I am sampling over the surface of a sphere. I evaluate a function at each position (like lat and lon or phi and theta)–the function I evaluate is fairly expensive. As a result I don’t want to sample like:
theta = linspace( -pi, pi, Ntheta)
phi = linspace( 0, pi/2, Nphi)
since theta will be grossly oversampled near the poles. There are a lot of solutions to this, but all require modifying the sampling near the poles. I use something I call “geodesic sampling”, but there are other approaches. See http://newsreader.mathworks.com/WebX/.ef0dfad?50@…1536…@ for some talk on the concept.
The crappy thing about working in these irregular sample spaces is that visualization is very difficult. I would be delighted to use Basemap in conjunction with these, but my understanding is that Basemap requires a regular grid. Scatter plots (with the value attribute assigned to color or marker size) are still mediocre because the user loses the sense of connectivity between the points.
Any thoughts on:
resampling an irregular grid?
displaying and graphing?
-Park