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  • psybot-ca · 1 ✖

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  • float32 instead of float64 when decoding int16 with scale_factor netcdf var using xarray · 1 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
731253022 https://github.com/pydata/xarray/issues/2304#issuecomment-731253022 https://api.github.com/repos/pydata/xarray/issues/2304 MDEyOklzc3VlQ29tbWVudDczMTI1MzAyMg== psybot-ca 66918146 2020-11-20T15:59:13Z 2020-11-20T15:59:13Z NONE

Hey everyone, tumbled on this while searching for approximately the same problem. Thought I'd share since the issue is still open. On my part, there is two situations that seem buggy. I haven't been using xarray for that long yet so maybe there is something I'm missing here...

My first problem relates to the data types of dimensions with float notation. To give another answer to @shoyer's question:

To clarify: why is it a problem for you

it is a problem in my case because I would like to perform slicing operations of a dataset using longitude values from another dataset. This operation raises a "KeyError : not all values found in index 'longitude'" since either one of the dataset's longitude is float32 and the other is float64 or because both datasets' float32 approximations are not exactly the same value in each dataset. I can work around this and assign new coords to be float64 after reading and it works, though it is kind of a hassle considering I have to perform this thousands of times. This situation also create a problem when concatenating multiple netCDF files together (along time dim in my case). The discrepancies between the approximations of float32 values or the float32 vs float 64 situation will add new dimension values where it shouldn't.

On the second part of my problem, it comes with writing/reading netCDF files (maybe more related to @daoudjahdou problem). I tried to change the data type to float64 for all my files, save them and then perform what I need to do, but for some reason even though dtype is float64 for all my dimensions when writing the files (using default args), it will sometime be float32, sometime float64 when reading the files (with default ags values) previously saved with float64 dtype. If using the default args, shouldn't the decoding makes the dtype of dimension the same for all files I read?

 
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   float32 instead of float64 when decoding int16 with scale_factor netcdf var using xarray  343659822

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