Thank you for the suggestion, unfortunately “nearest” method for interpolation
still does interpolation to some extra cells outside of my CA grid which fall
within the convex hull.
I thought I check if there is existing functionality for that within
matplotlib, but it seems that I have to manually “map” my grid to larger
rectangular grid for plotting.
Many thanks for your response!
Masha
--
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On Nov 21, 2014, at 12:15 AM, Shahar Shani Kadmiel
<[email protected]<mailto:[email protected]>> wrote:
When using scipy.interpolate.griddada, you could use 'nearest' if your data is
sufficiently dense. This will 'map' your grid onto whatever rectangular grid
leaving grid points outside the convex hull of the original grid empty. Well,
not empty but nan.
If you do wish to interpolate your dada, you could mask the resulting
rectangular grid post interpolation.
—
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On Fri, Nov 21, 2014 at 2:12 AM, Maria Liukis
<[email protected]<mailto:[email protected]>> wrote:
Hello,
I have a problem plotting data which is defined on a grid other than
rectangular mesh, and would greatly appreciate any advise. My data is defined
for 0.1degree grid for the state of California, and I don’t want to interpolate
my data outside of the defined grid when plotting it. I used pcolormesh()
function for rectangular area maps, but it only accepts rectangular grid and I
was wondering if there is a simple solution to my problem.
The only solution I could find was to use scipy.interpolate,griddata() to “map”
my grid to a bounding rectangular grid (bounding rectangle around CA state),
but that would also interpolate my data to grid cells outside of CA state,
which I don’t want to do.
Many thanks for any hints!
Masha
--
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