Issue in brain.add_volume_labels()

[Dr-Chen-Xiaoyu]

Description of the problem

Hi,

I am trying to go through the code of Working with sEEG data — MNE 1.4.2 documentation. However, when I am using “brain.add_volume_labels”, I found that the plot is different bewteen my Linux server and my laptop (windows system).

Steps to reproduce

%matplotlib qt
import mne
mne.viz.set_3d_backend('pyvistaqt') # GUI requires pyvista backend
mne.viz.set_3d_options(depth_peeling=False, antialias=False, multi_samples=1) # for bugs of pure black plot of 3D viz

fsaverage_dir="/data/xyc/codes/Tests/MNE_fetch_fsaverage"
mne.datasets.fetch_fsaverage(subjects_dir=fsaverage_dir, verbose=True)  # use mne-python's fsaverage data
mne.datasets.fetch_hcp_mmp_parcellation(subjects_dir=fsaverage_dir,verbose=True) # use mne-python's hcp mmp parcellation

brain = mne.viz.Brain(
    "fsaverage",
    subjects_dir=fsaverage_dir,
    cortex='low_contrast', alpha=0.2, background='white'
)

brain.add_volume_labels(aseg="aparc+aseg")

Link to data

No response

Expected results

The brain from fsaverage and its parcellation should be correctly aligned for both linux and windows.

Actual results

For windows, the same code (only change the path of fsaverage_dir) is Okay with correct plot.
However, Linux’s plot is wrong. Note that I run my code with jupyter notebook in a remote Linux server. %matplotlib qt can run well with mne’s 3D plot. This plot also runs well with no errors or warmings.

Plots can be found on https://mne.discourse.group/t/issue-in-brain-add-volume-labels/7037. Since Alexandre Gramfort also replicated this isssue, I think maybe it is some bug or mistake in brain.add_volume_labels() that the coordinates are misused in Linux.

Best，
Xiaoyu😊

Additional information

My outputs of “mne sys_info” for windows and Linux:

Platform             Linux-5.19.0-41-generic-x86_64-with-glibc2.35
Python               3.11.3 | packaged by conda-forge | (main, Apr  6 2023, 08:57:19) [GCC 11.3.0]
Executable           /home/xyc/anaconda/envs/env_mne/bin/python3.11
CPU                  x86_64 (128 cores)
Memory               1007.5 GB

Core
├☑ mne               1.4.0
├☑ numpy             1.24.3 (unknown linalg bindings)
├☑ scipy             1.10.1
├☑ matplotlib        3.7.1 (backend=module://matplotlib_inline.backend_inline)
├☑ pooch             1.7.0
└☑ jinja2            3.1.2

Numerical (optional)
├☑ sklearn           1.2.2
├☑ numba             0.57.0
├☑ nibabel           5.1.0
├☑ nilearn           0.10.1
├☑ dipy              1.7.0
├☑ openmeeg          2.5.6
├☑ pandas            2.0.1
└☐ unavailable       cupy

Visualization (optional)
├☑ pyvista           0.39.1 (OpenGL 4.5 (Core Profile) Mesa 22.2.5 via llvmpipe (LLVM 15.0.6, 256 bits))
├☑ pyvistaqt         0.0.0
├☑ ipyvtklink        0.2.2
├☑ vtk               9.2.6
├☑ qtpy              2.3.1 (PyQt5=5.15.6)
├☑ pyqtgraph         0.13.3
├☑ mne-qt-browser    0.5.0
└☐ unavailable       ipympl

Ecosystem (optional)
├☑ mne-bids          0.12
└☐ unavailable       mne-nirs, mne-features, mne-connectivity, mne-icalabel, mne-bids-pipeline

Platform:         Windows-10-10.0.22621-SP0
Python:           3.9.16 | packaged by conda-forge | (main, Feb  1 2023, 21:28:38) [MSC v.1929 64 bit (AMD64)]
Executable:       C:\Users\XYchen\anaconda3\envs\envmne\python.exe
CPU:              AMD64 Family 25 Model 80 Stepping 0, AuthenticAMD: 16 cores
Memory:           13.9 GB

mne:              1.3.1
numpy:            1.23.5 {MKL 2022.1-Product with 8 threads}
scipy:            1.10.1
matplotlib:       3.7.1 {backend=module://matplotlib_inline.backend_inline}

sklearn:          1.2.1
numba:            0.56.4
nibabel:          5.0.1
nilearn:          0.10.0
dipy:             1.6.0
openmeeg:         2.5.5
cupy:             Not found
pandas:           1.5.3
pyvista:          0.38.3 {OpenGL 4.6.0 Compatibility Profile Context 22.20.44.221025 via AMD Radeon(TM) Graphics}
pyvistaqt:        0.9.1
ipyvtklink:       0.2.2
vtk:              9.2.6
qtpy:             2.3.0 {PyQt5=5.15.6}
ipympl:           Not found
pyqtgraph:        0.13.2
pooch:            v1.7.0

mne_bids:         0.12
mne_nirs:         Not found
mne_features:     Not found
mne_qt_browser:   0.4.0
mne_connectivity: Not found
mne_icalabel:     Not found

[welcome]

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

[larsoner]

@alexrockhill can you replicate https://mne.discourse.group/t/issue-in-brain-add-volume-labels/7037 locally?

[alexrockhill]

I'll look into this in 3-4 hours.