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.

evokedEvoked | Epochs | Raw

The measurement file. Need to have info attribute.

transstr | ‘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.

subjectstr | None

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


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

ch_typeNone | ‘eeg’ | ‘meg’

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

mode‘accurate’ | ‘fast’

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

meg_surf‘helmet’ | ‘head’

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

originarray_like, shape (3,) | ‘auto’

Origin of the sphere in the head coordinate frame and in meters. Can be 'auto', which means a head-digitization-based origin fit. Default is (0., 0., 0.04).

New in version 0.11.


The number of jobs to run in parallel (default 1). Requires the joblib package.

verbosebool, str, int, or None

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


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).