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  • jthielen · 3 ✖

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  • Pint support for DataArray · 3 ✖

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  • CONTRIBUTOR 3
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
610159680 https://github.com/pydata/xarray/pull/3643#issuecomment-610159680 https://api.github.com/repos/pydata/xarray/issues/3643 MDEyOklzc3VlQ29tbWVudDYxMDE1OTY4MA== jthielen 3460034 2020-04-07T03:58:05Z 2020-04-07T03:58:05Z CONTRIBUTOR

Also, after glancing through all this, it seems like xarray is dealing inconsistently with the type casting hierarchy:

  • Construction/wrapping allowing __array_function__-defining duck arrays among other explictly listed additions (pandas.Index, dask arrays, etc., see https://github.com/pydata/xarray/blob/9b5140e0711247c373987b56726282140b406d7f/xarray/core/variable.py#L166)
  • Binary ops only denying based on xarray's internal hierarchy (Dataset, DataArray, Variable), otherwise deferring to underlying data
  • __array_ufunc__ allowing a list of supported types (https://github.com/pydata/xarray/blob/9b5140e0711247c373987b56726282140b406d7f/xarray/core/arithmetic.py#L24-L30 along with SupportsArithmetic)
  • (__array_function__ yet to be defined)

Should this be its own issue?

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  Pint support for DataArray 539988974
610159608 https://github.com/pydata/xarray/pull/3643#issuecomment-610159608 https://api.github.com/repos/pydata/xarray/issues/3643 MDEyOklzc3VlQ29tbWVudDYxMDE1OTYwOA== jthielen 3460034 2020-04-07T03:57:45Z 2020-04-07T03:57:45Z CONTRIBUTOR

@keewis Is part of the specific problem that Pint has a guarded import of xarray when defining its upcast types? Would it help if it checked for the fully qualified class name instead?

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  Pint support for DataArray 539988974
569166918 https://github.com/pydata/xarray/pull/3643#issuecomment-569166918 https://api.github.com/repos/pydata/xarray/issues/3643 MDEyOklzc3VlQ29tbWVudDU2OTE2NjkxOA== jthielen 3460034 2019-12-27T02:09:45Z 2019-12-27T02:09:45Z CONTRIBUTOR

@jthielen, it looks like this needs numpy.pad and numpy.resize in pint. I tried to implement it myself, but while numpy.resize is easy (add an entry to the implement_consistent_units_by_argument loop), that is not the case for numpy.pad. Regardless of whether my proposed fixes are actually the best way, numpy.pad is used in other places of the code base so we'd probably need both, anyway. What do you think?

No problem at all to add these! See https://github.com/hgrecco/pint/pull/956.

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  Pint support for DataArray 539988974

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