mne.io.read_raw_fif#
- mne.io.read_raw_fif(fname, allow_maxshield=False, preload=False, on_split_missing='raise', verbose=None) Raw[source]#
Reader function for Raw FIF data.
- Parameters:
- fnamepath-like | file-like
The raw filename to load. For files that have automatically been split, the split part will be automatically loaded. Filenames should end with raw.fif, raw.fif.gz, raw_sss.fif, raw_sss.fif.gz, raw_tsss.fif, raw_tsss.fif.gz, or _meg.fif. If a file-like object is provided, preloading must be used.
Changed in version 0.18: Support for file-like objects.
- allow_maxshieldbool |
str(defaultFalse) If True, allow loading of data that has been recorded with internal active compensation (MaxShield). Data recorded with MaxShield should generally not be loaded directly, but should first be processed using SSS/tSSS to remove the compensation signals that may also affect brain activity. Can also be “yes” to load without eliciting a warning.
- preloadbool or
str(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).
- on_split_missing
str Can be
'raise'(default) to raise an error,'warn'to emit a warning, or'ignore'to ignore when split file is missing.New in v0.22.
- verbosebool |
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 FIF data.
- rawinstance of
Notes
New in v0.9.0.
When reading a FIF file, note that the first N seconds annotated
BAD_ACQ_SKIPare skipped. They are removed fromraw.timesandraw.n_timesparameters butraw.first_sampandraw.first_timeare updated accordingly.
Examples using mne.io.read_raw_fif#
How to convert 3D electrode positions to a 2D image