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Saved matplotlib animation file (mp4, gif) corrupted

I have a python script that animates a curve and shades the area underneath the curve. The code is pretty much the same as for the example with the sine wave below, but the time evolution of the curve is read from a file. The animation that pops up when the program is done is fine, but the mp4 that is saved has issues with the shading beneath the curve: it accumulates. This is only the case for the curve that I read from the file and not for the simple sine wave. It also doesn't work if I save it as a gif with the writer set to imagemagick.
I wonder why my particular case fails and what I could try to fix it?
Here's the working example:
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation
plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True
fig = plt.figure()
ax = plt.axes(xlim=(0, 2), ylim=(-2, 2))
line, = ax.plot([], [], lw=2)
def init():
line.set_data([], [])
return line,
def animate(i):
x = np.linspace(0, 2, 1000)
y = np.sin(2 * np.pi * (x - 0.01 * i))
line.set_data(x, y)
p = plt.fill_between(x, y, 0, facecolor="slateblue")
return line, p,
anim = animation.FuncAnimation(fig, animate, init_func=init, frames=200, interval=20, blit=True)
anim.save("testanimateion.mp4", writer='ffmpeg')
plt.show()
and a screenshot of the saved animation (it should be a wavy surface, the numerical solution of the linearized 1D shallow water equations):

Trying to make a gif in Python

I'm approximating functions with Fourier Series and I would like to make, hopefully in a simple way, an animated gif of the different approximations. With a for and plt.savefig commands I generate the different frames for the gif but I haven't been able to animate them. The idea is to obtain something like this

This can be done using matplotlib.animation.
EDIT
I'm going to show you how to plot even powers of x like x^2, x^4 and so on. take a look at following example :
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation
# Setting up the figure, the axis, and the plot element we want to animate
fig = plt.figure()
ax = plt.axes(xlim=(-10, 10), ylim=(-10, 1000))
line, = ax.plot([], [], lw=2)
# initialization method: plot the background of each frame
def init():
line.set_data([], [])
return line,
# animation method. This method will be called sequentially
pow_ = 2
def animate(i):
global pow_
x = np.linspace(-10, 10, 1000)
y = x**pow_
pow_+=2
line.set_data(x, y)
return line,
# call the animator. blit=True means only re-draw the parts that have changed.
anim = animation.FuncAnimation(fig, animate, init_func=init,
frames=10, interval=200, blit=True)
# if you want to save this animation as an mp4 file, uncomment the line bellow
# anim.save('basic_animation.mp4', fps=30, extra_args=['-vcodec', 'libx264'])
plt.show()

Matplotlib Animation: how to dynamically extend x limits?

I have a simple animation plot like so:
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation
# First set up the figure, the axis, and the plot element we want to animate
fig = plt.figure()
ax = plt.axes(xlim=(0, 100), ylim=(0, 100))
line, = ax.plot([], [], lw=2)
x = []
y = []
# initialization function: plot the background of each frame
def init():
line.set_data([], [])
return line,
# animation function. This is called sequentially
def animate(i):
x.append(i + 1)
y.append(10)
line.set_data(x, y)
return line,
# call the animator. blit=True means only re-draw the parts that have changed.
anim = animation.FuncAnimation(fig, animate, init_func=init,
frames=200, interval=20, blit=True)
plt.show()
Now, this works okay, but I want it to expand like one of the subplots in here http://www.roboticslab.ca/matplotlib-animation/ where the x-axis dynamically extends to accommodate the incoming data points.
How do I accomplish this?

I came across this problem (but for set_ylim) and I had some trial and error with the comment of #ImportanceOfBeingErnest and this is what I got, adapted to #nz_21 question.
def animate(i):
x.append(i + 1)
y.append(10)
ax.set_xlim(min(x), max(x)) #added ax attribute here
line.set_data(x, y)
return line,
# call the animator. blit=True means only re-draw the parts that have changed.
anim = animation.FuncAnimation(fig, animate, init_func=init,
frames=500, interval=20)
Actually in the web quoted by #nz_21 there is a similar solution.

There is a workaround for this even when blit=True if you send a resize event to the canvas, forcing MPL to flush the canvas. To be clear, the fact that the code in #fffff answer doesn't work with blit is a bug in the MPL codebase, but if you add fig.canvas.resize_event() after setting the new x-axis, it will work in MPL 3.1.3. Of course, you should only do this sporadically to actually get any benefit from blitting --- if you're doing it every frame, you're just performing the non-blit procedure anyway, but with extra steps.

