python - Animation with pcolormesh routine in matplotlib, how do I initialize the data?

Question

I am trying to animate a pcolormesh in matplotlib. I have seen many of the examples using the package animation, most of them using a 1D plot routine, and some of them with imshow(). First, I wan to use the FuncAnimation routine. My problem is, first, that I do not know if I can initialize the plot

fig,ax = plt.subplots()
quad = ax.pcolormesh(X,Y,Z)

I have tried a few simple lines:

fig,ax = plt.subplots()
quad = ax.pcolormesh([])

def init():
    quad.set_array([])
    return quad,

def animate(ktime):  
    quad.set_array(X,Y,np.sin(Z)+ktime)
return quad,

anim = animation.FuncAnimation(fig,animate,init_func=init,frames=Ntime,interval=200,blit=True)

plt.show()

By the way, How do I set labels into and animated plot? Can I animate the title, if it is showing a number that changes in time? Thanks

Answer 1

The problem was that I was wrongly using set_array() routine. It is very important to note that you must pass a 1D array to this routine. To do so, regarding that color, pcolormesh and so on usually plots multidimensional arrays, you should use .ravel() . One more important thing: In order to animate different plots at the same time, the blitz option at animate.FuncAnimation must be False (See section "Animating selected plot elements" of this link).

Here I post the code that simple program with various subplots:

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

y, x = np.meshgrid(np.linspace(-10, 10,100), np.linspace(-10, 10,100))

z = np.sin(x)*np.sin(x)+np.sin(y)*np.sin(y)

v = np.linspace(-10, 10,100)
t = np.sin(v)*np.sin(v)
tt = np.cos(v)*np.cos(v)
###########

fig = plt.figure(figsize=(16, 8),facecolor='white')
gs = gridspec.GridSpec(5, 2)
ax1 = plt.subplot(gs[0,0])

line, = ax1.plot([],[],'b-.',linewidth=2)
ax1.set_xlim(-10,10)
ax1.set_ylim(0,1)
ax1.set_xlabel('time')
ax1.set_ylabel('amplitude')
ax1.set_title('Oscillationsssss')
time_text = ax1.text(0.02, 0.95, '', transform=ax1.transAxes)

#############################
ax2 = plt.subplot(gs[1:3,0])
quad1 = ax2.pcolormesh(x,y,z,shading='gouraud')
ax2.set_xlabel('time')
ax2.set_ylabel('amplitude')
cb2 = fig.colorbar(quad1,ax=ax2)

#########################
ax3 = plt.subplot(gs[3:,0])
quad2 = ax3.pcolormesh(x, y, z,shading='gouraud')
ax3.set_xlabel('time')
ax3.set_ylabel('amplitude')
cb3 = fig.colorbar(quad2,ax=ax3)

############################
ax4 = plt.subplot(gs[:,1])
line2, = ax4.plot(v,tt,'b',linewidth=2)
ax4.set_xlim(-10,10)
ax4.set_ylim(0,1)

def init():
    line.set_data([],[])
    line2.set_data([],[])
    quad1.set_array([])
    return line,line2,quad1

def animate(iter):
    t = np.sin(2*v-iter/(2*np.pi))*np.sin(2*v-iter/(2*np.pi))
    tt = np.cos(2*v-iter/(2*np.pi))*np.cos(2*v-iter/(2*np.pi))
    z = np.sin(x-iter/(2*np.pi))*np.sin(x-iter/(2*np.pi))+np.sin(y)*np.sin(y)
    line.set_data(v,t)
    quad1.set_array(z.ravel())
    line2.set_data(v,tt)
    return line,line2,quad1

gs.tight_layout(fig)

anim = animation.FuncAnimation(fig,animate,frames=100,interval=50,blit=False,repeat=False)
plt.show()

print 'Finished!!'