Version 0.13 broke my ufunc #3339
Comments
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@rsignell-usgs - can you add the output from INSTALLED VERSIONScommit: None xarray: 0.13.0 |
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There was a recent bug fix in dask about this (dask/dask#5334). Can you try updating to the latest dask release? |
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Yep, upgrading to dask=2.4.0 fixed the problem! Phew. |
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Related: #3222 |
This simple xarray ufunc to calculate wind speed worked under
xarray=0.12.3:but with
xarray=0.13.0,merge_variablesfails and dumps this traceback:--------------------------------------------------------------------------- ValueError Traceback (most recent call last) <ipython-input-4-2ac66965ccfc> in <module> ----> 1 windspeed = xr.ufuncs.sqrt(ds['u-component_of_wind_height_above_ground']**2 + ds['v-component_of_wind_height_above_ground']**2) /srv/conda/envs/notebook/lib/python3.7/site-packages/xarray/core/dataarray.py in func(self, other) 2495 else f(other_variable, self.variable) 2496 ) -> 2497 coords = self.coords._merge_raw(other_coords) 2498 name = self._result_name(other) 2499 /srv/conda/envs/notebook/lib/python3.7/site-packages/xarray/core/coordinates.py in _merge_raw(self, other) 128 else: 129 # don't align because we already called xarray.align --> 130 variables = expand_and_merge_variables([self.variables, other.variables]) 131 return variables 132 /srv/conda/envs/notebook/lib/python3.7/site-packages/xarray/core/merge.py in expand_and_merge_variables(objs, priority_arg) 380 expanded = expand_variable_dicts(objs) 381 priority_vars = _get_priority_vars(objs, priority_arg) --> 382 variables = merge_variables(expanded, priority_vars) 383 return variables 384 /srv/conda/envs/notebook/lib/python3.7/site-packages/xarray/core/merge.py in merge_variables(list_of_variables_dicts, priority_vars, compat) 202 else: 203 try: --> 204 merged[name] = unique_variable(name, var_list, compat) 205 except MergeError: 206 if compat != "minimal": /srv/conda/envs/notebook/lib/python3.7/site-packages/xarray/core/merge.py in unique_variable(name, variables, compat, equals) 116 out = out.compute() 117 for var in variables[1:]: --> 118 equals = getattr(out, compat)(var) 119 if not equals: 120 break /srv/conda/envs/notebook/lib/python3.7/site-packages/xarray/core/variable.py in broadcast_equals(self, other, equiv) 1574 except (ValueError, AttributeError): 1575 return False -> 1576 return self.equals(other, equiv=equiv) 1577 1578 def identical(self, other): /srv/conda/envs/notebook/lib/python3.7/site-packages/xarray/core/variable.py in equals(self, other, equiv) 1558 try: 1559 return self.dims == other.dims and ( -> 1560 self._data is other._data or equiv(self.data, other.data) 1561 ) 1562 except (TypeError, AttributeError): /srv/conda/envs/notebook/lib/python3.7/site-packages/xarray/core/duck_array_ops.py in array_equiv(arr1, arr2) 200 with warnings.catch_warnings(): 201 warnings.filterwarnings("ignore", "In the future, 'NAT == x'") --> 202 flag_array = (arr1 == arr2) | (isnull(arr1) & isnull(arr2)) 203 return bool(flag_array.all()) 204 /srv/conda/envs/notebook/lib/python3.7/site-packages/dask/array/core.py in __eq__(self, other) 1740 1741 def __eq__(self, other): -> 1742 return elemwise(operator.eq, self, other) 1743 1744 def __gt__(self, other): /srv/conda/envs/notebook/lib/python3.7/site-packages/dask/array/core.py in elemwise(op, *args, **kwargs) 3765 for a in args 3766 ), -> 3767 **blockwise_kwargs 3768 ) 3769 /srv/conda/envs/notebook/lib/python3.7/site-packages/dask/array/blockwise.py in blockwise(func, out_ind, name, token, dtype, adjust_chunks, new_axes, align_arrays, concatenate, meta, *args, **kwargs) 143 144 if align_arrays: --> 145 chunkss, arrays = unify_chunks(*args) 146 else: 147 arginds = [(a, i) for (a, i) in toolz.partition(2, args) if i is not None] /srv/conda/envs/notebook/lib/python3.7/site-packages/dask/array/core.py in unify_chunks(*args, **kwargs) 3034 3035 arginds = [ -> 3036 (asanyarray(a) if ind is not None else a, ind) for a, ind in partition(2, args) 3037 ] # [x, ij, y, jk] 3038 args = list(concat(arginds)) # [(x, ij), (y, jk)] /srv/conda/envs/notebook/lib/python3.7/site-packages/dask/array/core.py in <listcomp>(.0) 3034 3035 arginds = [ -> 3036 (asanyarray(a) if ind is not None else a, ind) for a, ind in partition(2, args) 3037 ] # [x, ij, y, jk] 3038 args = list(concat(arginds)) # [(x, ij), (y, jk)] /srv/conda/envs/notebook/lib/python3.7/site-packages/dask/array/core.py in asanyarray(a) 3609 elif hasattr(a, "to_dask_array"): 3610 return a.to_dask_array() -> 3611 elif hasattr(a, "data") and type(a).__module__.startswith("xarray."): 3612 return asanyarray(a.data) 3613 elif isinstance(a, (list, tuple)) and any(isinstance(i, Array) for i in a): ValueError: cannot include dtype 'M' in a bufferIs this a bug or a feature that I should be handling differently in my code?
Output of
xr.show_versions()INSTALLED VERSIONS
commit: None
python: 3.7.3 | packaged by conda-forge | (default, Jul 1 2019, 21:52:21)
[GCC 7.3.0]
python-bits: 64
OS: Linux
OS-release: 4.14.138-114.102.amzn2.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: en_US.UTF-8
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
libhdf5: 1.10.5
libnetcdf: 4.6.2
xarray: 0.13.0
pandas: 0.24.2
numpy: 1.17.2
scipy: 1.3.1
netCDF4: 1.5.1.2
pydap: installed
h5netcdf: 0.7.4
h5py: 2.10.0
Nio: None
zarr: 2.3.2
cftime: 1.0.3.4
nc_time_axis: None
PseudoNetCDF: None
rasterio: 1.0.28
cfgrib: None
iris: 2.2.0
bottleneck: None
dask: 2.2.0
distributed: 2.2.0
matplotlib: 3.1.1
cartopy: 0.17.0
seaborn: None
numbagg: None
setuptools: 41.2.0
pip: 19.2.3
conda: None
pytest: None
IPython: 7.8.0
sphinx: None
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