I'm trying to animate a figure using matplotlib->FuncAnimate function. However, I'm having trouble understanding how Blit works. With each frame, I want to draw only the new data point on top of the old one. It says that using Blit it should automatically update only the values that changed. Thus, if I turn it on (blit=True) the previous data points should remain in my figure. But this is not the case. The previous data get deleted and the figure gets redraw from scratch.
In the documentation, it says that I have to return "iterable_of_artists" and the algorithm will know which data has changed. I want to just pass the new data and just plot on top of the old one. By the way, what is an "iterable_of_artists", is that just a list of objects that can be drawn? if someone could point me out to the definition, I would appreciate it.
Anyway, I have worked several base examples that show the odd behavior. In the first example, I'm turning Blit=True and drawing only the new data using the animate function. This in theory should draw on top of the old ones, but is not the case, only the new data is drawn.
import time
import random
import numpy
import matplotlib
import matplotlib.pyplot as pyplot
from matplotlib.animation import FuncAnimation
def livePlot():
fig, ax = pyplot.subplots(1,1)
ax = pyplot.axes(xlim=(0, 2), ylim=(0, 100))
line, = ax.plot([], [], 'ro') #ax.plot will return a tupple
def init():
line.set_data(0, 50)
return line, #Return is not necessary when blit=False
def animate(frame):
x = frame
y = random.randint(0, 100)
line.set_data(x,y)
return line, #Return is not necessary when blit=False
animation = FuncAnimation(
fig, animate,
init_func = init,
frames= [0.5, 1, 1.5, 2.0],
interval=1000,
repeat=False,
blit=True, # Turning on Blit
cache_frame_data = True)
pyplot.show()
if __name__ == "__main__":
livePlot()
I was able to achieve my goal by tricking the FuncAnimate method. I can use the ax and plot in each frame the new data. If I do that, the old data remains and only the new data is drawn. However, I can do that with Blit=True or Blit=False, it has no effect. So, I'm so confused on how Blit works and what would be the correct way to plot only the new data without having to create a list with all the data to plot. Passing a large list will create a large variable in memory if I have a long set of data points. Here is my workaround but I'm not sure if this is the correct way to do it or if there is a better ways of using Blit=True and just redraw the new data.
import time
import random
import numpy
import matplotlib
import matplotlib.pyplot as pyplot
from matplotlib.animation import FuncAnimation
def livePlot():
fig, ax = pyplot.subplots(1,1)
ax = pyplot.axes(xlim=(0, 2), ylim=(0, 100))
def init():
ax.plot(0, 50, 'ro')
return []
def animate(frame):
x = frame
y = random.randint(0, 100)
ax.plot(x, y, 'ro') # plotting directly on the axis. This keeps the old data
return [] # fooling the blit algorithm with an empty stream
animation = FuncAnimation(
fig, animate,
init_func = init,
frames= [0.5, 1, 1.5, 2.0],
interval=1000,
repeat=False,
blit=True,
cache_frame_data = True)
pyplot.show()
if __name__ == "__main__":
livePlot()
Related
I am trying to use matplotlib's FuncAnimation to make an animated video. Each frame is just a boolean n x n array visualised as white/black squares. I can do this successfully by defining all the arrays in advance and then going through them one by one. This uses code similar to matplotlib's example.
My items are rather large and I want to run the simulation for a long time. I thus don't want to create the entire list of arrays then go through them one by one. Instead, I want to define the animate function to do each step. Let me explain with a minimal non-working example. My actual example includes far larger arrays!
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
def create_video(n):
global X
X = np.random.binomial(1, 0.3, size = (n,n))
fig = plt.figure()
im = plt.imshow(X, cmap = plt.cm.gray)
def animate(t):
global X
X = np.roll(X, +1, axis = 0)
im.set_array(X)
anim = FuncAnimation(
fig,
animate,
frames = 100,
interval = 1000 / 30,
blit = True
)
return anim
anim = create_video(10)
This initialises some random 10 x 10 set of 0/1s then just 'rolls' it at each step. I get an error.
RuntimeError: The animation function must return a sequence of Artist objects.
If I remove the return anim, replacing it with pass, and replacing anim = create_video(10) with create_video(10), then I get a warning.
UserWarning: Animation was deleted without rendering anything. This is most likely unintended. To prevent deletion, assign the Animation to a variable that exists for as long as you need the Animation.
Clearly, I don't understand well enough FuncAnimation. What I want to happen is for the function animate to update the array X, by 'rolling' it one step, as well as doing im.set_array(X).
