- MNE version: 1.1.1 or 1.0.0
- operating system: Linux
Hi! guys,
I installed mne_connectivity in the MNE environment (version 1.0.0) first, it showed that installation was done. But I cannot import mne_connectivity, here is the error message:
In [61]: import mne_connectivity
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
Input In [61], in <cell line: 1>()
----> 1 import mne_connectivity
File ~/.conda/envs/mne/lib/python3.9/site-packages/mne_connectivity/__init__.py:11, in <module>
3 # Authors: Adam Li <ali39@jhu.edu>
4 # Eric Larson <larson.eric.d@gmail.com>
5 # Britta Westner <britta.wstnr@gmail.com>
6 #
7 # License: BSD (3-clause)
9 __version__ = '0.3'
---> 11 from .base import (Connectivity, EpochConnectivity, EpochSpectralConnectivity,
12 EpochSpectroTemporalConnectivity, EpochTemporalConnectivity,
13 SpectralConnectivity, SpectroTemporalConnectivity,
14 TemporalConnectivity)
15 from .effective import phase_slope_index
16 from .envelope import envelope_correlation, symmetric_orth
File ~/.conda/envs/mne/lib/python3.9/site-packages/mne_connectivity/base.py:4, in <module>
1 from copy import copy, deepcopy
3 import numpy as np
----> 4 import xarray as xr
5 import pandas as pd
6 from mne.utils import (_check_combine, _check_option, _validate_type,
7 copy_function_doc_to_method_doc, object_size,
8 sizeof_fmt, _check_event_id, _ensure_events,
9 _on_missing, warn, check_random_state)
File ~/.conda/envs/mne/lib/python3.9/site-packages/xarray/__init__.py:1, in <module>
----> 1 from . import testing, tutorial
2 from .backends.api import (
3 load_dataarray,
4 load_dataset,
(...)
8 save_mfdataset,
9 )
10 from .backends.rasterio_ import open_rasterio
File ~/.conda/envs/mne/lib/python3.9/site-packages/xarray/testing.py:9, in <module>
6 import numpy as np
7 import pandas as pd
----> 9 from xarray.core import duck_array_ops, formatting, utils
10 from xarray.core.dataarray import DataArray
11 from xarray.core.dataset import Dataset
File ~/.conda/envs/mne/lib/python3.9/site-packages/xarray/core/duck_array_ops.py:26, in <module>
23 from numpy import take, tensordot, transpose, unravel_index # noqa
24 from numpy import where as _where
---> 26 from . import dask_array_compat, dask_array_ops, dtypes, npcompat, nputils
27 from .nputils import nanfirst, nanlast
28 from .pycompat import cupy_array_type, dask_array_type, is_duck_dask_array
File ~/.conda/envs/mne/lib/python3.9/site-packages/xarray/core/npcompat.py:72, in <module>
49 from numpy.typing._dtype_like import _DTypeLikeNested, _ShapeLike, _SupportsDType
51 # Xarray requires a Mapping[Hashable, dtype] in many places which
52 # conflics with numpys own DTypeLike (with dtypes for fields).
53 # https://numpy.org/devdocs/reference/typing.html#numpy.typing.DTypeLike
54 # This is a copy of this DTypeLike that allows only non-Mapping dtypes.
55 DTypeLikeSave = Union[
56 np.dtype,
57 # default data type (float64)
58 None,
59 # array-scalar types and generic types
60 Type[Any],
61 # character codes, type strings or comma-separated fields, e.g., 'float64'
62 str,
63 # (flexible_dtype, itemsize)
64 Tuple[_DTypeLikeNested, int],
65 # (fixed_dtype, shape)
66 Tuple[_DTypeLikeNested, _ShapeLike],
67 # (base_dtype, new_dtype)
68 Tuple[_DTypeLikeNested, _DTypeLikeNested],
69 # because numpy does the same?
70 List[Any],
71 # anything with a dtype attribute
---> 72 _SupportsDType[np.dtype],
73 ]
74 except ImportError:
75 # fall back for numpy < 1.20, ArrayLike adapted from numpy.typing._array_like
76 from typing import Protocol
File ~/.conda/envs/mne/lib/python3.9/typing.py:277, in _tp_cache.<locals>.decorator.<locals>.inner(*args, **kwds)
275 except TypeError:
276 pass # All real errors (not unhashable args) are raised below.
--> 277 return func(*args, **kwds)
File ~/.conda/envs/mne/lib/python3.9/typing.py:1004, in Generic.__class_getitem__(cls, params)
1000 raise TypeError(
1001 f"Parameters to {cls.__name__}[...] must all be unique")
1002 else:
1003 # Subscripting a regular Generic subclass.
-> 1004 _check_generic(cls, params, len(cls.__parameters__))
1005 return _GenericAlias(cls, params)
File ~/.conda/envs/mne/lib/python3.9/site-packages/typing_extensions.py:101, in _check_generic(cls, parameters, elen)
97 """Check correct count for parameters of a generic cls (internal helper).
98 This gives a nice error message in case of count mismatch.
99 """
100 if not elen:
--> 101 raise TypeError(f"{cls} is not a generic class")
102 if elen is _marker:
103 if not hasattr(cls, "__parameters__") or not cls.__parameters__:
TypeError: <class 'numpy.typing._dtype_like._SupportsDType'> is not a generic class
I also update mne to 1.1.1, mne_connectivity still cannot be imported.
I don’t know if something wrong with xarray package, so I’m trying to install xarray via conda install -c conda-forge xarray dask netCDF4 bottleneck. Any suggestions what should I do to solve this problem? Thanks a lot! 
