In opposition to argmin/argmax, idxmax/idxmin fails on DataArrays of more than 2 dimensions, when the data is stored in dask arrays.

MCVE Code Sample

```python

Your code here

import xarray as xr ds = xr.tutorial.open_dataset('air_temperature').resample(time='D').mean() dsc = ds.chunk({'time':-1, 'lat': 5, 'lon': 5}) dsc.air.argmax('time').values # Works (I added .values to be sure all computation is done) dsc.air.idxmin('time') # Fails ```

Expected Output

Something like: <xarray.DataArray 'time' (lat: 25, lon: 53)> dask.array<where, shape=(25, 53), dtype=datetime64[ns], chunksize=(5, 5), chunktype=numpy.ndarray> Coordinates: * lon (lon) float32 200.0 202.5 205.0 207.5 ... 322.5 325.0 327.5 330.0 * lat (lat) float32 75.0 72.5 70.0 67.5 65.0 ... 25.0 22.5 20.0 17.5 15.0

Problem Description

Throws an error: ```

---

NotImplementedError Traceback (most recent call last) <ipython-input-11-0b9bf50bc3ab> in <module> 3 dsc = ds.chunk({'time':-1, 'lat': 5, 'lon': 5}) 4 dsc.air.argmax('time').values ----> 5 dsc.air.idxmin('time')

~/Python/myxarray/xarray/core/dataarray.py in idxmin(self, dim, skipna, fill_value, keep_attrs) 3626 * y (y) int64 -1 0 1 3627 """ -> 3628 return computation._calc_idxminmax( 3629 array=self, 3630 func=lambda x, args, kwargs: x.argmin(args, **kwargs),

~/Python/myxarray/xarray/core/computation.py in _calc_idxminmax(array, func, dim, skipna, fill_value, keep_attrs) 1564 chunks = dict(zip(array.dims, array.chunks)) 1565 dask_coord = dask.array.from_array(array[dim].data, chunks=chunks[dim]) -> 1566 res = indx.copy(data=dask_coord[(indx.data,)]) 1567 # we need to attach back the dim name 1568 res.name = dim

~/.conda/envs/xarray-xclim-dev/lib/python3.8/site-packages/dask/array/core.py in getitem(self, index) 1539 1540 if any(isinstance(i, Array) and i.dtype.kind in "iu" for i in index2): -> 1541 self, index2 = slice_with_int_dask_array(self, index2) 1542 if any(isinstance(i, Array) and i.dtype == bool for i in index2): 1543 self, index2 = slice_with_bool_dask_array(self, index2)

~/.conda/envs/xarray-xclim-dev/lib/python3.8/site-packages/dask/array/slicing.py in slice_with_int_dask_array(x, index) 934 out_index.append(slice(None)) 935 else: --> 936 raise NotImplementedError( 937 "Slicing with dask.array of ints only permitted when " 938 "the indexer has zero or one dimensions"

NotImplementedError: Slicing with dask.array of ints only permitted when the indexer has zero or one dimensions ```

I saw #3922 and thought this PR was aiming to make this work, so I'm a bit confused.

(I tested with dask 2.17.2 also and it still fails)

Versions

Output of <tt>xr.show_versions()</tt>

INSTALLED VERSIONS ------------------ commit: None python: 3.8.2 | packaged by conda-forge | (default, Apr 24 2020, 08:20:52) [GCC 7.3.0] python-bits: 64 OS: Linux OS-release: 5.6.15-arch1-1 machine: x86_64 processor: byteorder: little LC_ALL: None LANG: fr_CA.utf8 LOCALE: fr_CA.UTF-8 libhdf5: 1.10.5 libnetcdf: 4.7.4 xarray: 0.15.2.dev9+g6378a711.d20200505 pandas: 1.0.3 numpy: 1.18.4 scipy: 1.4.1 netCDF4: 1.5.3 pydap: None h5netcdf: None h5py: 2.10.0 Nio: None zarr: None cftime: 1.1.1.2 nc_time_axis: 1.2.0 PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.3.2 dask: 2.16.0 distributed: 2.17.0 matplotlib: 3.2.1 cartopy: None seaborn: None numbagg: None pint: 0.12 setuptools: 46.1.3.post20200325 pip: 20.0.2 conda: None pytest: 5.4.1 IPython: 7.13.0 sphinx: 3.0.2