animating pngs in matplotlib using artistanimation

You need to store your animation object in a variable:

my_anim = animation.ArtistAnimation(fig, myimages, interval = 100)

Here is the modified code:

import matplotlib.pyplot as plt
import matplotlib.image as mgimg
from matplotlib
import animation

fig = plt.figure()

# initiate an empty list of "plotted"
images
myimages = []

#loops through available png: s
for p in range(1, 4):

   # # Read in picture
fname = "heatflow%03d.png" % p
img = mgimg.imread(fname)
imgplot = plt.imshow(img)

# append AxesImage object to the list
myimages.append([imgplot])

# # create an instance of animation
my_anim = animation.ArtistAnimation(fig, myimages, interval = 1000, blit = True, repeat_delay = 1000)

# # NB: The 'save'
method here belongs to the object you created above
#my_anim.save("animation.mp4")

# # Showtime!
   plt.show()

Here is the second code:

from matplotlib
import pyplot as plt
from matplotlib
import animation
import matplotlib.image as mgimg
import numpy as np

#set up the figure
fig = plt.figure()
ax = plt.gca()

#initialization of animation, plot array of zeros
def init():
   imobj.set_data(np.zeros((100, 100)))

return imobj,

   def animate(i):
   # # Read in picture
fname = "heatflow%03d.png" % i

# # here I use[-1::-1], to invert the array
# IOtherwise it plots up - side down
img = mgimg.imread(fname)[-1::-1]
imobj.set_data(img)

return imobj,

   # # create an AxesImage object
imobj = ax.imshow(np.zeros((100, 100)), origin = 'lower', alpha = 1.0, zorder = 1, aspect = 1)

anim = animation.FuncAnimation(fig, animate, init_func = init, repeat = True,
   frames = range(1, 4), interval = 200, blit = True, repeat_delay = 1000)

plt.show()

It works if you user a writer like this:

Writer = animation.writers['ffmpeg']
writer = Writer(fps = 15, metadata = dict(artist = 'Me'), bitrate = 1800)
my_anim.save("animation.mp4", writer = writer)

Suggestion : 2

matplotlib.animation.ArtistAnimation , matplotlib.animation.MovieWriterRegistry , matplotlib.animation.TimedAnimation , matplotlib.artist.Artist.set_animated

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

fig, ax = plt.subplots()

def f(x, y):
   return np.sin(x) + np.cos(y)

x = np.linspace(0, 2 * np.pi, 120)
y = np.linspace(0, 2 * np.pi, 100).reshape(-1, 1)

# ims is a list of lists, each row is a list of artists to draw in the
# current frame;
here we are just animating one artist, the image, in
# each frame
ims = []
for i in range(60):
   x += np.pi / 15.
y += np.pi / 20.
im = ax.imshow(f(x, y), animated = True)
if i == 0:
   ax.imshow(f(x, y)) # show an initial one first
ims.append([im])

ani = animation.ArtistAnimation(fig, ims, interval = 50, blit = True,
   repeat_delay = 1000)

# To save the animation, use e.g.
#
# ani.save("movie.mp4")
#
# or
#
# writer = animation.FFMpegWriter(
   # fps = 15, metadata = dict(artist = 'Me'), bitrate = 1800)
# ani.save("movie.mp4", writer = writer)

plt.show()

Suggestion : 3

You need to store your animation object in a variable: ,Without any animation instance, it will not be possible to save a figure either. This is because the save method belongs to the ArtistAnimation class. What you did was calling save from the animation module, this is what raised the error.,This requirement is specific for animation and is not consistent with other plotting function in matplotlib, where you can usually use my_plot=plt.plot() or plt.plot() indifferently. ,Issue 1: Images are not displayed

You need to store your animation object in a variable:

my_anim = animation.ArtistAnimation(fig, myimages, interval = 100)

Here is the modified code:

import matplotlib.pyplot as plt
import matplotlib.image as mgimg
from matplotlib
import animation

fig = plt.figure()

# initiate an empty list of "plotted"
images
myimages = []

#loops through available png: s
for p in range(1, 4):

   # # Read in picture
fname = "heatflow%03d.png" % p
img = mgimg.imread(fname)
imgplot = plt.imshow(img)

# append AxesImage object to the list
myimages.append([imgplot])

# # create an instance of animation
my_anim = animation.ArtistAnimation(fig, myimages, interval = 1000, blit = True, repeat_delay = 1000)

# # NB: The 'save'
method here belongs to the object you created above
#my_anim.save("animation.mp4")

# # Showtime!
   plt.show()

Here is the second code:

from matplotlib
import pyplot as plt
from matplotlib
import animation
import matplotlib.image as mgimg
import numpy as np

#set up the figure
fig = plt.figure()
ax = plt.gca()

#initialization of animation, plot array of zeros
def init():
   imobj.set_data(np.zeros((100, 100)))

return imobj,

   def animate(i):
   # # Read in picture
fname = "heatflow%03d.png" % i

# # here I use[-1::-1], to invert the array
# IOtherwise it plots up - side down
img = mgimg.imread(fname)[-1::-1]
imobj.set_data(img)

return imobj,

   # # create an AxesImage object
imobj = ax.imshow(np.zeros((100, 100)), origin = 'lower', alpha = 1.0, zorder = 1, aspect = 1)

anim = animation.FuncAnimation(fig, animate, init_func = init, repeat = True,
   frames = range(1, 4), interval = 200, blit = True, repeat_delay = 1000)

plt.show()

Suggestion : 4

Last Updated : 04 May, 2022

As we might already have guessed and as obvious as the saved file name suggests, it’s an animation of a continuously growing coil. Just as before, we first import all the modules. But this time, we import the matplotlib.animation library completely

import matplotlib.animation as animation

however, in the previous example, we imported just the FuncAnimation function from it

from matplotlib.animation
import FuncAnimation

Suggestion : 5

Consider the example from the notebook on Partial Differential Equations: (note that u and x is defined earlier and that matplotlib.pyplot is imported as plt),There are several examples on animations in Jupyter Notebook on NumFys. Here, we will briefly mention a few pitfalls and a few tricks and hints.,It is in general more inconvenient to create animations in Jupyter Notebook than in "ordinary" Python. In Jupyter notebook we need to embed the animation as HTML. This can be achieved in several ways.,An alternative method for embedding animations is by storing the animation locally (e.g. as gif, mp4 or html5) and then opening the file within the notebook. In the above example, one can store the animation in a file by using

import matplotlib.pyplot as plt
from matplotlib
import animation
from IPython.display
import display, Image

from matplotlib
import animation
from IPython.display
import HTML

# First set up the figure, the axis, and the plot element we want to animate
fig = plt.figure()
ax = plt.axes(xlim = (0, 1), ylim = (-6, 10))
line, = ax.plot([], [], lw = 1)

# Initialization
function: plot the background of each frame
def init():
   line.set_data([], [])
return line,

   # Animation
function which updates figure data.This is called sequentially
def animate(i):
   line.set_data(x, u[i,: ])
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 = Nt, interval = 20, blit = True)

plt.close(anim._fig)

# Call
function to display the animation
HTML(anim.to_html5_video())

anim.save('filename.gif', writer = 'ffmpeg')

from IPython.display
import Image
with open('filename.gif', 'rb') as file:
   display(Image(file.read()), format = 'png')