As explained in this answer:
As the error suggests, and as can be seen e.g. in the
simple_animation example, but also from the FuncAnimation
documentation, the init_func as well as the updating func are
supposed to return an iterable of artists to animate.
The documentation does not say that this is actually only needed when
using blit=True, but since you are using blitting here, it is
definitely needed.
So you have two ways:
add
return im,
to animate function
set blit = False in FuncAnimation
Complete Code
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
def create_video(n):
global X
X = np.random.binomial(1, 0.3, size = (n, n))
fig = plt.figure()
im = plt.imshow(X, cmap = plt.cm.gray)
def animate(t):
global X
X = np.roll(X, +1, axis = 0)
im.set_array(X)
return im,
anim = FuncAnimation(
fig,
animate,
frames = 100,
interval = 1000/30,
blit = True
)
plt.show()
return anim
anim = create_video(10)
I am making an animation in Matplotlib where new artists (specifically patches) are added every few frames, but when I run it, every frame in which a new artist is added is completely blank. I know there is some issue with the blitting since it works when I turn that off, but I need it on. I return every shape that is created or modified in each frame, just like the documentation requires. I am using the MacOSX backend.
My code looks similar to this:
from random import random
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
fig = plt.figure()
axe = fig.add_axes([0, 0, 1, 1], frameon=False)
circles = []
def update(i):
if not i % 10:
new_circle = plt.Circle((random(), random()), 0.05, color='black')
axe.add_patch(new_circle)
circles.append(new_circle)
for circle in circles:
circle.center = (random(), random())
return circles
animation = FuncAnimation(fig, update, frames=60, interval=1000/30, repeat=False, blit=True)
plt.show()
This appears to be a bug with matplotlib in the MacOSX backend, so the solution is just to work around it by using a different backend or not blitting if possible.
I have trajectory data where each vehicle has its own time to start. Each vehicle is a point in the animation. So, in the dataset, for each row there is coordinate point (x,y) along with a timestamp. So, fixed time interval would not work for me. I tried with loop and sleep but it not showing the animation but only the first result. But if debug line by line, it seems okay(updating with new points after each iteration). Here is my code (this is to test: loop, sleep and animation):
#sample data
x=[20,23,25,27,29,31]
y=[10,12,14,16,17,19]
t=[2,5,1,4,3,1,]
#code
fig, ax = plt.subplots()
ax.set(xlim=(10, 90), ylim=(0, 60))
for i in range(1,6):
ax.scatter(x[:i+1], y[:i+1])
plt.show()
time.sleep(t[i])
How can get the animation effect?
The already mentioned FuncAnimation has a parameter frame that the animation function can use an index:
import matplotlib.pyplot as plt
import matplotlib.animation as anim
fig = plt.figure()
x=[20,23,25,27,29,31]
y=[10,12,14,16,17,19]
t=[2,9,1,4,3,9]
#create index list for frames, i.e. how many cycles each frame will be displayed
frame_t = []
for i, item in enumerate(t):
frame_t.extend([i] * item)
def init():
fig.clear()
#animation function
def animate(i):
#prevent autoscaling of figure
plt.xlim(15, 35)
plt.ylim( 5, 25)
#set new point
plt.scatter(x[i], y[i], c = "b")
#animate scatter plot
ani = anim.FuncAnimation(fig, animate, init_func = init,
frames = frame_t, interval = 100, repeat = True)
plt.show()
Equivalently, you could store the same frame several time in the ArtistAnimation list. Basically the flipbook approach.
Sample output:
I am trying to do the following: Plot points and store a reference in a dictionary. While animating remove points. A minimal example looks as follows:
%matplotlib qt
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
import numpy as np
import matplotlib.animation as animation
fig = plt.figure()
m = Basemap(projection='aeqd',lat_0=72,lon_0=29, resolution='l',
llcrnrlon=15, llcrnrlat=69,
urcrnrlon=41, urcrnrlat=75.6,area_thresh = 100)
pointDict=dict()
pointDict[1]=m.plot (0, 0,marker='.',label='first')[0]
pointDict[2]=m.plot (0, 0,marker='.',label='second')[0]
def init():
print ("Init")
x,y = m(30, 73)
pointDict[1].set_data(x,y)
x,y = m(31, 73)
pointDict[2].set_data(x,y)
return pointDict.values()
def animate(i):
print ("Frame {0}".format(i))
if i==2:
l=pointDict.pop(1)
print ("Removing {0}".format(l.get_label()))
l.remove()
del l
return pointDict.values()
anim = animation.FuncAnimation(plt.gcf(), animate, init_func=init,
frames=10, interval=1000, blit=True)
plt.show()
Output:
Init
Init
Frame 0
Frame 1
Frame 2
Removing first
Frame 3
Interestingly, if I am plotting just the first point (that is, remove pointDict[2]=m.plot and pointDict[2].set_data in the init function), this works. But if both are plotted, neither removing the first, nor the second point works.
