mne.io.read_raw_nicolet#
- mne.io.read_raw_nicolet(input_fname, ch_type, eog=(), ecg=(), emg=(), misc=(), preload=False, verbose=None)[source]#
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_fnamepath-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 withEOG
are used. Defaults to empty tuple.- ecg
list
ortuple
|'auto'
Names of channels or list of indices that should be designated ECG channels. If
'auto'
, the channel names beginning withECG
are used. Defaults to empty tuple.- emg
list
ortuple
|'auto'
Names of channels or list of indices that should be designated EMG channels. If
'auto'
, the channel names beginning withEMG
are used. Defaults to empty tuple.- misc
list
ortuple
Names of channels or list of indices that should be designated MISC channels. Defaults to empty tuple.
- preload
bool
orstr
(defaultFalse
) Preload data into memory for data manipulation and faster indexing. If True, the data will be preloaded into memory (fast, requires large amount of memory). If preload is a string, preload is the file name of a memory-mapped file which is used to store the data on the hard drive (slower, requires less memory).
- verbose
bool
|str
|int
|None
Control verbosity of the logging output. If
None
, use the default verbosity level. See the logging documentation andmne.verbose()
for details. Should only be passed as a keyword argument.
- Returns:
- rawinstance of
Raw
A Raw object containing the data.
- rawinstance of
See also
mne.io.Raw
Documentation of attributes and methods.
- ..note:: This reader takes data files with the extension
Examples using mne.io.read_raw_nicolet
#
Importing data from EEG devices