Note

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.view_img_on_surf#

nilearn.plotting.view_img_on_surf(stat_map_img, surf_mesh='fsaverage5', threshold=None, cmap=<matplotlib.colors.LinearSegmentedColormap object>, black_bg=False, vmax=None, vmin=None, symmetric_cmap=True, colorbar=True, colorbar_height=0.5, colorbar_fontsize=25, title=None, title_fontsize=25, vol_to_surf_kwargs={})[source]#

Insert a surface plot of a statistical map into an HTML page.

Parameters:
stat_map_imgNiimg-like object, 3D

See Input and output: neuroimaging data representation.

surf_meshstr or dict, optional.

If a string, it should be one of the following values:

  • ‘fsaverage3’: the low-resolution fsaverage3 mesh (642 nodes)

  • ‘fsaverage4’: the low-resolution fsaverage4 mesh (2562 nodes)

  • ‘fsaverage5’: the low-resolution fsaverage5 mesh (10242 nodes)

  • ‘fsaverage6’: the medium-resolution fsaverage6 mesh (40962 nodes)

  • ‘fsaverage7’: same as ‘fsaverage’

  • ‘fsaverage’: the high-resolution fsaverage mesh (163842 nodes)

    Note

    The high-resolution fsaverage will result in more computation time and memory usage

If a dictionary, it should have the same structure as those returned by nilearn.datasets.fetch_surf_fsaverage, i.e. keys should be ‘infl_left’, ‘pial_left’, ‘sulc_left’, ‘infl_right’, ‘pial_right’, and ‘sulc_right’, containing inflated and pial meshes, and sulcal depth values for left and right hemispheres. Default=’fsaverage5’.

thresholdstr, number or None, optional

If None, no thresholding. If it is a number only values of amplitude greater than threshold will be shown. If it is a string it must finish with a percent sign, e.g. “25.3%”, and only values of amplitude above the given percentile will be shown.

cmapstr or matplotlib colormap, optional

Colormap to use. Default=cm.cold_hot.

black_bgbool, optional

If True, image is plotted on a black background. Otherwise on a white background. Default=False.

vmaxfloat or None, optional

upper bound for the colorbar. if None, use the absolute max of the brain map.

vminfloat or None, optional

min value for mapping colors. If symmetric_cmap is True, vmin is always equal to -vmax and cannot be chosen. If symmetric_cmap is False, vmin defaults to the min of the image, or 0 when a threshold is used.

symmetric_cmapbool, optional

Make colormap symmetric (ranging from -vmax to vmax). You can set it to False if you are plotting only positive values. Default=True.

colorbarbool, optional

Add a colorbar or not. Default=True.

colorbar_heightfloat, optional

Height of the colorbar, relative to the figure height. Default=0.5.

colorbar_fontsizeint, optional

Fontsize of the colorbar tick labels. Default=25.

titlestr, optional

Title for the plot.

title_fontsizeint, optional

Fontsize of the title. Default=25.

vol_to_surf_kwargsdict, optional

Dictionary of keyword arguments that are passed on to nilearn.surface.vol_to_surf when extracting a surface from the input image. See the function documentation for details.This parameter is especially useful when plotting an atlas. See https://nilearn.github.io/stable/auto_examples/01_plotting/plot_3d_map_to_surface_projection.html

Returns:
SurfaceViewplot of the stat map.

It can be saved as an html page or rendered (transparently) by the Jupyter notebook. Useful methods are :

  • ‘resize’ to resize the plot displayed in a Jupyter notebook

  • ‘save_as_html’ to save the plot to a file

  • ‘open_in_browser’ to save the plot and open it in a web browser.

See also

nilearn.plotting.view_surf

plot from a surface map on a cortical mesh.

Examples using nilearn.plotting.view_img_on_surf#

Making a surface plot of a 3D statistical map

Making a surface plot of a 3D statistical map

Making a surface plot of a 3D statistical map