| Parameters: |
- raw : instance of Raw
The raw data
- ch_name : str
The name of the channel to use for EOG peak detection.
The argument is mandatory if the dataset contains no EOG channels.
- event_id : int
The index to assign to found events
- picks : array-like of int | None (default)
Indices of channels to include (if None, all channels
are used).
- tmin : float
Start time before event.
- tmax : float
End time after event.
- l_freq : float
Low pass frequency to apply to the EOG channel while finding events.
- h_freq : float
High pass frequency to apply to the EOG channel while finding events.
- reject : dict | None
Rejection parameters based on peak-to-peak amplitude.
Valid keys are ‘grad’ | ‘mag’ | ‘eeg’ | ‘eog’ | ‘ecg’.
If reject is None then no rejection is done. Example:
reject = dict(grad=4000e-13, # T / m (gradiometers)
mag=4e-12, # T (magnetometers)
eeg=40e-6, # V (EEG channels)
eog=250e-6 # V (EOG channels)
)
- flat : dict | None
Rejection parameters based on flatness of signal.
Valid keys are ‘grad’ | ‘mag’ | ‘eeg’ | ‘eog’ | ‘ecg’, and values
are floats that set the minimum acceptable peak-to-peak amplitude.
If flat is None then no rejection is done.
- baseline : tuple or list of length 2, or None
The time interval to apply rescaling / baseline correction.
If None do not apply it. If baseline is (a, b)
the interval is between “a (s)” and “b (s)”.
If a is None the beginning of the data is used
and if b is None then b is set to the end of the interval.
If baseline is equal ot (None, None) all the time
interval is used. If None, no correction is applied.
- preload : bool
Preload epochs or not.
- reject_by_annotation : bool
Whether to reject based on annotations. If True (default), segments
whose description begins with 'bad' are not used for finding
artifacts and epochs overlapping with them are rejected. If False, no
rejection based on annotations is performed.
- verbose : bool, str, int, or None
If not None, override default verbose level (see mne.verbose()
and Logging documentation for more).
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