Note
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Animated histogram#
Use histogram's BarContainer
to draw a bunch of rectangles for an animated
histogram.
import functools
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.animation as animation
# Setting up a random number generator with a fixed state for reproducibility.
rng = np.random.default_rng(seed=19680801)
# Fixing bin edges.
HIST_BINS = np.linspace(-4, 4, 100)
# Histogram our data with numpy.
data = rng.standard_normal(1000)
n, _ = np.histogram(data, HIST_BINS)
To animate the histogram, we need an animate
function, which generates
a random set of numbers and updates the heights of rectangles. The animate
function updates the Rectangle
patches on an instance of BarContainer
.
def animate(frame_number, bar_container):
# Simulate new data coming in.
data = rng.standard_normal(1000)
n, _ = np.histogram(data, HIST_BINS)
for count, rect in zip(n, bar_container.patches):
rect.set_height(count)
return bar_container.patches
Using hist()
allows us to get an instance of
BarContainer
, which is a collection of Rectangle
instances. Since
FuncAnimation
will only pass the frame number parameter to the animation
function, we use functools.partial
to fix the bar_container
parameter.
# Output generated via `matplotlib.animation.Animation.to_jshtml`.
fig, ax = plt.subplots()
_, _, bar_container = ax.hist(data, HIST_BINS, lw=1,
ec="yellow", fc="green", alpha=0.5)
ax.set_ylim(top=55) # set safe limit to ensure that all data is visible.
anim = functools.partial(animate, bar_container=bar_container)
ani = animation.FuncAnimation(fig, anim, 50, repeat=False, blit=True)
plt.show()
Total running time of the script: (0 minutes 13.650 seconds)