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  • lstngr · 5 ✖

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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
1141699498 https://github.com/pydata/xarray/pull/6639#issuecomment-1141699498 https://api.github.com/repos/pydata/xarray/issues/6639 IC_kwDOAMm_X85EDPOq lstngr 40182387 2022-05-31T06:02:28Z 2022-05-31T06:02:28Z CONTRIBUTOR

Thank you for the heads-up @Illviljan. Should be good now

 
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   Fix kwargs used for extrapolation in docs 1249350841
1140409653 https://github.com/pydata/xarray/pull/6639#issuecomment-1140409653 https://api.github.com/repos/pydata/xarray/issues/6639 IC_kwDOAMm_X85D-UU1 lstngr 40182387 2022-05-29T09:17:49Z 2022-05-29T09:17:49Z CONTRIBUTOR

@pums974 You maybe have an opinion on the accuracy of this PR, since you originally implemented this behavior?

 
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   Fix kwargs used for extrapolation in docs 1249350841
1139582688 https://github.com/pydata/xarray/pull/6639#issuecomment-1139582688 https://api.github.com/repos/pydata/xarray/issues/6639 IC_kwDOAMm_X85D7Kbg lstngr 40182387 2022-05-27T12:41:56Z 2022-05-27T12:41:56Z CONTRIBUTOR

Hopefully this looks better: it now states that interp1d may be called when preforming multivariate interpolation. Let me know if you think the extended summaries can be improved.

 
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   Fix kwargs used for extrapolation in docs 1249350841
1138892993 https://github.com/pydata/xarray/pull/6639#issuecomment-1138892993 https://api.github.com/repos/pydata/xarray/issues/6639 IC_kwDOAMm_X85D4iDB lstngr 40182387 2022-05-26T18:37:32Z 2022-05-26T18:37:32Z CONTRIBUTOR

Right now, the docstring only suggests different interpolation may be used depending on the input, but typically refers to "1-dimensional" vs "multi-dimensional" arrays. I would do it this way:

  1. an extended summary is added, explaining when scipy.interpolate.interp1d or scipy.interpolate.interpnd are used,
  2. modify the parameters section to refer to arguments accepted when interp1d or interpnd is used.

Does that look alright to you?

 
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   Fix kwargs used for extrapolation in docs 1249350841
1133833687 https://github.com/pydata/xarray/issues/6617#issuecomment-1133833687 https://api.github.com/repos/pydata/xarray/issues/6617 IC_kwDOAMm_X85DlO3X lstngr 40182387 2022-05-22T07:09:33Z 2022-05-22T07:09:33Z CONTRIBUTOR

You're right, thanks for the help. It seems that orthogonal dimensions are now interpolated independently by calling SciPy's interp1d multiple times, which explains why passing 'extrapolate' works. This behaviour has been introduced in #4155, in particular 7daad4fce3bf8ad9b9bc8e7baa104c476437e68d.

The documentation should be adapted to use @keewis's approach. I'd suggest including an example combining "advanced interpolation" and extrapolation, such as the one below:

python da = xr.DataArray( np.sin(0.3 * np.arange(20).reshape(5, 4)), [("x", np.arange(5)), ("y", [0.1, 0.2, 0.3, 0.4])], ) x = xr.DataArray([0.5, 1.5, 2.5, 3.5], dims="z") y = xr.DataArray([0.15, 0.25, 0.35, 0.45], dims="z")

Without extrapolation: python da.interp(x=x, y=y) <xarray.DataArray (z: 4)> array([ 0.55626357, 0.63496063, -0.46643289, nan]) Coordinates: x (z) float64 0.5 1.5 2.5 3.5 y (z) float64 0.15 0.25 0.35 0.45 Dimensions without coordinates: z

With extrapolation: python da.interp(x=x, y=y, kwargs={'fill_value': None}) <xarray.DataArray (z: 4)> array([ 0.55626357, 0.63496063, -0.46643289, -0.73507668]) Coordinates: x (z) float64 0.5 1.5 2.5 3.5 y (z) float64 0.15 0.25 0.35 0.45 Dimensions without coordinates: z

 
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   Multi-dimensional extrapolation doesn't work 1238838588

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