- evoked : instance of Evoked or list of instances of Evoked
Evoked data to invert.
- forward : dict
Forward operator.
- noise_cov : instance of Covariance
Noise covariance to compute whitener.
- alpha : float in range [0, 100)
Regularization parameter. 0 means no regularization, 100 would give 0
active dipole.
- 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.
- active_set_size : int | None
Size of active set increment. If None, no active set strategy is used.
- pca : bool
If True the rank of the data is reduced to true dimension.
- debias : bool
Remove coefficient amplitude bias due to L1 penalty.
- time_pca : bool or int
If True the rank of the concatenated epochs is reduced to
its true dimension. If is ‘int’ the rank is limited to this value.
- weights : None | array | SourceEstimate
Weight for penalty in mixed_norm. Can be None, a
1d array with shape (n_sources,), or a SourceEstimate (e.g. obtained
with wMNE, dSPM, or fMRI).
- weights_min : float
Do not consider in the estimation sources for which weights
is less than weights_min.
- solver : ‘prox’ | ‘cd’ | ‘bcd’ | ‘auto’
The algorithm to use for the optimization. ‘prox’ stands for
proximal iterations using the FISTA algorithm, ‘cd’ uses
coordinate descent, and ‘bcd’ applies block coordinate descent.
‘cd’ is only available for fixed orientation.
- n_mxne_iter : int
The number of MxNE iterations. If > 1, iterative reweighting
is applied.
- 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.
- dgap_freq : int or np.inf
The duality gap is evaluated every dgap_freq iterations. Ignored if
solver is ‘cd’.
- verbose : bool, str, int, or None
If not None, override default verbose level (see mne.verbose()
and Logging documentation for more).
