issue_comments: 123305768

Pyresample is probably overkill for that case. Aggregating / decimating regular lat-lon grids could probably be done much more simply. For example

python N = 10 fac = 2 x = np.arange(N, dtype=np.float64) np.add.reduceat(x, np.arange(0,N,fac)) / fac

This gives array([ 0.5, 2.5, 4.5, 6.5, 8.5])

This type of resampling has the advantage of preserving certain integral invariants, as opposed to the nearest neighbor resampling in the example above. (Imagine if there had been lots of spatial variance below the 5 degree scale in that example--it would have been aliased horribly. That was only avoided because the original field was very smooth.) It is also very fast.

Pyresample seems best for complicated transformations from one map projection to another. I'm not sure I fully understand how xray handles grids where the coordinates are themselves 2d fields, as in this example.