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

RAP-MUSIC source localization method.

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


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

evokedinstance of Evoked

Evoked data to localize.

forwardinstance of Forward

Forward operator.

noise_covinstance of Covariance

The noise covariance.


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


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.

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



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

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