import os.path as op
import mne
from mne.datasets import somato

data_path = somato.data_path()
subject = '01'
task = 'somato'
raw_fname = op.join(data_path, 'sub-{}'.format(subject), 'meg',
                    'sub-{}_task-{}_meg.fif'.format(subject, task))

raw = mne.io.read_raw_fif(raw_fname)
events = mne.find_events(raw, stim_channel='STI 014')
picks = mne.pick_types(raw.info, meg=True, eeg=False, eog=True, stim=False)
event_id, tmin, tmax = 1, -1., 3.
baseline = (None, 0)
epochs = mne.Epochs(raw, events, event_id, tmin, tmax, picks=picks,
                    baseline=baseline, reject=dict(grad=4000e-13, eog=350e-6),
                    preload=True)
evoked = epochs.average()

print('Rank with all MEG')
print(mne.compute_rank(evoked, 'info'))

print('Rank with only GRAD')
print(mne.compute_rank(evoked.copy().pick('grad'), 'info'))