Inverting Datasets or DataArrays with dask float data throws wrong ValueError instead of TypeError

What happened?

Inverting (__invert__) a DataArray or Dataset containing dask float data throws a ValueError with a message about the dimensions not matching the data. This should throw a TypeError with a message indicating an unsupported type for that operation.

What did you expect to happen?

I expected a TypeError with a relevant message about the type (shown below), not a ValueError with a misleading message.

import xarray as xr
import dask.array as da

data = da.from_array([1.0])
x = xr.DataArray(data)
~x
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/USEr/anaconda3/envs/rstools/lib/python3.8/site-packages/xarray/core/_typed_ops.py", line 329, in __invert__
    return self._unary_op(operator.invert)
  File "/home/USER/anaconda3/envs/rstools/lib/python3.8/site-packages/xarray/core/dataarray.py", line 3078, in _unary_op
    da = self.__array_wrap__(f(self.variable.data, *args, **kwargs))
TypeError: ufunc 'invert' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

Minimal Complete Verifiable Example

import xarray as xr
import dask.array as da

data = da.from_array([1.0])
x = xr.DataArray(data)
~x

Relevant log output

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/USER/anaconda3/envs/rstools/lib/python3.8/site-packages/xarray/core/_typed_ops.py", line 329, in __invert__
    return self._unary_op(operator.invert)
  File "/home/USER/anaconda3/envs/rstools/lib/python3.8/site-packages/xarray/core/dataarray.py", line 3078, in _unary_op
    da = self.__array_wrap__(f(self.variable.data, *args, **kwargs))
  File "/home/USER/anaconda3/envs/rstools/lib/python3.8/site-packages/xarray/core/dataarray.py", line 3057, in __array_wrap__
    new_var = self.variable.__array_wrap__(obj, context)
  File "/home/USER/anaconda3/envs/rstools/lib/python3.8/site-packages/xarray/core/variable.py", line 2444, in __array_wrap__
    return Variable(self.dims, obj)
  File "/home/USER/anaconda3/envs/rstools/lib/python3.8/site-packages/xarray/core/variable.py", line 305, in __init__
    self._dims = self._parse_dimensions(dims)
  File "/home/USER/anaconda3/envs/rstools/lib/python3.8/site-packages/xarray/core/variable.py", line 573, in _parse_dimensions
    raise ValueError(
ValueError: dimensions ('dim_0',) must have the same length as the number of data dimensions, ndim=0

Anything else we need to know?

No response

Environment

/home/USER/anaconda3/envs/rstools/lib/python3.8/site-packages/_distutils_hack/init.py:30: UserWarning: Setuptools is replacing distutils.
warnings.warn("Setuptools is replacing distutils.")

INSTALLED VERSIONS

commit: None
python: 3.8.13 | packaged by conda-forge | (default, Mar 25 2022, 06:04:10)
[GCC 10.3.0]
python-bits: 64
OS: Linux
OS-release: 5.13.0-35-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: ('en_US', 'UTF-8')
libhdf5: None
libnetcdf: None

xarray: 2022.3.0
pandas: 1.4.1
numpy: 1.21.5
scipy: 1.8.0
netCDF4: None
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: None
nc_time_axis: None
PseudoNetCDF: None
rasterio: 1.2.10
cfgrib: None
iris: None
bottleneck: None
dask: 2022.03.0
distributed: 2022.3.0
matplotlib: 3.5.1
cartopy: None
seaborn: None
numbagg: None
fsspec: 2022.02.0
cupy: None
pint: None
sparse: None
setuptools: 61.2.0
pip: 22.0.4
conda: None
pytest: 7.1.1
IPython: 8.2.0
sphinx: None

Reproduce the minimal example, then inspect xarray/core/_typed_ops.py, dataarray.py, and variable.py, especially _unary_op and array_wrap shown in the traceback. Add or locate coverage for inverting dask-backed float data and verify that the operation raises a TypeError with a relevant unsupported-type message rather than the misleading dimensions ValueError.