mne.channels.DigMontage¶

class mne.channels.DigMontage(dev_head_t=None, dig=None, ch_names=None)[source]¶

Montage for digitized electrode and headshape position data.

Warning

Montages are typically created using one of the helper functions in the See Also section below instead of instantiating this class directly.

Parameters

dev_head_tarray, shape (4, 4): A Device-to-Head transformation matrix.
diglist of dict: The object containing all the dig points.
ch_nameslist of str: The names of the EEG channels.

See also

read_dig_captrak
read_dig_dat
read_dig_egi
read_dig_fif
read_dig_hpts
read_dig_polhemus_isotrak
make_dig_montage

Notes

New in version 0.9.0.

Methods

`__add__`(other)	Add two DigMontages.
`__hash__`(/)	Return hash(self).
`add_estimated_fiducials`(subject[, …])	Estimate fiducials based on FreeSurfer `fsaverage` subject.
`copy`()	Copy the DigMontage object.
`get_positions`()	Get all channel and fiducial positions.
`plot`([scale_factor, show_names, kind, show, …])	Plot a montage.
`rename_channels`(mapping[, allow_duplicates])	Rename the channels.
`save`(fname)	Save digitization points to FIF.

__add__(other)[source]¶: Add two DigMontages.

add_estimated_fiducials(subject, subjects_dir=None, verbose=None)[source]¶

Estimate fiducials based on FreeSurfer fsaverage subject.

This takes a montage with the mri coordinate frame, corresponding to the FreeSurfer RAS (xyz in the volume) T1w image of the specific subject. It will call mne.coreg.get_mni_fiducials() to estimate LPA, RPA and Nasion fiducial points.

Parameters

subjectstr: The FreeSurfer subject name.
subjects_dirstr | None: The path to the FreeSurfer subjects reconstructions. It corresponds to FreeSurfer environment variable SUBJECTS_DIR.
verbosebool, str, int, or None: If not None, override default verbose level (see mne.verbose() and Logging documentation for more). If used, it should be passed as a keyword-argument only.

Returns

instinstance of DigMontage: The instance, modified in-place.

See also

Source alignment and coordinate frames

Notes

Since MNE uses the FIF data structure, it relies on the head coordinate frame. Any coordinate frame can be transformed to head if the fiducials (i.e. LPA, RPA and Nasion) are defined. One can use this function to estimate those fiducials and then use montage.get_native_head_t() to get the head <-> MRI transform.

copy()[source]¶

Copy the DigMontage object.

Returns

diginstance of DigMontage: The copied DigMontage instance.

get_positions()[source]¶

Get all channel and fiducial positions.

Returns

positionsdict

A dictionary of the positions for channels (ch_pos), coordinate frame (coord_frame), nasion (nasion), left preauricular point (lpa), right preauricular point (rpa), Head Shape Polhemus (hsp), and Head Position Indicator(hpi). E.g.:

{
    'ch_pos': {'EEG061': [0, 0, 0]},
    'nasion': [0, 0, 1],
    'coord_frame': 'mni_tal',
    'lpa': [0, 1, 0],
    'rpa': [1, 0, 0],
    'hsp': None,
    'hpi': None
}

Examples using get_positions:

How to plot topomaps the way EEGLAB does¶

plot(scale_factor=20, show_names=True, kind='topomap', show=True, sphere=None, verbose=None)[source]¶

Plot a montage.

Parameters

scale_factorfloat: Determines the size of the points.
show_namesbool: Whether to show the channel names.
kindstr: Whether to plot the montage as ‘3d’ or ‘topomap’ (default).
showbool: Show figure if True.
spherefloat | array_like | str | None: The sphere parameters to use for the cartoon head. Can be array-like of shape (4,) to give the X/Y/Z origin and radius in meters, or a single float to give the radius (origin assumed 0, 0, 0). Can also be a spherical ConductorModel, which will use the origin and radius. Can be “auto” to use a digitization-based fit. Can also be None (default) to use ‘auto’ when enough extra digitization points are available, and 0.095 otherwise. Currently the head radius does not affect plotting.

New in version 0.20.
verbosebool, str, int, or None: If not None, override default verbose level (see mne.verbose() and Logging documentation for more). If used, it should be passed as a keyword-argument only.

Returns

figinstance of matplotlib.figure.Figure: The figure object.

Examples using plot:

Working with sensor locations¶

EEG source localization given electrode locations on an MRI¶

rename_channels(mapping, allow_duplicates=False)[source]¶

Rename the channels.

Parameters

mappingdict | callable(): A dictionary mapping the old channel to a new channel name e.g. {‘EEG061’ : ‘EEG161’}. Can also be a callable function that takes and returns a string.

Changed in version 0.10.0: Support for a callable function.
allow_duplicatesbool: If True (default False), allow duplicates, which will automatically be renamed with -N at the end.

New in version 0.22.0.

Returns

instinstance of DigMontage: The instance. Operates in-place.

Examples using rename_channels:

EEG forward operator with a template MRI¶

save(fname)[source]¶

Save digitization points to FIF.

Parameters

fnamestr: The filename to use. Should end in .fif or .fif.gz.

Examples using save:

Working with sensor locations¶

mne.channels.Layout mne.channels.compute_native_head_t

mne.channels.DigMontage¶

Examples using mne.channels.DigMontage¶

Examples using `mne.channels.DigMontage`¶