mne.Dipole¶

class mne.Dipole(times, pos, amplitude, ori, gof, name=None)¶

Dipole class for sequential dipole fits

Note

This class should usually not be instantiated directly, instead mne.read_dipole() should be used.

Used to store positions, orientations, amplitudes, times, goodness of fit of dipoles, typically obtained with Neuromag/xfit, mne_dipole_fit or certain inverse solvers. Note that dipole position vectors are given in the head coordinate frame.

Parameters:

times : array, shape (n_dipoles,) The time instants at which each dipole was fitted (sec). pos : array, shape (n_dipoles, 3) The dipoles positions (m) in head coordinates. amplitude : array, shape (n_dipoles,) The amplitude of the dipoles (nAm). ori : array, shape (n_dipoles, 3) The dipole orientations (normalized to unit length). gof : array, shape (n_dipoles,) The goodness of fit. name : str | None Name of the dipole.

See also

read_dipole, DipoleFixed

Notes

This class is for sequential dipole fits, where the position changes as a function of time. For fixed dipole fits, where the position is fixed as a function of time, use mne.DipoleFixed.

Methods

__getitem__(item)	Get a time slice
__hash__() <==> hash(x)
__len__()	The number of dipoles
copy()	Copy the Dipoles object
crop([tmin, tmax])	Crop data to a given time interval
plot_amplitudes([color, show])	Plot the dipole amplitudes as a function of time
plot_locations(trans, subject[, ...])	Plot dipole locations as arrows
save(fname)	Save dipole in a .dip file

__getitem__(item)¶

Get a time slice

Parameters:	item : array-like or slice The slice of time points to use.
Returns:	dip : instance of Dipole The sliced dipole.

__hash__() <==> hash(x)¶

__len__()¶

The number of dipoles

Returns:	len : int The number of dipoles.

Examples

This can be used as:

>>> len(dipoles)  
10

copy()¶

Copy the Dipoles object

Returns:	dip : instance of Dipole The copied dipole instance.

crop(tmin=None, tmax=None)¶

Crop data to a given time interval

Parameters:	tmin : float | None Start time of selection in seconds. tmax : float | None End time of selection in seconds.

plot_amplitudes(color='k', show=True)¶

Plot the dipole amplitudes as a function of time

Parameters:	color: matplotlib Color Color to use for the trace. show : bool Show figure if True.
Returns:	fig : matplotlib.figure.Figure The figure object containing the plot.

plot_locations(trans, subject, subjects_dir=None, bgcolor=(1, 1, 1), opacity=0.3, brain_color=(1, 1, 0), fig_name=None, fig_size=(600, 600), mode='cone', scale_factor=0.01, colors=None, verbose=None)¶

Plot dipole locations as arrows

Parameters:

trans : dict The mri to head trans. subject : str The subject name corresponding to FreeSurfer environment variable SUBJECT. subjects_dir : None | str The path to the freesurfer subjects reconstructions. It corresponds to Freesurfer environment variable SUBJECTS_DIR. The default is None. bgcolor : tuple of length 3 Background color in 3D. opacity : float in [0, 1] Opacity of brain mesh. brain_color : tuple of length 3 Brain color. fig_name : tuple of length 2 Mayavi figure name. fig_size : tuple of length 2 Mayavi figure size. mode : str Should be 'cone' or 'sphere' to specify how the dipoles should be shown. scale_factor : float The scaling applied to amplitudes for the plot. colors: list of colors | None Color to plot with each dipole. If None defaults colors are used. verbose : bool, str, int, or None If not None, override default verbose level (see mne.verbose).

Returns:

fig : instance of mlab.Figure The mayavi figure.

save(fname)¶

Save dipole in a .dip file

Parameters:	fname : str The name of the .dip file.