Python: matplotlib - loop, clear and show different plots over the same figure

Question

I want to see how a plot varies with different values using a loop. I want to see it on the same plot. But i do not want to remains of the previous plot in the figure. In MATLAB this is possible by creating a figure and just plotting over the same figure. Closing it when the loop ends.

Like,

fh = figure();
%for loop here
%do something with x and y    
subplot(211), plot(x);
subplot(212), plot(y); 
pause(1)
%loop done
close(fh);

I am not able to find the equivalent of this in matplotlib. Usually all the questions are related to plotting different series on the same plot, which seems to come naturally on matplotlib, by plotting several series using plt.plot() and then showing them all finally using plt.show() . But I want to refresh the plot.

Answer 1

There are essentially two different ways to create animations in matplotlib

interactive mode

Turning on interactive more is done using plt.ion() . This will create a plot even though show has not yet been called. The plot can be updated by calling plt.draw() or for an animation, plt.pause() .

import matplotlib.pyplot as plt

x = [1,1]
y = [1,2]

fig, (ax1,ax2) = plt.subplots(nrows=2, sharex=True, sharey=True)
line1, = ax1.plot(x)
line2, = ax2.plot(y)
ax1.set_xlim(-1,17)
ax1.set_ylim(-400,3000)
plt.ion()

for i in range(15):
    x.append(x[-1]+x[-2])
    line1.set_data(range(len(x)), x)
    y.append(y[-1]+y[-2])
    line2.set_data(range(len(y)), y)

    plt.pause(0.1)

plt.ioff()    
plt.show()

FuncAnimation

Matplotlib provides an animation submodule , which simplifies creating animations and also allows to easily save them. The same as above, using FuncAnimation would look like:

import matplotlib.pyplot as plt
import matplotlib.animation

x = [1,1]
y = [1,2]

fig, (ax1,ax2) = plt.subplots(nrows=2, sharex=True, sharey=True)
line1, = ax1.plot(x)
line2, = ax2.plot(y)
ax1.set_xlim(-1,18)
ax1.set_ylim(-400,3000)


def update(i):
    x.append(x[-1]+x[-2])
    line1.set_data(range(len(x)), x)
    y.append(y[-1]+y[-2])
    line2.set_data(range(len(y)), y)

ani = matplotlib.animation.FuncAnimation(fig, update, frames=14, repeat=False)   
plt.show()

An example to animate a sine wave with changing frequency and its power spectrum would be the following:

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

x = np.linspace(0,24*np.pi,512)
y = np.sin(x)

def fft(x):
    fft = np.abs(np.fft.rfft(x))
    return fft**2/(fft**2).max()

fig, (ax1,ax2) = plt.subplots(nrows=2)
line1, = ax1.plot(x,y)
line2, = ax2.plot(fft(y))
ax2.set_xlim(0,50)
ax2.set_ylim(0,1)

def update(i):
    y = np.sin((i+1)/30.*x)
    line1.set_data(x,y)
    y2 = fft(y)
    line2.set_data(range(len(y2)), y2)

ani = matplotlib.animation.FuncAnimation(fig, update, frames=60, repeat=True)  
plt.show()

Answer 2

If you call plt.show() inside the loop you will see the plot for each element on the loop as long as you close the window containing the figure. The process, will be plot for the first element, then if you close the window you will see the plot for the second element in the loop, etc