# Load experimental RAW files for the visual condition
raw_fnames = load_data(condition=condition,
data_format='raw',
data_type='experimental')
# Load simulation evoked files for the visual condition
evoked_fnames = load_data(condition=condition,
data_format='evoked',
data_type='simulation')
raw = Raw(raw_fnames[0])
events = find_events(raw, stim_channel="STI 014", shortest_event=1)
# Visualize raw file
raw.plot()
# Make an evoked file from the experimental data
picks = pick_types(raw.info, meg=True, eog=True, exclude='bads')
# Read epochs
event_id, tmin, tmax = 9, -0.2, 0.5
epochs = Epochs(raw,
events,
event_id,
tmin,
tmax,
baseline=(None, 0),
picks=picks,
reject=dict(grad=4000e-13, mag=4e-12, eog=150e-6))
evoked = epochs.average() # average epochs and get an Evoked dataset.
condition = 'visual' # or 'auditory' or 'somatosensory'
# Load experimental RAW files for the visual condition
raw_fnames = load_data(condition=condition, data_format='raw',
data_type='experimental')
# Load simulation evoked files for the visual condition
evoked_fnames = load_data(condition=condition, data_format='evoked',
data_type='simulation')
raw = Raw(raw_fnames[0])
events = find_events(raw, stim_channel="STI 014", shortest_event=1)
# Visualize raw file
raw.plot()
# Make an evoked file from the experimental data
picks = pick_types(raw.info, meg=True, eog=True, exclude='bads')
# Read epochs
event_id, tmin, tmax = 9, -0.2, 0.5
epochs = Epochs(raw, events, event_id, tmin, tmax, baseline=(None, 0),
picks=picks, reject=dict(grad=4000e-13, mag=4e-12, eog=150e-6))
evoked = epochs.average() # average epochs and get an Evoked dataset.
evoked.plot()
# Compare to the simulated data
evoked_sim = read_evokeds(evoked_fnames[0])
evoked_sim.plot()
