mne.beamformer.rap_music

mne.beamformer.rap_music(evoked, forward, noise_cov, n_dipoles=5, return_residual=False, verbose=None)

RAP-MUSIC source localization method.

Compute Recursively Applied and Projected MUltiple SIgnal Classification (RAP-MUSIC) on evoked data.

Note

The goodness of fit (GOF) of all the returned dipoles is the same and corresponds to the GOF of the full set of dipoles.

Parameters

evokedinstance of Evoked

Evoked data to localize.

forwardinstance of Forward

Forward operator.

noise_covinstance of Covariance

The noise covariance.

n_dipolesint

The number of dipoles to look for. The default value is 5.

return_residualbool

If True, the residual is returned as an Evoked instance.

verbosebool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more). If used, it should be passed as a keyword-argument only.

Returns

dipoleslist of instance of Dipole

The dipole fits.

residualinstance of Evoked

The residual a.k.a. data not explained by the dipoles. Only returned if return_residual is True.

See also

mne.fit_dipole

Notes

The references are:

J.C. Mosher and R.M. Leahy. 1999. Source localization using recursively applied and projected (RAP) MUSIC. Signal Processing, IEEE Trans. 47, 2 (February 1999), 332-340. DOI=10.1109/78.740118 https://doi.org/10.1109/78.740118

Mosher, J.C.; Leahy, R.M., EEG and MEG source localization using recursively applied (RAP) MUSIC, Signals, Systems and Computers, 1996. pp.1201,1207 vol.2, 3-6 Nov. 1996 doi: 10.1109/ACSSC.1996.599135

New in version 0.9.0.

Examples using mne.beamformer.rap_music

Compute Rap-Music on evoked data