Animated title in matplotlib

问题:

I can't figure out how to get an animated title working on a FuncAnimation plot (that uses blit). Based on http://jakevdp.github.io/blog/2012/08/18/matplotlib-animation-tutorial/ and Python/Matplotlib - Quickly Updating Text on Axes, I've built an animation, but the text parts just won't animate. Simplified example:

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

vls = np.linspace(0,2*2*np.pi,100)

fig=plt.figure()
img, = plt.plot(np.sin(vls))
ax = plt.axes()
ax.set_xlim([0,2*2*np.pi])
#ttl = ax.set_title('',animated=True)
ttl = ax.text(.5, 1.005, '', transform = ax.transAxes)

def init():
    ttl.set_text('')
    img.set_data([0],[0])
    return img, ttl
def func(n):
    ttl.set_text(str(n))
    img.set_data(vls,np.sin(vls+.02*n*2*np.pi))
    return img, ttl

ani = animation.FuncAnimation(fig,func,init_func=init,frames=50,interval=30,blit=True)

plt.show()

If blit=True is removed, the text shows up, but it slows way down. It seems to fail with plt.title, ax.set_title, and ax.text.

Edit: I found out why the second example in the first link worked; the text was inside the img part. If you make the above 1.005 a .99, you'll see what I mean. There probably is a way to do this with a bounding box, somehow...

回答1:

See Animating matplotlib axes/ticks and python matplotlib blit to axes or sides of the figure?

So, the problem is that in the guts of animation where the blit backgrounds are actually saved (line 792 of animation.py), it grabs what is in the axes bounding box. This makes sense when you have multiple axes being independently animated. In your case you only have one axes to worry about and we want to animate stuff outside of the axes bounding box. With a bit of monkey patching, a level of tolerance for reaching into the guts of mpl and poking around a bit, and acceptance of the quickest and dirtyest solution we can solve your problem as such:

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

def _blit_draw(self, artists, bg_cache):
    # Handles blitted drawing, which renders only the artists given instead
    # of the entire figure.
    updated_ax = []
    for a in artists:
        # If we haven't cached the background for this axes object, do
        # so now. This might not always be reliable, but it's an attempt
        # to automate the process.
        if a.axes not in bg_cache:
            # bg_cache[a.axes] = a.figure.canvas.copy_from_bbox(a.axes.bbox)
            # change here
            bg_cache[a.axes] = a.figure.canvas.copy_from_bbox(a.axes.figure.bbox)
        a.axes.draw_artist(a)
        updated_ax.append(a.axes)

    # After rendering all the needed artists, blit each axes individually.
    for ax in set(updated_ax):
        # and here
        # ax.figure.canvas.blit(ax.bbox)
        ax.figure.canvas.blit(ax.figure.bbox)

# MONKEY PATCH!!
matplotlib.animation.Animation._blit_draw = _blit_draw

vls = np.linspace(0,2*2*np.pi,100)

fig=plt.figure()
img, = plt.plot(np.sin(vls))
ax = plt.axes()
ax.set_xlim([0,2*2*np.pi])
#ttl = ax.set_title('',animated=True)
ttl = ax.text(.5, 1.05, '', transform = ax.transAxes, va='center')

def init():
    ttl.set_text('')
    img.set_data([0],[0])
    return img, ttl

def func(n):
    ttl.set_text(str(n))
    img.set_data(vls,np.sin(vls+.02*n*2*np.pi))
    return img, ttl

ani = animation.FuncAnimation(fig,func,init_func=init,frames=50,interval=30,blit=True)

plt.show()

Note that this may not work as expected if you have more than one axes in your figure. A much better solution is to expand the axes.bbox just enough to capture your title + axis tick labels. I suspect there is code someplace in mpl to do that, but I don't know where it is off the top of my head.

回答2:

To add to tcaswell's "monkey patching" solution, here is how you can add animation to the axis tick labels. Specifically, to animate the x-axis, set ax.xaxis.set_animated(True) and return ax.xaxis from the animation functions.

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

def _blit_draw(self, artists, bg_cache):
    # Handles blitted drawing, which renders only the artists given instead
    # of the entire figure.
    updated_ax = []
    for a in artists:
        # If we haven't cached the background for this axes object, do
        # so now. This might not always be reliable, but it's an attempt
        # to automate the process.
        if a.axes not in bg_cache:
            # bg_cache[a.axes] = a.figure.canvas.copy_from_bbox(a.axes.bbox)
            # change here
            bg_cache[a.axes] = a.figure.canvas.copy_from_bbox(a.axes.figure.bbox)
        a.axes.draw_artist(a)
        updated_ax.append(a.axes)

    # After rendering all the needed artists, blit each axes individually.
    for ax in set(updated_ax):
        # and here
        # ax.figure.canvas.blit(ax.bbox)
        ax.figure.canvas.blit(ax.figure.bbox)

# MONKEY PATCH!!
matplotlib.animation.Animation._blit_draw = _blit_draw

vls = np.linspace(0,2*2*np.pi,100)

fig=plt.figure()
img, = plt.plot(np.sin(vls))
ax = plt.axes()
ax.set_xlim([0,2*2*np.pi])
#ttl = ax.set_title('',animated=True)
ttl = ax.text(.5, 1.05, '', transform = ax.transAxes, va='center')

ax.xaxis.set_animated(True)

def init():
    ttl.set_text('')
    img.set_data([0],[0])
    return img, ttl, ax.xaxis

def func(n):
    ttl.set_text(str(n))
    vls = np.linspace(0.2*n,0.2*n+2*2*np.pi,100)
    img.set_data(vls,np.sin(vls))
    ax.set_xlim(vls[0],vls[-1])
    return img, ttl, ax.xaxis

ani = animation.FuncAnimation(fig,func,init_func=init,frames=60,interval=200,blit=True)

plt.show()

回答3:

If you need to fix the title, you could just update the title with:

fig.suptitle()

See the figure API document.

回答4:

You must call

plt.draw()

After

ttl.set_text(str(n))

---

Here there is a very simple example of a text-animation inside a figure "without FuncAnimation()". Try it, you will see if it is useful for you.

import matplotlib.pyplot as plt
import numpy as np
titles = np.arange(100)
plt.ion()
fig = plt.figure()
for text in titles:
    plt.clf()
    fig.text(0.5,0.5,str(text))
    plt.draw()