我正在使用xarray来使用xarray.open_mfdataset连接多个netcsf文件.然而，当我try 运行我的代码时，我会遇到以下错误:
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
Cell In[21], line 1
----> 1 ds = xarray.open_mfdataset('oisst_*.nc', combine="nested", concat_dim="time")
File ~/miniconda3/lib/python3.10/site-packages/xarray/backends/api.py:1056, in open_mfdataset(paths, chunks, concat_dim, compat, preprocess, engine, data_vars, coords, combine, parallel, join, attrs_file, combine_attrs, **kwargs)
1053 open_ = open_dataset
1054 getattr_ = getattr
-> 1056 datasets = [open_(p, **open_kwargs) for p in paths]
1057 closers = [getattr_(ds, "_close") for ds in datasets]
1058 if preprocess is not None:
File ~/miniconda3/lib/python3.10/site-packages/xarray/backends/api.py:1056, in <listcomp>(.0)
1053 open_ = open_dataset
1054 getattr_ = getattr
-> 1056 datasets = [open_(p, **open_kwargs) for p in paths]
1057 closers = [getattr_(ds, "_close") for ds in datasets]
1058 if preprocess is not None:
File ~/miniconda3/lib/python3.10/site-packages/xarray/backends/api.py:579, in open_dataset(filename_or_obj, engine, chunks, cache, decode_cf, mask_and_scale, decode_times, decode_timedelta, use_cftime, concat_characters, decode_coords, drop_variables, inline_array, chunked_array_type, from_array_kwargs, backend_kwargs, **kwargs)
572 overwrite_encoded_chunks = kwargs.pop("overwrite_encoded_chunks", None)
573 backend_ds = backend.open_dataset(
574 filename_or_obj,
575 drop_variables=drop_variables,
576 **decoders,
577 **kwargs,
578 )
--> 579 ds = _dataset_from_backend_dataset(
580 backend_ds,
581 filename_or_obj,
582 engine,
583 chunks,
584 cache,
585 overwrite_encoded_chunks,
586 inline_array,
587 chunked_array_type,
588 from_array_kwargs,
589 drop_variables=drop_variables,
590 **decoders,
591 **kwargs,
592 )
593 return ds
File ~/miniconda3/lib/python3.10/site-packages/xarray/backends/api.py:372, in _dataset_from_backend_dataset(backend_ds, filename_or_obj, engine, chunks, cache, overwrite_encoded_chunks, inline_array, chunked_array_type, from_array_kwargs, **extra_tokens)
370 ds = backend_ds
371 else:
--> 372 ds = _chunk_ds(
373 backend_ds,
374 filename_or_obj,
375 engine,
376 chunks,
377 overwrite_encoded_chunks,
378 inline_array,
379 chunked_array_type,
380 from_array_kwargs,
381 **extra_tokens,
382 )
384 ds.set_close(backend_ds._close)
386 # Ensure source filename always stored in dataset object
File ~/miniconda3/lib/python3.10/site-packages/xarray/backends/api.py:320, in _chunk_ds(backend_ds, filename_or_obj, engine, chunks, overwrite_encoded_chunks, inline_array, chunked_array_type, from_array_kwargs, **extra_tokens)
309 def _chunk_ds(
310 backend_ds,
311 filename_or_obj,
(...)
318 **extra_tokens,
319 ):
--> 320 chunkmanager = guess_chunkmanager(chunked_array_type)
322 # TODO refactor to move this dask-specific logic inside the DaskManager class
323 if isinstance(chunkmanager, DaskManager):
File ~/miniconda3/lib/python3.10/site-packages/xarray/namedarray/parallelcompat.py:110, in guess_chunkmanager(manager)
108 if isinstance(manager, str):
109 if manager not in chunkmanagers:
--> 110 raise ValueError(
111 f"unrecognized chunk manager {manager} - must be one of: {list(chunkmanagers)}"
112 )
114 return chunkmanagers[manager]
115 elif isinstance(manager, ChunkManagerEntrypoint):
116 # already a valid ChunkManager so just pass through
ValueError: unrecognized chunk manager dask - must be one of: []
我正在使用以下代码:
import netCDF4
import numpy
import xarray
ds = xarray.open_mfdataset('oisst_*.nc', combine="nested", concat_dim="time")
我引用的是this medium page这个代码.
我已经try 了this种现有方法.我按照OP的建议将xArray降级到2022.11.0，然后降级到0.21.1，重新安装dask并将xArray升级回2024.2.0，但发现没有成功解决这个问题.
我的xray和dask当前版本是:
INSTALLED VERSIONS
------------------
commit: None
python: 3.10.10 (main, Mar 21 2023, 13:41:39) [Clang 14.0.6 ]
python-bits: 64
OS: Darwin
OS-release: 23.4.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: None
LOCALE: (None, 'UTF-8')
libhdf5: 1.12.2
libnetcdf: 4.9.3-development
xarray: 2024.2.0
pandas: 1.5.3
numpy: 1.23.5
scipy: 1.10.1
netCDF4: 1.6.5
pydap: None
h5netcdf: None
h5py: 3.8.0
Nio: None
zarr: None
cftime: 1.6.3
nc_time_axis: None
iris: None
bottleneck: None
dask: 2024.4.1
distributed: None
matplotlib: 3.7.1
cartopy: None
seaborn: 0.12.2
numbagg: None
fsspec: 2024.3.1
cupy: None
pint: None
sparse: None
flox: None
numpy_groupies: None
setuptools: 69.1.1
pip: 24.0
conda: 23.3.1
pytest: None
mypy: None
IPython: 8.12.0
sphinx: None