def test_infer_eeg_placement_scheme():
"""Test inferring a correct EEG placement scheme."""
# no eeg channels case (e.g., MEG data)
data_path = op.join(base_path, 'bti', 'tests', 'data')
raw_fname = op.join(data_path, 'test_pdf_linux')
config_fname = op.join(data_path, 'test_config_linux')
headshape_fname = op.join(data_path, 'test_hs_linux')
raw = mne.io.read_raw_bti(raw_fname, config_fname, headshape_fname)
placement_scheme = _infer_eeg_placement_scheme(raw)
assert placement_scheme == 'n/a'
# 1020 case
data_path = op.join(base_path, 'brainvision', 'tests', 'data')
raw_fname = op.join(data_path, 'test.vhdr')
raw = mne.io.read_raw_brainvision(raw_fname)
placement_scheme = _infer_eeg_placement_scheme(raw)
assert placement_scheme == 'based on the extended 10/20 system'
# Unknown case, use raw from 1020 case but rename a channel
raw.rename_channels({'P3': 'foo'})
placement_scheme = _infer_eeg_placement_scheme(raw)
assert placement_scheme == 'n/a'
def _sidecar_json(raw, task, manufacturer, fname, kind, overwrite=False,
verbose=True):
"""Create a sidecar json file depending on the kind and save it.
The sidecar json file provides meta data about the data of a certain kind.
Parameters
----------
raw : instance of Raw
The data as MNE-Python Raw object.
task : str
Name of the task the data is based on.
manufacturer : str
Manufacturer of the acquisition system. For MEG also used to define the
coordinate system for the MEG sensors.
fname : str
Filename to save the sidecar json to.
kind : str
Type of the data as in ALLOWED_KINDS.
overwrite : bool
Whether to overwrite the existing file.
Defaults to False.
verbose : bool
Set verbose output to true or false. Defaults to true.
"""
sfreq = raw.info['sfreq']
powerlinefrequency = raw.info.get('line_freq', None)
if powerlinefrequency is None:
warn('No line frequency found, defaulting to 50 Hz')
powerlinefrequency = 50
if isinstance(raw, BaseRaw):
rec_type = 'continuous'
elif isinstance(raw, Epochs):
rec_type = 'epoched'
else:
rec_type = 'n/a'
# determine whether any channels have to be ignored:
n_ignored = len([ch_name for ch_name in
IGNORED_CHANNELS.get(manufacturer, list()) if
ch_name in raw.ch_names])
# all ignored channels are trigger channels at the moment...
n_megchan = len([ch for ch in raw.info['chs']
if ch['kind'] == FIFF.FIFFV_MEG_CH])
n_megrefchan = len([ch for ch in raw.info['chs']
if ch['kind'] == FIFF.FIFFV_REF_MEG_CH])
n_eegchan = len([ch for ch in raw.info['chs']
if ch['kind'] == FIFF.FIFFV_EEG_CH])
n_ecogchan = len([ch for ch in raw.info['chs']
if ch['kind'] == FIFF.FIFFV_ECOG_CH])
n_seegchan = len([ch for ch in raw.info['chs']
if ch['kind'] == FIFF.FIFFV_SEEG_CH])
n_eogchan = len([ch for ch in raw.info['chs']
if ch['kind'] == FIFF.FIFFV_EOG_CH])
n_ecgchan = len([ch for ch in raw.info['chs']
if ch['kind'] == FIFF.FIFFV_ECG_CH])
n_emgchan = len([ch for ch in raw.info['chs']
if ch['kind'] == FIFF.FIFFV_EMG_CH])
n_miscchan = len([ch for ch in raw.info['chs']
if ch['kind'] == FIFF.FIFFV_MISC_CH])
n_stimchan = len([ch for ch in raw.info['chs']
if ch['kind'] == FIFF.FIFFV_STIM_CH]) - n_ignored
# Define modality-specific JSON dictionaries
ch_info_json_common = [
('TaskName', task),
('Manufacturer', manufacturer),
('PowerLineFrequency', powerlinefrequency),
('SamplingFrequency', sfreq),
('SoftwareFilters', 'n/a'),
('RecordingDuration', raw.times[-1]),
('RecordingType', rec_type)]
ch_info_json_meg = [
('DewarPosition', 'n/a'),
('DigitizedLandmarks', False),
('DigitizedHeadPoints', False),
('MEGChannelCount', n_megchan),
('MEGREFChannelCount', n_megrefchan)]
ch_info_json_eeg = [
('EEGReference', 'n/a'),
('EEGGround', 'n/a'),
('EEGPlacementScheme', _infer_eeg_placement_scheme(raw)),
('Manufacturer', manufacturer)]
ch_info_json_ieeg = [
('iEEGReference', 'n/a'),
('ECOGChannelCount', n_ecogchan),
('SEEGChannelCount', n_seegchan)]
ch_info_ch_counts = [
('EEGChannelCount', n_eegchan),
('EOGChannelCount', n_eogchan),
('ECGChannelCount', n_ecgchan),
('EMGChannelCount', n_emgchan),
('MiscChannelCount', n_miscchan),
('TriggerChannelCount', n_stimchan)]
# Stitch together the complete JSON dictionary
ch_info_json = ch_info_json_common
if kind == 'meg':
append_kind_json = ch_info_json_meg
elif kind == 'eeg':
append_kind_json = ch_info_json_eeg
elif kind == 'ieeg':
append_kind_json = ch_info_json_ieeg
ch_info_json += append_kind_json
ch_info_json += ch_info_ch_counts
ch_info_json = OrderedDict(ch_info_json)
_write_json(fname, ch_info_json, overwrite, verbose)
return fname
