Note

This page is a reference documentation. It only explains the class signature, and not how to use it. Please refer to the user guide for the big picture.

nilearn.plotting.displays.MosaicSlicer#

class nilearn.plotting.displays.MosaicSlicer(cut_coords, axes=None, black_bg=False, brain_color=(0.5, 0.5, 0.5), **kwargs)[source]#

A class to create 3 Axes for plotting cuts of 3D maps, in multiple rows and columns. This visualization mode can be activated from Nilearn plotting functions, like plot_img, by setting display_mode='mosaic'.

from nilearn.datasets import load_mni152_template
from nilearn.plotting import plot_img
img = load_mni152_template()
# display is an instance of the MosaicSlicer class
display = plot_img(img, display_mode='mosaic')

See also

nilearn.plotting.displays.TiledSlicer: Three cuts are performed in orthogonal directions.
nilearn.plotting.displays.OrthoSlicer: Three cuts are performed and arranged in a 2x2 grid.

Attributes

cut_coordsdict <str: 1D ndarray>: The cut coordinates in a dictionary. The keys are the directions (‘x’, ‘y’, ‘z’), and the values are arrays holding the cut coordinates.
axesdict of Axes: The 3 axes used to plot multiple views.
frame_axesAxes: The axes framing the whole set of views.

__init__(cut_coords, axes=None, black_bg=False, brain_color=(0.5, 0.5, 0.5), **kwargs)[source]#

classmethod find_cut_coords(img=None, threshold=None, cut_coords=None)[source]#

Instantiate the slicer and find cut coordinates for mosaic plotting.

Parameters

img3D Nifti1Image, optional: The brain image.
thresholdfloat, optional: The lower threshold to the positive activation. If None, the activation threshold is computed using the 80% percentile of the absolute value of the map.
cut_coordslist / tuple of 3 float, int, optional: xyz world coordinates of cuts. If cut_coords are not provided, 7 coordinates of cuts are automatically calculated.

Returns

cut_coordsdict: xyz world coordinates of cuts in a direction. Each key denotes the direction.

draw_cross(cut_coords=None, **kwargs)[source]#

Draw a crossbar on the plot to show where the cut is performed.

Parameters

cut_coords3-tuple of float, optional: The position of the cross to draw. If None is passed, the OrthoSlicer’s cut coordinates are used.
kwargsdict: Extra keyword arguments are passed to function matplotlib.pyplot.axhline.

add_contours(img, threshold=1e-06, filled=False, **kwargs)[source]#

Contour a 3D map in all the views.

Parameters

imgNiimg-like object

See input-output. Provides image to plot.

thresholdint or float or None, optional

Threshold to apply:

If None is given, the maps are not thresholded.

If a number is given, it is used to threshold the maps, values below the threshold (in absolute value) are plotted as transparent.

Default=1e-6.

filledbool, optional

If filled=True, contours are displayed with color fillings. Default=False.

kwargsdict

Extra keyword arguments are passed to function contour, or function contourf. Useful, arguments are typical “levels”, which is a list of values to use for plotting a contour or contour fillings (if filled=True), and “colors”, which is one color or a list of colors for these contours.

Notes

If colors are not specified, default coloring choices (from matplotlib) for contours and contour_fillings can be different.

add_edges(img, color='r')[source]#

Plot the edges of a 3D map in all the views.

Parameters

imgNiimg-like object: See input-output. The 3D map to be plotted. If it is a masked array, only the non-masked part will be plotted.
colormatplotlib color: str or (r, g, b) value: The color used to display the edge map. Default=’r’.

add_markers(marker_coords, marker_color='r', marker_size=30, **kwargs)[source]#

Add markers to the plot.

Parameters

marker_coordsndarray of shape (n_markers, 3): Coordinates of the markers to plot. For each slice, only markers that are 2 millimeters away from the slice are plotted.
marker_colorpyplot compatible color or list of shape (n_markers,), optional: List of colors for each marker that can be string or matplotlib colors. Default=’r’.
marker_sizefloat or list of float of shape (n_markers,), optional: Size in pixel for each marker. Default=30.

add_overlay(img, threshold=1e-06, colorbar=False, cbar_tick_format='%.2g', cbar_vmin=None, cbar_vmax=None, **kwargs)[source]#

Plot a 3D map in all the views.

