Decay

This example showcases:

• using a generator to drive an animation,

• changing axes limits during an animation.

Output generated via matplotlib.animation.Animation.to_jshtml.

import itertools

import matplotlib.pyplot as plt
import numpy as np

import matplotlib.animation as animation


def data_gen():
    for cnt in itertools.count():
        t = cnt / 10
        yield t, np.sin(2*np.pi*t) * np.exp(-t/10.)


def init():
    ax.set_ylim(-1.1, 1.1)
    ax.set_xlim(0, 1)
    del xdata[:]
    del ydata[:]
    line.set_data(xdata, ydata)
    return line,

fig, ax = plt.subplots()
line, = ax.plot([], [], lw=2)
ax.grid()
xdata, ydata = [], []


def run(data):
    # update the data
    t, y = data
    xdata.append(t)
    ydata.append(y)
    xmin, xmax = ax.get_xlim()

    if t >= xmax:
        ax.set_xlim(xmin, 2*xmax)
        ax.figure.canvas.draw()
    line.set_data(xdata, ydata)

    return line,

# Only save last 100 frames, but run forever
ani = animation.FuncAnimation(fig, run, data_gen, interval=100, init_func=init,
                              save_count=100)
plt.show()