- raw : instance of Raw
The raw data
- inverse_operator : instance of InverseOperator
The inverse operator
- lambda2: float
The regularization parameter
- method: “MNE” | “dSPM” | “sLORETA”
Use mininum norm, dSPM (default), sLORETA, or eLORETA.
- tmin : float | None
The beginning of the time interval of interest (in seconds). If None
start from the beginning of the file.
- tmax : float | None
The end of the time interval of interest (in seconds). If None
stop at the end of the file.
- fmin : float
The lower frequency of interest
- fmax : float
The upper frequency of interest
- n_fft: int
Window size for the FFT. Should be a power of 2.
- overlap: float
The overlap fraction between windows. Should be between 0 and 1.
0 means no overlap.
- 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.
- label: Label
Restricts the source estimates to a given label
- nave : int
The number of averages used to scale the noise covariance matrix.
- pca: bool
If True, the true dimension of data is estimated before running
the time-frequency transforms. It reduces the computation times
e.g. with a dataset that was maxfiltered (true dim is 64).
- prepared : bool
If True, do not call prepare_inverse_operator()
.
- method_params : dict | None
Additional options for eLORETA. See Notes of apply_inverse()
.
- verbose : bool, str, int, or None
If not None, override default verbose level (see mne.verbose()
and Logging documentation for more).