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.plot_markers#

nilearn.plotting.plot_markers(node_values, node_coords, node_size='auto', node_cmap=<matplotlib.colors.ListedColormap object>, node_vmin=None, node_vmax=None, node_threshold=None, alpha=0.7, output_file=None, display_mode='ortho', figure=None, axes=None, title=None, annotate=True, black_bg=False, node_kwargs=None, colorbar=True)[source]#

Plot network nodes (markers) on top of the brain glass schematics.

Nodes are color coded according to provided nodal measure. Nodal measure usually represents some notion of node importance.

Parameters:
node_valuesarray_like of length n

Vector containing nodal importance measure. Each node will be colored according to corresponding node value.

node_coordsnumpy array_like of shape (n, 3)

3d coordinates of the graph nodes in world space.

node_size‘auto’ or scalar or array-like, optional

Size(s) of the nodes in points^2. By default the size of the node is inversely proportional to the number of nodes.

node_cmapstr or colormap, optional

Colormap used to represent the node measure. Default=plt.cm.viridis_r.

node_vminfloat, optional

Lower bound of the colormap. If None, the min of the node_values is used.

node_vmaxfloat, optional

Upper bound of the colormap. If None, the min of the node_values is used.

node_thresholdfloat

If provided only the nodes with a value greater than node_threshold will be shown.

alphafloat between 0 and 1, optional

Alpha transparency for markers. Default=0.7.

output_filestr, 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.

display_modestring, optional

Choose the direction of the cuts: ‘x’ - sagittal, ‘y’ - coronal, ‘z’ - axial, ‘l’ - sagittal left hemisphere only, ‘r’ - sagittal right hemisphere only, ‘ortho’ - three cuts are performed in orthogonal directions. Possible values are: ‘ortho’, ‘x’, ‘y’, ‘z’, ‘xz’, ‘yx’, ‘yz’, ‘l’, ‘r’, ‘lr’, ‘lzr’, ‘lyr’, ‘lzry’, ‘lyrz’. Default=’ortho’.

figureint, or matplotlib.figure.Figure, or None, optional

Matplotlib figure used or its number. If None is given, a new figure is created.

axesmatplotlib.axes.Axes, or 4 tupleof float: (xmin, ymin, width, height), optional

The axes, or the coordinates, in matplotlib figure space, of the axes used to display the plot. If None, the complete figure is used.

titlestr, or None, optional

The title displayed on the figure. Default=None.

annotatebool, optional

If annotate is True, positions and left/right annotation are added to the plot. Default=True.

black_bgbool, or ‘auto’, optional

If True, the background of the image is set to be black. If you wish to save figures with a black background, you will need to pass facecolor=’k’, edgecolor=’k’ to matplotlib.pyplot.savefig. Default=False.

node_kwargsdict, optional

will be passed as kwargs to the plt.scatter call that plots all the nodes in one go

colorbarbool, optional

If True, display a colorbar on the right of the plots. Default=True.

Examples using nilearn.plotting.plot_markers#

Extract signals on spheres and plot a connectome

Extract signals on spheres and plot a connectome

Extract signals on spheres and plot a connectome