raw : Raw object
inverse_operator : dict
Inverse operator returned from mne.read_inverse_operator,
prepare_inverse_operator or make_inverse_operator.
lambda2 : float
The regularization parameter.
method : “MNE”  “dSPM”  “sLORETA”
Use mininum norm, dSPM or sLORETA.
label : Label  None
Restricts the source estimates to a given label. If None,
source estimates will be computed for the entire source space.
start : int
Index of first time sample (index not time is seconds).
stop : int
Index of first time sample not to include (index not time is seconds).
nave : int
Number of averages used to regularize the solution.
Set to 1 on raw data.
time_func : callable
Linear function applied to sensor space time series.
pick_ori : None  “normal”
If “normal”, rather than pooling the orientations by taking the norm,
only the radial component is kept. This is only implemented
when working with loose orientations.
buffer_size : int (or None)
If not None, the computation of the inverse and the combination of the
current components is performed in segments of length buffer_size
samples. While slightly slower, this is useful for long datasets as it
reduces the memory requirements by approx. a factor of 3 (assuming
buffer_size << data length).
Note that this setting has no effect for fixedorientation inverse
operators.
prepared : bool
If True, do not call prepare_inverse_operator.
verbose : bool, str, int, or None
If not None, override default verbose level (see mne.verbose).
