#!/usr/bin/env python
"""
pcolormesh uses a QuadMesh, a faster generalization of pcolor, but
with some restrictions.
"""

from matplotlib.mlab import linspace, meshgrid
import matplotlib.numerix as nx
from pylab import figure,show
import matplotlib.numerix.ma as ma
from matplotlib import cm, colors

n = 56
x = linspace(-1.5,1.5,n)
X,Y = meshgrid(x,x);
Qx = nx.cos(Y) - nx.cos(X)
Qz = nx.sin(Y) + nx.sin(X)
Qx = (Qx + 1.1)
Z = nx.sqrt(X**2 + Y**2)/5;
Z = (Z - nx.mlab.amin(Z)) / (nx.mlab.amax(Z) - nx.mlab.amin(Z))

# The color array can include masked values:
Zm = ma.masked_where(nx.fabs(Qz) < 0.5*nx.mlab.amax(Qz), Z)


fig = figure()
ax = fig.add_subplot(121)
ax.pcolormesh(Qx,Qz,Z)
ax.set_title('Without masked values')

ax = fig.add_subplot(122)
#  You can control the color of the masked region:
#cmap = cm.jet
#cmap.set_bad('r', 1.0)
#ax.pcolormesh(Qx,Qz,Zm, cmap=cmap)
#  Or use the default, which is transparent:
col = ax.pcolormesh(Qx,Qz,Zm)
ax.set_title('With masked values')
show()