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# Authors: The MNE-Python contributors.
# License: BSD-3-Clause
# Copyright the MNE-Python contributors.
import calendar
import datetime
from os import path
import numpy as np
from ..._fiff.constants import FIFF
from ..._fiff.meas_info import _empty_info
from ..._fiff.utils import _create_chs, _find_channels, _read_segments_file
from ...utils import fill_doc, logger
from ..base import BaseRaw
@fill_doc
def read_raw_nicolet(
input_fname, ch_type, eog=(), ecg=(), emg=(), misc=(), preload=False, verbose=None
) -> "RawNicolet":
"""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 : path-like
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 attributes 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) 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"] = 0.0
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 : path-like
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 attributes and methods.
"""
def __init__(
self,
input_fname,
ch_type,
eog=(),
ecg=(),
emg=(),
misc=(),
preload=False,
verbose=None,
):
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().__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")
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