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labs.viz_tools.ortho_slicer

Module: labs.viz_tools.ortho_slicer

Inheritance diagram for nipy.labs.viz_tools.ortho_slicer:

OrthoSlicer

class nipy.labs.viz_tools.ortho_slicer.OrthoSlicer(cut_coords, axes=None, black_bg=False)

Bases: object

A class to create 3 linked axes for plotting orthogonal cuts of 3D maps.

Notes

The extent of the different axes are adjusted to fit the data best in the viewing area.

Attributes

axes: dictionnary of axes The 3 axes used to plot each view.
frame_axes: axes The axes framing the whole set of views.

Methods

annotate
contour_map
draw_cross
edge_map
plot_map
title
__init__(cut_coords, axes=None, black_bg=False)

Create 3 linked axes for plotting orthogonal cuts.

Parameters :

cut_coords: 3 tuple of ints :

The cut position, in world space.

axes: matplotlib axes object, optional :

The axes that will be subdivided in 3.

black_bg: boolean, optional :

If True, the background of the figure will be put to black. If you whish to save figures with a black background, you will need to pass “facecolor=’k’, edgecolor=’k’” to pylab’s savefig.

annotate(left_right=True, positions=True, size=12, **kwargs)

Add annotations to the plot.

Parameters :

left_right: boolean, optional :

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

positions: boolean, optional :

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

size: integer, optional :

The size of the text used.

kwargs: :

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

contour_map(map, affine, **kwargs)

Contour a 3D map in all the views.

Parameters :

map: 3D ndarray :

The 3D map to be plotted. If it is a masked array, only the non-masked part will be plotted.

affine: 4x4 ndarray :

The affine matrix giving the transformation from voxel indices to world space.

kwargs: :

Extra keyword arguments are passed to contour.

draw_cross(cut_coords=None, **kwargs)

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

Parameters :

cut_coords: 3-tuple of floats, optional :

The position of the cross to draw. If none is passed, the ortho_slicer’s cut coordinnates are used.

kwargs: :

Extra keyword arguments are passed to axhline

edge_map(map, affine, color='r')

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

Parameters :

map: 3D ndarray :

The 3D map to be plotted. If it is a masked array, only the non-masked part will be plotted.

affine: 4x4 ndarray :

The affine matrix giving the transformation from voxel indices to world space.

color: matplotlib color: string or (r, g, b) value :

The color used to display the edge map

plot_map(map, affine, threshold=None, **kwargs)

Plot a 3D map in all the views.

Parameters :

map: 3D ndarray :

The 3D map to be plotted. If it is a masked array, only the non-masked part will be plotted.

affine: 4x4 ndarray :

The affine matrix giving the transformation from voxel indices to world space.

threshold : a number, None, or ‘auto’

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 are plotted as transparent.

kwargs: :

Extra keyword arguments are passed to imshow.

title(text, x=0.01, y=0.98999999999999999, size=15, color=None, bgcolor=None, alpha=0.90000000000000002, **kwargs)

Write a title to the view.

Parameters :

text: string :

The text of the title

x: float, optional :

The horizontal position of the title on the frame in fraction of the frame width.

y: float, optional :

The vertical position of the title on the frame in fraction of the frame height.

size: integer, optional :

The size of the title text.

color: matplotlib color specifier, optional :

The color of the font of the title.

bgcolor: matplotlib color specifier, optional :

The color of the background of the title.

alpha: float, optional :

The alpha value for the background.

kwargs: :

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

nipy.labs.viz_tools.ortho_slicer.demo_ortho_slicer()

A small demo of the OrthoSlicer functionality.