<s> """<STR_LIT>""" <EOL> import mne <EOL> from mne import io <EOL> from mne . datasets import sample <EOL> from mne . cov import compute_covariance <EOL> print ( __doc__ ) <EOL> data_path = sample . data_path ( ) <EOL> raw_fname = data_path + '<STR_LIT>' <EOL> event_fname = data_path + '<STR_LIT>' <EOL> raw = io . read_raw_fif ( raw_fname , preload = True ) <EOL> raw . filter ( <NUM_LIT:1> , <NUM_LIT> , method = '<STR_LIT>' , n_jobs = <NUM_LIT:1> ) <EOL> raw . info [ '<STR_LIT>' ] += [ '<STR_LIT>' ] <EOL> events = mne . read_events ( event_fname ) <EOL> event_id , tmin , tmax = <NUM_LIT:2> , - <NUM_LIT> , <NUM_LIT:0.5> <EOL> picks = mne . pick_types ( raw . info , meg = True , eeg = True , eog = True , exclude = '<STR_LIT>' ) <EOL> reject = dict ( mag = <NUM_LIT> , grad = <NUM_LIT> , eeg = <NUM_LIT> ) <EOL> epochs = mne . Epochs ( raw , events , event_id , tmin , tmax , picks = picks , <EOL> baseline = None , reject = reject , preload = True ) <EOL> noise_covs = compute_covariance ( epochs , tmin = None , tmax = <NUM_LIT:0> , method = '<STR_LIT>' , <EOL> return_estimators = True , verbose = True , n_jobs = <NUM_LIT:1> , <EOL> projs = None ) <EOL> print ( '<STR_LIT>' ) <EOL> for c in noise_covs : <EOL> print ( "<STR_LIT>" % ( c [ '<STR_LIT>' ] , c [ '<STR_LIT>' ] ) ) <EOL> evoked = epochs . average ( ) <EOL> evoked . plot ( ) <EOL> evoked . plot_white ( noise_covs ) </s>
