I’m having a familiar problem, but the usual solutions don’t seem to be working and I can’t figure out why!
When using raw.plot(), everything on the GUI that pops up is extremely slow. For instance I can’t smoothly drag the scroll/pan bar, but rather it takes ~2-3 seconds to update with each move.
The solutions from similar threads don’t seem to be working this time. Further, it’s working just fine on one my macbooks (M1 with Sequoia), but not on my other (M2 with Tahoe).
I’m now using pycharm, but I had the same problem in VSCode (which is what worked on the other one). The other difference is I set up a new venv in pycharm whereas the first/working computer is using a conda env, but I wouldn’t expect these differences to change performance?
import mne
from mne.viz import set_browser_backend
set_browser_backend("qt")
import matplotlib
import matplotlib.pyplot as plt
mne.sys_info()
raw_file = mne.io.read_raw_fif(fname, verbose=True, preload=False)
raw_file.load_data()
n_show = max(1, total_chs // 2)
raw_file.plot(block=True, use_opengl=False,
n_channels=n_show,
scalings=dict(block=True, mag=1e-12, grad=4e-11, eeg=350e-6, eog=150e-6, ecg=5e-4,
emg=1e-3, ref_meg=1e-12, misc=1e-3, stim=1,
resp=1, chpi=1e-4, whitened=1e2),
)
The mne.sys_info() for the non-working computer:
Using qt as 2D backend.
Platform macOS-26.0.1-arm64-arm-64bit
Python 3.11.9 (v3.11.9:de54cf5be3, Apr 2 2024, 07:12:50) [Clang 13.0.0 (clang-1300.0.29.30)]
Executable ~/PyCharmMiscProject/.venv/.venv/bin/python
CPU Apple M2 Max (12 cores)
Memory 64.0 GiB
Core
├☑ mne 1.10.2 (unable to check for latest version on GitHub, SSL error)
├☑ numpy 2.3.4 (unknown linalg bindings (threadpoolctl module not found: No module named ‘threadpoolctl’))
├☑ scipy 1.16.2
└☑ matplotlib 3.10.7 (backend=module://backend_interagg)
Numerical (optional)
├☑ pandas 2.3.3
└☐ unavailable sklearn, numba, nibabel, nilearn, dipy, openmeeg, cupy, h5io, h5py
Visualization (optional)
├☑ qtpy 2.4.3 (PyQt5=5.15.14)
├☑ pyqtgraph 0.13.7
├☑ mne-qt-browser 0.7.3
└☐ unavailable pyvista, pyvistaqt, vtk, ipympl, ipywidgets, trame_client, trame_server, trame_vtk, trame_vuetify
The mne.sys_info() for the working computer:
Platform macOS-10.16-x86_64-i386-64bit
Python 3.9.13 (main, Aug 25 2022, 18:29:29) [Clang 12.0.0 ]
Executable ~/anaconda3/envs/EEGenv/bin/python
CPU i386 (10 cores)
Memory 16.0 GB
Core
├☒ mne 1.8.0 (outdated, release 1.10.2 is available!)
├☑ numpy 1.23.4 (OpenBLAS 0.3.20 with 10 threads)
├☑ scipy 1.9.2
└☑ matplotlib 3.6.2 (backend=MacOSX)
Numerical (optional)
├☑ sklearn 1.1.2
├☑ nibabel 5.3.2
├☑ pandas 1.5.0
├☑ h5py 3.7.0
└☐ unavailable numba, nilearn, dipy, openmeeg, cupy, h5io
Visualization (optional)
├☑ qtpy 2.4.3 (PySide2=5.15.2)
├☑ ipympl 0.9.2
├☑ pyqtgraph 0.13.7
├☑ mne-qt-browser 0.6.3
├☑ ipywidgets 8.0.2
└☐ unavailable pyvista, pyvistaqt, vtk, trame_client, trame_server, trame_vtk, trame_vuetify
Ecosystem (optional)
└☐ unavailable mne-bids, mne-nirs, mne-features, mne-connectivity, mne-icalabel, mne-bids-pipeline, neo, eeglabio, edfio, mffpy, pybv