Error in "Spatiotemporal permutation F-test on full sensor data" tutorial

[joebathelt]

Proposed documentation enhancement

First, thank you for developing MNE-Python and for all the work that went into creating such comprehensive and useful tutorials.

I recently completed the spatiotemporal clustering tutorial for full sensor data using MNE version 1.8. However, when I reached the clustering step, I encountered an error at Line 312 that prevented the clustering from completing successfully:

Exception ignored in: 'scipy.sparse.csgraph._traversal._connected_components_undirected'
Traceback (most recent call last):
  File "/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py", line 304, in _get_components
    _, components = connected_components(adjacency)
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: Buffer dtype mismatch, expected 'ITYPE_t' but got 'long'

It seems the issue is related to the format or type of the adjacency matrix, but I’m unsure how to resolve it. Could you please advise on what might be causing this error and any steps I could take to fix it?

[welcome]

Hello! 👋 Thanks for opening your first issue here! ❤️ We will try to get back to you soon. 🚴

[larsoner]

Can you paste the full traceback and also the output of mne sys_info? I suspect that this is a SciPy bug having to do with connected_components but to replicate and investigate I need a bit more info!

[joebathelt]

Hi @larsoner,

Thank you for the swift response.

Here is the full traceback:

stat_fun(H1): min=6.752417666025855e-07 max=38.40836555950498
Running initial clustering …
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'ITYPE_t' but got 'long'
Exception ignored in: 'scipy.sparse.csgraph._traversal._connected_components_undirected'
Traceback (most recent call last):
  File "/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py", line 304, in _get_components
    _, components = connected_components(adjacency)
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: Buffer dtype mismatch, expected 'ITYPE_t' but got 'long'
---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
File /Users/joebathelt/Downloads/Spatiotemporal F-test full sensor (1).py:15
     [12](https://file+.vscode-resource.vscode-cdn.net/Users/joebathelt/Downloads/Spatiotemporal%20F-test%20full%20sensor%20(1).py:12) tfr_threshold = 15.0
     [14](https://file+.vscode-resource.vscode-cdn.net/Users/joebathelt/Downloads/Spatiotemporal%20F-test%20full%20sensor%20(1).py:14) # run cluster based permutation analysis
---> [15](https://file+.vscode-resource.vscode-cdn.net/Users/joebathelt/Downloads/Spatiotemporal%20F-test%20full%20sensor%20(1).py:15) cluster_stats = spatio_temporal_cluster_test(
     [16](https://file+.vscode-resource.vscode-cdn.net/Users/joebathelt/Downloads/Spatiotemporal%20F-test%20full%20sensor%20(1).py:16)     X,
     [17](https://file+.vscode-resource.vscode-cdn.net/Users/joebathelt/Downloads/Spatiotemporal%20F-test%20full%20sensor%20(1).py:17)     n_permutations=1000,
     [18](https://file+.vscode-resource.vscode-cdn.net/Users/joebathelt/Downloads/Spatiotemporal%20F-test%20full%20sensor%20(1).py:18)     threshold=tfr_threshold,
     [19](https://file+.vscode-resource.vscode-cdn.net/Users/joebathelt/Downloads/Spatiotemporal%20F-test%20full%20sensor%20(1).py:19)     tail=1,
     [20](https://file+.vscode-resource.vscode-cdn.net/Users/joebathelt/Downloads/Spatiotemporal%20F-test%20full%20sensor%20(1).py:20)     n_jobs=None,
     [21](https://file+.vscode-resource.vscode-cdn.net/Users/joebathelt/Downloads/Spatiotemporal%20F-test%20full%20sensor%20(1).py:21)     buffer_size=None,
     [22](https://file+.vscode-resource.vscode-cdn.net/Users/joebathelt/Downloads/Spatiotemporal%20F-test%20full%20sensor%20(1).py:22)     adjacency=tfr_adjacency,
     [23](https://file+.vscode-resource.vscode-cdn.net/Users/joebathelt/Downloads/Spatiotemporal%20F-test%20full%20sensor%20(1).py:23) )

