issues: 666270493

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
666270493 MDU6SXNzdWU2NjYyNzA0OTM= 4275 Interpolation along dimension with a single element 31126826 open 0     3 2020-07-27T12:52:35Z 2022-05-21T20:50:29Z   CONTRIBUTOR      

Let me consider a DataArray with a dimension containing a single element:

```python In [1]: import numpy as np

In [2]: import xarray as xr

In [3]: da = xr.DataArray(np.linspace(0.0, 100.0, 101).reshape(1, 101), coords=[('x', [1.0]), ('y', np.linspace(0.0, 1.0, 101))]) ```

Asking x=1.0 in interp fails.

More precisely, the 2D interpolation returns a NaN python In [5]: da.interp(x=1.0, y=0.4) /opt/anaconda3/lib/python3.7/site-packages/scipy/interpolate/interpolate.py:2533: RuntimeWarning: invalid value encountered in true_divide (grid[i + 1] - grid[i])) Out[5]: <xarray.DataArray ()> array(nan) Coordinates: x float64 1.0 y float64 0.4 and the 1D interpolation returns a ValueError: ```python In [6]: da.interp(x=1.0)

ValueError Traceback (most recent call last) <ipython-input-6-efd4490bc97e> in <module> ----> 1 da.interp(x=1.0) ... ValueError: x and y arrays must have at least 2 entries ```

I understand why the interpolation is impossible in an array with a single element.

However, this behavior breaks my assumption that interp is a superset of sel, meaning that it gives the same result as sel for all inputs that are valid inputs for sel (except for a possible int to float type conversion).

Here, I would expect da.interp(x=1.0) to give me the same result as da.sel(x=1.0).

What do you think of this corner case?

 
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