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.YZProjector¶
- class nilearn.plotting.displays.YZProjector(cut_coords, axes=None, black_bg=False, brain_color=(0.5, 0.5, 0.5), **kwargs)[source]¶
The
YZProjector
class enables to combine coronal and axial views on the same figure through 2D projections withplot_glass_brain
.This visualization mode can be activated by setting
display_mode='yz'
:from nilearn.datasets import load_mni152_template from nilearn.plotting import plot_glass_brain img = load_mni152_template() # display is an instance of the YZProjector class display = plot_glass_brain(img, display_mode="yz")
- Attributes:
- axes
dict
ofGlassBrainAxes
The axes used for plotting in each direction (‘y’ and ‘z’ here).
- frame_axes
Axes
The axes framing the whole set of views.
- axes
See also
nilearn.plotting.displays.XZProjector
Sagittal + Axial views
nilearn.plotting.displays.YXProjector
Coronal + Sagittal views
- 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.
- threshold
int
orfloat
orNone
, default=1e-6 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.
- filled
bool
, default=False If
filled=True
, contours are displayed with color fillings.- kwargs
dict
Extra keyword arguments are passed to function
contour
, or functioncontourf
. Useful, arguments are typical “levels”, which is a list of values to use for plotting a contour or contour fillings (iffilled=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 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=<matplotlib.colors.LinearSegmentedColormap object>, 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_matrix
numpy.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_coords
numpy.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_cmap
Colormap
, default=cm.bwr Colormap used for representing the strength of the edges.
- edge_vmin, edge_vmax
float
, 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_threshold
str
orint
orfloat
, 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_kwargs
dict
, optional Will be passed as kwargs for each edge
Line2D
.- node_kwargs
dict
Will be passed as kwargs to the function
scatter
which plots all the nodes at one.
- adjacency_matrix
- add_markers(marker_coords, marker_color='r', marker_size=30, **kwargs)[source]¶
Add markers to the plot.
- Parameters:
- marker_coords
ndarray
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_size
float
orlist
offloat
of shape(n_markers,)
, default=30 Size in pixel for each marker.
- marker_coords
- 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 and output: neuroimaging data representation. If it is a masked array, only the non-masked part will be plotted.
- threshold
int
orfloat
orNone
, default=1e-6 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.
- cbar_tick_formatstr, default=”%.2g” (scientific notation)
Controls how to format the tick labels of the colorbar. Ex: use “%i” to display as integers.
- colorbar
bool
, default=False If
True
, display a colorbar on the right of the plots.- kwargs
dict
Extra keyword arguments are passed to function
imshow
.- cbar_vmin
float
, optional Minimal value for the colorbar. If None, the minimal value is computed based on the data.
- cbar_vmax
float
, 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_right
bool
, default=True If
True
, annotations indicating which side is left and which side is right are drawn.- positions
bool
, default=True If
True
, annotations indicating the positions of the cuts are drawn.- scalebar
bool
, default=False If
True
, cuts are annotated with a reference scale bar. For finer control of the scale bar, please check out thedraw_scale_bar
method on the axes in “axes” attribute of this object.- size
int
, default=12 The size of the text used.
- scale_size
int
orfloat
, 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_loc
int
, 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”
- decimals
int
, default=0 Number of decimal places on slice position annotation. If zero, the slice position is integer without decimal point.
- kwargs
dict
Extra keyword arguments are passed to matplotlib’s text function.
- left_right
- property black_bg¶
Return black background.
- property brain_color¶
Return brain color.
- 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
- cut_coords3
tuple
ofint
The cut position, in world space.
- axes
matplotlib.axes.Axes
, optional The axes that will be subdivided in 3.
- black_bg
bool
, 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 passfacecolor='k', edgecolor='k'
tomatplotlib.pyplot.savefig
.- brain_color
tuple
, default=(0.5, 0.5, 0.5) The brain color to use as the background color (e.g., for transparent colorbars).
- savefig(filename, dpi=None)[source]¶
Save the figure to a file.
- Parameters:
- filename
str
The file name to save to. Its extension determines the file type, typically ‘.png’, ‘.svg’ or ‘.pdf’.
- dpi
None
or scalar, default=None The resolution in dots per inch.
- filename
- 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:
- text
str
The text of the title.
- x
float
, default=0.01 The horizontal position of the title on the frame in fraction of the frame width.
- y
float
, default=0.99 The vertical position of the title on the frame in fraction of the frame height.
- size
int
, 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.
- alpha
float
, default=1 The alpha value for the background.
- kwargs
Extra keyword arguments are passed to matplotlib’s text function.
- text
Examples using nilearn.plotting.displays.YZProjector
¶
Glass brain plotting in nilearn (all options)