mne.make_field_map

mne.make_field_map(evoked, trans=’auto’, subject=None, subjects_dir=None, ch_type=None, mode=’fast’, meg_surf=’helmet’, origin=(0.0, 0.0, 0.04), n_jobs=1, verbose=None)[source]

Compute surface maps used for field display in 3D.

Parameters:

evoked : Evoked | Epochs | Raw

The measurement file. Need to have info attribute.

trans : str | ‘auto’ | None

The full path to the *-trans.fif file produced during coregistration. If present or found using ‘auto’ the maps will be in MRI coordinates. If None, map for EEG data will not be available.

subject : str | None

The subject name corresponding to FreeSurfer environment variable SUBJECT. If None, map for EEG data will not be available.

subjects_dir : str

The path to the freesurfer subjects reconstructions. It corresponds to Freesurfer environment variable SUBJECTS_DIR.

ch_type : None | ‘eeg’ | ‘meg’

If None, a map for each available channel type will be returned. Else only the specified type will be used.

mode : str

Either ‘accurate’ or ‘fast’, determines the quality of the Legendre polynomial expansion used. ‘fast’ should be sufficient for most applications.

meg_surf : str

Should be 'helmet' or 'head' to specify in which surface to compute the MEG field map. The default value is 'helmet'

origin : array-like, shape (3,) | str

Origin of internal and external multipolar moment space in head coords and in meters. The default is 'auto', which means a head-digitization-based origin fit.

New in version 0.11.

n_jobs : int

The number of jobs to run in parallel.

verbose : bool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more).

New in version 0.11.
Returns:

surf_maps : list

The surface maps to be used for field plots. The list contains separate ones for MEG and EEG (if both MEG and EEG are present).