Kernel appears to have crashed with mne.viz

MNE version 0.22.1 Python version 3.8.5 Remote jupyter notebook/google colab

Describe the bug

I have been trying to run several of the jupyter tutorials from the mne website in a remote jupyter notebook. Each time I try to run any command that uses mne.viz(), or any other interactive visualization, the kernel restarts and I get the message “the kernel appears to have died”

Steps to Reproduce

For example, I get the “kernel appears to have died” message when I run the following code:

%matplotlib inline

import mne
Brain = mne.viz.get_brain_class()

subjects_dir = mne.datasets.sample.data_path() + '/subjects'
mne.datasets.fetch_hcp_mmp_parcellation(subjects_dir=subjects_dir,
                                        verbose=True)

mne.datasets.fetch_aparc_sub_parcellation(subjects_dir=subjects_dir,
                                          verbose=True)

labels = mne.read_labels_from_annot(
    'fsaverage', 'HCPMMP1', 'lh', subjects_dir=subjects_dir)

brain = Brain('fsaverage', 'lh', 'inflated', subjects_dir=subjects_dir,
              cortex='low_contrast', background='white', size=(800, 600))

In particular, the kernel crashes on the last line, when there is a call to mne.viz.get_brain_class()

Is there a workaround (maybe specific to remote jupyter notebooks) to stop this crash from happening?

Additional information I have tried running the same code in Google colab as well, which also results in the same problem. I have also tried running other tutorials, which similarly crash whenever I try to run any of the mne.viz() functions

Platform: Remote jupyter notebook (in CoCalc), have also tried in Google Colab Python: 3.8.5 Executable: C:\Users\yxie\Anaconda3\python.exe CPU: Intel® Xeon® CPU Model 85 Stepping 7 Memory: 32887760 kB

mne: 0.22.1 numpy: 1.19.5 {blas=D:\a\1\s\numpy\build\openblas_info, lapack=D:\a\1\s\numpy\build\openblas_lapack_info} scipy: 1.5.0 matplotlib: 3.2.2 {backend=module://ipykernel.pylab.backend_inline}

sklearn: 0.0 numba: 0.51.2 nibabel: 3.1.0 nilearn: 0.6.2 dipy: Not found cupy: Not found pandas: 1.2.3 mayavi: Not found pyvista: 0.29.1 vtk: 9.0.1

[GuillaumeFavelier]

As a side note, Google Colab is not yet supported with this backend, you can follow the progress on this in the following thread:

https://github.com/mne-tools/mne-python/issues/8704#issue-781224584.

[leosunpsy]

You can try the following operations：

(1) Make sure mesa is installed on your ubuntu：

sudo apt update && sudo apt upgrade -y
sudo apt install mesa-utils -y
glxinfo | grep "OpenGL version"

Install/Upgrade Mesa Drivers – oibaf/graphics-drivers

sudo add-apt-repository ppa:oibaf/graphics-drivers -y
sudo apt update
sudo apt upgrade -y
glxinfo | grep "OpenGL version"

(2)Check the soft link " libstdc++.so.6" and the target file"libstdc++.so.6.0.30" (My system has libstdc++.so.6.0.30 in that folder, yours may be libstdc++.so.6.0.29 or 28)is the same (name and size) in both paths “/lib/x86_64-linux-gnu” and " /path to your anaconda/anaconda3/lib"

cd /lib/x86_64-linux-gnu
ls -al | grep libstdc++

cd /home/xxx/anaconda3/lib (I installed the anaconda here)
ls -al | grep libstdc++

If the above files are not the same in both paths： （a）Delete the soft link “libstdc++.so, libstdc++.so.6” and target file “libstdc++.so.6.0.X” in the path “/home/xxx/anaconda3/lib” （b）copy the target file “libstdc++.so.6.0.X” from “/lib/x86_64-linux-gnu” to " /home/xxx/anaconda3/lib":

sudo cp /lib/x86_64-linux-gnu/libstdc++.so.6.0.X  /home/xxx/anaconda3/lib

Create the soft links "libstdc++.so " and “libstdc++.so.6” for "libstdc++.so.6.0.X ":

 ln -s libstdc++.so.6.0.X libstdc++.so 
 ln -s libstdc++.so.6.0.X libstdc++.so.6

(3) Set up mne

mne.viz.set_3d_backend("pyvistaqt")
mne.viz.set_3d_options(antialias=False) 

False is useful when renderers have problems (such as software MESA renderers).