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

TRAP-MUSIC source localization method.

Compute Truncated Recursively Applied and Projected MUltiple SIgnal Classification (TRAP-MUSIC) 1 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 | None

Control verbosity of the logging output. If None, use the default verbosity level. See the logging documentation and mne.verbose() for details. Should only be passed as a keyword argument.

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.


New in v1.4.



Niko Mäkelä, Matti Stenroos, Jukka Sarvas, and Risto J. Ilmoniemi. Truncated rap-music (trap-music) for meg and eeg source localization. Neuroimage, 167():73–83, 2018. doi:10.1016/j.neuroimage.2017.11.013.

Examples using mne.beamformer.trap_music#

Compute Trap-Music on evoked data

Compute Trap-Music on evoked data