What happened?

I was trying to use polyval with a cftime coordinate and it failed with TypeError: unsupported operand type(s) for *: 'float' and 'cftime._cftime.DatetimeNoLeap'. The error seems to originate from #6548, where the process transforming coordinates to numerical values was modified. The new _ensure_numeric method seems to ignore the possibility of cftime arrays.

What did you expect to happen?

A polynomial to be evaluated along my coordinate.

Minimal Complete Verifiable Example

```Python import xarray as xr import numpy as np

use_cftime=False will work

t = xr.date_range('2001-01-01', periods=100, use_cftime=True, freq='YS') da = xr.DataArray(np.arange(100) ** 3, dims=('time',), coords={'time': t}) coeffs = da.polyfit('time', 4) da2 = xr.polyval(da.time, coeffs).polyfit_coefficients ```

MVCE confirmation

• [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [X] Complete example — the example is self-contained, including all data and the text of any traceback.
• [X] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• [X] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

```Python

TypeError Traceback (most recent call last) Input In [5], in <cell line: 4>() 2 da = xr.DataArray(np.arange(100) ** 3, dims=('time',), coords={'time': t}) 3 coeffs = da.polyfit('time', 4) ----> 4 da2 = xr.polyval(da.time, coeffs).polyfit_coefficients

File ~/Python/xarray/xarray/core/computation.py:1931, in polyval(coord, coeffs, degree_dim) 1929 res = zeros_like(coord) + coeffs.isel({degree_dim: max_deg}, drop=True) 1930 for deg in range(max_deg - 1, -1, -1): -> 1931 res *= coord 1932 res += coeffs.isel({degree_dim: deg}, drop=True) 1934 return res

File ~/Python/xarray/xarray/core/_typed_ops.py:103, in DatasetOpsMixin.imul(self, other) 102 def imul(self, other): --> 103 return self._inplace_binary_op(other, operator.imul)

File ~/Python/xarray/xarray/core/dataset.py:6107, in Dataset._inplace_binary_op(self, other, f) 6105 other = other.reindex_like(self, copy=False) 6106 g = ops.inplace_to_noninplace_op(f) -> 6107 ds = self._calculate_binary_op(g, other, inplace=True) 6108 self._replace_with_new_dims( 6109 ds._variables, 6110 ds._coord_names, (...) 6113 inplace=True, 6114 ) 6115 return self

File ~/Python/xarray/xarray/core/dataset.py:6154, in Dataset._calculate_binary_op(self, f, other, join, inplace) 6152 else: 6153 other_variable = getattr(other, "variable", other) -> 6154 new_vars = {k: f(self.variables[k], other_variable) for k in self.data_vars} 6155 ds._variables.update(new_vars) 6156 ds._dims = calculate_dimensions(ds._variables)

File ~/Python/xarray/xarray/core/dataset.py:6154, in <dictcomp>(.0) 6152 else: 6153 other_variable = getattr(other, "variable", other) -> 6154 new_vars = {k: f(self.variables[k], other_variable) for k in self.data_vars} 6155 ds._variables.update(new_vars) 6156 ds._dims = calculate_dimensions(ds._variables)

File ~/Python/xarray/xarray/core/_typed_ops.py:402, in VariableOpsMixin.mul(self, other) 401 def mul(self, other): --> 402 return self._binary_op(other, operator.mul)

File ~/Python/xarray/xarray/core/variable.py:2494, in Variable._binary_op(self, other, f, reflexive) 2491 attrs = self._attrs if keep_attrs else None 2492 with np.errstate(all="ignore"): 2493 new_data = ( -> 2494 f(self_data, other_data) if not reflexive else f(other_data, self_data) 2495 ) 2496 result = Variable(dims, new_data, attrs=attrs) 2497 return result

TypeError: unsupported operand type(s) for *: 'float' and 'cftime._cftime.DatetimeGregorian' ```

Anything else we need to know?

I also noticed that since the Horner PR, polyfit and polyval do not use the same function to convert coordinates into numerical values. Isn't this dangerous?

Environment

INSTALLED VERSIONS ------------------ commit: None python: 3.10.4 | packaged by conda-forge | (main, Mar 24 2022, 17:38:57) [GCC 10.3.0] python-bits: 64 OS: Linux OS-release: 3.10.0-1160.49.1.el7.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_CA.UTF-8 LOCALE: ('en_CA', 'UTF-8') libhdf5: 1.12.1 libnetcdf: 4.8.1 xarray: 2022.3.1.dev267+gd711d58 pandas: 1.4.2 numpy: 1.21.6 scipy: 1.8.0 netCDF4: 1.5.8 pydap: None h5netcdf: None h5py: 3.6.0 Nio: None zarr: 2.11.3 cftime: 1.6.0 nc_time_axis: 1.4.1 PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.3.4 dask: 2022.04.1 distributed: 2022.4.1 matplotlib: 3.5.1 cartopy: 0.20.2 seaborn: None numbagg: None fsspec: 2022.3.0 cupy: None pint: 0.19.2 sparse: 0.13.0 flox: 0.5.0 numpy_groupies: 0.9.15 setuptools: 62.1.0 pip: 22.0.4 conda: None pytest: None IPython: 8.2.0 sphinx: 4.5.0