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.LYRProjector¶

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

The LYRProjector class enables ? visualization on the same figure through 2D projections with plot_glass_brain.

This visualization mode can be activated by setting display_mode='lyr':

from nilearn.datasets import load_mni152_template
from nilearn.plotting import plot_glass_brain

img = load_mni152_template()
# display is an instance of the LYRProjector class
display = plot_glass_brain(img, display_mode="lyr")

Attributes:

axesdict of GlassBrainAxes: The axes used for plotting in each direction (‘l’, ‘y’ and ‘r’ here).
frame_axesAxes: The axes framing the whole set of views.

See also

nilearn.plotting.displays.LZRProjector: ?? views

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

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

Contour a 3D map in all the views.

Parameters:

imgNiimg-like object

See Input and output: neuroimaging data representation. Provides image to plot.

thresholdint or float or None, default=1e-6

Threshold to apply:

If None is given, the maps are not thresholded.

If number is given, it must be non-negative. The specified value is used to threshold the image: values below the threshold (in absolute value) are plotted as transparent.

filledbool, default=False

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

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.

Raises:

ValueError: if the specified threshold is a negative number

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 and output: neuroimaging data representation. 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, default=’r’: The color used to display the edge map.

add_graph(adjacency_matrix, node_coords, node_color='auto', node_size=50, edge_cmap='RdBu_r', edge_vmin=None, edge_vmax=None, edge_threshold=None, edge_kwargs=None, node_kwargs=None, colorbar=False)[source]¶

Plot undirected graph on each of the axes.

Parameters:

adjacency_matrixnumpy.ndarray of shape (n, n)

Represents the edges strengths of the graph. The matrix can be symmetric which will result in an undirected graph, or not symmetric which will result in a directed graph.

node_coordsnumpy.ndarray of shape (n, 3)

3D coordinates of the graph nodes in world space.

node_colorcolor or sequence of colors, default=’auto’

Color(s) of the nodes.

node_sizescalar or array_like, default=50

Size(s) of the nodes in points^2.

edge_cmapColormap, default=”RdBu_r”

Colormap used for representing the strength of the edges.

edge_vmin, edge_vmaxfloat, optional

If not None, either or both of these values will be used to as the minimum and maximum values to color edges.
If None are supplied, the maximum absolute value within the given threshold will be used as minimum (multiplied by -1) and maximum coloring levels.

edge_thresholdstr or int or float, optional

If it is a number only the edges with a value greater than edge_threshold will be shown.
If it is a string it must finish with a percent sign, e.g. “25.3%”, and only the edges with a abs(value) above the given percentile will be shown.

edge_kwargsdict, optional

Will be passed as kwargs for each edge Line2D.

node_kwargsdict

Will be passed as kwargs to the function scatter which plots all the nodes at one.

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,), default=’r’: List of colors for each marker that can be string or matplotlib colors.
marker_sizefloat or list of float of shape (n_markers,), default=30: Size in pixel for each marker.

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

Plot a 3D map in all the views.

Parameters:

imgNiimg-like object

See Input and output: neuroimaging data representation. If it is a masked array, only the non-masked part will be plotted.

thresholdint or float or None, default=1e-6

Threshold to apply:

If None is given, the maps are not thresholded.
If number is given, it must be non-negative. The specified
value is used to threshold the image: values below the threshold (in absolute value) are plotted as transparent.

cbar_tick_formatstr, default=”%.2g” (scientific notation)

Controls how to format the tick labels of the colorbar. Ex: use “%i” to display as integers.

colorbarbool, default=False

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

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.

transparencyfloat between 0 and 1, or a Niimg-Like object, or None, default = None

Value to be passed as alpha value to imshow. if None is passed, it will be set to 1. If an image is passed, voxel-wise alpha blending will be applied, by relying on the absolute value of transparency at each voxel.

Added in Nilearn 0.12.0.

transparency_rangetuple or list of 2 non-negative numbers, or None, default = None

When an image is passed to transparency, this determines the range of values in the image to use for transparency (alpha blending). For example with transparency_range = [1.96, 3], any voxel / vertex ( $v_i$ ):

with a value between between -1.96 and 1.96, would be fully transparent (alpha = 0),
with a value less than -3 or greater than 3, would be fully opaque (alpha = 1),
with a value in the intervals [-3.0, -1.96] or [1.96, 3.0], would have an alpha_i value scaled linearly between 0 and 1 : $alpha_i = (\lvert v_i \lvert - 1.96) / (3.0 - 1.96)$ .

This parameter will be ignored unless an image is passed as transparency. The first number must be greater than 0 and less than the second one. if None is passed, this will be set to [0, max(abs(transparency))].

Added in Nilearn 0.12.0.

kwargsdict

Extra keyword arguments are passed to function imshow.

Raises:

ValueError: if the specified threshold is a negative number

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, default=True

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

positionsbool, default=True

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

scalebarbool, default=False

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.

sizeint, default=12

The size of the text used.

scale_sizeint or float, default=5.0

The length of the scalebar, in units of scale_units.

scale_units{‘cm’, ‘mm’}, default=’cm’

The units for the scalebar.

scale_locint, default=4

The positioning for the scalebar. 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, default=0

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

kwargsdict

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

property black_bg¶: Return black background.

property brain_color¶: Return brain color.

close()[source]¶

Close the figure.

This is necessary to avoid leaking memory.

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

Do nothing.

It does not make sense to draw crosses for the position of the cuts since we are taking the max along one axis.

classmethod find_cut_coords(img=None, threshold=None, cut_coords=None)[source]¶: Find the coordinates of the cut.

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 and output: neuroimaging data representation.
thresholdint or float, None, or ‘auto’, optional: If None is given, the image is not thresholded. If number is given, it must be non-negative. The specified value is used to threshold the image: values below the threshold (in absolute value) are plotted as transparent. If “auto” is given, the threshold is determined based on the score obtained using percentile value “80%” on the absolute value of the image data.
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, default=False: 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.
brain_colortuple, default=(0.5, 0.5, 0.5): The brain color to use as the background color (e.g., for transparent colorbars).

Raises:

ValueError: if the specified threshold is a negative number

savefig(filename, dpi=None, **kwargs)[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, default=None: The resolution in dots per inch.

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, default=0.01: The horizontal position of the title on the frame in fraction of the frame width.
yfloat, default=0.99: The vertical position of the title on the frame in fraction of the frame height.
sizeint, default=15: The size of the title text.
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, default=1: The alpha value for the background.
kwargs: Extra keyword arguments are passed to matplotlib’s text function.

Examples using `nilearn.plotting.displays.LYRProjector`¶

Glass brain plotting in nilearn (all options)

nilearn.plotting.displays.LYRProjector¶

Examples using nilearn.plotting.displays.LYRProjector¶

Examples using `nilearn.plotting.displays.LYRProjector`¶