mne.viz.plot_source_estimates#
- mne.viz.plot_source_estimates(stc, subject=None, surface='inflated', hemi='lh', colormap='auto', time_label='auto', smoothing_steps=10, transparent=True, alpha=1.0, time_viewer='auto', subjects_dir=None, figure=None, views='auto', colorbar=True, clim='auto', cortex='classic', size=800, background='black', foreground=None, initial_time=None, time_unit='s', backend='auto', spacing='oct6', title=None, show_traces='auto', src=None, volume_options=1.0, view_layout='vertical', add_data_kwargs=None, brain_kwargs=None, verbose=None)[source]#
Plot SourceEstimate.
- Parameters:
- stc
SourceEstimate The source estimates to plot.
- subject
str|None The FreeSurfer subject name. If
None,stc.subjectwill be used.- surface
str The type of surface (inflated, white etc.).
- hemi
str Hemisphere id (ie ‘lh’, ‘rh’, ‘both’, or ‘split’). In the case of ‘both’, both hemispheres are shown in the same window. In the case of ‘split’ hemispheres are displayed side-by-side in different viewing panes.
- colormap
str|np.ndarrayoffloat, shape(n_colors, 3 | 4) Name of colormap to use or a custom look up table. If array, must be (n x 3) or (n x 4) array for with RGB or RGBA values between 0 and 255. The default (‘auto’) uses ‘hot’ for one-sided data and ‘mne’ for two-sided data.
- time_label
str|callable()|None Format of the time label (a format string, a function that maps floating point time values to strings, or None for no label). The default is
'auto', which will usetime=%0.2f msif there is more than one time point.- smoothing_steps
int The amount of smoothing.
- transparentbool |
None If True: use a linear transparency between fmin and fmid and make values below fmin fully transparent (symmetrically for divergent colormaps). None will choose automatically based on colormap type.
- alpha
float Alpha value to apply globally to the overlay. Has no effect with mpl backend.
- time_viewerbool |
str Display time viewer GUI. Can also be ‘auto’, which will mean True for the PyVista backend and False otherwise.
Changed in version 0.20.0: “auto” mode added.
- subjects_dirpath-like |
None The path to the directory containing the FreeSurfer subjects reconstructions. If
None, defaults to theSUBJECTS_DIRenvironment variable.- figureinstance of
Figure3D| instance ofmatplotlib.figure.Figure|list|int|None If None, a new figure will be created. If multiple views or a split view is requested, this must be a list of the appropriate length. If int is provided it will be used to identify the PyVista figure by it’s id or create a new figure with the given id. If an instance of matplotlib figure, mpl backend is used for plotting.
- views
str|list View to use. Using multiple views (list) is not supported for mpl backend. See
Brain.show_viewfor valid string options.When plotting a standard SourceEstimate (not volume, mixed, or vector) and using the PyVista backend,
views='flat'is also supported to plot cortex as a flatmap.Using multiple views (list) is not supported by the matplotlib backend.
Changed in version 0.21.0: Support for flatmaps.
- colorbarbool
If True, display colorbar on scene.
- clim
str|dict Colorbar properties specification. If ‘auto’, set clim automatically based on data percentiles. If dict, should contain:
kind‘value’ | ‘percent’Flag to specify type of limits.
limslist | np.ndarray | tuple of float, 3 elementsLower, middle, and upper bounds for colormap.
pos_limslist | np.ndarray | tuple of float, 3 elementsLower, middle, and upper bound for colormap. Positive values will be mirrored directly across zero during colormap construction to obtain negative control points.
Note
Only one of
limsorpos_limsshould be provided. Only sequential colormaps should be used withlims, and only divergent colormaps should be used withpos_lims.- cortex
strortuple Specifies how binarized curvature values are rendered. Either the name of a preset Brain cortex colorscheme (one of ‘classic’, ‘bone’, ‘low_contrast’, or ‘high_contrast’), or the name of a colormap, or a tuple with values (colormap, min, max, reverse) to fully specify the curvature colors. Has no effect with mpl backend.
