ImagePanel
: A wx.Panel for Image Display¶
The ImagePanel
class supports image display, including gray-scale
and false-color maps or contour plots for 2-D arrays of intensity.
ImagePanel
is derived from a wx.Panel
and so can be
easily included in a wxPython GUI application.
While the image can be customized programmatically, the only interactivity
built in to the ImagePanel
itself is the ability to zoom in and
out. In contrast, an ImageFrame
provides many more ways to
manipulate the displayed image, as will be discussed below.
- class ImagePanel(parent, size=(525, 450), dpi=100, messenger=None, **kws)¶
Create an Image Panel, a
wx.Panel
- Parameters
parent – wx parent object.
size – figure size in pixel.
dpi – dots per inch for figure.
messenger (callable or
None
) – function for accepting output messages.
The size, and dpi arguments are sent to matplotlib’s
Figure
. The messenger should should be a function that accepts text messages from the panel for informational display. The default value is to usesys.stdout.write()
.Extra keyword parameters are sent to the wx.Panel.
The configuration settings for an image (its colormap, smoothing, orientation, and so on) are controlled through configuration attributes.
ImagePanel
methods¶
- display(data, x=None, y=None, style='image', **kws)¶
display a new image from the 2-D numpy array data. If provided, the x and y values will be used as coordinates for the pixels for display purposes.
- clear()¶
clear the image
- update_image(data)¶
update the image with new data. This can be significantly faster than re-displaying the data.
- redraw()¶
redraw the image, as when the configuration attributes have been changed.
ImagePanel
callback attributes¶
An ImagePanel
instance has several callback attributes that can be used to get information from the
image panel.
- data_callback¶
A function that is called with the data and x and y values each time
display()
is called.
- lasso_callback¶
A function that is called with the data and selected points when the cursor is in lasso mode and a new set of points has been selected.
- cursor_callback¶
A function that is called with the x and y position clicked on each left-button event.
ImageFrame
: A wx.Frame for Image Display¶
In addition to providing a top-level window frame holding an
ImagePanel
, an ImageFrame
provides the end-user with many ways to
manipulate the image:
display x, y, intensity coordinates (left-click)
zoom in on a particular region of the plot (left-drag).
change color maps.
flip and rotate image.
select optional smoothing interpolation.
modify intensity scales.
save high-quality plot images (as PNGs), copy to system clipboard, or print.
These options are all available programmatically as well, by setting the configuration attributes and redrawing the image.
- class ImageFrame(parent, size=(550, 450), **kws)¶
Create an Image Frame, a
wx.Frame
. This is a Frame with anImagePanel
and several menus and controls for changing the color table and smoothing options as well as switching the display style between “image” and “contour”.
Image configuration with ImageConfig
¶
To change any of the attributes of the image on an ImagePanel
, you
can set the corresponding attribute of the panel’s conf
. That is,
if you create an ImagePanel
, you can set the colormap with:
import matplotlib.cm as cmap
im_panel = ImagePanel(parent)
im_panel.display(data_array)
# now change colormap:
im_panel.conf.cmap = cmap.cool
im_panel.redraw()
# now rotate the image by 90 degrees (clockwise):
im_panel.conf.rot = True
im_panel.redraw()
# now flip the image (top/bottom), apply log-scaling,
# and apply gaussian interpolation
im_panel.conf.flip_ud = True
im_panel.conf.log_scale = True
im_panel.conf.interp = 'gaussian'
im_panel.redraw()
For a ImageFrame
, you can access this attribute as frame.panel.conf.cmap.
The list of configuration attributes and their meaning are given in the Table of Image Configuration attributes
Table of Image Configuration attributes: All of these are members of the panel.conf object, as shown in the example above.
attribute
type
default
meaning
rot
bool
False
rotate image 90 degrees clockwise
flip_ud
bool
False
flip image top/bottom
flip_lr
bool
False
flip image left/right
log_scale
bool
False
display log(image)
contrast_level
float
0
contrast level (percentage)
cmap
colormap
gray
colormap for intensity scale
cmap_reverse
bool
False
reverse colormap
interp
string
nearest
interpolation, smoothing algorithm
xylims
list
None
xmin, xmax, ymin, ymax for display
cmap_lo
int
0
low intensity percent for colormap mapping
cmap_hi
int
100
high intensity percent for colormap mapping
int_lo
float
None
low intensity when autoscaling is off
int_hi
float
None
high intensity when autoscaling is off
style
string
‘image’
‘image’ or ‘contour’
ncontour_levels
int
10
number of contour levels
contour_levels
list
None
list of contour levels
contour_labels
list
None
list of contour labels
Some notes:
cmap is an instance of a matplotlib colormap.
cmap_lo and cmap_hi set the low and high values for the sliders that compress the colormap, and are on a scale from 0 to 100.
In contrast, int_lo and int_hi set the map intensity values and so can be used to put two different maps on the same intensity intensity scale.
contrast_level can be used to automatically set the int_lo and int_hi values based on the distribution of intensities in the data.