Maintaining one colorbar for maptlotlib FuncAnimation

Question

I\'ve made a script which uses matplotlib\'s FuncAnimation function to animate a series of contour plots for paraboloid surface functions. I\'d lik

Answer 1

Here is a lazy way to add colorbar. Instead of updating colorbar object, this code delete and create all objects in fig.

N = 10 # number of color steps
vmin, vmax = 0, 10 # this should be min and max of z
V = np.linspace(vmin, vmax, N) 

fig = plt.figure()
def animate(index):
    fig.clear()
    ax = plt.subplot(1,1,1)
    zi = ml.griddata(x, y, zlist[index], xi, yi, interp='linear')
    contourplot = ax.contourf(xi, yi, zi, V, cmap=plt.cm.hsv,origin='lower')
    cbar = plt.colorbar(contourplot)
    ax.set_title('%03d'%(index))
    return ax

Answer 2

As usual, I got beaten to the punch by @ImportanceOfBeingErnest, but I have a slightly different approach, which I thinks works as well.

I created a separate axe for the color bar, and I created a standalone color bar using the example from matplotlib's documentation. This requires to know the extend of the color scale before hand though.

Then I just plot the contourf in the animation using the same colorbar and normalization.

#Generate some lists
def f(x,y,a):
    return a*(x**2+y**2)

avals = list(np.linspace(0,1,10))
xaxis = list(np.linspace(-2,2,9))
yaxis = list(np.linspace(-2,2,9))

xy = list(itertools.product(xaxis,yaxis))
xy = list(map(list,xy))
xy = np.array(xy)

x = xy[:,0]
y = xy[:,1]
x = list(x)
y = list(y)

zlist = []

for a in avals:
    z = []
    for i, xval in enumerate(x):
        z.append(f(x[i],y[i],a))
    zlist.append(z)

xi = np.linspace(min(x),max(x),len(x))
yi = np.linspace(min(y), max(y), len(y))

fig,[ax,cax] = plt.subplots(1,2, gridspec_kw={"width_ratios":[10,1]})


# Set the colormap and norm to correspond to the data for which
# the colorbar will be used.
cmap = mpl.cm.hsv
norm = mpl.colors.Normalize(vmin=0, vmax=10)

cb1 = mpl.colorbar.ColorbarBase(cax, cmap=cmap,
                                norm=norm,
                                orientation='vertical')

def animate(index):
    zi = ml.griddata(x, y, zlist[index], xi, yi, interp='linear')
    ax.clear()
    contourplot = ax.contourf(xi, yi, zi, cmap=cmap, norm=norm, origin='lower')
    #cbar = plt.colorbar(contourplot)
    ax.set_title('%03d'%(index))
    return ax

ani = animation.FuncAnimation(fig,animate,np.array([0,1,2,3,4,5,6,7,8,9]),interval=200,blit=False)

Answer 3

I guess the idea would be to create a contour plot outside the updating function once and give it a colorbar. The contour plot would then need to have defined levels and the colorrange needs to be defined.

ax.contourf(..., levels=levels, vmin=zmin, vmax=zmax)

where zmin and zmax are the minimum and maximum data to be shown, and levels is the list or array of levels to use.

Then, inside the animating function, you would only create a new contour plot with those same parameters without touching the colorbar at all.

import numpy as np
import itertools
import matplotlib.pyplot as plt
import matplotlib.mlab as ml
import matplotlib.animation as animation

def f(x,y,a):
    return a*(x**2+y**2)

avals = list(np.linspace(0,1,10))
xaxis = list(np.linspace(-2,2,9))
yaxis = list(np.linspace(-2,2,9))

xy = list(itertools.product(xaxis,yaxis))
xy = np.array(list(map(list,xy)))

x = xy[:,0]
y = xy[:,1]

zlist = []

for a in avals:
    z = []
    for i, xval in enumerate(x):
        z.append(f(x[i],y[i],a))
    zlist.append(z)

xi = np.linspace(min(x),max(x),len(x))
yi = np.linspace(min(y), max(y), len(y))

zmin = min([min(zl) for zl in zlist])
zmax = max([max(zl) for zl in zlist])
levels = np.linspace(zmin, zmax,41)
kw = dict(levels=levels, cmap=plt.cm.hsv, vmin=zmin, vmax=zmax, origin='lower')

fig,ax = plt.subplots()
zi = ml.griddata(x, y, zlist[0], xi, yi, interp='linear')
contourplot = ax.contourf(xi, yi, zi, **kw)
cbar = plt.colorbar(contourplot)

def animate(index):
    zi = ml.griddata(x, y, zlist[index], xi, yi, interp='linear')
    ax.clear()
    ax.contourf(xi, yi, zi, **kw)
    ax.set_title('%03d'%(index))


ani = animation.FuncAnimation(fig,animate,10,interval=200,blit=False)
plt.show()