issues: 724777139

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724777139 MDU6SXNzdWU3MjQ3NzcxMzk= 4524 xr.DataArray.where(drop=True) crashes if the result is False everywhere (h5netcdf engine) 38501935 open 0     4 2020-10-19T16:24:15Z 2021-01-03T12:10:31Z   NONE      

Description of the issue:

For the bug to occur, it looks like the following requirements need to be met : 1. Crashes occured with both xarray v0.16.1 and the current master. The bug does not seem to exist with v0.15.1. 2. The file must be opened using the h5netcdf engine. 3. The DataArray, before the call to where(), must contain auxiliary coordinates that will get dropped (in the example below, lon_rho, lat_rho and h). Edit: By "auxiliary coordinate", I mean coordinates that depend on a dimension, without being dimensions themselves. 4. The call to .where() must give False results everywhere. 4. The argument drop=True must be used.

Minimal Complete Verifiable Example: python import xarray as xr ds = xr.tutorial.open_dataset('ROMS_example', engine='h5netcdf') da = ds["zeta"] print(da.where(da>1000, drop=True))

This is what da looks like before the call to .where() python print(da) <xarray.DataArray 'zeta' (ocean_time: 2, eta_rho: 191, xi_rho: 371)> [141722 values with dtype=float32] Coordinates: lon_rho (eta_rho, xi_rho) float64 ... hc float64 ... h (eta_rho, xi_rho) float64 ... lat_rho (eta_rho, xi_rho) float64 ... Vtransform int32 ... * ocean_time (ocean_time) datetime64[ns] 2001-08-01 2001-08-08 Dimensions without coordinates: eta_rho, xi_rho Attributes: long_name: free-surface units: meter time: ocean_time field: free-surface, scalar, series

What happened:

This is the result obtained from the example above with xarray v0.16.1, as well as the current master.

python-traceback Traceback (most recent call last): File "/usr/local/pycharm-community-2017.3.4/helpers/pydev/_pydevd_bundle/pydevd_exec2.py", line 3, in Exec exec(exp, global_vars, local_vars) File "<string>", line 1, in <module> File "/home/rondeau/python/github/xarray/xarray/core/common.py", line 1268, in where return ops.where_method(self, cond, other) File "/home/rondeau/python/github/xarray/xarray/core/ops.py", line 193, in where_method return apply_ufunc( File "/home/rondeau/python/github/xarray/xarray/core/computation.py", line 1126, in apply_ufunc return apply_dataarray_vfunc( File "/home/rondeau/python/github/xarray/xarray/core/computation.py", line 268, in apply_dataarray_vfunc result_coords = build_output_coords(args, signature, exclude_dims) File "/home/rondeau/python/github/xarray/xarray/core/computation.py", line 232, in build_output_coords merged_vars, unused_indexes = merge_coordinates_without_align( File "/home/rondeau/python/github/xarray/xarray/core/merge.py", line 329, in merge_coordinates_without_align return merge_collected(filtered, prioritized) File "/home/rondeau/python/github/xarray/xarray/core/merge.py", line 229, in merge_collected merged_vars[name] = unique_variable(name, variables, compat) File "/home/rondeau/python/github/xarray/xarray/core/merge.py", line 120, in unique_variable out = out.set_dims(dim_lengths) File "/home/rondeau/python/github/xarray/xarray/core/variable.py", line 1442, in set_dims expanded_data = self.data File "/home/rondeau/python/github/xarray/xarray/core/variable.py", line 361, in data return self.values File "/home/rondeau/python/github/xarray/xarray/core/variable.py", line 512, in values return _as_array_or_item(self._data) File "/home/rondeau/python/github/xarray/xarray/core/variable.py", line 274, in _as_array_or_item data = np.asarray(data) File "/home/rondeau/.conda/envs/pyscen/lib/python3.8/site-packages/numpy/core/_asarray.py", line 85, in asarray return array(a, dtype, copy=False, order=order) File "/home/rondeau/python/github/xarray/xarray/core/indexing.py", line 685, in __array__ self._ensure_cached() File "/home/rondeau/python/github/xarray/xarray/core/indexing.py", line 682, in _ensure_cached self.array = NumpyIndexingAdapter(np.asarray(self.array)) File "/home/rondeau/.conda/envs/pyscen/lib/python3.8/site-packages/numpy/core/_asarray.py", line 85, in asarray return array(a, dtype, copy=False, order=order) File "/home/rondeau/python/github/xarray/xarray/core/indexing.py", line 655, in __array__ return np.asarray(self.array, dtype=dtype) File "/home/rondeau/.conda/envs/pyscen/lib/python3.8/site-packages/numpy/core/_asarray.py", line 85, in asarray return array(a, dtype, copy=False, order=order) File "/home/rondeau/python/github/xarray/xarray/core/indexing.py", line 560, in __array__ return np.asarray(array[self.key], dtype=None) File "/home/rondeau/python/github/xarray/xarray/backends/h5netcdf_.py", line 28, in __getitem__ return indexing.explicit_indexing_adapter( File "/home/rondeau/python/github/xarray/xarray/core/indexing.py", line 844, in explicit_indexing_adapter raw_key, numpy_indices = decompose_indexer(key, shape, indexing_support) File "/home/rondeau/python/github/xarray/xarray/core/indexing.py", line 858, in decompose_indexer return _decompose_outer_indexer(indexer, shape, indexing_support) File "/home/rondeau/python/github/xarray/xarray/core/indexing.py", line 1021, in _decompose_outer_indexer gains = [ File "/home/rondeau/python/github/xarray/xarray/core/indexing.py", line 1022, in <listcomp> (np.max(k) - np.min(k) + 1.0) / len(np.unique(k)) File "<__array_function__ internals>", line 5, in amax File "/home/rondeau/.conda/envs/pyscen/lib/python3.8/site-packages/numpy/core/fromnumeric.py", line 2667, in amax return _wrapreduction(a, np.maximum, 'max', axis, None, out, File "/home/rondeau/.conda/envs/pyscen/lib/python3.8/site-packages/numpy/core/fromnumeric.py", line 90, in _wrapreduction return ufunc.reduce(obj, axis, dtype, out, **passkwargs) ValueError: zero-size array to reduction operation maximum which has no identity

