- mne.events_from_annotations(raw, event_id='auto', regexp='^(?![Bb][Aa][Dd]|[Ee][Dd][Gg][Ee]).*$', use_rounding=True, chunk_duration=None, verbose=None)#
Get events and
event_idfrom an Annotations object.
- rawinstance of
The raw data for which Annotations are defined.
dict: map descriptions (keys) to integer event codes (values). Only the descriptions present will be mapped, others will be ignored.
callable: must take a string input and return an integer event code, or return
Noneto ignore the event.
None: Map descriptions to unique integer values based on their
‘auto’ (default): prefer a raw-format-specific parser:
Brainvision: map stimulus events to their integer part; response events to integer part + 1000; optic events to integer part + 2000; ‘SyncStatus/Sync On’ to 99998; ‘New Segment/’ to 99999; all others like
Nonewith an offset of 10000.
Other raw formats: Behaves like None.
New in version 0.18.
Regular expression used to filter the annotations whose descriptions is a match. The default ignores descriptions beginning
Changed in version 0.18: Default ignores bad and edge descriptions.
If True, use rounding (instead of truncation) when converting times to indices. This can help avoid non-unique indices.
Chunk duration in seconds. If
chunk_durationis set to None (default), generated events correspond to the annotation onsets. If not,
mne.events_from_annotations()returns as many events as they fit within the annotation duration spaced according to
chunk_duration. As a consequence annotations with duration shorter than
chunk_durationwill not contribute events.
- verbosebool |
- rawinstance of
For data formats that store integer events as strings (e.g., NeuroScan
.cntfiles), passing the Python built-in function
event_idparameter will do what most users probably want in those circumstances: return an
event_iddictionary that maps event
'1'to integer event code