issue_comments: 712450334
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| html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| https://github.com/pydata/xarray/issues/4524#issuecomment-712450334 | https://api.github.com/repos/pydata/xarray/issues/4524 | 712450334 | MDEyOklzc3VlQ29tbWVudDcxMjQ1MDMzNA== | 10194086 | 2020-10-19T21:23:06Z | 2020-10-19T21:23:06Z | MEMBER | This also fails for
Traceback
```python-traceback
ValueError Traceback (most recent call last)
<ipython-input-14-9df3a1c8f9e1> in <module>
----> 1 da.where(da>1000, drop=True)
~/conda/envs/xarray_dev/lib/python3.8/site-packages/xarray/core/common.py in where(self, cond, other, drop)
1266 cond = cond.isel(**indexers)
1267
-> 1268 return ops.where_method(self, cond, other)
1269
1270 def close(self: Any) -> None:
~/conda/envs/xarray_dev/lib/python3.8/site-packages/xarray/core/ops.py in where_method(self, cond, other)
191 # alignment for three arguments is complicated, so don't support it yet
192 join = "inner" if other is dtypes.NA else "exact"
--> 193 return apply_ufunc(
194 duck_array_ops.where_method,
195 self,
~/conda/envs/xarray_dev/lib/python3.8/site-packages/xarray/core/computation.py in apply_ufunc(func, input_core_dims, output_core_dims, exclude_dims, vectorize, join, dataset_join, dataset_fill_value, keep_attrs, kwargs, dask, output_dtypes, output_sizes, meta, dask_gufunc_kwargs, *args)
1102 # feed DataArray apply_variable_ufunc through apply_dataarray_vfunc
1103 elif any(isinstance(a, DataArray) for a in args):
-> 1104 return apply_dataarray_vfunc(
1105 variables_vfunc,
1106 *args,
~/conda/envs/xarray_dev/lib/python3.8/site-packages/xarray/core/computation.py in apply_dataarray_vfunc(func, signature, join, exclude_dims, keep_attrs, *args)
257 else:
258 name = result_name(args)
--> 259 result_coords = build_output_coords(args, signature, exclude_dims)
260
261 data_vars = [getattr(a, "variable", a) for a in args]
~/conda/envs/xarray_dev/lib/python3.8/site-packages/xarray/core/computation.py in build_output_coords(args, signature, exclude_dims)
222 else:
223 # TODO: save these merged indexes, instead of re-computing them later
--> 224 merged_vars, unused_indexes = merge_coordinates_without_align(
225 coords_list, exclude_dims=exclude_dims
226 )
~/conda/envs/xarray_dev/lib/python3.8/site-packages/xarray/core/merge.py in merge_coordinates_without_align(objects, prioritized, exclude_dims)
327 filtered = collected
328
--> 329 return merge_collected(filtered, prioritized)
330
331
~/conda/envs/xarray_dev/lib/python3.8/site-packages/xarray/core/merge.py in merge_collected(grouped, prioritized, compat)
227 variables = [variable for variable, _ in elements_list]
228 try:
--> 229 merged_vars[name] = unique_variable(name, variables, compat)
230 except MergeError:
231 if compat != "minimal":
~/conda/envs/xarray_dev/lib/python3.8/site-packages/xarray/core/merge.py in unique_variable(name, variables, compat, equals)
118 if compat == "broadcast_equals":
119 dim_lengths = broadcast_dimension_size(variables)
--> 120 out = out.set_dims(dim_lengths)
121
122 if compat == "no_conflicts":
~/conda/envs/xarray_dev/lib/python3.8/site-packages/xarray/core/variable.py in set_dims(self, dims, shape)
1438 # don't use broadcast_to unless necessary so the result remains
1439 # writeable if possible
-> 1440 expanded_data = self.data
1441 elif shape is not None:
1442 dims_map = dict(zip(dims, shape))
~/conda/envs/xarray_dev/lib/python3.8/site-packages/xarray/core/variable.py in data(self)
357 return self._data
358 else:
--> 359 return self.values
360
361 @data.setter
~/conda/envs/xarray_dev/lib/python3.8/site-packages/xarray/core/variable.py in values(self)
508 def values(self):
509 """The variable's data as a numpy.ndarray"""
--> 510 return _as_array_or_item(self._data)
