mne.scale_bem(subject_to, bem_name, subject_from=None, scale=None, subjects_dir=None, *, on_defects='raise', verbose=None)[source]#

Scale a bem file.


Name of the scaled MRI subject (the destination mri subject).


Name of the bem file. For example, to scale fsaverage-inner_skull-bem.fif, the bem_name would be “inner_skull-bem”.

subject_fromNone | str

The subject from which to read the source space. If None, subject_from is read from subject_to’s config file.

scaleNone | float | array, shape = (3,)

Scaling factor. Has to be specified if subjects_from is specified, otherwise it is read from subject_to’s config file.

subjects_dirNone | str

Override the SUBJECTS_DIR environment variable.

on_defects‘raise’ | ‘warn’ | ‘ignore’

What to do if the surface is found to have topological defects. Can be 'raise' (default) to raise an error, 'warn' to emit a warning, or 'ignore' to ignore when one or more defects are found. Note that a lot of computations in MNE-Python assume the surfaces to be topologically correct, topological defects may still make other computations (e.g., mne.make_bem_model and mne.make_bem_solution) fail irrespective of this parameter.

New in v1.0.

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.