[python #PXA-368178]: pcolormesh and contours are offset by half a grid cell?

Brian,

You are correct, there *is* an offset...for complicated reasons. Let me start 
by pointing you to the docs for pcolor (pcolormesh is just a fast version of 
pcolor):

https://matplotlib.org/api/_as_gen/matplotlib.pyplot.pcolor.html#matplotlib.pyplot.pcolor

So what that's saying is that you're *supposed* to be passing in the *corners* 
of the grid cells, NOT the centers (that makes pcolor very useful for oddly 
shaped grids, like radar data); for that to be the case, you need to be passing 
in X and Y arrays that have an extra row and column compared to the data array. 
Unfortunately (at least in my opinion), matplotlib copied some poor behavior 
from MATLAB; if you pass in X, Y, and data arrays that have dimensions of 
matching size, pcolor will silently drop the last row and column of the data 
array:

https://matplotlib.org/api/_as_gen/matplotlib.pyplot.pcolor.html#axes-pcolor-grid-orientation

I wish it didn't do this, but alas, that's the behavior we have--blame MATLAB!

So to fix this properly, you need to convert the grid centers to grid edges; 
I'm happy to help you work that out. Any chance the original data files have 1D 
lons and lats?

Ryan


> My treasured Unidata Python mavens,
> 
> It seems like pcolormesh and contour are misaligned: the contours are on the 
> lower left corners of the pixels. Apparently the contours agree with the map 
> (Brian says), so it’s all about pcolormesh being offset.
> 
> 
> We have resorted to manually subtracting 0.5 degrees latitude, but it remains 
> a discomfort:
> cf1= plt.pcolormesh((lon_2d-0.5), (lat_2d-0.5), pcp, cmap='Greens', 
> norm=norm_global, transform=ccrs.PlateCarree())
> 
> at https 
> ://github.com/bmatilla/Precip_MultiPanel/blob/master/NASANEWS_teleport.py<https://github.com/bmatilla/Precip_MultiPanel/blob/master/NASANEWS_teleport.py>
> 
> 
> --------
> 
> Any suggestions? Ring any bells?


Ticket Details
===================
Ticket ID: PXA-368178
Department: Support Python
Priority: Low
Status: Closed
===================
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