[FIXED] How do you make a matplotlib funcanimation animation out of matplotlib.image.AxesImage objects?

Issue

I have a list of matplotlib.image.AxesImage objects that are the output of a fluid model. From what I can gather these are artists and so I should be able to iterate over them using FuncAnimation and make a movie.

However, so far this has not worked, where am I going wrong:

import matplotlib.animation as animation

# frames is a list of matplotlib.image.AxesImage objects

fig = plt.figure()

def animate(frame):
    art = [frames[frame]]
    return art

ani = animation.FuncAnimation(fig,animate,frames=10)
ani.save('test_anim.mp4', fps=1, extra_args=['-vcodec', 'libx264'])

So far I am suspicious of defining the figure separately to the AxesImage objects and that I may not be returning the actual thing that can be iterated, similar to how you have to return line, in the line drawing case.

Edit1:

From what I understand so far, FuncAnimation works by calling the animation function you define which updates a particular artist (such as a line or AxisImage object). So my question should really be how to initialise and then update an AxisImage object in my scenario?

Edit2:

The answer of furas was very helpful, it turns out the real problem was that imshow does not take objects but rather the data from them. So you need frames[0].get_array!

What worked for me in the end was:

import matplotlib.animation as animation
import matplotlib as mpl

# frames is a list of matplotlib.image.AxesImage objects <- objects not data

fig = plt.figure()
ax = plt.gca()

draw_image = ax.imshow(frames[0].get_array(),animated=True)

def animate(frame):
    art = frames[frame].get_array()
    draw_image.set_array(art) 
    return draw_image

ani = animation.FuncAnimation(fig,animate,frames=len(frames),blit=True,interval=25)
plt.show()
ani.save('SQGdemo1.mp4', fps=30, extra_args=['-vcodec', 'libx264'])

Because it's pretty here is what I was trying to make (see pyqg project on Github for the code):

Solution

I use image Lenna from Wikipedia.

---

You mentioned matplotlib.image.AxesImage so I load image with Pillow and generate list of rotated images with matplotlib.image.pil_to_array()

image = Image.open('/home/furas/test/lenna.png')

frames = [
    matplotlib.image.pil_to_array(image.rotate(-angle)) for angle in range(0, 360, 10)
]   

I animate() I remove prevous image from axes, get new image from list and I draw it in axes. That's all.

def animate(number):

    # remove previous image
    ax.clear()
    
    # get new image from list
    art = frames[number % len(frames)]
    
    # display new image
    ax.imshow(art)

    #return (art,)  # I don't need it if I don't use `FuncAnimation(..., blit=True)`

I don't have to use return because I don't use FuncAnimation(..., blit=True) which gets elements and draw it faster - but I have to draw it on my own in animate.

---

Full code:

import matplotlib
import matplotlib.image
import matplotlib.animation as animation
import matplotlib.pyplot as plt
from PIL import Image


# frames is a list of matplotlib.image.AxesImage

image = Image.open('lenna.png')

frames = [
    matplotlib.image.pil_to_array(image.rotate(-angle)) for angle in range(0, 360, 10)
]    

fig = plt.figure()
ax = plt.gca()

def animate(frame):

    # remove previous image
    ax.clear()
    
    # get new image from list
    art = frames[frame % len(frames)]
    
    # display new image
    ax.imshow(art)

    #return art  # I don't need it if I don't use `FuncAnimation(..., blit=True)`

ani = animation.FuncAnimation(fig, animate, frames=36)
plt.show()

#ani.save('animated_lenna.mp4', fps=5, extra_args=['-vcodec', 'libx264'])
ani.save('animated_lenna.gif', fps=5, writer='imagemagick')

---

I create random data for plot

plot_data_x = list(range(0, 501, 25))
plot_data_y = [randint(0, 500) for x in range(21)]

And in animate() I clear plot, remove first item from list, add new item at the end, and draw it again.

# remove all from ax
ax.clear()

# remove first item from list
plot_data_y.pop(0) 

# add last item on the list
plot_data_y.append(randint(0, 500)) 

# plot all again
ax.plot(plot_data_x, plot_data_y)

---

import matplotlib
import matplotlib.image
import matplotlib.animation as animation
import matplotlib.pyplot as plt
from PIL import Image
from random import randint

# frames is a list of matplotlib.image.AxesImage

image = Image.open('/home/furas/test/lenna.png')

frames = [
    matplotlib.image.pil_to_array(image.rotate(-angle)) for angle in range(0, 360, 10)
]    

plot_data_x = list(range(0, 501, 25))
plot_data_y = [randint(0, 500) for x in range(21)]

fig = plt.figure()
ax = plt.gca()

def animate(frame):

    # remove all from ax
    ax.clear()
    
    # get new image from list
    art = frames[frame % len(frames)]
    
    # display new image
    ax.imshow(art)

    # remove first item from list
    plot_data_y.pop(0) 
    
    # add last item on list
    plot_data_y.append(randint(0, 500)) 
    
    # plot all again
    ax.plot(plot_data_x, plot_data_y)
    
    #return art  # I don't need it if I don't use `FuncAnimation(..., blit=True)`

ani = animation.FuncAnimation(fig, animate, frames=36)
plt.show()

ani.save('animated_lenna_plot.mp4', fps=5, extra_args=['-vcodec', 'libx264'])
#ani.save('animated_lenna_plot.gif', fps=5, writer='imagemagick')

---

EDIT:

Version which uses blit=True

Previous version can also write so fast animation but it can't display it so fast.

I create plot and image at start to assign them to varaibles and later update data in this object and send them back with return. And later matplot draws it much fast with blit=True

import matplotlib
import matplotlib.image
import matplotlib.animation as animation
import matplotlib.pyplot as plt
from PIL import Image
from random import randint

# frames is a list of matplotlib.image.AxesImage

image = Image.open('/home/furas/test/lenna.png')

frames = [
    matplotlib.image.pil_to_array(image.rotate(-angle)) for angle in range(0, 360, 10)
]    

plot_data_x = list(range(0, 501, 25))
plot_data_y = [randint(0, 500) for x in range(21)]

fig = plt.figure()
ax = plt.gca()

draw_image = ax.imshow(frames[0], animated=True)
draw_plot, = plt.plot(plot_data_x, plot_data_y)

def animate(frame):

    # remove all from ax
    #ax.clear()
    
    # get new image from list
    art = frames[frame % len(frames)]
    
    # display new image
    draw_image.set_array(art)

    # remove first item from list
    plot_data_y.pop(0) 
    
    # add last item on list
    plot_data_y.append(randint(0, 500)) 

    # update data in plot    
    #draw_plot.set_data(plot_data_x, plot_data_y)
    draw_plot.set_ydata(plot_data_y)
    
    return (draw_image, draw_plot) 
    
ani = animation.FuncAnimation(fig, animate, frames=36, interval=25, blit=True)
plt.show()

ani.save('animated_lenna_plot_blit.mp4', fps=50, extra_args=['-vcodec', 'libx264'])
#ani.save('animated_lenna_plot_blit.gif', fps=50, writer='imagemagick')

Answered By - furas