我正在使用python xarray的open_mfdataset打开一个分布在多个HDF5文件中的数据集。我有2个数据集，结构上应该几乎相同。第一个数据集工作正常，但是当我尝试打开另一个数据集时，出现错误：
ValueError: axes don't match array
我不知道是什么原因引起的错误，每个Google搜索结果都涉及有关神经网络的问题，这些神经网络似乎会跳出相同的错误，但原因有所不同。
编辑：我应该分享一下，发生错误的行如下所示：
df = xr.open_mfdataset("/some/directory/*.h5", concat_dim='TIME')
我会共享文件，但是它们很大，我不确定这样做的合法性，也不确定在没有文件的情况下如何重现问题。
编辑2：
我认为我找到了问题。数据的（x，y，z）尺寸为（300，300，60）。但是，我使用的模型对x和y使用相同的命名维，因为它的nx和ny数量相同（这是非常愚蠢的imo）。因此，文件标题指出：
-> % ncdump -h icefix-A-2014-02-05-120000-g1.h5
netcdf icefix-A-2014-02-05-120000-g1 {
dimensions:
phony_dim_0 = 300 ;
phony_dim_1 = 60 ;
phony_dim_2 = 2 ;
phony_dim_3 = 5 ;
phony_dim_4 = 11 ;
3D变量看起来像
float CCP(phony_dim_1, phony_dim_0, phony_dim_0) ;
我认为xarray在处理具有重复命名维度的变量时遇到问题。除了改变模型输出文件的方式之外，我不确定是否有办法解决此问题。
完整的回溯如下：
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-10-cb4a12bd492e> in <module>
----> 1 control_d1 = xr.open_mfdataset(datadir + "feb2014_control/icefix*g1.h5", concat_dim='TIME')
~/anaconda3/lib/python3.7/site-packages/xarray/backends/api.py in open_mfdataset(paths, chunks, concat_dim, compat, preprocess, engine, lock, data_vars, coords, autoclose, parallel, **kwargs)
717 data_vars=data_vars, coords=coords,
718 infer_order_from_coords=infer_order_from_coords,
--> 719 ids=ids)
720 except ValueError:
721 for ds in datasets:
~/anaconda3/lib/python3.7/site-packages/xarray/core/combine.py in _auto_combine(datasets, concat_dims, compat, data_vars, coords, infer_order_from_coords, ids)
551 # Repeatedly concatenate then merge along each dimension
552 combined = _combine_nd(combined_ids, concat_dims, compat=compat,
--> 553 data_vars=data_vars, coords=coords)
554 return combined
555
~/anaconda3/lib/python3.7/site-packages/xarray/core/combine.py in _combine_nd(combined_ids, concat_dims, data_vars, coords, compat)
473 data_vars=data_vars,
474 coords=coords,
--> 475 compat=compat)
476 combined_ds = list(combined_ids.values())[0]
477 return combined_ds
~/anaconda3/lib/python3.7/site-packages/xarray/core/combine.py in _auto_combine_all_along_first_dim(combined_ids, dim, data_vars, coords, compat)
491 datasets = combined_ids.values()
492 new_combined_ids[new_id] = _auto_combine_1d(datasets, dim, compat,
--> 493 data_vars, coords)
494 return new_combined_ids
495
~/anaconda3/lib/python3.7/site-packages/xarray/core/combine.py in _auto_combine_1d(datasets, concat_dim, compat, data_vars, coords)
509 concatenated = [_auto_concat(list(ds_group), dim=dim,
510 data_vars=data_vars, coords=coords)
--> 511 for id, ds_group in grouped_by_vars]
512 else:
513 concatenated = datasets
~/anaconda3/lib/python3.7/site-packages/xarray/core/combine.py in <listcomp>(.0)
509 concatenated = [_auto_concat(list(ds_group), dim=dim,
510 data_vars=data_vars, coords=coords)
--> 511 for id, ds_group in grouped_by_vars]
512 else:
513 concatenated = datasets
~/anaconda3/lib/python3.7/site-packages/xarray/core/combine.py in _auto_concat(datasets, dim, data_vars, coords)
367 'explicitly')
368 dim, = concat_dims
--> 369 return concat(datasets, dim=dim, data_vars=data_vars, coords=coords)
370
371
~/anaconda3/lib/python3.7/site-packages/xarray/core/combine.py in concat(objs, dim, data_vars, coords, compat, positions, indexers, mode, concat_over)
118 raise TypeError('can only concatenate xarray Dataset and DataArray '
119 'objects, got %s' % type(first_obj))
--> 120 return f(objs, dim, data_vars, coords, compat, positions)
121
122
~/anaconda3/lib/python3.7/site-packages/xarray/core/combine.py in _dataset_concat(datasets, dim, data_vars, coords, compat, positions)
303 if k in concat_over:
304 vars = ensure_common_dims([ds.variables[k] for ds in datasets])
--> 305 combined = concat_vars(vars, dim, positions)
306 insert_result_variable(k, combined)
307
~/anaconda3/lib/python3.7/site-packages/xarray/core/variable.py in concat(variables, dim, positions, shortcut)
2083 along the given dimension.
2084 """
-> 2085 variables = list(variables)
2086 if all(isinstance(v, IndexVariable) for v in variables):
2087 return IndexVariable.concat(variables, dim, positions, shortcut)
~/anaconda3/lib/python3.7/site-packages/xarray/core/combine.py in ensure_common_dims(vars)
296 common_shape = tuple(non_concat_dims.get(d, dim_len)
297 for d in common_dims)
--> 298 var = var.set_dims(common_dims, common_shape)
299 yield var
300
~/anaconda3/lib/python3.7/site-packages/xarray/core/variable.py in set_dims(self, dims, shape)
1209 expanded_var = Variable(expanded_dims, expanded_data, self._attrs,
1210 self._encoding, fastpath=True)
-> 1211 return expanded_var.transpose(*dims)
1212
1213 def _stack_once(self, dims, new_dim):
~/anaconda3/lib/python3.7/site-packages/xarray/core/variable.py in transpose(self, *dims)
1152 return self.copy(deep=False)
1153
-> 1154 data = as_indexable(self._data).transpose(axes)
1155 return type(self)(dims, data, self._attrs, self._encoding,
1156 fastpath=True)
~/anaconda3/lib/python3.7/site-packages/xarray/core/indexing.py in transpose(self, order)
1210
1211 def transpose(self, order):
-> 1212 return self.array.transpose(order)
1213
1214
~/anaconda3/lib/python3.7/site-packages/dask/array/core.py in transpose(self, *axes)
1331 See Also
1332 --------
-> 1333 da.store
1334 h5py.File.create_dataset
1335 """
~/anaconda3/lib/python3.7/site-packages/dask/array/routines.py in transpose(a, axes)
136
137
--> 138 @derived_from(np)
139 def swapaxes(a, axis1, axis2):
140 if axis1 == axis2:
ValueError: axes don't match array