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774553196 MDU6SXNzdWU3NzQ1NTMxOTY= 4733 Xarray with cfgrib backend errors with .where() when drop=True DanielAdriaansen 18426352 closed 0     4 2020-12-24T20:26:58Z 2021-01-02T08:17:37Z 2021-01-02T08:17:37Z CONTRIBUTOR      

What happened: When loading a HRRR GRIBv2 file in this manner: ds = xr.open_dataset(gribfile_path,engine='cfgrib',backend_kwargs={'filter_by_keys':{'typeOfLevel':'hybrid'}})

I have trouble using the .where() method when drop=True. If I set drop=False, it works fine. I am attempting to subset via latitude and longitude like this:

ds_sub = ds.where((ds.latitude>=40.0)&(ds.latitude<=50.0)&(ds.longitude>=252.0)&(ds.longitude<=280.0),drop=True)

However I receive the following errors: Traceback (most recent call last): File "read_interp_format_grib.py", line 77, in <module> test = ds.where(mask_lat & mask_lon,drop=True) File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/xarray/core/common.py", line 1268, in where return ops.where_method(self, cond, other) File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/xarray/core/ops.py", line 193, in where_method return apply_ufunc( File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/xarray/core/computation.py", line 1092, in apply_ufunc return apply_dataset_vfunc( File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/xarray/core/computation.py", line 410, in apply_dataset_vfunc result_vars = apply_dict_of_variables_vfunc( File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/xarray/core/computation.py", line 356, in apply_dict_of_variables_vfunc result_vars[name] = func(*variable_args) File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/xarray/core/computation.py", line 606, in apply_variable_ufunc input_data = [ File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/xarray/core/computation.py", line 607, in <listcomp> broadcast_compat_data(arg, broadcast_dims, core_dims) File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/xarray/core/computation.py", line 522, in broadcast_compat_data data = variable.data File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/xarray/core/variable.py", line 359, in data return self.values File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/xarray/core/variable.py", line 510, in values return _as_array_or_item(self._data) File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/xarray/core/variable.py", line 272, in _as_array_or_item data = np.asarray(data) File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/numpy/core/_asarray.py", line 83, in asarray return array(a, dtype, copy=False, order=order) File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/xarray/core/indexing.py", line 685, in __array__ self._ensure_cached() File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/xarray/core/indexing.py", line 682, in _ensure_cached self.array = NumpyIndexingAdapter(np.asarray(self.array)) File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/numpy/core/_asarray.py", line 83, in asarray return array(a, dtype, copy=False, order=order) File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/xarray/core/indexing.py", line 655, in __array__ return np.asarray(self.array, dtype=dtype) File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/numpy/core/_asarray.py", line 83, in asarray return array(a, dtype, copy=False, order=order) File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/xarray/core/indexing.py", line 560, in __array__ return np.asarray(array[self.key], dtype=None) File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/xarray/backends/cfgrib_.py", line 23, in __getitem__ return indexing.explicit_indexing_adapter( File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/xarray/core/indexing.py", line 848, in explicit_indexing_adapter result = NumpyIndexingAdapter(np.asarray(result))[numpy_indices] File "/d1/anaconda3/envs/era5/lib/python3.8/site-packages/xarray/core/indexing.py", line 1294, in __getitem__ return array[key] IndexError: too many indices for array: array is 2-dimensional, but 3 were indexed

What you expected to happen: I expect the dataset to be reduced in the x and y (latitude/longitude) dimensions where cond=False from .where() when drop=True.

Minimal Complete Verifiable Example:

```python

Put your MCVE code here

```

Anything else we need to know?: I was able to confirm cfgrib is where the issue lies by doing the following: ds = xr.open_dataset(gribfile_path,engine='cfgrib',backend_kwargs={'filter_by_keys':{'typeOfLevel':'hybrid'}}) ds.to_netcdf('test.nc') dsnc = xr.open_dataset('test.nc') ds_sub = dsnc.where((dsnc.latitude>=40.0)&(dsnc.latitude<=50.0)&(dsnc.longitude>=252.0)&(dsnc.longitude<=280.0),drop=True)

That correctly gives me: Dimensions: (hybrid: 50, x: 792, y: 414)

Originally x=1799 and y=1059.

Environment:

Output of <tt>xr.show_versions()</tt> INSTALLED VERSIONS ------------------ commit: None python: 3.8.6 | packaged by conda-forge | (default, Oct 7 2020, 19:08:05) [GCC 7.5.0] python-bits: 64 OS: Linux OS-release: 4.9.0-14-amd64 machine: x86_64 processor: byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: en_US.UTF-8 libhdf5: 1.10.6 libnetcdf: 4.7.4 xarray: 0.16.1 pandas: 1.1.3 numpy: 1.19.1 scipy: 1.5.2 netCDF4: 1.5.5.1 pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: 1.2.1 nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: 0.9.8.5 iris: None bottleneck: None dask: 2.30.0 distributed: 2.30.0 matplotlib: 3.3.2 cartopy: 0.17.0 seaborn: None numbagg: None pint: 0.16.1 setuptools: 49.6.0.post20200917 pip: 20.2.3 conda: None pytest: None IPython: None sphinx: None 
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   completed xarray 13221727 issue

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