[BUG/Feature request] plotting dipoles gives unsatisfying and buggy results

[jasmainak]

Description of the problem

There doesn't seem to be a satisfying way to plot the dipoles obtained from dipole fit in MNE-Python. There are 4 options:

1. Orthoview: this is a bit low-contrast and it's not possible to traverse the slices. It's very difficult to identify anatomical landmarks as a result

2. Outlines: Similar problem as 1. If you get the dipoles at the wrong location, you can't interactively explore how far from the expected location you are.

3. Arrow/Sphere: seems buggy for me (see below)

Here is an example figure from a paper:

Why not have a vanilla option that resembles this with an option to interactively traverse slices? I saw this issue: https://github.com/mne-tools/mne-python/issues/2995, not sure if it's related. Please feel free to migrate the discussion there if relevant.

Steps to reproduce

import os.path as op
import numpy as np
import matplotlib.pyplot as plt

import mne
from mne.forward import make_forward_dipole
from mne.evoked import combine_evoked
from mne.simulation import simulate_evoked

from nilearn.plotting import plot_anat
from nilearn.datasets import load_mni152_template

data_path = mne.datasets.sample.data_path()
subjects_dir = data_path / 'subjects'
fname_ave = data_path / 'MEG' / 'sample' / 'sample_audvis-ave.fif'
fname_cov = data_path / 'MEG' / 'sample' / 'sample_audvis-cov.fif'
fname_bem = subjects_dir / 'sample' / 'bem' / 'sample-5120-bem-sol.fif'
fname_trans = data_path / 'MEG' / 'sample' / 'sample_audvis_raw-trans.fif'
fname_surf_lh = subjects_dir / 'sample' / 'surf' / 'lh.white'

evoked = mne.read_evokeds(fname_ave, condition='Right Auditory',
                          baseline=(None, 0))
evoked.pick_types(meg=True, eeg=False)
evoked_full = evoked.copy()
evoked.crop(0.07, 0.08)

# Fit a dipole
dip = mne.fit_dipole(evoked, fname_cov, fname_bem, fname_trans)[0]

# Plot the result in 3D brain with the MRI image.
dip.plot_locations(fname_trans, 'sample', subjects_dir, mode='arrow')

Link to data

No response

Expected results

Documentation says:

"Plot in 3D mode using PyVista with the given glyph type."

I am not sure what to expect since there is no example online ...

Actual results

I see this, not sure if it's an installation problem:

Additional information

In [11]: mne.sys_info() Platform: macOS-11.5.2-x86_64-i386-64bit Python: 3.9.7 | packaged by conda-forge | (default, Sep 2 2021, 17:58:46) [Clang 11.1.0 ] Executable: /Users/mainak/anaconda3/envs/mne/bin/python CPU: i386: 4 cores Memory: 8.0 GB

mne: 1.3.dev0 numpy: 1.21.2 {unknown linalg bindings} scipy: 1.7.1 matplotlib: 3.4.3 {backend=MacOSX}

sklearn: 0.24.2 numba: Not found nibabel: 3.2.1 nilearn: 0.8.0 dipy: 1.4.1 openmeeg: Not found cupy: Not found pandas: 1.3.3 pyvista: 0.32.1 {OpenGL 4.1 INTEL-16.5.2 via Intel(R) HD Graphics 6000} pyvistaqt: 0.5.0 ipyvtklink: 0.2.2 vtk: 9.0.1 qtpy: 1.11.0 {PyQt5=5.12.9} ipympl: 0.9.1 pyqtgraph: 0.12.4 pooch: v1.6.0

mne_bids: Not found mne_nirs: Not found mne_features: Not found mne_qt_browser: 0.2.5 mne_connectivity: Not found mne_icalabel: Not found

[larsoner]

Agreed the 3D one looks buggy.

So far our dipole plotting doesn't really support interactivity in the way you want. To me it sound like you want something like a vtkImagePlaneWidget like freeview has, e.g., the lower-right view here (taken from here):

Is that right? If so we could make such a mode, and maybe add it to the broken 3D one while fixing it. But it would be a bit of work

[jasmainak]

That would of course be super-awesome. The freeview visualizer is really good. But even something simpler like what we implemented with volume source estimates might be an improvement. Being able to click on a point on one of the slices and updating the other slices from that. The main thing is the contrast needs to be better + being able to change slices somehow. Arrow-based keyboard shortcuts to navigate slices can also be a quality-of-life improvement!