mne.viz.plot_alignment#
- mne.viz.plot_alignment(info=None, trans=None, subject=None, subjects_dir=None, surfaces='auto', coord_frame='auto', meg=None, eeg='original', fwd=None, dig=False, ecog=True, src=None, mri_fiducials=False, bem=None, seeg=True, fnirs=True, show_axes=False, dbs=True, fig=None, interaction='terrain', verbose=None)[source]#
Plot head, sensor, and source space alignment in 3D.
- Parameters:
- info
mne.Info
|None
The
mne.Info
object with information about the sensors and methods of measurement. If None (default), no sensor information will be shown.- transpath-like |
dict
| instance ofTransform
|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” will load trans from the FreeSurfer directory specified bysubject
andsubjects_dir
parameters.Changed in version 0.19: Support for ‘fsaverage’ argument.
- subject
str
The FreeSurfer subject name. Can be omitted if
src
is provided.- subjects_dirpath-like |
None
The path to the directory containing the FreeSurfer subjects reconstructions. If
None
, defaults to theSUBJECTS_DIR
environment variable.- surfaces
str
|list
|dict
Surfaces to plot. Supported values:
scalp: one of ‘head’, ‘outer_skin’ (alias for ‘head’), ‘head-dense’, or ‘seghead’ (alias for ‘head-dense’)
skull: ‘outer_skull’, ‘inner_skull’, ‘brain’ (alias for ‘inner_skull’)
brain: one of ‘pial’, ‘white’, ‘inflated’, or ‘brain’ (alias for ‘pial’).
Can be dict to specify alpha values for each surface. Use None to specify default value. Specified values must be between 0 and 1. for example:
surfaces=dict(brain=0.4, outer_skull=0.6, head=None)
Defaults to ‘auto’, which will look for a head surface and plot it if found.
Note
For single layer BEMs it is recommended to use
'brain'
.- coord_frame‘auto’ | ‘head’ | ‘meg’ | ‘mri’
The coordinate frame to use. If
'auto'
(default), chooses'mri'
iftrans
was passed, and'head'
otherwise.Changed in version 1.0: Defaults to
'auto'
.- meg
str
|list
|bool
|None
Can be “helmet”, “sensors” or “ref” to show the MEG helmet, sensors or reference sensors respectively, or a combination like
('helmet', 'sensors')
(same as None, default). True translates to('helmet', 'sensors', 'ref')
.- eeg
bool
|str
|list
String options are:
- “original” (default; equivalent to
True
) Shows EEG sensors using their digitized locations (after transformation to the chosen
coord_frame
)
- “original” (default; equivalent to
- “projected”
The EEG locations projected onto the scalp, as is done in forward modeling
Can also be a list of these options, or an empty list (
[]
, equivalent ofFalse
).- fwdinstance of
Forward
The forward solution. If present, the orientations of the dipoles present in the forward solution are displayed.
- dig
bool
| ‘fiducials’ If True, plot the digitization points; ‘fiducials’ to plot fiducial points only.
- ecog
bool
If True (default), show ECoG sensors.
- srcinstance of
SourceSpaces
|None
If not None, also plot the source space points.
- mri_fiducials
bool
|str
Plot MRI fiducials (default False). If
True
, look for a file with the canonical name (bem/{subject}-fiducials.fif
). Ifstr
, it can be'estimated'
to usemne.coreg.get_mni_fiducials()
, otherwise it should provide the full path to the fiducials file.New in version 0.22: Support for
'estimated'
.- bem
list
ofdict
| instance ofConductorModel
|None
Can be either the BEM surfaces (list of dict), a BEM solution or a sphere model. If None, we first try loading
'$SUBJECTS_DIR/$SUBJECT/bem/$SUBJECT-$SOURCE.fif'
, and then look for'$SUBJECT*$SOURCE.fif'
in the same directory. For'outer_skin'
, the subjects bem and bem/flash folders are searched. Defaults to None.- seeg
bool
If True (default), show sEEG electrodes.
- fnirs
str
|list
|bool
|None
Can be “channels”, “pairs”, “detectors”, and/or “sources” to show the fNIRS channel locations, optode locations, or line between source-detector pairs, or a combination like
('pairs', 'channels')
. True translates to('pairs',)
. .. versionadded:: 0.20- show_axes
bool
If True (default False), coordinate frame axis indicators will be shown:
head in pink.
MRI in gray (if
trans is not None
).MEG in blue (if MEG sensors are present).
New in version 0.16.
- dbs
bool
If True (default), show DBS (deep brain stimulation) electrodes.
- fig
Figure3D
|None
PyVista scene in which to plot the alignment. If
None
, creates a new 600x600 pixel figure with black background.New in version 0.16.
- interaction‘trackball’ | ‘terrain’
How interactions with the scene via an input device (e.g., mouse or trackpad) modify the camera position. If
'terrain'
, one axis is fixed, enabling “turntable-style” rotations. If'trackball'
, movement along all axes is possible, which provides more freedom of movement, but you may incidentally perform unintentional rotations along some axes.New in version 0.16.
Changed in version 1.0: Defaults to
'terrain'
.- verbose
bool
|str
|int
|None
Control verbosity of the logging output. If
None
, use the default verbosity level. See the logging documentation andmne.verbose()
for details. Should only be passed as a keyword argument.
- info
- Returns:
- figinstance of
Figure3D
The figure.
- figinstance of
See also
Notes
This function serves the purpose of checking the validity of the many different steps of source reconstruction:
Transform matrix (keywords
trans
,meg
andmri_fiducials
),BEM surfaces (keywords
bem
andsurfaces
),sphere conductor model (keywords
bem
andsurfaces
) andsource space (keywords
surfaces
andsrc
).
New in version 0.15.
Examples using mne.viz.plot_alignment
#
Source alignment and coordinate frames
Using an automated approach to coregistration
Head model and forward computation
EEG forward operator with a template MRI
The role of dipole orientations in distributed source localization
EEG source localization given electrode locations on an MRI
Brainstorm Elekta phantom dataset tutorial
Brainstorm CTF phantom dataset tutorial
4D Neuroimaging/BTi phantom dataset tutorial
Annotate movement artifacts and reestimate dev_head_t
How to convert 3D electrode positions to a 2D image
Plotting EEG sensors on the scalp
Plotting sensor layouts of MEG systems
Plotting sensor layouts of EEG systems
Compute source power spectral density (PSD) of VectorView and OPM data
Generate a left cerebellum volume source space
Optically pumped magnetometer (OPM) data