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nicolet.py
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nicolet.py
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# Author: Jaakko Leppakangas <jaeilepp@student.jyu.fi>
#
# License: BSD-3-Clause
import numpy as np
from os import path
import datetime
import calendar
from ...utils import logger, fill_doc
from ..utils import _read_segments_file, _find_channels, _create_chs
from ..base import BaseRaw
from ..meas_info import _empty_info
from ..constants import FIFF
@fill_doc
def read_raw_nicolet(input_fname, ch_type, eog=(),
ecg=(), emg=(), misc=(), preload=False, verbose=None):
"""Read Nicolet data as raw object.
..note:: This reader takes data files with the extension ``.data`` as an
input. The header file with the same file name stem and an
extension ``.head`` is expected to be found in the same
directory.
Parameters
----------
input_fname : str
Path to the data file (ending with ``.data`` not ``.head``).
ch_type : str
Channel type to designate to the data channels. Supported data types
include 'eeg', 'dbs'.
eog : list | tuple | 'auto'
Names of channels or list of indices that should be designated
EOG channels. If 'auto', the channel names beginning with
``EOG`` are used. Defaults to empty tuple.
ecg : list or tuple | 'auto'
Names of channels or list of indices that should be designated
ECG channels. If 'auto', the channel names beginning with
``ECG`` are used. Defaults to empty tuple.
emg : list or tuple | 'auto'
Names of channels or list of indices that should be designated
EMG channels. If 'auto', the channel names beginning with
``EMG`` are used. Defaults to empty tuple.
misc : list or tuple
Names of channels or list of indices that should be designated
MISC channels. Defaults to empty tuple.
%(preload)s
%(verbose)s
Returns
-------
raw : instance of Raw
A Raw object containing the data.
See Also
--------
mne.io.Raw : Documentation of attribute and methods.
"""
return RawNicolet(input_fname, ch_type, eog=eog, ecg=ecg,
emg=emg, misc=misc, preload=preload, verbose=verbose)
def _get_nicolet_info(fname, ch_type, eog, ecg, emg, misc):
"""Extract info from Nicolet header files."""
fname, extension = path.splitext(fname)
if extension != '.data':
raise ValueError(
f'File name should end with .data not "{extension}".'
)
header = fname + '.head'
logger.info('Reading header...')
header_info = dict()
with open(header, 'r') as fid:
for line in fid:
var, value = line.split('=')
if var == 'elec_names':
value = value[1:-2].split(',') # strip brackets
elif var == 'conversion_factor':
value = float(value)
elif var in ['num_channels', 'rec_id', 'adm_id', 'pat_id',
'num_samples']:
value = int(value)
elif var != 'start_ts':
value = float(value)
header_info[var] = value
ch_names = header_info['elec_names']
if eog == 'auto':
eog = _find_channels(ch_names, 'EOG')
if ecg == 'auto':
ecg = _find_channels(ch_names, 'ECG')
if emg == 'auto':
emg = _find_channels(ch_names, 'EMG')
date, time = header_info['start_ts'].split()
date = date.split('-')
time = time.split(':')
sec, msec = time[2].split('.')
date = datetime.datetime(int(date[0]), int(date[1]), int(date[2]),
int(time[0]), int(time[1]), int(sec), int(msec))
info = _empty_info(header_info['sample_freq'])
info['meas_date'] = (calendar.timegm(date.utctimetuple()), 0)
if ch_type == 'eeg':
ch_coil = FIFF.FIFFV_COIL_EEG
ch_kind = FIFF.FIFFV_EEG_CH
elif ch_type == 'seeg':
ch_coil = FIFF.FIFFV_COIL_EEG
ch_kind = FIFF.FIFFV_SEEG_CH
else:
raise TypeError("Channel type not recognized. Available types are "
"'eeg' and 'seeg'.")
cals = np.repeat(header_info['conversion_factor'] * 1e-6, len(ch_names))
info['chs'] = _create_chs(ch_names, cals, ch_coil, ch_kind, eog, ecg, emg,
misc)
info['highpass'] = 0.
info['lowpass'] = info['sfreq'] / 2.0
info._unlocked = False
info._update_redundant()
return info, header_info
class RawNicolet(BaseRaw):
"""Raw object from Nicolet file.
Parameters
----------
input_fname : str
Path to the Nicolet file.
ch_type : str
Channel type to designate to the data channels. Supported data types
include 'eeg', 'seeg'.
eog : list | tuple | 'auto'
Names of channels or list of indices that should be designated
EOG channels. If 'auto', the channel names beginning with
``EOG`` are used. Defaults to empty tuple.
ecg : list or tuple | 'auto'
Names of channels or list of indices that should be designated
ECG channels. If 'auto', the channel names beginning with
``ECG`` are used. Defaults to empty tuple.
emg : list or tuple | 'auto'
Names of channels or list of indices that should be designated
EMG channels. If 'auto', the channel names beginning with
``EMG`` are used. Defaults to empty tuple.
misc : list or tuple
Names of channels or list of indices that should be designated
MISC channels. Defaults to empty tuple.
%(preload)s
%(verbose)s
See Also
--------
mne.io.Raw : Documentation of attribute and methods.
"""
def __init__(self, input_fname, ch_type, eog=(),
ecg=(), emg=(), misc=(), preload=False,
verbose=None): # noqa: D102
input_fname = path.abspath(input_fname)
info, header_info = _get_nicolet_info(input_fname, ch_type, eog, ecg,
emg, misc)
last_samps = [header_info['num_samples'] - 1]
super(RawNicolet, self).__init__(
info, preload, filenames=[input_fname], raw_extras=[header_info],
last_samps=last_samps, orig_format='int',
verbose=verbose)
def _read_segment_file(self, data, idx, fi, start, stop, cals, mult):
"""Read a chunk of raw data."""
_read_segments_file(
self, data, idx, fi, start, stop, cals, mult, dtype='<i2')