def _initialize(self):
if not self.source_name:
raise ValueError("Please set LSL stream name.")
stream_infos = lsl.resolve_byprop(
"name",
self.source_name,
timeout=self.SECONDS_TO_WAIT_FOR_THE_STREAM,
)
if len(stream_infos) == 0:
raise ValueError("Cannot find LSL stream with name {}".format(
self.source_name))
elif len(stream_infos) > 1:
raise ValueError("Multiple LSL streams with name {}.".format(
self.source_name))
else:
info = stream_infos[0]
self._inlet = _FixedStreamInlet(info)
self._inlet.open_stream()
frequency = info.nominal_srate()
self.dtype = DTYPE
channel_labels, channel_types = read_channel_labels_from_info(
self._inlet.info())
self.mne_info = mne.create_info(channel_labels,
frequency,
ch_types=channel_types)
capitalize_chnames(self.mne_info)
self.timestamps = []
def _initialize(self):
self._time_of_the_last_update = None
self._n_samples_already_read = 0
if self.file_path is not None:
basename = os.path.basename(self.file_path)
_, ext = os.path.splitext(basename)
if ext in self.SUPPORTED_EXTENSIONS["Brainvision"]:
self.data, self.mne_info, self.times = read_brain_vision_data(
file_path=self.file_path, time_axis=TIME_AXIS)
elif ext in self.SUPPORTED_EXTENSIONS["MNE-python"]:
self.data, self.mne_info, self.times = read_fif_data(
file_path=self.file_path, time_axis=TIME_AXIS)
elif ext in self.SUPPORTED_EXTENSIONS["European Data Format"]:
self.data, self.mne_info, self.times = read_edf_data(
file_path=self.file_path, time_axis=TIME_AXIS)
else:
raise ValueError("Cannot read {}.".format(basename) +
"Extension must be one of the following: {}".
format(self.SUPPORTED_EXTENSIONS.values()))
self.dtype = DTYPE
self.data = self.data.astype(self.dtype)
self.timestamps = []
capitalize_chnames(self.mne_info)
else:
exc = ValueError("File path is not set.")
self._logger.exception(exc)
raise exc
def info(scope="session"):
"""Get info with applied average projection"""
logging.basicConfig(filename=None, level=logging.INFO)
dloader = DataDownloader()
info_src_path = dloader.get_file("Koleno_raw.fif")
raw = Raw(info_src_path, preload=True)
raw.set_eeg_reference("average", projection=True)
capitalize_chnames(raw.info)
return raw.info
def _initialize(self):
self.nchan = self._mne_info["nchan"]
self.mne_info = self._mne_info
capitalize_chnames(self.mne_info)
def create_dummy_info(nchan=32, sfreq=500):
ch_names = [str(i).zfill(2) for i in range(nchan)]
info = create_info(ch_names, sfreq, ch_types="eeg")
capitalize_chnames(info)
return info