Parameters

imgNiimg-like object

See input-output. If it is a masked array, only the non-masked part will be plotted.

thresholdint or float or None, optional

Threshold to apply:

If None is given, the maps are not thresholded.

If a number is given, it is used to threshold the maps: values below the threshold (in absolute value) are plotted as transparent.

Default=1e-6.

cbar_tick_format: str, optional

Controls how to format the tick labels of the colorbar. Ex: use “%i” to display as integers. Default is ‘%.2g’ for scientific notation.

colorbarbool, optional

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

kwargsdict

Extra keyword arguments are passed to function imshow.

cbar_vminfloat, optional

Minimal value for the colorbar. If None, the minimal value is computed based on the data.

cbar_vmaxfloat, optional

Maximal value for the colorbar. If None, the maximal value is computed based on the data.

annotate(left_right=True, positions=True, scalebar=False, size=12, scale_size=5.0, scale_units='cm', scale_loc=4, decimals=0, **kwargs)[source]#

Add annotations to the plot.

Parameters

left_rightbool, optional

If True, annotations indicating which side is left and which side is right are drawn. Default=True.

positionsbool, optional

If True, annotations indicating the positions of the cuts are drawn. Default=True.

scalebarbool, optional

If True, cuts are annotated with a reference scale bar. For finer control of the scale bar, please check out the draw_scale_bar method on the axes in “axes” attribute of this object. Default=False.

sizeint, optional

The size of the text used. Default=12.

scale_sizeint or float, optional

The length of the scalebar, in units of scale_units. Default=5.0.

scale_units{‘cm’, ‘mm’}, optional

The units for the scalebar. Default=’cm’.

scale_locint, optional

The positioning for the scalebar. Default=4. Valid location codes are:

1: “upper right”

2: “upper left”

3: “lower left”

4: “lower right”

5: “right”

6: “center left”

7: “center right”

8: “lower center”

9: “upper center”

10: “center”

decimalsint, optional

Number of decimal places on slice position annotation. If zero, the slice position is integer without decimal point. Default=0.

kwargsdict

Extra keyword arguments are passed to matplotlib’s text function.

property black_bg#

property brain_color#

close()[source]#: Close the figure. This is necessary to avoid leaking memory.

classmethod init_with_figure(img, threshold=None, cut_coords=None, figure=None, axes=None, black_bg=False, leave_space=False, colorbar=False, brain_color=(0.5, 0.5, 0.5), **kwargs)[source]#

Initialize the slicer with an image.

Parameters

imgNiimg-like object: See input-output.
cut_coords3 tuple of int: The cut position, in world space.
axesmatplotlib.axes.Axes, optional: The axes that will be subdivided in 3.
black_bgbool, optional: If True, the background of the figure will be put to 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.
brain_colortuple, optional: The brain color to use as the background color (e.g., for transparent colorbars). Default=(0.5, 0.5, 0.5).

savefig(filename, dpi=None)[source]#

Save the figure to a file.

Parameters

filenamestr: The file name to save to. Its extension determines the file type, typically ‘.png’, ‘.svg’ or ‘.pdf’.
dpiNone or scalar, optional: The resolution in dots per inch. Default=None.

title(text, x=0.01, y=0.99, size=15, color=None, bgcolor=None, alpha=1, **kwargs)[source]#

Write a title to the view.

Parameters

textstr: The text of the title.
xfloat, optional: The horizontal position of the title on the frame in fraction of the frame width. Default=0.01.
yfloat, optional: The vertical position of the title on the frame in fraction of the frame height. Default=0.99.
sizeint, optional: The size of the title text. Default=15.
colormatplotlib color specifier, optional: The color of the font of the title.
bgcolormatplotlib color specifier, optional: The color of the background of the title.
alphafloat, optional: The alpha value for the background. Default=1.
kwargs: Extra keyword arguments are passed to matplotlib’s text function.

Examples using `nilearn.plotting.displays.MosaicSlicer`#

More plotting tools from nilearn

nilearn.plotting.displays.MosaicSlicer#

Examples using nilearn.plotting.displays.MosaicSlicer#

Examples using `nilearn.plotting.displays.MosaicSlicer`#