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  • max-sixty · 4 ✖

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  • Transpose modifies dtype of index, when a PeriodIndex · 4 ✖

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168527832 https://github.com/pydata/xarray/issues/692#issuecomment-168527832 https://api.github.com/repos/pydata/xarray/issues/692 MDEyOklzc3VlQ29tbWVudDE2ODUyNzgzMg== max-sixty 5635139 2016-01-03T18:41:04Z 2016-01-03T18:41:04Z MEMBER

OK, I guess that's how I think about the distinction with Indexes - they're role is for selection in one dimension, each.

Maybe this is a more conceptual issue then...

 
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   Transpose modifies dtype of index, when a PeriodIndex 124441012
168355707 https://github.com/pydata/xarray/issues/692#issuecomment-168355707 https://api.github.com/repos/pydata/xarray/issues/692 MDEyOklzc3VlQ29tbWVudDE2ODM1NTcwNw== max-sixty 5635139 2016-01-02T01:46:09Z 2016-01-02T01:46:09Z MEMBER

That did fix it! Apologies for not testing on master.

On the broader issue, I hadn't thought of the need to expand dims / indexes to more than one dimension. I was thinking that there would be a 1D index per dim, and the result of slicing a multidimensional array would be the intersection of each dim's slice. Am I missing something more fundamental?

 
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   Transpose modifies dtype of index, when a PeriodIndex 124441012
168348251 https://github.com/pydata/xarray/issues/692#issuecomment-168348251 https://api.github.com/repos/pydata/xarray/issues/692 MDEyOklzc3VlQ29tbWVudDE2ODM0ODI1MQ== max-sixty 5635139 2016-01-01T23:07:06Z 2016-01-01T23:07:06Z MEMBER

Yeah, that seems fairly hacky (presumably this is would still be a problem if we have nim > 2?)

From my POV I'm still thinking whether XRay can fall back to pandas indexing more extensively (as discussed here). Dims could be stored as Pandas indexes rather than dask / numpy arrays, and the (much cleaner) XRay indexing API could be a simple wrapper of the Pandas API. And it sounds like from your comment the lazy contract could still be honored, if they're loaded when needed?

Does that make sense? What are the arguments in the other direction?

 
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   Transpose modifies dtype of index, when a PeriodIndex 124441012
168138939 https://github.com/pydata/xarray/issues/692#issuecomment-168138939 https://api.github.com/repos/pydata/xarray/issues/692 MDEyOklzc3VlQ29tbWVudDE2ODEzODkzOQ== max-sixty 5635139 2015-12-31T07:20:11Z 2016-01-01T22:12:08Z MEMBER

Also peculiar - setting the coord to the original coord (saved above, but not shown here) causes the ds.date.dtype to report 'O', although not to display that in its repr, nor to cascade that for a DataArray extracted from it.

``` python In [80]:

ds.date = date ds, ds.date.dtype, ds['number 1'].date.dtype Out[80]: (<xray.Dataset> Dimensions: (date: 10) Coordinates: * date (date) int64 10957 10958 10959 10960 10961 10962 10963 10964 ... Data variables: number 1 (date) float64 0.1225 0.7202 0.5921 0.3005 0.8746 0.4186 ... number 2 (date) float64 0.1225 0.7202 0.5921 0.3005 0.8746 0.4186 ... number 3 (date) float64 0.1225 0.7202 0.5921 0.3005 0.8746 0.4186 ... number 4 (date) float64 0.1225 0.7202 0.5921 0.3005 0.8746 nan nan nan ..., dtype('O'), dtype('int64')) ```

Currently my workaround is ds=ds.assign_coords(**dict(date=date.to_index()))

 
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   Transpose modifies dtype of index, when a PeriodIndex 124441012

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