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=None, *, head_source=('bem', 'head'), verbose=None)[source]#

Compute surface maps used for field display in 3D.

Parameters:
evokedEvoked | Epochs | Raw

The measurement file. Need to have info attribute.

transpath-like | dict | instance of Transform | None

If str, the path to the head<->MRI transform *-trans.fif file produced during coregistration. Can also be 'fsaverage' to use the built-in fsaverage transformation. If trans is None, an identity matrix is assumed. "auto" (default) will load trans from the FreeSurfer directory specified by subject and subjects_dir parameters.

Changed in version 0.19: Support for 'fsaverage' argument.

subjectstr | None

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

subjects_dirpath-like

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.

n_jobsint | None

The number of jobs to run in parallel. If -1, it is set to the number of CPU cores. Requires the joblib package. None (default) is a marker for ‘unset’ that will be interpreted as n_jobs=1 (sequential execution) unless the call is performed under a joblib.parallel_backend() context manager that sets another value for n_jobs.

head_sourcestr | list of str

Head source(s) to use. See the source option of mne.get_head_surf() for more information.

New in version 1.1.

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.

Returns:
surf_mapslist

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).

Examples using mne.make_field_map#

Visualizing Evoked data

Visualizing Evoked data

Plot the MNE brain and helmet

Plot the MNE brain and helmet

From raw data to dSPM on SPM Faces dataset

From raw data to dSPM on SPM Faces dataset