animated subplots using matplotlib

I have this code. I want to add a subplot to draw the cosine function. (I do not want to create a class). The second plot should be dynamically updated as well

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

def data_gen():
    t = data_gen.t
    cnt = 0
    while cnt < 1000:
        cnt+=1
        t += 0.05
        yield t, np.sin(2*np.pi*t) * np.exp(-t/10.)
data_gen.t = 0

fig, ax = plt.subplots()
line, = ax.plot([], [], lw=2)
ax.set_ylim(-1.1, 1.1)
ax.set_xlim(0, 5)
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,

ani = animation.FuncAnimation(fig, run, data_gen, blit=True, interval=10,
    repeat=False)
plt.show()

Answers:

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Method 1

Basically you can use a very similar structure as the one you have in your example. You only need to create an additional axes (subplot) and a second line object:

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

def data_gen():
    t = data_gen.t
    cnt = 0
    while cnt < 1000:
        cnt+=1
        t += 0.05
        y1 = np.sin(2*np.pi*t) * np.exp(-t/10.)
        y2 = np.cos(2*np.pi*t) * np.exp(-t/10.)
        # adapted the data generator to yield both sin and cos
        yield t, y1, y2

data_gen.t = 0

# create a figure with two subplots
fig, (ax1, ax2) = plt.subplots(2,1)

# intialize two line objects (one in each axes)
line1, = ax1.plot([], [], lw=2)
line2, = ax2.plot([], [], lw=2, color='r')
line = [line1, line2]

# the same axes initalizations as before (just now we do it for both of them)
for ax in [ax1, ax2]:
    ax.set_ylim(-1.1, 1.1)
    ax.set_xlim(0, 5)
    ax.grid()

# initialize the data arrays 
xdata, y1data, y2data = [], [], []
def run(data):
    # update the data
    t, y1, y2 = data
    xdata.append(t)
    y1data.append(y1)
    y2data.append(y2)

    # axis limits checking. Same as before, just for both axes
    for ax in [ax1, ax2]:
        xmin, xmax = ax.get_xlim()
        if t >= xmax:
            ax.set_xlim(xmin, 2*xmax)
            ax.figure.canvas.draw()

    # update the data of both line objects
    line[0].set_data(xdata, y1data)
    line[1].set_data(xdata, y2data)

    return line

ani = animation.FuncAnimation(fig, run, data_gen, blit=True, interval=10,
    repeat=False)
plt.show()

All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0