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_surf(surf_mesh, surf_map=None, bg_map=None, threshold=None, cmap=<matplotlib.colors.LinearSegmentedColormap object>, black_bg=False, vmax=None, vmin=None, bg_on_data=False, darkness=0.7, symmetric_cmap=True, colorbar=True, colorbar_height=0.5, colorbar_fontsize=25, title=None, title_fontsize=25)[source]#

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

surf_meshstr or list of two numpy.ndarray

Surface mesh geometry, can be a file (valid formats are .gii or Freesurfer specific files such as .orig, .pial, .sphere, .white, .inflated) or a list of two Numpy arrays, the first containing the x-y-z coordinates of the mesh vertices, the second containing the indices (into coords) of the mesh faces.

surf_mapstr or numpy.ndarray, optional

Data to be displayed on the surface mesh. Can be a file (valid formats are .gii, .mgz, .nii, .nii.gz, or Freesurfer specific files such as .thickness, .area, .curv, .sulc, .annot, .label) or a Numpy array

bg_mapstr or numpy.ndarray, optional

Background image to be plotted on the mesh underneath the surf_data in greyscale, most likely a sulcal depth map for realistic shading. If the map contains values outside [0, 1], it will be rescaled such that all values are in [0, 1]. Otherwise, it will not be modified. Default=None.

bg_on_databool, default=False

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.

darknessfloat between 0 and 1, optional

Specifying the darkness of the background image:

  • 1 indicates that the original values of the background are used

  • 0.5 indicates that the background values are reduced by half before being applied.


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

You might want to change it to ‘gnist_ncar’ if plotting a surface atlas. Default=cm.cold_hot.

black_bgbool, optional

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

symmetric_cmapbool, optional

Make colormap symmetric (ranging from -vmax to vmax). Set it to False if you are plotting a surface atlas. Default=True.

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.

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.

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


Surface plot from a 3D statistical map.

Examples using nilearn.plotting.view_surf#

Loading and plotting of a cortical surface atlas

Loading and plotting of a cortical surface atlas

Making a surface plot of a 3D statistical map

Making a surface plot of a 3D statistical map