labs.viz_tools.slicers

Module: labs.viz_tools.slicers

Inheritance diagram for nipy.labs.viz_tools.slicers:

The Slicer classes.

The main purpose of these classes is to have auto adjust of axes size to the data with different layout of cuts.

Classes

BaseSlicer

class nipy.labs.viz_tools.slicers.BaseSlicer(cut_coords, axes=None, black_bg=False)

Bases: object

The main purpose of these class is to have auto adjust of axes size to the data with different layout of cuts.

Methods

annotate
contour_map
edge_map
find_cut_coords(map[, mask, ...])	Find the center of the largest activation connect component.
init_with_figure
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.

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

static find_cut_coords(data=None, affine=None, threshold=None, cut_coords=None)

classmethod init_with_figure(data=None, affine=None, threshold=None, cut_coords=None, figure=None, axes=None, black_bg=False, leave_space=False)

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=1, **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.

BaseStackedSlicer

class nipy.labs.viz_tools.slicers.BaseStackedSlicer(cut_coords, axes=None, black_bg=False)

Bases: nipy.labs.viz_tools.slicers.BaseSlicer

A class to create linked axes for plotting stacked 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 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
find_cut_coords(map[, mask, ...])	Find the center of the largest activation connect component.
init_with_figure
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

classmethod find_cut_coords(data=None, affine=None, threshold=None, cut_coords=None)

classmethod init_with_figure(data=None, affine=None, threshold=None, cut_coords=None, figure=None, axes=None, black_bg=False, leave_space=False)

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=1, **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.

CutAxes

class nipy.labs.viz_tools.slicers.CutAxes(ax, direction, coord)

Bases: object

An MPL axis-like object that displays a cut of 3D volumes

Methods

do_cut
draw_cut
draw_left_right
draw_position
get_object_bounds

__init__(ax, direction, coord)

An MPL axis-like object that displays a cut of 3D volumes

Parameters :

ax: a MPL axes instance :

The axes in which the plots will be drawn

direction: {‘x’, ‘y’, ‘z’} :

The directions of the cut

coord: float :

The coordinnate along the direction of the cut

do_cut(map, affine)

Cut the 3D volume into a 2D slice

Parameters :

map: 3D ndarray :

The 3D volume to cut

affine: 4x4 ndarray :

The affine of the volume

draw_cut(cut, data_bounds, bounding_box, type='imshow', **kwargs)

draw_left_right(size, bg_color, **kwargs)

draw_position(size, bg_color, **kwargs)

get_object_bounds()

Return the bounds of the objects on this axes.

OrthoSlicer

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

Bases: nipy.labs.viz_tools.slicers.BaseSlicer

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
find_cut_coords(map[, mask, ...])	Find the center of the largest activation connect component.
init_with_figure
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

static find_cut_coords(data=None, affine=None, threshold=None, cut_coords=None)

classmethod init_with_figure(data=None, affine=None, threshold=None, cut_coords=None, figure=None, axes=None, black_bg=False, leave_space=False)

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=1, **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.

XSlicer

class nipy.labs.viz_tools.slicers.XSlicer(cut_coords, axes=None, black_bg=False)

Bases: nipy.labs.viz_tools.slicers.BaseStackedSlicer

Methods

annotate
contour_map
draw_cross
edge_map
find_cut_coords(map[, mask, ...])	Find the center of the largest activation connect component.
init_with_figure
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

classmethod find_cut_coords(data=None, affine=None, threshold=None, cut_coords=None)

classmethod init_with_figure(data=None, affine=None, threshold=None, cut_coords=None, figure=None, axes=None, black_bg=False, leave_space=False)

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=1, **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.

YSlicer

class nipy.labs.viz_tools.slicers.YSlicer(cut_coords, axes=None, black_bg=False)

Bases: nipy.labs.viz_tools.slicers.BaseStackedSlicer

Methods

annotate
contour_map
draw_cross
edge_map
find_cut_coords(map[, mask, ...])	Find the center of the largest activation connect component.
init_with_figure
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

classmethod find_cut_coords(data=None, affine=None, threshold=None, cut_coords=None)

classmethod init_with_figure(data=None, affine=None, threshold=None, cut_coords=None, figure=None, axes=None, black_bg=False, leave_space=False)

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=1, **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.

ZSlicer

class nipy.labs.viz_tools.slicers.ZSlicer(cut_coords, axes=None, black_bg=False)

Bases: nipy.labs.viz_tools.slicers.BaseStackedSlicer

Methods

annotate
contour_map
draw_cross
edge_map
find_cut_coords(map[, mask, ...])	Find the center of the largest activation connect component.
init_with_figure
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

classmethod find_cut_coords(data=None, affine=None, threshold=None, cut_coords=None)

classmethod init_with_figure(data=None, affine=None, threshold=None, cut_coords=None, figure=None, axes=None, black_bg=False, leave_space=False)

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=1, **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.

Function

nipy.labs.viz_tools.slicers.demo_ortho_slicer()

A small demo of the OrthoSlicer functionality.