Time dependent plot matplotlib

I would like to plot point-by-point a sine wave in Python via Matplotlib, for which, each point, is added every x milliseconds, in order to obtain a smooth animation of the drawing.
This is my attempt:
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from math import sin
fig, ax = plt.subplots()
x = [0]
line, = ax.plot(x, np.asarray(0))
def animate(i):
x.append(x[-1]+0.04)
line.set_xdata(np.asarray(x)*2*np.pi/5)
line.set_ydata(np.sin(np.asarray(x)*2*np.pi/5))
plt.draw()
def init():
line.set_ydata(np.ma.array(x, mask=True))
return line,
ani = animation.FuncAnimation(fig, animate, 10, init_func=init, interval=40, blit=True)
plt.show()
Which raises:
RuntimeError: The animation function must return a sequence of Artist objects.
What did I mistaken? What is, in your opinion, the most efficient way to obtain this effect?
PS The time axis should stay fixed and not move, so it should be wider than the plot

Firstly you are getting the error because your animate(i) is not returning anything. You need to return line,. Secondly you are not using the iin animate(i) aswell.
Here is a simple sine curve animation from https://jakevdp.github.io/blog/2012/08/18/matplotlib-animation-tutorial/:
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation
# First set up the figure, the axis, and the plot element we want to
animate
fig = plt.figure()
ax = plt.axes(xlim=(0, 2), ylim=(-2, 2))
line, = ax.plot([], [], lw=2)
# initialization function: plot the background of each frame
def init():
line.set_data([], [])
return line,
# animation function. This is called sequentially
def animate(i):
x = np.linspace(0, 2, 1000)
y = np.sin(2 * np.pi * (x - 0.01 * i))
line.set_data(x, y)
return line,
# call the animator. blit=True means only re-draw the parts that have
changed.
anim = animation.FuncAnimation(fig, animate, init_func=init,
frames=200, interval=20, blit=True)
plt.show()
There is additional inspiration in the link which might help you further.

Animate should return a sequence of artist objects:
You should add:
return line, to the end of the animate function
def animate(i):
x.append(x[-1]+0.04)
line.set_xdata(np.asarray(x)*2*np.pi/5)
line.set_ydata(np.sin(np.asarray(x)*2*np.pi/5))
return line,
Source:
Another answer
Simple Example

Matplotlib animation in for loop?

I'm trying to plot some data by animation in a for loop. I want it to wait until the animation is finished and then proceed in the for loop. Pause seems to work to allow this but sometimes the movies are very long and I want to close and move to the next one. Anybody know how I can achieve this?
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation
import time
for j in range(0,2):
fig = plt.figure(j)
mngr = plt.get_current_fig_manager()
mngr.window.setGeometry(j*256,0,256, 256)
ax = plt.axes(xlim=(0, 2), ylim=(-2, 2))
line, = ax.plot([], [], lw=2)
# initialization function: plot the background of each frame
def init():
line.set_data([], [])
return line,
# animation function. This is called sequentially
def animate(i):
x = np.linspace(0, 2, 1000)
y = np.sin(2 * np.pi * (x - 0.01 * i+j/4.))
line.set_data(x, y)
return line,
# call the animator. blit=True means only re-draw the parts that have changed.
anim = animation.FuncAnimation(fig, animate, init_func=init,
frames=200, interval=20, blit=True,repeat=False)
plt.pause(0.02*200)
plt.show(block=True)

One way is to use a KeyboardInterrupt exception to move to the next plot.
For better readability, move your plotting into a function:
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation
import time
def animate_multi(j):
fig = plt.figure(j)
mngr = plt.get_current_fig_manager()
mngr.window.setGeometry(j*256,0,256, 256)
ax = plt.axes(xlim=(0, 2), ylim=(-2, 2))
line, = ax.plot([], [], lw=2)
# initialization function: plot the background of each frame
def init():
line.set_data([], [])
return line,
# animation function. This is called sequentially
def animate(i):
x = np.linspace(0, 2, 1000)
y = np.sin(2 * np.pi * (x - 0.01 * i+j/4.))
line.set_data(x, y)
return line,
# call the animator. blit=True means only re-draw the parts that have changed.
anim = animation.FuncAnimation(fig, animate, init_func=init,
frames=200, interval=20, blit=True,repeat=False)
plt.pause(0.02*200)
plt.close()
plt.show(block=True)
Now, in your loop except KeyboardInterrup and continue to the next animation:
for j in range(5):
try:
print('Working on plot', j)
animate_multi(j)
except KeyboardInterrupt:
plt.close()
Note: You might have to press <Ctrl>-<C> twice to skip to the next animation.