511
512 @values.setter
~/conda/envs/xarray_dev/lib/python3.8/site-packages/xarray/core/variable.py in _as_array_or_item(data)
270 data = data.get()
271 else:
--> 272 data = np.asarray(data)
273 if data.ndim == 0:
274 if data.dtype.kind == "M":
~/conda/envs/xarray_dev/lib/python3.8/site-packages/numpy/core/_asarray.py in asarray(a, dtype, order)
81
82 """
---> 83 return array(a, dtype, copy=False, order=order)
84
85
~/conda/envs/xarray_dev/lib/python3.8/site-packages/xarray/core/indexing.py in __array__(self, dtype)
683
684 def __array__(self, dtype=None):
--> 685 self._ensure_cached()
686 return np.asarray(self.array, dtype=dtype)
687
~/conda/envs/xarray_dev/lib/python3.8/site-packages/xarray/core/indexing.py in _ensure_cached(self)
680 def _ensure_cached(self):
681 if not isinstance(self.array, NumpyIndexingAdapter):
--> 682 self.array = NumpyIndexingAdapter(np.asarray(self.array))
683
684 def __array__(self, dtype=None):
~/conda/envs/xarray_dev/lib/python3.8/site-packages/numpy/core/_asarray.py in asarray(a, dtype, order)
81
82 """
---> 83 return array(a, dtype, copy=False, order=order)
84
85
~/conda/envs/xarray_dev/lib/python3.8/site-packages/xarray/core/indexing.py in __array__(self, dtype)
653
654 def __array__(self, dtype=None):
--> 655 return np.asarray(self.array, dtype=dtype)
656
657 def __getitem__(self, key):
~/conda/envs/xarray_dev/lib/python3.8/site-packages/numpy/core/_asarray.py in asarray(a, dtype, order)
81
82 """
---> 83 return array(a, dtype, copy=False, order=order)
84
85
~/conda/envs/xarray_dev/lib/python3.8/site-packages/xarray/core/indexing.py in __array__(self, dtype)
558 def __array__(self, dtype=None):
559 array = as_indexable(self.array)
--> 560 return np.asarray(array[self.key], dtype=None)
561
562 def transpose(self, order):
~/conda/envs/xarray_dev/lib/python3.8/site-packages/xarray/backends/netCDF4_.py in __getitem__(self, key)
70
71 def __getitem__(self, key):
---> 72 return indexing.explicit_indexing_adapter(
73 key, self.shape, indexing.IndexingSupport.OUTER, self._getitem
74 )
~/conda/envs/xarray_dev/lib/python3.8/site-packages/xarray/core/indexing.py in explicit_indexing_adapter(key, shape, indexing_support, raw_indexing_method)
843 """
844 raw_key, numpy_indices = decompose_indexer(key, shape, indexing_support)
--> 845 result = raw_indexing_method(raw_key.tuple)
846 if numpy_indices.tuple:
847 # index the loaded np.ndarray
~/conda/envs/xarray_dev/lib/python3.8/site-packages/xarray/backends/netCDF4_.py in _getitem(self, key)
83 with self.datastore.lock:
84 original_array = self.get_array(needs_lock=False)
---> 85 array = getitem(original_array, key)
86 except IndexError:
87 # Catch IndexError in netCDF4 and return a more informative
netCDF4/_netCDF4.pyx in netCDF4._netCDF4.Variable.__getitem__()
~/conda/envs/xarray_dev/lib/python3.8/site-packages/netCDF4/utils.py in _StartCountStride(elem, shape, dimensions, grp, datashape, put, use_get_vars)
435 # ITERABLE #
436 elif np.iterable(e) and np.array(e).dtype.kind in 'i': # Sequence of integers
--> 437 start[...,i] = np.apply_along_axis(lambda x: e*x, i, np.ones(sdim[:-1]))
438 indices[...,i] = np.apply_along_axis(lambda x: np.arange(sdim[i])*x, i, np.ones(sdim[:-1], int))
439
<__array_function__ internals> in apply_along_axis(*args, **kwargs)
~/conda/envs/xarray_dev/lib/python3.8/site-packages/numpy/lib/shape_base.py in apply_along_axis(func1d, axis, arr, *args, **kwargs)
374 ind0 = next(inds)
375 except StopIteration as e:
--> 376 raise ValueError(
377 'Cannot apply_along_axis when any iteration dimensions are 0'
378 ) from None
ValueError: Cannot apply_along_axis when any iteration dimensions are 0
```
It does not fail when you load the data beforehand:
|
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724777139 |