Xarray combine_by_coords return the monotonic global index error

I asked this question on Stackoverflow and someone mentioned it might be a bug.

I am trying to combine two spatial xarray datasets using combine_by_coords. These two datasets are two tiles next to each other. So there are overlapping coordinates. In the overlapping regions, the variable values of one of the datasets is nan.

I used the “combine_by_coords” with compat=‘no_conflicts’ option. However, it returns the monotonic global indexes along dimension y error. It looks like it was an issue before but it was fixed (issue 3150). So I don’t really know why I get this error. Here is an example (the netcdf tiles are here):

import xarray as xr

print(xr.__version__)
>>>0.15.1

ds1=xr.open_dataset('Tile1.nc')
ds2=xr.open_dataset('Tile2.nc')
ds = xr.combine_by_coords([ds1,ds2], compat='no_conflicts')
>>>...
 ValueError: Resulting object does not have monotonic global indexes along dimension y

[TomNicholas]

Hi @hamiddashti , based on your description then this isn’t a bug, it’s throwing the error it should be throwing given your input. However I can now see how the documentation doesn’t make it very clear as to why this is happening!

combine_by_coords and combine_nested do two things: they concatenate (using xr.concat), and they merge (using xr.merge). The concatenate step is never supposed to handle partially overlapping coordinates, and the combine functions therefore have the same restriction.

That error is an explicit rejection of the input you gave it: “you gave me overlapping coordinates, I don’t know how to concatenate those, so I’ll reject them.” Normally this makes sense - when the overlapping coordinates aren’t NaNs then it’s ambiguous as to which values to choose.

In your case then you are asking it to perform a well-defined operation, and the discussion in the docs about merging overlapping coordinates here implies that compat='no_conflicts' would handle this situation. Unfortunately that’s only for xr.merge, not xr.concat, and so it doesn’t apply for combine_by_coords either. merge deals with variables of the same size, concat joins variables of different sizes onto the ends of one another. This is definitely confusing.

It might be possible to generalise the combine functions to handle the scenario you’re describing (where the overlapping parts of the coordinates are specified entirely by the non-NaN values), but I don’t really think it’s a good idea for complexity reasons.

(Issue #3150 was about something else, an actual bug in the handling of “coordinate dimensions which do not vary between each dataset”.)

Instead, what you need to do is trim off the overlap first. That shouldn’t be hard - presumably you know (or can determine) how big your overlap is, and all your NaNs are on one dataset. You just need to use the .isel() method with a slice. Once you’ve got rid of the overlapping NaNs then you should be able to combine it fine (and you shouldn’t need to specify compat either). If you’re using combine_by_coords as part of opening many files with open_mfdataset then it might be easier to write a trimming function which you apply first using the preprocess argument to open_mfdataset.

Would it be clearer if I added an example to the documentation where some overlapping data had to be trimmed first?

[TomNicholas]

@pl-marasco I’ve just been pointed to this issue on pangeo-data, which looks like a better place to discuss this.