from pyriemann.classification import MDM ################################################################################################### # Load Data # --------------------- # # ( See the n170 `load_and_visualize` example for further description of this) # eegnb_data_path = os.path.join(os.path.expanduser('~/'), '.eegnb', 'data') n170_data_path = os.path.join(eegnb_data_path, 'visual-N170', 'eegnb_examples') # If dataset hasn't been downloaded yet, download it if not os.path.isdir(n170_data_path): fetch_dataset(data_dir=eegnb_data_path, experiment='visual-N170', site='eegnb_examples') subject = 1 session = 1 raw = load_data(subject, session, experiment='visual-N170', site='eegnb_examples', device_name='muse2016', data_dir=eegnb_data_path) ################################################################################################### ################################################################################################### # Filteriing
# Load Data # --------------------- # # We will use the eeg-notebooks SSVEP example dataset # # Note that if you are running this locally, the following cell will download # the example dataset, if you do not already have it. # ################################################################################################### eegnb_data_path = os.path.join(os.path.expanduser('~/'),'.eegnb', 'data') ssvep_data_path = os.path.join(eegnb_data_path, 'visual-SSVEP', 'eegnb_examples') # If dataset hasn't been downloaded yet, download it if not os.path.isdir(ssvep_data_path): fetch_dataset(data_dir=eegnb_data_path, experiment='visual-SSVEP', site='eegnb_examples'); subject = 1 session = 1 raw = load_data(subject, session, experiment='visual-SSVEP', site='eegnb_examples', device_name='muse2016', data_dir = eegnb_data_path, replace_ch_names={'Right AUX': 'POz'}) ################################################################################################### # Visualize the power spectrum # ---------------------------- raw.plot_psd()
################################################################################################### # Load Data # --------------------- # # We will use the eeg-notebooks visual cueing example dataset # eegnb_data_path = os.path.join(os.path.expanduser('~/'), '.eegnb', 'data') cueing_data_path = os.path.join(eegnb_data_path, 'visual-cueing', 'kylemathlab_dev') # If dataset hasn't been downloaded yet, download it if not os.path.isdir(cueing_data_path): fetch_dataset(data_dir=eegnb_data_path, experiment='visual-cueing', site='kylemathlab_dev') subject = 1 session = 1 sub = 302 raw = load_data(eegnb_data_path, experiment='visual-cueing', site='kylemathlab_dev', sfreq=256., subject_nb=sub, session_nb=1) raw.append( load_data(eegnb_data_path,