Hi,
I am a new user to MNE and 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).
Here is my code:
%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 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")
For windows, the same code (only change the path of fsaverage_dir) is Okay with correct plot like this:
However, Linux’s plot is like this:
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.
My outputs of “mne sys_info” for windows and Linux are :
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
Could anyone help or repeat this? I am guessing maybe it is some bug or mistake in brain.add_volume_labels() that the coordinates are misused in Linux ?
Best,
Xiaoyu
SJTU