What you expected to happen:

This is the result obtained for the example above with xarray v0.15.1 python <xarray.DataArray 'zeta' (ocean_time: 0, eta_rho: 0, xi_rho: 0)> array([], shape=(0, 0, 0), dtype=float32) Coordinates: lon_rho (eta_rho, xi_rho) float64 hc float64 20.0 h (eta_rho, xi_rho) float64 lat_rho (eta_rho, xi_rho) float64 Vtransform int32 2 * ocean_time (ocean_time) datetime64[ns] Dimensions without coordinates: eta_rho, xi_rho Attributes: long_name: free-surface units: meter time: ocean_time field: free-surface, scalar, series

Anything else we need to know?:

This following example works as intended. This seems to occur because isel() eliminates auxiliary coordinates. python import xarray as xr ds = xr.tutorial.open_dataset('ROMS_example', engine='h5netcdf') da = ds["zeta"].isel(eta_rho=0, xi_rho=0) print(da.where(da>1000, drop=True)) python <xarray.DataArray 'zeta' (ocean_time: 0)> array([], dtype=float32) Coordinates: lon_rho float64 -93.6 hc float64 20.0 h float64 612.1 lat_rho float64 27.45 Vtransform int32 2 * ocean_time (ocean_time) datetime64[ns] Attributes: long_name: free-surface units: meter time: ocean_time field: free-surface, scalar, series

Environment:

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: 3.10.0-514.2.2.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: 1.10.5 libnetcdf: 4.7.4 xarray: 0.15.2.dev58+g0e43ba9.d20200521 pandas: 1.1.3 numpy: 1.19.1 scipy: 1.5.2 netCDF4: 1.5.3 pydap: None h5netcdf: 0.8.0 h5py: 2.10.0 Nio: None zarr: None cftime: 1.2.1 nc_time_axis: 1.2.0 PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.3.2 dask: 2.30.0 distributed: 2.30.0 matplotlib: 3.3.1 cartopy: 0.18.0 seaborn: 0.11.0 numbagg: None pint: 0.11 setuptools: 50.3.0.post20201006 pip: 20.2.3 conda: None pytest: None IPython: None sphinx: None ``` 
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