Here's something you shouldn't do with MNE-Python

sphere_model.py

import mne
from mayavi import mlab

data_path = mne.datasets.sample.data_path()
subjects_dir = f'{data_path}/subjects'

evoked = mne.read_evokeds(f'{data_path}/MEG/sample/sample_audvis-ave.fif', condition='Left Auditory').apply_baseline()
noise_cov = mne.read_cov(f'{data_path}/MEG/sample/sample_audvis-cov.fif')
bem = mne.make_sphere_model(r0='auto', head_radius='auto', info=evoked.info)
src = mne.setup_volume_source_space(bem=bem)
fwd = mne.make_forward_solution(evoked.info, trans=None, src=src, bem=bem, meg=True, eeg=False, mindist=5, n_jobs=4)
inv = mne.minimum_norm.make_inverse_operator(evoked.info, fwd, noise_cov)
stc = mne.minimum_norm.apply_inverse(evoked, inv)
peak_time = stc.get_peak(time_as_index=True)[1]
mlab.points3d(*fwd['source_rr'].T, stc.data[:, peak_time], scale_factor=1e-4)