In [ ]:

    

import mne
from mne.datasets import testing
data_path = testing.data_path()
raw_fname = data_path + '/MEG/sample/sample_audvis_trunc_raw.fif'
subjects_dir = data_path + '/subjects'
subject = 'sample'
trans = data_path + '/MEG/sample/sample_audvis_trunc-trans.fif'
info = mne.io.read_info(raw_fname)
mne.viz.set_3d_backend('notebook')
mne.viz.plot_alignment(info, trans, subject=subject, dig=True,
                       meg=['helmet', 'sensors'], subjects_dir=subjects_dir,
                       surfaces=['head-dense'])


    

In [ ]:

    

import os
import mne
from mne.datasets import testing
data_path = testing.data_path()
sample_dir = os.path.join(data_path, 'MEG', 'sample')
subjects_dir = os.path.join(data_path, 'subjects')
fname_stc = os.path.join(sample_dir, 'sample_audvis_trunc-meg')
stc = mne.read_source_estimate(fname_stc, subject='sample')
initial_time = 0.13
mne.viz.set_3d_backend('notebook')
brain = stc.plot(subjects_dir=subjects_dir, initial_time=initial_time,
                 clim=dict(kind='value', pos_lims=[3, 6, 9]),
                 time_viewer=True,
                 hemi='split')