Eric,

Yes, my data is exactly how you understood it. I thought, as you are 
suggesting, to create a masked array for rectangle that bounds state of CA, to 
be used with pcolormesh(). The only existing functionality that I could find is 
griddata(), but it also interpolates data to extra cells outside of my CA grid 
(even with method=‘nearest’ to extra cells within the convex hull). It looks 
like I have to “map” my CA grid to larger rectangular grid manually, I just 
wanted to check if such functionality already exists within matplotlib, numpy 
or scipy packages, and I am just not aware of it.

I also could plot each cell with ax.add_patch(), but would imagine that it 
would be much slower. 

And thank you for mentioning basemap, I am using it for my maps :)

Thank you very much for your response!
Masha


On Nov 21, 2014, at 6:54 AM, Eric Firing <efir...@hawaii.edu> wrote:

> On 2014/11/20, 7:11 PM, Maria Liukis 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.
> 
> Masha,
> 
> When you say your data "is defined for a 0.1 degree grid", that makes it 
> sound like it is on a quadrilateral grid, so there should be no problem 
> with using pcolormesh.  Is it on 0.1 degree lon by 0.1 degree lat 
> points, but only for points within California?  Then you can make a 
> masked array with this grid for a rectangle in which the points outside 
> California are masked, and the ones inside are set to your data values. 
>  Your X and Y inputs to pcolormesh should be 2-D arrays with the 
> boundary values rather than the centers.  It sounds like you would want 
> to do all this via mpl_toolkits.basemap.Basemap so that you will end up 
> with a properly proportioned and labeled map.
> 
> Maybe I am misinterpreting your description of your data, however.
> 
> Eric
> 
>> 
>> 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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