code to create an animation.
pip install celluloid
Follow these steps:
Figure
and create a Camera
from it:from celluloid import Camera
fig = plt.figure()
camera = Camera(fig)
plt.plot(...)
plt.fancy_stuff()
camera.snap()
animation = camera.animate()
animation.save('animation.mp4')
The entire module is less than 50 lines of code.
View videos in notebooks with IPython.
from IPython.display import HTML
animation = camera.animate()
HTML(animation.to_html5_video())
As simple as it gets.
from matplotlib import pyplot as plt
from celluloid import Camera
fig = plt.figure()
camera = Camera(fig)
for i in range(10):
plt.plot([i] * 10)
camera.snap()
animation = camera.animate()
Animation at the top.
import numpy as np
from matplotlib import pyplot as plt
from celluloid import Camera
fig, axes = plt.subplots(2)
camera = Camera(fig)
t = np.linspace(0, 2 * np.pi, 128, endpoint=False)
for i in t:
axes[0].plot(t, np.sin(t + i), color='blue')
axes[1].plot(t, np.sin(t - i), color='blue')
camera.snap()
animation = camera.animate()
Domain coloring example.
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import hsv_to_rgb
from celluloid import Camera
fig = plt.figure()
camera = Camera(fig)
for a in np.linspace(0, 2 * np.pi, 30, endpoint=False):
x = np.linspace(-3, 3, 800)
X, Y = np.meshgrid(x, x)
x = X + 1j * Y
y = (x ** 2 - 2.5) * (x - 2.5 * 1j) * (x + 2.5 * 1j) \
* (x - 2 - 1j) ** 2 / ((x - np.exp(1j * a)) ** 2
* (x - np.exp(1j * 2 * a)) ** 2)
H = np.angle(y) / (2 * np.pi) + .5
r = np.log2(1. + np.abs(y))
S = (1. + np.abs(np.sin(2. * np.pi * r))) / 2.
V = (1. + np.abs(np.cos(2. * np.pi * r))) / 2.
rgb = hsv_to_rgb(np.dstack((H, S, V)))
ax.imshow(rgb)
camera.snap()
animation = camera.animate()
import matplotlib
from matplotlib import pyplot as plt
from celluloid import Camera
fig = plt.figure()
camera = Camera(fig)
for i in range(5):
t = plt.plot(range(i, i + 5))
plt.legend(t, [f'line {i}'])
camera.snap()
animation = camera.animate()
legend
function to draw them separately.ax.text(0.5, 1.01, 'computed title', transform=ax.transAxes)
ArtistAnimation
under the hood. This means that all artists are saved to memory before the animation is constructed.Inspired by plotnine.