issues: 1112925311

What happened?

I'm trying to interpolate multi-dimensional data. But, it doesn't work with extrapolating.

What did you expect to happen?

No response

Minimal Complete Verifiable Example

```python import xarray as xr import numpy as np

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], dims="z")

y = xr.DataArray([0.15, 0.25, 0.35], dims="z")

da.interp(x=x, y=y, kwargs={"fill_value": "extrapolate"}) ```

Relevant log output

```python

ValueError Traceback (most recent call last) Input In [2], in <module> 8 x = xr.DataArray([-0.5, 1.5, 2.5], dims="z") 10 y = xr.DataArray([0.15, 0.25, 0.35], dims="z") ---> 12 da.interp(x=x, y=y, kwargs={"fill_value": "extrapolate"})

File ~/miniconda3/lib/python3.9/site-packages/xarray/core/dataarray.py:1742, in DataArray.interp(self, coords, method, assume_sorted, kwargs, coords_kwargs) 1737 if self.dtype.kind not in "uifc": 1738 raise TypeError( 1739 "interp only works for a numeric type array. " 1740 "Given {}.".format(self.dtype) 1741 ) -> 1742 ds = self._to_temp_dataset().interp( 1743 coords, 1744 method=method, 1745 kwargs=kwargs, 1746 assume_sorted=assume_sorted, 1747 coords_kwargs, 1748 ) 1749 return self._from_temp_dataset(ds)

File ~/miniconda3/lib/python3.9/site-packages/xarray/core/dataset.py:3192, in Dataset.interp(self, coords, method, assume_sorted, kwargs, method_non_numeric, coords_kwargs) 3189 if dtype_kind in "uifc": 3190 # For normal number types do the interpolation: 3191 var_indexers = {k: v for k, v in use_indexers.items() if k in var.dims} -> 3192 variables[name] = missing.interp(var, var_indexers, method, kwargs) 3193 elif dtype_kind in "ObU" and (use_indexers.keys() & var.dims): 3194 # For types that we do not understand do stepwise 3195 # interpolation to avoid modifying the elements. (...) 3198 # this loop there might be some duplicate code that slows it 3199 # down, therefore collect these signals and run it later: 3200 to_reindex[name] = var

File ~/miniconda3/lib/python3.9/site-packages/xarray/core/missing.py:640, in interp(var, indexes_coords, method, *kwargs) 638 original_dims = broadcast_dims + dims 639 new_dims = broadcast_dims + list(destination[0].dims) --> 640 interped = interp_func( 641 var.transpose(original_dims).data, x, destination, method, kwargs 642 ) 644 result = Variable(new_dims, interped, attrs=var.attrs) 646 # dimension of the output array

File ~/miniconda3/lib/python3.9/site-packages/xarray/core/missing.py:765, in interp_func(var, x, new_x, method, kwargs) 749 meta = var._meta 751 return da.blockwise( 752 _dask_aware_interpnd, 753 out_ind, (...) 762 align_arrays=False, 763 ) --> 765 return _interpnd(var, x, new_x, func, kwargs)

File ~/miniconda3/lib/python3.9/site-packages/xarray/core/missing.py:789, in _interpnd(var, x, new_x, func, kwargs) 787 # stack new_x to 1 vector, with reshape 788 xi = np.stack([x1.values.ravel() for x1 in new_x], axis=-1) --> 789 rslt = func(x, var, xi, **kwargs) 790 # move back the interpolation axes to the last position 791 rslt = rslt.transpose(range(-rslt.ndim + 1, 1))

File ~/miniconda3/lib/python3.9/site-packages/scipy/interpolate/interpolate.py:2703, in interpn(points, values, xi, method, bounds_error, fill_value) 2701 # perform interpolation 2702 if method == "linear": -> 2703 interp = RegularGridInterpolator(points, values, method="linear", 2704 bounds_error=bounds_error, 2705 fill_value=fill_value) 2706 return interp(xi) 2707 elif method == "nearest":

File ~/miniconda3/lib/python3.9/site-packages/scipy/interpolate/interpolate.py:2469, in RegularGridInterpolator.init(self, points, values, method, bounds_error, fill_value) 2465 fill_value_dtype = np.asarray(fill_value).dtype 2466 if (hasattr(values, 'dtype') and not 2467 np.can_cast(fill_value_dtype, values.dtype, 2468 casting='same_kind')): -> 2469 raise ValueError("fill_value must be either 'None' or " 2470 "of a type compatible with values") 2472 for i, p in enumerate(points): 2473 if not np.all(np.diff(p) > 0.):

ValueError: fill_value must be either 'None' or of a type compatible with values ```

Anything else we need to know?

