mne.events_from_annotations¶
- mne.events_from_annotations(raw, event_id='auto', regexp='^(?![Bb][Aa][Dd]|[Ee][Dd][Gg][Ee]).*$', use_rounding=True, chunk_duration=None, verbose=None)[source]¶
Get events and event_id from an Annotations object.
- Parameters
- rawinstance of
Raw
The raw data for which Annotations are defined.
- event_id
dict
|callable()
|None
| ‘auto’ Can be:
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
None
to ignore the event.None: Map descriptions to unique integer values based on their
sorted
order.‘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
None
with an offset of 10000.Other raw formats: Behaves like None.
New in version 0.18.
- regexp
str
|None
Regular expression used to filter the annotations whose descriptions is a match. The default ignores descriptions beginning
'bad'
or'edge'
(case-insensitive).Changed in version 0.18: Default ignores bad and edge descriptions.
- use_roundingbool
If True, use rounding (instead of truncation) when converting times to indices. This can help avoid non-unique indices.
- chunk_duration
float
|None
Chunk duration in seconds. If
chunk_duration
is 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 tochunk_duration
. As a consequence annotations with duration shorter thanchunk_duration
will not contribute events.- verbosebool,
str
,int
, orNone
If not None, override default verbose level (see
mne.verbose()
and Logging documentation for more). If used, it should be passed as a keyword-argument only.
- rawinstance of
- Returns
See also
Notes
For data formats that store integer events as strings (e.g., NeuroScan
.cnt
files), passing the Python built-in functionint
as theevent_id
parameter will do what most users probably want in those circumstances: return anevent_id
dictionary that maps event'1'
to integer event code1
,'2'
to2
, etc.