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, radiological=False)

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, default=’auto’

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, default=plt.cm.viridis_r.

Colormap used to represent the node measure.

node_vminfloat or None, default=None

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

node_vmaxfloat or None, default=None

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

node_thresholdfloat or None, default=None

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

alphafloat between 0 and 1, default=0.7

Alpha transparency for markers.

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_modestr, default=’ortho’

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’.

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 tuple of float: (xmin, ymin, width, height), default=None

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, default=None

The title displayed on the figure.

annotatebool, default=True

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

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 or None, default=None

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.

radiologicalbool, default=False

Invert x axis and R L labels to plot sections as a radiological view. If False (default), the left hemisphere is on the left of a coronal image. If True, left hemisphere is on the right.

Returns:

displayOrthoProjector or None

An instance of the OrthoProjector class. If output_file is defined, None is returned.

Examples using nilearn.plotting.plot_markers

Extract signals on spheres and plot a connectome

Extract signals on spheres and plot a connectome