mne.channels.DigMontage¶

class mne.channels.DigMontage(hsp, hpi, elp, point_names, nasion=None, lpa=None, rpa=None, dev_head_t=None, dig_ch_pos=None)¶

Montage for Digitized data

Montages are typically loaded from a file using read_dig_montage. Only use this class directly if you’re constructing a new montage.

Parameters:

hsp : array, shape (n_points, 3) The positions of the headshape points in 3d. These points are in the native digitizer space. hpi : array, shape (n_hpi, 3) The positions of the head-position indicator coils in 3d. These points are in the MEG device space. elp : array, shape (n_hpi, 3) The positions of the head-position indicator coils in 3d. This is typically in the native digitizer space. point_names : list, shape (n_elp) The names of the digitized points for hpi and elp. nasion : array, shape (1, 3) The position of the nasion fidicual point. lpa : array, shape (1, 3) The position of the left periauricular fidicual point. rpa : array, shape (1, 3) The position of the right periauricular fidicual point. dev_head_t : array, shape (4, 4) A Device-to-Head transformation matrix. dig_ch_pos : dict Dictionary of channel positions. New in version 0.12.

Notes

New in version 0.9.0.

Methods

__hash__() <==> hash(x)
plot([scale_factor, show_names])	Plot EEG sensor montage

__hash__() <==> hash(x)¶

plot(scale_factor=1.5, show_names=False)¶

Plot EEG sensor montage

Parameters:	scale_factor : float Determines the size of the points. Defaults to 1.5 show_names : bool Whether to show the channel names. Defaults to False
Returns:	fig : Instance of matplotlib.figure.Figure The figure object.