i agree, these examples are a great resource.
Yes, tiptop.
here's an example of how, given some data in a 2d numpy array/grid to
set the geotransform, save to a.tif, then reload and plot with MPL.
http://gist.github.com/205115
Thanks a lot for posting this. I will investigate the code.
there's a few interpolation resources in scipy/mpl, griddata in mpl is
pretty easy to use:
http://www.scipy.org/Cookbook/Matplotlib/Gridding_irregularly_spaced_data
I never really understood MPL distinction between regular and irregular
spaced data.
I mean:
Following the MPL documentation, if I have regular data points I would
never need a interpolation.
just use the surface functions.
But imagine a hydrologic or meteorological model. The data may be
provided in regular form (every 1°) but to create a vector map, you may
definately need spatial interpolation. If it was soil data, there are
complex methods to derive the best result...
Maybe my understanding of regular/irregular is wrong.
Kind regards,
Timmie
