Compute distances between head shape points and the scalp surface.
This function is useful to check that coregistration is correct. Unless outliers are present in the head shape points, one can assume an average distance around 2-3 mm.
mne.Info
The mne.Info
object with information about the sensors and methods of measurement. Must contain the head shape points in info['dig']
.
str
| instance of Transform
The head<->MRI transform. If str is passed it is the path to file on disk.
str
The name of the subject.
str
| None
Directory containing subjects data. If None use the Freesurfer SUBJECTS_DIR environment variable.
list
of str
| str
Kind of digitization points to use in the fitting. These can be any combination of (‘cardinal’, ‘hpi’, ‘eeg’, ‘extra’). Can also be ‘auto’ (default), which will use only the ‘extra’ points if enough (more than 4) are available, and if not, uses ‘extra’ and ‘eeg’ points.
If True, exclude points that have both negative Z values (below the nasion) and positivy Y values (in front of the LPA/RPA). Default is False.
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 version 1.0.
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.
array
, shape (n_points,)The distances.
See also
Notes
New in version 0.19.
mne.dig_mri_distances
#Source alignment and coordinate frames