mne.annotations_from_events

mne.annotations_from_events(events, sfreq, event_desc=None, first_samp=0, orig_time=None, verbose=None)[source]

Convert an event array to an Annotations object.

Parameters
eventsndarray, shape (n_events, 3)

The events.

sfreqfloat

Sampling frequency.

event_descdict | array_like | callable() | None

Events description. Can be:

  • dict: map integer event codes (keys) to descriptions (values). Only the descriptions present will be mapped, others will be ignored.

  • array-like: list, or 1d array of integers event codes to include. Only the event codes present will be mapped, others will be ignored. Event codes will be passed as string descriptions.

  • callable: must take a integer event code as input and return a string description or None to ignore it.

  • None: Use integer event codes as descriptions.

first_sampint

The first data sample (default=0). See mne.io.Raw.first_samp docstring.

orig_timefloat | str | datetime | tuple of int | None

Determines the starting time of annotation acquisition. If None (default), starting time is determined from beginning of raw data acquisition. For details, see mne.Annotations() docstring.

verbosebool, str, int, or None

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.

Returns
annotinstance of Annotations

The annotations.

Notes

Annotations returned by this function will all have zero (null) duration.

Creating events from annotations via the function mne.events_from_annotations takes in event mappings with key→value pairs as description→ID, whereas mne.annotations_from_events takes in event mappings with key→value pairs as ID→description. If you need to use these together, you can invert the mapping by doing:

event_desc = {v: k for k, v in event_id.items()}

Examples using mne.annotations_from_events