- evoked : instance of Evoked
Evoked data to invert.
- forward : dict
Forward operator.
- noise_cov : instance of Covariance
Noise covariance to compute whitener.
- loose : float in [0, 1] | ‘auto’
Value that weights the source variances of the dipole components
that are parallel (tangential) to the cortical surface. If loose
is 0 then the solution is computed with fixed orientation.
If loose is 1, it corresponds to free orientations.
The default value (‘auto’) is set to 0.2 for surface-oriented source
space and set to 1.0 for volumic or discrete source space.
- depth: None | float in [0, 1]
Depth weighting coefficients. If None, no depth weighting is performed.
- maxit : int
Maximum number of iterations.
- tol : float
Tolerance parameter.
- weights: None | array | SourceEstimate
Weight for penalty in mixed_norm. Can be None or
1d array of length n_sources or a SourceEstimate e.g. obtained
with wMNE or dSPM or fMRI.
- weights_min: float
Do not consider in the estimation sources for which weights
is less than weights_min.
- pca: bool
If True the rank of the data is reduced to true dimension.
- debias: bool
Remove coefficient amplitude bias due to L1 penalty.
- wsize: int or array-like
Length of the STFT window in samples (must be a multiple of 4).
If an array is passed, multiple TF dictionaries are used (each having
its own wsize and tstep) and each entry of wsize must be a multiple
of 4. See [3].
- tstep: int or array-like
Step between successive windows in samples (must be a multiple of 2,
a divider of wsize and smaller than wsize/2) (default: wsize/2).
If an array is passed, multiple TF dictionaries are used (each having
its own wsize and tstep), and each entry of tstep must be a multiple
of 2 and divide the corresponding entry of wsize. See [3].
- window : float or (float, float)
Length of time window used to take care of edge artifacts in seconds.
It can be one float or float if the values are different for left
and right window length.
- return_residual : bool
If True, the residual is returned as an Evoked instance.
- return_as_dipoles : bool
If True, the sources are returned as a list of Dipole instances.
- alpha : float in [0, 100) or None
Overall regularization parameter.
If alpha and l1_ratio are not None, alpha_space and alpha_time are
overridden by alpha * alpha_max * (1. - l1_ratio) and alpha * alpha_max
* l1_ratio. 0 means no regularization, 100 would give 0 active dipole.
- l1_ratio : float in [0, 1] or None
Proportion of temporal regularization.
If l1_ratio and alpha are not None, alpha_space and alpha_time are
overridden by alpha * alpha_max * (1. - l1_ratio) and alpha * alpha_max
* l1_ratio. 0 means no time regularization aka MxNE.
- dgap_freq : int or np.inf
The duality gap is evaluated every dgap_freq iterations.
- verbose : bool, str, int, or None
If not None, override default verbose level (see mne.verbose()
and Logging documentation for more).