issue_comments: 1200314984

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https://github.com/pydata/xarray/issues/2304#issuecomment-1200314984 https://api.github.com/repos/pydata/xarray/issues/2304 1200314984 IC_kwDOAMm_X85Hi1po 1217238 2022-07-30T23:55:04Z 2022-07-30T23:55:04Z MEMBER

the unpacked data should match the type of these attributes, which must both be of type float or both be of type double. An additional restriction in this case is that the variable containing the packed data must be of type byte, short or int. It is not advised to unpack an int into a float as there is a potential precision loss.

I find this is ambiguous. is float above referring to float16 or float32? Is double referring to float64?

Yes, I'm pretty sure "float" means single precision (np.float32), given that "double" certainly means double precision (no.float64).

If so, then they do recommend float64, as requested by the OP, because the test data is short and the scale_factor is float64 (a.k.a double?)

Yes, I believe so.

The broader discussion here is about CF compliance. I find the spec ambiguous and xarray non-compliant. So many tests rely on the existing behavior, that I am unsure how best to proceed to improve compliance. I worry it may be a major refactor, and possibly break things relying on the existing behavior. I'd like to discuss architecture. Should this be in a new issue, if this closes with PR #6851? Should there be a new keyword for cf_strict or something?

I think we can treat this a bug fix and just go forward with it. Yes, some people are going to be surprised, but I don't think it's distruptive enough that we need to go to a major effort to preserve backwards compatibility. It should already be straightforward to work around by setting decode_cf=False when opening a file and then explicitly calling xarray.decode_cf().

 
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