mne.cov.
regularize
(cov, info, mag=0.1, grad=0.1, eeg=0.1, exclude='bads', proj=True, verbose=None)¶Regularize noise covariance matrix.
This method works by adding a constant to the diagonal for each channel type separately. Special care is taken to keep the rank of the data constant.
Note: This function is kept for reasons of backward-compatibility.
Please consider explicitly using the method
parameter in
compute_covariance to directly combine estimation with regularization
in a data-driven fashion see the
faq
for more information.
Parameters: | cov : Covariance
info : dict
mag : float (default 0.1)
grad : float (default 0.1)
eeg : float (default 0.1)
exclude : list | ‘bads’ (default ‘bads’)
proj : bool (default true)
verbose : bool | str | int | None (default None)
|
---|---|
Returns: | reg_cov : Covariance
|
See also
compute_covariance