mne.fit_dipole

mne.fit_dipole(evoked, cov, bem, trans=None, min_dist=5.0, n_jobs=1, verbose=None)

Fit a dipole

Parameters:

evoked : instance of Evoked

The dataset to fit.

cov : str | instance of Covariance

The noise covariance.

bem : str | dict

The BEM filename (str) or a loaded sphere model (dict).

trans : str | None

The head<->MRI transform filename. Must be provided unless BEM is a sphere model.

min_dist : float

Minimum distance (in milimeters) from the dipole to the inner skull. Must be positive. Note that because this is a constraint passed to a solver it is not strict but close, i.e. for a min_dist=5. the fits could be 4.9 mm from the inner skull.

n_jobs : int

Number of jobs to run in parallel (used in field computation and fitting).

verbose : bool, str, int, or None

If not None, override default verbose level (see mne.verbose).

Returns:

dip : instance of Dipole

The dipole fits.

residual : ndarray, shape (n_meeg_channels, n_times)

The good M-EEG data channels with the fitted dipolar activity removed.

Notes

New in version 0.9.0.