def test_needs_eeg_average_ref_proj():
"""Test checking whether a recording needs an EEG average reference"""
raw = Raw(raw_fname, add_eeg_ref=False, preload=False)
assert_true(_needs_eeg_average_ref_proj(raw.info))
raw = Raw(raw_fname, add_eeg_ref=True, preload=False)
assert_true(not _needs_eeg_average_ref_proj(raw.info))
# No EEG channels
raw = Raw(raw_fname, add_eeg_ref=False, preload=True)
eeg = [raw.ch_names[c] for c in pick_types(raw.info, meg=False, eeg=True)]
raw.drop_channels(eeg)
assert_true(not _needs_eeg_average_ref_proj(raw.info))
# Custom ref flag set
raw = Raw(raw_fname, add_eeg_ref=False, preload=False)
raw.info['custom_ref_applied'] = True
assert_true(not _needs_eeg_average_ref_proj(raw.info))
def test_needs_eeg_average_ref_proj():
"""Test checking whether a recording needs an EEG average reference"""
raw = Raw(raw_fname, add_eeg_ref=False, preload=False)
assert_true(_needs_eeg_average_ref_proj(raw.info))
raw = Raw(raw_fname, add_eeg_ref=True, preload=False)
assert_true(not _needs_eeg_average_ref_proj(raw.info))
# No EEG channels
raw = Raw(raw_fname, add_eeg_ref=False, preload=True)
eeg = [raw.ch_names[c] for c in pick_types(raw.info, meg=False, eeg=True)]
raw.drop_channels(eeg)
assert_true(not _needs_eeg_average_ref_proj(raw.info))
# Custom ref flag set
raw = Raw(raw_fname, add_eeg_ref=False, preload=False)
raw.info['custom_ref_applied'] = True
assert_true(not _needs_eeg_average_ref_proj(raw.info))
def test_needs_eeg_average_ref_proj():
"""Test checking whether a recording needs an EEG average reference."""
raw = read_raw_fif(raw_fname)
assert _needs_eeg_average_ref_proj(raw.info)
raw.set_eeg_reference(projection=True)
assert not _needs_eeg_average_ref_proj(raw.info)
# No EEG channels
raw = read_raw_fif(raw_fname, preload=True)
eeg = [raw.ch_names[c] for c in pick_types(raw.info, meg=False, eeg=True)]
raw.drop_channels(eeg)
assert not _needs_eeg_average_ref_proj(raw.info)
# Custom ref flag set
raw = read_raw_fif(raw_fname)
raw.info['custom_ref_applied'] = True
assert not _needs_eeg_average_ref_proj(raw.info)
def test_needs_eeg_average_ref_proj():
"""Test checking whether a recording needs an EEG average reference."""
raw = read_raw_fif(raw_fname)
assert _needs_eeg_average_ref_proj(raw.info)
raw.set_eeg_reference(projection=True)
assert not _needs_eeg_average_ref_proj(raw.info)
# No EEG channels
raw = read_raw_fif(raw_fname, preload=True)
eeg = [raw.ch_names[c] for c in pick_types(raw.info, meg=False, eeg=True)]
raw.drop_channels(eeg)
assert not _needs_eeg_average_ref_proj(raw.info)
# Custom ref flag set
raw = read_raw_fif(raw_fname)
raw.info['custom_ref_applied'] = True
assert not _needs_eeg_average_ref_proj(raw.info)
def _raw_LRFCP(raw_names, sfreq, l_freq, h_freq, n_jobs, n_jobs_resample,
projs, bad_file, disp_files=False, method='fir',
filter_length=32768, apply_proj=True, preload=True,
force_bads=False, l_trans=0.5, h_trans=0.5,
allow_maxshield=False, phase='zero-double', fir_window='hann',
fir_design='firwin2', pick=True,
skip_by_annotation=('bad', 'skip')):
"""Helper to load, filter, concatenate, then project raw files"""
from mne.io.proj import _needs_eeg_average_ref_proj
if isinstance(raw_names, str):
raw_names = [raw_names]
if disp_files:
print(f' Loading and filtering {len(raw_names)} '
f'file{_pl(raw_names)}.')
raw = list()
for rn in raw_names:
r = read_raw_fif(rn, preload=True, allow_maxshield='yes')
r.load_bad_channels(bad_file, force=force_bads)
if pick:
r.pick_types(meg=True, eeg=True, eog=True, ecg=True, exclude=[])
if _needs_eeg_average_ref_proj(r.info):
r.set_eeg_reference(projection=True)
if sfreq is not None:
r.resample(sfreq, n_jobs=n_jobs_resample, npad='auto')
fir_kwargs = _get_fir_kwargs(fir_design)[0]
if l_freq is not None or h_freq is not None:
r.filter(l_freq=l_freq, h_freq=h_freq, picks=None,
n_jobs=n_jobs, method=method,
filter_length=filter_length, phase=phase,
l_trans_bandwidth=l_trans, h_trans_bandwidth=h_trans,
fir_window=fir_window, **fir_kwargs)
raw.append(r)
_fix_raw_eog_cals(raw)
raws_del = raw[1:]
raw = concatenate_raws(raw, preload=preload)
for r in raws_del:
del r
if disp_files and apply_proj and len(projs) > 0:
print(' Adding and applying projectors.')
raw.add_proj(projs)
if apply_proj:
raw.apply_proj()
return raw
