- raw : instance of Raw
Raw data
- tmin : float
Beginning of time interval in seconds. Defaults to 0.
- tmax : float | None (default None)
End of time interval in seconds. If None (default), use the end of the
recording.
- tstep : float (default 0.2)
Length of data chunks for artifact rejection in seconds.
Can also be None to use a single epoch of (tmax - tmin)
duration. This can use a lot of memory for large Raw
instances.
- reject : dict | None (default 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 (default 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.
- picks : str | list | slice | None
Channels to include. Slices and lists of integers will be
interpreted as channel indices. In lists, channel type strings
(e.g., ['meg', 'eeg']) will pick channels of those
types, channel name strings (e.g., ['MEG0111', 'MEG2623']
will pick the given channels. Can also be the string values
“all” to pick all channels, or “data” to pick data channels.
None (default) will pick good data channels(excluding reference MEG channels).
- method : str | list | None (default ‘empirical’)
The method used for covariance estimation.
See mne.compute_covariance().
- method_params : dict | None (default None)
Additional parameters to the estimation procedure.
See mne.compute_covariance().
- cv : int | sklearn.model_selection object (default 3)
The cross validation method. Defaults to 3, which will
internally trigger by default sklearn.model_selection.KFold
with 3 splits.
- scalings : dict | None (default None)
Defaults to dict(mag=1e15, grad=1e13, eeg=1e6).
These defaults will scale magnetometers and gradiometers
at the same unit.
- n_jobs : int (default 1)
Number of jobs to run in parallel.
- return_estimators : bool (default False)
Whether to return all estimators or the best. Only considered if
method equals ‘auto’ or is a list of str. Defaults to False
- reject_by_annotation : bool
Whether to reject based on annotations. If True (default), epochs
overlapping with segments whose description begins with 'bad' are
rejected. If False, no rejection based on annotations is performed.
- rank : None | int | dict | ‘full’
Specified rank of the noise covariance matrix. If None(default),
the rank is detected automatically.
If int, the rank is specified for the MEG
channels. A dictionary with entries ‘eeg’, ‘meg’ or any other
data channel type such as ‘seeg’ or ‘ecog’ can be used
to specify the rank for each modality. If ‘full’,
the covariance is assumed to be full-rank when regularizing.
- verbose : bool, str, int, or None
If not None, override default verbose level (see mne.verbose()
and Logging documentation for more).
