plotting a 2D animated data surface on MatPlotLib

Question

I'm trying to get an animated 2D data surface on MatPlotLib. After a bit of search on the internet, i've found an example that almost works:

from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
import numpy as np
import time

def generate(X, Y, phi):
    R = 1 - np.sqrt(X**2 + Y**2)
    return np.cos(2 * np.pi * X + phi) * R

plt.ion()
fig = plt.figure()
ax = axes3d.Axes3D(fig)

xs = np.linspace(-1, 1, 50)
ys = np.linspace(-1, 1, 50)
X, Y = np.meshgrid(xs, ys)
Z = generate(X, Y, 0.0)

wframe = None
tstart = time.time()
for phi in np.linspace(0, 360 / 2 / np.pi, 100):

    oldcol = wframe

    Z = generate(X, Y, phi)
    wframe = ax.plot_wireframe(X, Y, Z, rstride=2, cstride=2)

    # Remove old line collection before drawing
    if oldcol is not None:
        ax.collections.remove(oldcol)

    plt.draw()

print 'FPS: %f' % (100 / (time.time() - tstart))

reference: http://www.mail-archive.com/[email protected]/msg14674.html

The problem with this plot is that is not interactive, the window does not rotate. It seems the computation and/or the rendering blocks the UI

is there a better approach for animated 2D data surface plotting?

Answer 1

Use the animation module. Here is a nice tutorial.

Tweaking your code a bit,

from mpl_toolkits.mplot3d import axes3d
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation

def generate(X, Y, phi):
    R = 1 - np.sqrt(X**2 + Y**2)
    return np.cos(2 * np.pi * X + phi) * R

fig = plt.figure()
ax = axes3d.Axes3D(fig)

xs = np.linspace(-1, 1, 50)
ys = np.linspace(-1, 1, 50)
X, Y = np.meshgrid(xs, ys)
Z = generate(X, Y, 0.0)
wframe = ax.plot_wireframe(X, Y, Z, rstride=2, cstride=2)
ax.set_zlim(-1,1)

def update(i, ax, fig):
    ax.cla()
    phi = i * 360 / 2 / np.pi / 100
    Z = generate(X, Y, phi)
    wframe = ax.plot_wireframe(X, Y, Z, rstride=2, cstride=2)
    ax.set_zlim(-1,1)
    return wframe,

ani = animation.FuncAnimation(fig, update, 
        frames=xrange(100), 
        fargs=(ax, fig), interval=100)
plt.show()

Answer 2

from mpl_toolkits.mplot3d import axes3d
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation

def generate(X, Y, phi):
    R = 1 - np.sqrt(X**2 + Y**2)
    return np.cos(2 * np.pi * X + phi) * R

fig = plt.figure()
ax = axes3d.Axes3D(fig)

xs = np.linspace(-1, 1, 50)
ys = np.linspace(-1, 1, 50)
X, Y = np.meshgrid(xs, ys)
Z = generate(X, Y, 0.0)
wframe = ax.plot_wireframe(X, Y, Z, rstride=2, cstride=2)
ax.set_zlim(-1,1)

def update(i, ax, fig):
    ax.cla()
    phi = i * 360 / 2 / np.pi / 100
    Z = generate(X, Y, phi)
    wframe = ax.plot_wireframe(X, Y, Z, rstride=2, cstride=2)
    ax.set_zlim(-1,1)
    return wframe,

def xrange(x):
    return iter(range(x))

ani = animation.FuncAnimation(fig, update, frames=xrange(100), 
    fargs=(ax, fig), interval=100)
plt.show()