- size
floatortupleoffloat The size of the window, in pixels. can be one number to specify a square window, or the (width, height) of a rectangular window. Has no effect with mpl backend.
- backgroundmatplotlib color
Color of the background of the display window.
- foregroundmatplotlib color |
None Color of the foreground of the display window. Has no effect with mpl backend. None will choose white or black based on the background color.
- initial_time
float|None The time to display on the plot initially.
Noneto display the first time sample (default).- time_unit‘s’ | ‘ms’
Whether time is represented in seconds (“s”, default) or milliseconds (“ms”).
- backend‘auto’ | ‘pyvistaqt’ | ‘matplotlib’
Which backend to use. If
'auto'(default), tries to plot with pyvistaqt, but resorts to matplotlib if no 3d backend is available.New in version 0.15.0.
- spacing
str Only affects the matplotlib backend. The spacing to use for the source space. Can be
'ico#'for a recursively subdivided icosahedron,'oct#'for a recursively subdivided octahedron, or'all'for all points. In general, you can speed up the plotting by selecting a sparser source space. Defaults to ‘oct6’.New in version 0.15.0.
- title
str|None Title for the figure. If None, the subject name will be used.
New in version 0.17.0.
- show_tracesbool |
str|float If True, enable interactive picking of a point on the surface of the brain and plot its time course. This feature is only available with the PyVista 3d backend, and requires
time_viewer=True. Defaults to ‘auto’, which will use True if and only iftime_viewer=True, the backend is PyVista, and there is more than one time point. If float (between zero and one), it specifies what proportion of the total window should be devoted to traces (True is equivalent to 0.25, i.e., it will occupy the bottom 1/4 of the figure).New in version 0.20.0.
- srcinstance of
SourceSpaces|None The source space corresponding to the source estimate. Only necessary if the STC is a volume or mixed source estimate.
- volume_options
float|dict|None Options for volumetric source estimate plotting, with key/value pairs:
'resolution'float | NoneResolution (in mm) of volume rendering. Smaller (e.g., 1.) looks better at the cost of speed. None (default) uses the volume source space resolution, which is often something like 7 or 5 mm, without resampling.
'blending'strCan be “mip” (default) for maximum intensity projection or “composite” for composite blending using alpha values.
'alpha'float | NoneAlpha for the volumetric rendering. Defaults are 0.4 for vector source estimates and 1.0 for scalar source estimates.
'surface_alpha'float | NoneAlpha for the surface enclosing the volume(s). None (default) will use half the volume alpha. Set to zero to avoid plotting the surface.
'silhouette_alpha'float | NoneAlpha for a silhouette along the outside of the volume. None (default) will use
0.25 * surface_alpha.
'silhouette_linewidth'floatThe line width to use for the silhouette. Default is 2.
A float input (default 1.) or None will be used for the
'resolution'entry.- view_layout
str Can be “vertical” (default) or “horizontal”. When using “horizontal” mode, the PyVista backend must be used and hemi cannot be “split”.
- add_data_kwargs
dict|None Additional arguments to brain.add_data (e.g.,
dict(time_label_size=10)).- brain_kwargs
dict|None Additional arguments to the
mne.viz.Brainconstructor (e.g.,dict(silhouette=True)).- verbosebool |
str|int|None Control verbosity of the logging output. If
None, use the default verbosity level. See the logging documentation andmne.verbose()for details. Should only be passed as a keyword argument.
- stc
- Returns:
- figureinstance of
mne.viz.Brain|matplotlib.figure.Figure An instance of
mne.viz.Brainor matplotlib figure.
- figureinstance of
Notes
Flatmaps are available by default for
fsaveragebut not for other subjects reconstructed by FreeSurfer. We recommend usingmne.compute_source_morph()to morph source estimates tofsaveragefor flatmap plotting. If you want to construct your own flatmap for a given subject, these links might help:
