issue_comments

Ok. I realized this problem occurs only because x was a dimension of the new index idx and the original dataset. Perhaps sel should warn the user or raise an error when this happens.

Ok. I started playing around with this, but I am getting errors when indexing arrays with ND variables. data.sel(x=nd_x) works, but any subsequent operations complain that IndexVariable objects must be 1-dimensional: ```

import xarray as xr import numpy as np npdata = np.tile(np.arange(10), (5, 1)) ... data = xr.DataArray(npdata, dims=['y', 'x'], ... coords={'x': np.r_[:10], 'y': np.r_[:5]}) ... idx = xr.DataArray(npdata, dims=['z', 'x']) ... ... ans = data.sel(x=idx, method='bfill') ... assert set(ans.dims) == {'z', 'y', 'x'} ... print(ans) Traceback (most recent call last): File "<ipython-input-4-1d0ac0cac680>", line 8, in <module> print(ans) File "/Users/noah/workspace/software/xarray/xarray/core/common.py", line 129, in repr return formatting.array_repr(self) File "/Users/noah/workspace/software/xarray/xarray/core/formatting.py", line 463, in array_repr summary.append(repr(arr.coords)) File "/Users/noah/workspace/software/xarray/xarray/core/coordinates.py", line 78, in repr return formatting.coords_repr(self) File "/Users/noah/workspace/software/xarray/xarray/core/formatting.py", line 381, in coords_repr coords, title="Coordinates", summarizer=summarize_coord, col_width=col_width File "/Users/noah/workspace/software/xarray/xarray/core/formatting.py", line 361, in _mapping_repr summary += [summarizer(k, v, col_width) for k, v in mapping.items()] File "/Users/noah/workspace/software/xarray/xarray/core/formatting.py", line 361, in <listcomp> summary += [summarizer(k, v, col_width) for k, v in mapping.items()] File "/Users/noah/workspace/software/xarray/xarray/core/formatting.py", line 307, in summarize_coord coord = var.variable.to_index_variable() File "/Users/noah/workspace/software/xarray/xarray/core/variable.py", line 440, in to_index_variable self.dims, self._data, self._attrs, encoding=self._encoding, fastpath=True File "/Users/noah/workspace/software/xarray/xarray/core/variable.py", line 1943, in init raise ValueError("%s objects must be 1-dimensional" % type(self).name) ValueError: IndexVariable objects must be 1-dimensional ```

So when would interp use this manual interpolation method? Would it try it only if scipy fails or check the dimensions?

After reading the method='ffill' docs, I agree with you.

In my experience, computing w efficiently is the tricky part. The function is slightly different, but metpy uses a lot of tricks to make this work efficiently. A manual for-loop is much cleaner for this kind of stencil calculation IMO. What kind of duck arrays were you thinking of?

I have some numba code which does this for linear interpolation. Does scipy support this pattern?