File <decorator-gen-306>:12, in spatio_temporal_cluster_test(X, threshold, n_permutations, tail, stat_fun, adjacency, n_jobs, seed, max_step, spatial_exclude, step_down_p, t_power, out_type, check_disjoint, buffer_size, verbose)

File /opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1548, in spatio_temporal_cluster_test(X, threshold, n_permutations, tail, stat_fun, adjacency, n_jobs, seed, max_step, spatial_exclude, step_down_p, t_power, out_type, check_disjoint, buffer_size, verbose)
   [1546](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1546) else:
   [1547](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1547)     exclude = None
-> [1548](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1548) return permutation_cluster_test(
   [1549](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1549)     X,
   [1550](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1550)     threshold=threshold,
   [1551](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1551)     stat_fun=stat_fun,
   [1552](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1552)     tail=tail,
   [1553](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1553)     n_permutations=n_permutations,
   [1554](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1554)     adjacency=adjacency,
   [1555](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1555)     n_jobs=n_jobs,
   [1556](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1556)     seed=seed,
   [1557](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1557)     max_step=max_step,
   [1558](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1558)     exclude=exclude,
   [1559](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1559)     step_down_p=step_down_p,
   [1560](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1560)     t_power=t_power,
   [1561](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1561)     out_type=out_type,
   [1562](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1562)     check_disjoint=check_disjoint,
   [1563](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1563)     buffer_size=buffer_size,
   [1564](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1564) )

File <decorator-gen-303>:12, in permutation_cluster_test(X, threshold, n_permutations, tail, stat_fun, adjacency, n_jobs, seed, max_step, exclude, step_down_p, t_power, out_type, check_disjoint, buffer_size, verbose)

File /opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1242, in permutation_cluster_test(X, threshold, n_permutations, tail, stat_fun, adjacency, n_jobs, seed, max_step, exclude, step_down_p, t_power, out_type, check_disjoint, buffer_size, verbose)
   [1182](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1182) """Cluster-level statistical permutation test.
   [1183](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1183) 
   [1184](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1184) For a list of :class:`NumPy arrays <numpy.ndarray>` of data,
   (...)
   [1239](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1239) .. footbibliography::
   [1240](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1240) """
   [1241](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1241) stat_fun, threshold = _check_fun(X, stat_fun, threshold, tail, "between")
-> [1242](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1242) return _permutation_cluster_test(
   [1243](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1243)     X=X,
   [1244](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1244)     threshold=threshold,
   [1245](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1245)     n_permutations=n_permutations,
   [1246](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1246)     tail=tail,
   [1247](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1247)     stat_fun=stat_fun,
   [1248](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1248)     adjacency=adjacency,
   [1249](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1249)     n_jobs=n_jobs,
   [1250](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1250)     seed=seed,
   [1251](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1251)     max_step=max_step,
   [1252](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1252)     exclude=exclude,
   [1253](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1253)     step_down_p=step_down_p,
   [1254](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1254)     t_power=t_power,
   [1255](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1255)     out_type=out_type,
   [1256](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1256)     check_disjoint=check_disjoint,
   [1257](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1257)     buffer_size=buffer_size,
   [1258](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1258) )

File /opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:987, in _permutation_cluster_test(X, threshold, n_permutations, tail, stat_fun, adjacency, n_jobs, seed, max_step, exclude, step_down_p, t_power, out_type, check_disjoint, buffer_size)
    [985](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:985)     partitions = None
    [986](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:986) logger.info("Running initial clustering …")
--> [987](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:987) out = _find_clusters(
    [988](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:988)     t_obs,
    [989](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:989)     threshold,
    [990](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:990)     tail,
    [991](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:991)     adjacency,
    [992](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:992)     max_step=max_step,
    [993](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:993)     include=include,
    [994](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:994)     partitions=partitions,
    [995](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:995)     t_power=t_power,
    [996](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:996)     show_info=True,
    [997](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:997) )
    [998](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:998) clusters, cluster_stats = out
   [1000](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:1000) # The stat should have the same shape as the samples

