mne-python: BUG: Bugs with VTK 9

@GuillaumeFavelier you can now pretty easily build and install VTK 9 (which is good because they are on RC3, and it should fix some bugs and bring 3.8 support):

git clone --recursive https://gitlab.kitware.com/vtk/vtk.git
mkdir vtk-build
cd vtk-build
cmake -GNinja -DVTK_BUILD_TESTING=OFF -DVTK_WHEEL_BUILD=ON -DVTK_PYTHON_VERSION=3 -DVTK_WRAP_PYTHON=ON ../vtk
ninja -j 4
python setup.py bdist_wheel
pip install dist/vtk-*.whl

However, there is at least one rendering bug (depth peeling again maybe?) where the surface overlay gets cut off at some distance based on rotation (note the rightward “v” cut of the overlay):

Screenshot from 2020-04-11 09-36-36

We might need to figure out how to properly resolve the coincident topology here – relying on VTK to do it automagically might not work anymore. Or maybe it’s something else…?

About this issue

Original URL
State: closed
Created 4 years ago
Reactions: 2
Comments: 28 (27 by maintainers)

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VTK9 rc3 wheels are up so you can try @GuillaumeFavelier :

https://vtk.org/download/

For me the stc.py example we always runs just freezes, I think due in part to this:

https://github.com/pyvista/pyvista/pull/686

It occurred to me that we actually need to fix this soon because once VTK9 wheels land on PyPi and are incorporated by Anaconda, anyone who installs or upgrades MNE will be stuck with unusable plotting 😦

Can you look into it?

larsoner on Apr 23, 2020

FWIW, PyVista worked “out of the box” this way, while Mayavi fails to compile (which I’ll look into) 😃

larsoner on Apr 11, 2020

@GuillaumeFavelier might be good to fix this before looking into coreg

larsoner on Nov 9, 2020

Hooray! With pip install --upgrade --user pyqt5 which gives 5.14.2 everything works fine

larsoner on Apr 23, 2020

(FYI I forgot a ninja -j 4 in the command list above, I’ve updated it now)

larsoner on Apr 13, 2020

WARNING: Will download 1.5 GB of data to ~/mne_data (unless you give it a different path to use)

import faulthandler
import os.path as op
import mne

faulthandler.enable()
data_path = mne.datasets.sample.data_path()
sample_dir = op.join(data_path, 'MEG', 'sample')
subjects_dir = op.join(data_path, 'subjects')
inv = mne.minimum_norm.read_inverse_operator(op.join(
    sample_dir, 'sample_audvis-meg-eeg-oct-6-meg-eeg-inv.fif'))
evoked = mne.read_evokeds(op.join(sample_dir, 'sample_audvis-ave.fif'))[0]
evoked.apply_baseline((None, 0))
stc = mne.minimum_norm.apply_inverse(
    evoked, inv, method='dSPM', verbose='debug', pick_ori=None)  # 'vector')
initial_time = 0.1

with mne.viz.use_3d_backend('pyvista'):
    brain = stc.plot(subjects_dir=subjects_dir, initial_time=initial_time,
                     clim='auto', views='lat', hemi='lh',
                     smoothing_steps='nearest', verbose=True)

You will probably need to pip install nibabel https://github.com/mne-tools/mne-python/zipball/master first.

This is the code I was using (last I recall!), but for some reason now it hangs when I try it.

larsoner on Apr 13, 2020