Giving credit

Table Of Contents

Previous topic

7.10.9. nilearn.plotting.plot_connectome

Next topic

7.10.11. nilearn.plotting.show

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.

7.10.10. nilearn.plotting.plot_prob_atlas

nilearn.plotting.plot_prob_atlas(maps_img, anat_img=<MNI152Template>, view_type='auto', threshold='auto', linewidths=2.5, cut_coords=None, output_file=None, display_mode='ortho', figure=None, axes=None, title=None, annotate=True, draw_cross=True, black_bg='auto', dim='auto', colorbar=False, cmap=<matplotlib.colors.LinearSegmentedColormap object at 0x2b1ecaf3a050>, vmin=None, vmax=None, alpha=0.5, **kwargs)

Plot the probabilistic atlases onto the anatomical image by default MNI template

Parameters:

maps_img : Niimg-like object or the filename

4D image of the probabilistic atlas maps

anat_img : Niimg-like object

See http://nilearn.github.io/manipulating_images/input_output.html The anatomical image to be used as a background. If nothing is specified, the MNI152 template will be used. To turn off background image, just pass “anat_img=False”.

view_type : {‘auto’, ‘contours’, ‘filled_contours’, ‘continuous’}, optional

By default view_type == ‘auto’, means maps will be displayed automatically using any one of the three view types. The automatic selection of view type depends on the total number of maps. If view_type == ‘contours’, maps are overlayed as contours If view_type == ‘filled_contours’, maps are overlayed as contours along with color fillings inside the contours. If view_type == ‘continuous’, maps are overlayed as continous colors irrespective of the number maps.

threshold : a str or a number, list of str or numbers, None

This parameter is optional and is used to threshold the maps image using the given value or automatically selected value. The values in the image above the threshold level will be visualized. The default strategy, computes a threshold level that seeks to minimize (yet not eliminate completely) the overlap between several maps for a better visualization. The threshold can also be expressed as a percentile over the values of the whole atlas. In that case, the value must be specified as string finishing with a percent sign, e.g., “25.3%”. If a single string is provided, the same percentile will be applied over the whole atlas. Otherwise, if a list of percentiles is provided, each 3D map is thresholded with certain percentile sequentially. Length of percentiles given should match the number of 3D map in time (4th) dimension. If a number or a list of numbers, the given value will be used directly to threshold the maps without any percentile calculation. If None, a very small threshold is applied to remove numerical noise from the maps background.

linewidths : float, optional

This option can be used to set the boundary thickness of the contours.

cut_coords : None, a tuple of floats, or an integer

The MNI coordinates of the point where the cut is performed If display_mode is ‘ortho’, this should be a 3-tuple: (x, y, z) For display_mode == ‘x’, ‘y’, or ‘z’, then these are the coordinates of each cut in the corresponding direction. If None is given, the cuts is calculated automaticaly. If display_mode is ‘x’, ‘y’ or ‘z’, cut_coords can be an integer, in which case it specifies the number of cuts to perform

output_file : string, 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_mode : {‘ortho’, ‘x’, ‘y’, ‘z’, ‘yx’, ‘xz’, ‘yz’}

Choose the direction of the cuts: ‘x’ - sagittal, ‘y’ - coronal, ‘z’ - axial, ‘ortho’ - three cuts are performed in orthogonal directions.

figure : integer or matplotlib figure, optional

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

axes : matplotlib axes or 4 tuple of 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.

title : string, optional

The title displayed on the figure.

annotate : boolean, optional

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

draw_cross : boolean, optional

If draw_cross is True, a cross is drawn on the plot to indicate the cut plosition.

black_bg: boolean, 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 pylab’s savefig.

dim : float, ‘auto’ (by default), optional

Dimming factor applied to background image. By default, automatic heuristics are applied based upon the background image intensity. Accepted float values, where a typical span is -1 to 1 (-1 = increase contrast; 1 = decrease contrast), but larger values can be used for a more pronounced effect. 0 means no dimming.

cmap : matplotlib colormap, optional

The colormap for the atlas maps

colorbar : boolean, optional

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

vmin : float

Lower bound for plotting, passed to matplotlib.pyplot.imshow

vmax : float

Upper bound for plotting, passed to matplotlib.pyplot.imshow

alpha : float between 0 and 1

Alpha sets the transparency of the color inside the filled contours.

See also

nilearn.plotting.plot_roi
To simply plot max-prob atlases (3D images)