File /opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:455, in _find_clusters(x, threshold, tail, adjacency, max_step, include, partitions, t_power, show_info)
    [453](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:453) for x_in in x_ins:
    [454](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:454)     if np.any(x_in):
--> [455](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:455)         out = _find_clusters_1dir_parts(
    [456](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:456)             x, x_in, adjacency, max_step, partitions, t_power, ndimage
    [457](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:457)         )
    [458](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:458)         clusters += out[0]
    [459](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:459)         sums.append(out[1])

File /opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:493, in _find_clusters_1dir_parts(x, x_in, adjacency, max_step, partitions, t_power, ndimage)
    [491](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:491) """Deal with partitions, and pass the work to _find_clusters_1dir."""
    [492](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:492) if partitions is None:
--> [493](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:493)     clusters, sums = _find_clusters_1dir(
    [494](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:494)         x, x_in, adjacency, max_step, t_power, ndimage
    [495](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:495)     )
    [496](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:496) else:
    [497](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:497)     # cluster each partition separately
    [498](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:498)     clusters = list()

File /opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:547, in _find_clusters_1dir(x, x_in, adjacency, max_step, t_power, ndimage)
    [545](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:545)     adjacency = sparse.coo_array(adjacency)
    [546](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:546) if sparse.issparse(adjacency) or adjacency is False:
--> [547](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:547)     clusters = _get_components(x_in, adjacency)
    [548](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:548) elif isinstance(adjacency, list):  # use temporal adjacency
    [549](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:549)     clusters = _get_clusters_st(x_in, adjacency, max_step)

File /opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:311, in _get_components(x_in, adjacency, return_list)
    [309](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:309) mask = np.zeros(len(comp_list), dtype=bool)
    [310](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:310) for ii, comp in enumerate(components):
--> [311](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:311)     comp_list[comp].append(ii)
    [312](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:312)     mask[comp] += x_in[ii]
    [313](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/lib/python3.11/site-packages/mne/stats/cluster_level.py:313) clusters = [np.array(k) for k, m in zip(comp_list, mask) if m]

IndexError: list index out of range

... and here is the output from mne.sys_info():

Platform             macOS-15.0.1-arm64-arm-64bit
Python               3.11.3 | packaged by conda-forge | (main, Apr  6 2023, 08:58:31) [Clang 14.0.6 ]
Executable           [/opt/homebrew/anaconda3/envs/LonelyEEG/bin/python](https://file+.vscode-resource.vscode-cdn.net/opt/homebrew/anaconda3/envs/LonelyEEG/bin/python)
CPU                  arm (10 cores)
Memory               16.0 GB

Core
├☑ mne               1.8.0 (latest release)
├☑ numpy             1.24.3 (OpenBLAS 0.3.21 with 10 threads)
├☑ scipy             1.11.1
└☑ matplotlib        3.7.2 (backend=module://matplotlib_inline.backend_inline)

Numerical (optional)
├☑ sklearn           1.3.0
├☑ numba             0.57.1
├☑ nibabel           5.0.1
├☑ nilearn           0.10.1
├☑ dipy              1.7.0
├☑ openmeeg          2.5.6
├☑ pandas            2.0.3
├☑ h5io              0.1.7
├☑ h5py              3.8.0
└☐ unavailable       cupy

Visualization (optional)
├☑ pyvista           0.39.1 (OpenGL 4.1 Metal - 89.3 via Apple M2 Pro)
├☑ pyvistaqt         0.0.0
├☑ vtk               9.2.6
├☑ qtpy              2.2.0 (PyQt5=5.15.6)
├☑ pyqtgraph         0.13.1
├☑ mne-qt-browser    0.5.0
├☑ ipywidgets        7.7.5
├☑ trame_client      3.4.0
├☑ trame_server      2.17.3
├☑ trame_vtk         2.8.11
├☑ trame_vuetify     2.7.1
└☐ unavailable       ipympl

Ecosystem (optional)
├☑ eeglabio          0.0.2-3
├☑ edfio             0.4.4
├☑ mffpy             0.8.0
├☑ pybv              0.7.5
└☐ unavailable       mne-bids, mne-nirs, mne-features, mne-connectivity, mne-icalabel, mne-bids-pipeline, neo