def test_with_missing_channels():
"""Test _create_info when channels are missing from info."""
cur_system = 'neuromag306'
test_data_folder_ft = get_data_paths(cur_system)
info = get_raw_info(cur_system)
del info['chs'][1:20]
info._update_redundant()
with pytest.warns(RuntimeWarning):
mne.io.read_raw_fieldtrip(
os.path.join(test_data_folder_ft, 'raw_v7.mat'), info)
mne.read_evoked_fieldtrip(
os.path.join(test_data_folder_ft, 'averaged_v7.mat'), info)
mne.read_epochs_fieldtrip(
os.path.join(test_data_folder_ft, 'epoched_v7.mat'), info)
def test_throw_exception_on_cellarray(version, type):
"""Test for a meaningful exception when the data is a cell array."""
fname = os.path.join(get_data_paths('cellarray'),
'%s_%s.mat' % (type, version))
info = get_raw_info('CNT')
with pytest.raises(RuntimeError, match='Loading of data in cell arrays '
'is not supported'):
if type == 'averaged':
mne.read_evoked_fieldtrip(fname, info)
elif type == 'epoched':
mne.read_epochs_fieldtrip(fname, info)
elif type == 'raw':
mne.io.read_raw_fieldtrip(fname, info)
def autoreject_epochs(ft_file, out_file, log_file):
import mne
import autoreject
import json
# Load the file
#info = mne.io.read_info(raw_file)
epochs = mne.read_epochs_fieldtrip(ft_file, info=None)
# Resample the data
#epochs.resample(500,npad='auto')
# Apply autoreject
ar = autoreject.AutoReject()
epochs, reject_log = ar.fit_transform(epochs, return_log=True)
reject_log = reject_log.bad_epochs
reject_log = reject_log.tolist()
# Write to disk
with open(log_file, 'w') as f:
json.dump(reject_log, f)
#Save data to file
epochs.save(out_file)
return
def autoreject_log(ft_file, out_file):
import mne
import autoreject
import json
# Load the file
#info = mne.io.read_info(raw_file)
epochs = mne.read_epochs_fieldtrip(ft_file, info=None)
# Resample the data - we're only going to use the thresholds
#epochs.resample(400,npad='auto')
# Apply autoreject to find bad channels
ar = autoreject.AutoReject()
ar.fit(epochs)
reject_log = ar.get_reject_log(epochs)
reject_log = reject_log.bad_epochs
reject_log = reject_log.tolist()
# Write to disk
with open(out_file, 'w') as f:
json.dump(reject_log, f)
return
def autoreject_threshold(ft_file, out_file, raw_file=0):
import sys
import mne
import autoreject
import json
PY3 = sys.version_info[0] == 3
if PY3:
string_types = str,
else:
string_types = basestring,
if isinstance(raw_file, string_types):
info = mne.io.read_info(raw_file)
epochs = mne.read_epochs_fieldtrip(ft_file, info)
else:
epochs = mne.read_epochs_fieldtrip(ft_file, info=None)
reject = autoreject.get_rejection_threshold(epochs)
with open(out_file, 'w') as f:
json.dump(reject, f)
'noise_cov_10_17Hz',
verbose=None)
original_data = mne.io.read_raw_fif(raw_fname, preload=False)
original_info = original_data.info
original_info['sfreq'] = 500
#for the first 3 CSP components and the second 3 CSP components (commented)
diff = []
CSP = ['1', '2', '3', '4', '5', '6', '97', '98', '99', '100', '101', '102']
for num in CSP:
#load csp data for fast from fieldtrip
ftname = savepath + subject + '/' + subject + '_fieldtrip_csp_1_6_and_97_102_new_to_mne.mat'
fast_epo = mne.read_epochs_fieldtrip(ftname,
original_info,
data_name='epochs_fast' + num,
trialinfo_column=0)
fast_epo.save(PATHfrom + 'SUBJECTS/' + subject +
'/ICA_nonotch_crop/epochs/' + subject + '_epo_fast.fif',
overwrite=True)
fast_fname = PATHfrom + 'SUBJECTS/' + subject + '/ICA_nonotch_crop/epochs/' + subject + '_epo_fast.fif'
fast_epo = mne.read_epochs(fast_fname, proj=False, verbose=None)
#load csp data for slow from fieldtrip
slow_epo = mne.read_epochs_fieldtrip(ftname,
original_info,
data_name='epochs_slow' + num,
trialinfo_column=0)
slow_epo.save(PATHfrom + 'SUBJECTS/' + subject +
'/ICA_nonotch_crop/epochs/' + subject + '_epo_slow.fif',
overwrite=True)