Alex Mont and Paul Kienzle just contributed a patch for more efficient

handling of quadrilateral meshes, which supports non-rectangular

meshes.

http://peds-pc311.bsd.uchicago.edu/misc/quadmesh.png

Right now this is *Agg only, but I think/hope they will be adding

support for other backends in the near future.

Their original patch with detailed description can be found here

https://sourceforge.net/tracker/index.php?func=detail&aid=1409190&group_id=80706&atid=560722

and I just committed this to CVS.

Combined with Nicholas Young's nonuniform image, this provides some

new alternatives to those needing efficient pseudo-color plots (see

http://www.nabble.com/interpolated-pcolor-image-t659211.html for a

NonuniformImage example)

Thus we now have

pcolor - rectangular, possibly nonuniform mesh with optional facets.

Slow for large grids. No interpolation.

pcolormesh - Arbitrary quadrilateral meshes, agg only, faster than

pcolor and more efficient in memory. No interpolation.

imshow - Pseudocolor plots with interpolation but no faceting. Faster

than pcolor or pcolormesh

NonUniformImage - uses image machinery but supports nonuniform,

rectangular meshes with interpolation and no faceting. Again,

faster than pcolor or pcolormesh.

Given the bewildering array of options, it would be nice to have a

wiki entry with examples showing when and how to use these various

classes and functions. Volunteers welcome; a good starting point

would be this email and the example from the nonuniform image link

above and the discussion by Alex and Paul on the link at the

sourceforge site.

Here is a quadrilateral mesh example, which is now

examples/quadmesh_demo.py in CVS.

from matplotlib.mlab import linspace, meshgrid

import matplotlib.numerix as nx

from pylab import figure,show

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))

fig = figure()

ax = fig.add_subplot(111)

ax.pcolormesh(Qx,Qz,Z)

show()