As Thomas Caswell said, check out the "tri..." functions. No need for
interpolation. This question recently reappeared on Stackoverflow and was
answered there as well:
https://stackoverflow.com/questions/27004422/contour-imshow-plot-for-irregular-x-y-z-data
2014-11-21 9:15 GMT+01:00 Shahar Shani Kadmiel <kadm...@post.bgu.ac.il>:
> 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.
>
> —
> Sent from Mailbox <https://www.dropbox.com/mailbox>
>
>
> On Fri, Nov 21, 2014 at 2:12 AM, Maria Liukis <liu...@usc.edu> 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
>> --
>> liu...@usc.edu
>>
>>
>>
>>
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