This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the user guide for the big picture.
- nilearn.plotting.plot_img_on_surf(stat_map, surf_mesh='fsaverage5', mask_img=None, hemispheres=['left', 'right'], bg_on_data=False, inflate=False, views=['lateral', 'medial'], output_file=None, title=None, colorbar=True, vmin=None, vmax=None, threshold=None, symmetric_cbar='auto', cmap='cold_hot', **kwargs)#
Plot multiple views of plot_surf_stat_map in a single figure.
It projects stat_map into meshes and plots views of left and right hemispheres. The views argument defines the views that are shown. This function returns the fig, axes elements from matplotlib unless kwargs sets and output_file, in which case nothing is returned.
- stat_mapstr or 3D Niimg-like object
- surf_meshstr, dict, or None, optional
If str, either one of the two: ‘fsaverage5’: the low-resolution fsaverage5 mesh (10242 nodes) ‘fsaverage’: the high-resolution fsaverage mesh (163842 nodes) If dict, a dictionary with keys: [‘infl_left’, ‘infl_right’, ‘pial_left’, ‘pial_right’, ‘sulc_left’, ‘sulc_right’], where values are surface mesh geometries as accepted by plot_surf_stat_map. Default=’fsaverage5’.
- mask_imgNiimg-like object or None, optional
The mask is passed to vol_to_surf. Samples falling out of this mask or out of the image are ignored during projection of the volume to the surface. If
None, don’t apply any mask.
If True and a bg_map is specified, the surf_data data is multiplied by the background image, so that e.g. sulcal depth is jointly visible with surf_data. Otherwise, the background image will only be visible where there is no surface data (either because surf_data contains nans or because is was thresholded).
This non-uniformly changes the surf_data values according to e.g the sulcal depth.
str, default=[“left”, “right”]
Hemispheres to display.
- inflatebool, optional
If True, display images in inflated brain. If False, display images in pial surface. Default=False.
- viewslist of strings, optional
A list containing all views to display. The montage will contain as many rows as views specified by display mode. Order is preserved, and left and right hemispheres are shown on the left and right sides of the figure. Default=[‘lateral’, ‘medial’].
str, or None, optional
The name of an image file to export the plot to. Valid extensions are .png, .pdf, .svg. If output_file is not None, the plot is saved to a file, and the display is closed.
str, or None, default=None
The title displayed on the figure.
If True, display a colorbar on the right of the plots.
This function uses a symmetric colorbar for the statistical map.
Lower bound of the colormap. If None, the min of the image is used. Passed to
Upper bound of the colormap. If None, the max of the image is used. Passed to
- thresholda number, None, or ‘auto’, optional
If None is given, the image is not thresholded. If a number is given, it is used to threshold the image: values below the threshold (in absolute value) are plotted as transparent. If “auto” is given, the threshold is determined magically by analysis of the image.
bool, or “auto”, optional
Specifies whether the colorbar should range from -vmax to vmax (or from vmin to -vmin if -vmin is greater than vmax) or from vmin to vmax. Default=True.
The colormap to use. Either a string which is a name of a matplotlib colormap, or a matplotlib colormap object. Default=’cold_hot’.
- kwargsdict, optional
keyword arguments passed to plot_surf_stat_map.