issue_comments: 386658665

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https://github.com/pydata/xarray/pull/2104#issuecomment-386658665 https://api.github.com/repos/pydata/xarray/issues/2104 386658665 MDEyOklzc3VlQ29tbWVudDM4NjY1ODY2NQ== 1217238 2018-05-04T16:40:03Z 2018-05-04T16:40:03Z MEMBER

First of all, this is awesome!

One question: since I think this new interpolation method will be used quite frequently (more often than interpolate_na and reindex), perhaps we should give it a shorter name. Maybe interp?

We should also consider adding interp_like or interpolate_like by analogy to reindex_like.

I would like to this method working similar to isel, which may support vectorized interpolation.

Yes, I agree. Interpolation should be vectorized similarly to isel/sel.

In particular, in the long term I think we should aim to make interpolate_at(..., method='nearest') and reindex(..., method='nearest') equivalent.

How many interpolate methods should we support?

I think this is fine to start (we can always add more later).

How do we handle nan?

Which NaN are you referring to?

  1. data on the arrays being indexed
  2. Coordinates on the arrays being indexed
  3. Points at which to interpolate

Case (1) should definitely be supported. Especially if data is stored in dask arrays, we cannot necessarily check if there are NaNs.

Cases (2) and (3) are not important, because there are relatively few use-cases for NaN in coordinate arrays.

Do we support interpolation along dimension without coordinate? In that case, do we attach new coordinate to the object?

Currently we don't support this for reindex(), but I suppose we could do so unambiguous.

How should we do if new coordinate has the dimensional coordinate for the dimension to be interpolated?

I think the new coordinates should take priority, and the dimension coordinates on the new coordinate should be dropped. This is similar to what we do for sel():

``` In [10]: da = xr.DataArray([0, 0.1, 0.2, 0.1], dims='x', coords={'x': [0, 1, 2, 3]}) ...:

In [11]: da.sel(x=xr.DataArray([1, 2], dims=['x'], coords={'x': [1, 3]})) ...: Out[11]: <xarray.DataArray (x: 2)> array([0.1, 0.2]) Coordinates: * x (x) int64 1 2 ```

 
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