def test():
"""Running the analysis of the Brainstorm tutorial in MNE-Python"""
print(__doc__)
# Get test dataset
data_path = bst_raw.data_path()
# Read CTF dataset
raw_fname = bst_raw.data_path(
) + '/MEG/bst_raw/' + 'subj001_somatosensory_20111109_01_AUX-f.ds'
raw = mne.io.read_raw_ctf(raw_fname, preload=True)
# Plot raw data
raw.plot()
# Set EOG channel
raw.set_channel_types({'EEG058': 'eog'})
# Show power line interference
raw.plot_psd()
# Notch filter: 60Hz
# raw.notch_filter(np.arange(60, 181, 60))
# Read events
events = mne.find_events(raw, stim_channel='UPPT001')
event_id = 2 # take right-hand somato
# Pick MEG channels
picks = mne.pick_types(raw.info,
meg=True,
eeg=False,
stim=False,
eog=True,
exclude='bads')
# Compute epochs: [-100, +300]ms
epochs = mne.Epochs(raw,
events,
event_id,
-0.1,
0.3,
picks=picks,
baseline=(None, 0),
reject=dict(mag=4e-12, eog=250e-6),
preload=False)
# Compute evoked
evoked = epochs.average()
# Fix stim artifact
mne.preprocessing.fix_stim_artifact(evoked)
# Correct delays due to hardware (stim artifact is at 4 ms)
evoked.shift_time(-0.004)
# Plot the result
evoked.plot()
evoked.plot_topomap(times=np.array([0.016, 0.030, 0.060, 0.070]))
def test():
"""Running the analysis of the Brainstorm tutorial in MNE-Python"""
print(__doc__)
tmin, tmax, event_id = -0.1, 0.3, 2 # take right-hand somato
reject = dict(mag=4e-12, eog=250e-6)
data_path = bst_raw.data_path()
raw_fname = data_path + '/MEG/bst_raw/' + 'subj001_somatosensory_20111109_01_AUX-f_raw.fif'
raw = mne.io.read_raw_fif(raw_fname, preload=True, add_eeg_ref=False)
raw.plot()
return raw
"""
# Authors: Mainak Jas <*****@*****.**>
#
# License: BSD (3-clause)
import numpy as np
import mne
from mne.datasets.brainstorm import bst_raw
print(__doc__)
tmin, tmax, event_id = -0.1, 0.3, 2 # take right-hand somato
reject = dict(mag=4e-12, eog=250e-6)
data_path = bst_raw.data_path()
raw_fname = data_path + '/MEG/bst_raw/' + \
'subj001_somatosensory_20111109_01_AUX-f_raw.fif'
raw = mne.io.read_raw_fif(raw_fname, preload=True, add_eeg_ref=False)
raw.plot()
# set EOG channel
raw.set_channel_types({'EEG058': 'eog'})
raw.add_eeg_average_proj()
# show power line interference and remove it
raw.plot_psd()
raw.notch_filter(np.arange(60, 181, 60))
events = mne.find_events(raw, stim_channel='UPPT001')
# Authors: Mainak Jas <*****@*****.**>
#
# License: BSD (3-clause)
import numpy as np
import mne
from mne.datasets.brainstorm import bst_raw
print(__doc__)
tmin, tmax, event_id = -0.1, 0.3, 2 # take right-hand somato
reject = dict(mag=4e-12, eog=250e-6)
data_path = bst_raw.data_path()
raw_fname = data_path + '/MEG/bst_raw/' + \
'subj001_somatosensory_20111109_01_AUX-f_raw.fif'
raw = mne.io.read_raw_fif(raw_fname, preload=True)
raw.plot()
# set EOG channel
raw.set_channel_types({'EEG058': 'eog'})
raw.set_eeg_reference('average', projection=True)
# show power line interference and remove it
raw.plot_psd(tmax=60., average=False)
raw.notch_filter(np.arange(60, 181, 60), fir_design='firwin')
events = mne.find_events(raw, stim_channel='UPPT001')