# 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.

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. 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. 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). 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.