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_missingstr
- 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 and- mne.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 from- raw.timesand- raw.n_timesparameters but- raw.first_sampand- raw.first_timeare updated accordingly.
Examples using mne.io.read_raw_fif#
 
How to convert 3D electrode positions to a 2D image
 
 
 