Related questions brought me just as far as I am now:
Matplotlib Basemap animation
How to remove lines in a Matplotlib plot
Matplotlib animating multiple lines and text
Python, Matplotlib, plot multi-lines (array) and animation
I am using Anaconda with Python-2.7 kernel.
I found out what the problem is and want therefore to answer my question by myself:
The problem with this is somewhat unexpected the blit=True.
Obviously, blitting can be only used if the point is set within the animate function. Thus, setting the data in the init routine causes problems.
So there are two options: set blit to False, but this is not very elegant. The other option is to set the points in the first frame.
Then the init and animate functions that work are as follows:
def init():
print ("Init")
pointDict[1].set_data([],[])
pointDict[2].set_data([],[])
return pointDict.values()
def animate(i):
print ("Frame {0}".format(i))
if i==0:
print ("Init")
x,y = m(30, 73)
pointDict[1].set_data(x,y)
x,y = m(31, 73)
pointDict[2].set_data(x,y)
if i==2:
l=pointDict.pop(1)
print ("Removing {0}".format(l.get_label()))
l.remove()
del l
return pointDict.values()
anim = animation.FuncAnimation(plt.gcf(), animate, init_func=init,
frames=10, interval=1000, blit=True)
plt.show()
I would like to save an animation using Python but I get the frames superposed! I want to get the frames displayed individually.
Please here what I used:
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation
from numpy import pi, cos, sin
fig = plt.figure()
plt.axis([-1.5, 1.5,-1.5, 1.5])
ax = plt.gca()
ax.set_aspect(1)
N=100
xp = [None] * N
yp = [None] * N
def init():
# initialize an empty list of cirlces
return []
def animate(i):
xp[i]=sin(i*pi/10)
yp[i]=cos(i*pi/10)
patches = []
patches.append(ax.add_patch( plt.Circle((xp[i],yp[i]),0.02,color='b') ))
return patches
anim = animation.FuncAnimation(fig, animate, init_func=init,
frames=N-1, interval=20, blit=True)
anim.save("example.avi")
plt.show()
There are some things I'm not sure about and it really seems to be that the axis.plot() behavior and FuncAnimate() behavior are different. However, the code below works for both.
Use only one patch (in your case)
The key point from your code is that you are adding a new circle in addition to the old circles every iteration:
patches = []
patches.append(ax.add_patch( plt.Circle((xp[i],yp[i]),0.02,color='b') ))
Even though you clear the patches list, they are still stored in the axis.
Instead, just create one circle and change its position.
Clear first frame with init()
Also, init() needs to clear the patch from the base frame.
Standalone Example
from matplotlib import pyplot as plt
from matplotlib import animation
from numpy import pi, cos, sin
fig = plt.figure()
plt.axis([-1.5, 1.5, -1.5, 1.5])
ax = plt.gca()
ax.set_aspect(1)
N = 100
xp = []
yp = []
# add one patch at the beginning and then change the position
patch = plt.Circle((0, 0), 0.02, color='b')
ax.add_patch(patch)
def init():
patch.set_visible(False)
# return what you want to be cleared when axes are reset
# this actually clears even if patch not returned it so I'm not sure
# what it really does
return tuple()
def animate(i):
patch.set_visible(True) # there is probably a more efficient way to do this
# just change the position of the patch
x, y = sin(i*pi/10), cos(i*pi/10)
patch.center = x, y
# I left this. I guess you need a history of positions.
xp.append(x)
yp.append(y)
# again return what you want to be cleared after each frame
# this actually clears even if patch not returned it so I'm not sure
# what it really does
return tuple()
anim = animation.FuncAnimation(fig, animate, init_func=init,
frames=N-1, interval=20, blit=True)
# for anyone else, if you get strange errors, make sure you have ffmpeg
# on your system and its bin folder in your path or use whatever
# writer you have as: writer=animation.MencoderWriter etc...
# and then passing it to save(.., writer=writer)
anim.save('example.mp4')
plt.show()
Return values???
Regarding the return values of init() and animate(), It doesn't seem to matter what is returned. The single patch still gets moved around and drawn correctly without clearing previous ones.