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,