I've also tried da.interp(x=x, kwargs={"fill_value": "extrapolate"}).interp(y=y), but I got this error: ```

---

KeyError Traceback (most recent call last) Input In [4], in <module> 10 y = xr.DataArray([0.15, 0.25, 0.35], dims="z") 12 # da.interp(x=x, y=y, kwargs={"fill_value": "extrapolate"}) ---> 13 da.interp(x=x, kwargs={"fill_value": "extrapolate"}).interp(y=y)

File ~/miniconda3/lib/python3.9/site-packages/xarray/core/dataarray.py:1742, in DataArray.interp(self, coords, method, assume_sorted, kwargs, coords_kwargs) 1737 if self.dtype.kind not in "uifc": 1738 raise TypeError( 1739 "interp only works for a numeric type array. " 1740 "Given {}.".format(self.dtype) 1741 ) -> 1742 ds = self._to_temp_dataset().interp( 1743 coords, 1744 method=method, 1745 kwargs=kwargs, 1746 assume_sorted=assume_sorted, 1747 coords_kwargs, 1748 ) 1749 return self._from_temp_dataset(ds)

File ~/miniconda3/lib/python3.9/site-packages/xarray/core/dataset.py:3130, in Dataset.interp(self, coords, method, assume_sorted, kwargs, method_non_numeric, *coords_kwargs) 3121 if coords: 3122 # This avoids broadcasting over coordinates that are both in 3123 # the original array AND in the indexing array. It essentially 3124 # forces interpolation along the shared coordinates. 3125 sdims = ( 3126 set(self.dims) 3127 .intersection([set(nx.dims) for nx in indexers.values()]) 3128 .difference(coords.keys()) 3129 ) -> 3130 indexers.update({d: self.variables[d] for d in sdims}) 3132 obj = self if assume_sorted else self.sortby([k for k in coords]) 3134 def maybe_variable(obj, k): 3135 # workaround to get variable for dimension without coordinate.

File ~/miniconda3/lib/python3.9/site-packages/xarray/core/dataset.py:3130, in <dictcomp>(.0) 3121 if coords: 3122 # This avoids broadcasting over coordinates that are both in 3123 # the original array AND in the indexing array. It essentially 3124 # forces interpolation along the shared coordinates. 3125 sdims = ( 3126 set(self.dims) 3127 .intersection(*[set(nx.dims) for nx in indexers.values()]) 3128 .difference(coords.keys()) 3129 ) -> 3130 indexers.update({d: self.variables[d] for d in sdims}) 3132 obj = self if assume_sorted else self.sortby([k for k in coords]) 3134 def maybe_variable(obj, k): 3135 # workaround to get variable for dimension without coordinate.

File ~/miniconda3/lib/python3.9/site-packages/xarray/core/utils.py:459, in Frozen.getitem(self, key) 458 def getitem(self, key: K) -> V: --> 459 return self.mapping[key]

KeyError: 'z' ```

Environment

```python INSTALLED VERSIONS

---

commit: None python: 3.9.7 | packaged by conda-forge | (default, Sep 29 2021, 19:20:46) [GCC 9.4.0] python-bits: 64 OS: Linux OS-release: 5.11.0-40-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: ('en_US', 'UTF-8') libhdf5: 1.12.1 libnetcdf: 4.8.1

xarray: 0.20.2 pandas: 1.3.5 numpy: 1.19.5 scipy: 1.7.3 netCDF4: 1.5.8 pydap: None h5netcdf: None h5py: 3.6.0 Nio: None zarr: 2.10.3 cftime: 1.5.1.1 nc_time_axis: None PseudoNetCDF: None rasterio: 1.2.10 cfgrib: None iris: None bottleneck: None dask: 2021.12.0 distributed: 2021.12.0 matplotlib: 3.5.1 cartopy: 0.20.2 seaborn: None numbagg: None fsspec: 2022.01.0 cupy: None pint: 0.18 sparse: None setuptools: 59.8.0 pip: 21.3.1 conda: 4.11.0 pytest: None IPython: 8.0.0 sphinx: None ```