mne.viz.plot_sparse_source_estimates

mne.viz.plot_sparse_source_estimates(src, stcs, colors=None, linewidth=2, fontsize=18, bgcolor=(0.05, 0, 0.1), opacity=0.2, brain_color=(0.7, 0.7, 0.7), show=True, high_resolution=False, fig_name=None, fig_number=None, labels=None, modes=('cone', 'sphere'), scale_factors=(1, 0.6), verbose=None, **kwargs)[source]

Plot source estimates obtained with sparse solver.

Active dipoles are represented in a “Glass” brain. If the same source is active in multiple source estimates it is displayed with a sphere otherwise with a cone in 3D.

Parameters
srcdict

The source space.

stcsinstance of SourceEstimate or list of instances of SourceEstimate

The source estimates (up to 3).

colorslist

List of colors.

linewidthint

Line width in 2D plot.

fontsizeint

Font size.

bgcolortuple of length 3

Background color in 3D.

opacityfloat in [0, 1]

Opacity of brain mesh.

brain_colortuple of length 3

Brain color.

showbool

Show figures if True.

high_resolutionbool

If True, plot on the original (non-downsampled) cortical mesh.

fig_namestr

Mayavi figure name.

fig_numberint

Matplotlib figure number.

labelsndarray or list of ndarray

Labels to show sources in clusters. Sources with the same label and the waveforms within each cluster are presented in the same color. labels should be a list of ndarrays when stcs is a list ie. one label for each stc.

modeslist

Should be a list, with each entry being 'cone' or 'sphere' to specify how the dipoles should be shown.

scale_factorslist

List of floating point scale factors for the markers.

verbosebool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more).

**kwargskwargs

Keyword arguments to pass to mlab.triangular_mesh.

Returns
surfaceinstance of mayavi.mlab.pipeline.surface

The triangular mesh surface.