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  • xr.DataArray.values fails with latest versions of netcdf4 · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
562353939 https://github.com/pydata/xarray/issues/3580#issuecomment-562353939 https://api.github.com/repos/pydata/xarray/issues/3580 MDEyOklzc3VlQ29tbWVudDU2MjM1MzkzOQ== kpegion 16332933 2019-12-05T22:50:22Z 2019-12-05T22:50:22Z NONE

The problem occurs for me even without explicit numpy-style slicing. I only did the slicing to make the output small for a simple example. I get the same error if I just do:

print(fullda['sst'].values)

 
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   xr.DataArray.values fails with latest versions of netcdf4 529644880
561261583 https://github.com/pydata/xarray/issues/3580#issuecomment-561261583 https://api.github.com/repos/pydata/xarray/issues/3580 MDEyOklzc3VlQ29tbWVudDU2MTI2MTU4Mw== bradyrx 8881170 2019-12-03T17:02:39Z 2019-12-03T17:02:39Z CONTRIBUTOR

I can't seem to replicate this issue for some reason. I have the same versions of xarray, numpy, and netCDF4 installed.

python-traceback IndexError: The indexing operation you are attempting to perform is not valid on netCDF4.Variable object. Try loading your data into memory first by calling .load().

This implies that it's having issues slicing numpy-style with a dask array. I bet if you load it into memory and slice that way it'll work. But at ~22GB you might not be able to do that.

The preferred way to slice in xarray is to use .sel() and .isel() to leverage the label-aware nature of xarray. So you should have no problem doing this operation explicitly with the following:

fullda['sst'].isel(M=0, S=0, X=0, Y=0). You of course don't need to slice the L dimension since you are taking the full thing, but the equivalent notation there is :fullda['sst'].isel(L=slice(0, None)).

 
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   xr.DataArray.values fails with latest versions of netcdf4 529644880

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