Well, at least not officially

The following trick restores the docking controls to figures in R2008a-compiled applications, enabling figure docking. Simply add one or both of the following alternatives in your application, after the figure has been created:

% Alternative #1 - uses pure Matlab
set(hFig, 'DockControls', 'on');
 
% Alternative #2 - uses the underlying Java frame
jFrame = get(handle(hFig), 'JavaFrame');
try
   % This works up to R2011a
   jFrame.fFigureClient.setClientDockable(true);
catch
   % This works from R2008b and up
   jFrame.fHG1Client.setClientDockable(true);
end

where hFig is the figure handle. This will have no effect for the regular interpreted (non-compiled) run of the application, where these controls are ‘on’ by default. But in the compiled application, although it may erroneously report that the controls are ‘on’, they are in fact ‘off’, so turning them ‘on’ fixes the problem.

Matlab figure docking control

Note: the two variants in alternative #2 above are actually identical, it is simply that the relevant field name has changed: Up to R2008a, only the fFigureClient existed; in R2008b, the fHG1Client field was added, which was simply an alias for fFigureClient, holding the same reference handle, so either of these fields could be used (a corresponding fHG2Client was also added – more on HG1 and HG2 here). In R2011b (at least the pre-release), the fFigureClient alias field was dropped and only fHG1Client remained. While the field name has changed, the underlying docking functionality appears to have remained stable over all these releases. For the record, in answer to a user question below, these fields can be listed using the built in fieldnames function:

% R2008b - R2011a:
>> fieldnames(jFrame)
ans = 
    'fFigureClient'
    'fHG2Client'
    'fHG1Client'
    'fUseHG2'
    'UICONTROLBACKGROUND_OS'
    'UICONTROLBACKGROUND_COMPATIBLE'

I was reminded of this trick by Aurélien’s recent comment, where he mentions MathWorks so-called workaround for this problem, which (IMHO) is really not a work-around at all: MathWorks advises to modify our application to use – would you believe this – tabbed panels to “dock” the separate figures contents onto separate panels. Not to mention the fact that this so-called “solution” relies on undocumented and unsupported Matlab functionality (that of tabbed-panels) and requires major rework of existing applications, it also results in far inferior look-and-feel than simple docking as G-d intended…

Since I have demonstrated above that the docking functionality actually exists in compiled apps just as in the interpreted m-file apps, I do not understand why MathWorks took such great pains to prevent this important functionality in the compiler. There must be some important reason for this, but I cannot think of any. Perhaps if there is enough public demand, MathWorks will agree to return the docking functionality.

Unfortunately, I recently discovered that in the most recent compiler, that ships with R2011a, alternative #1 above (which uses pure Matlab) no longer works. Sometime between R2008a and R2011a MathWorks discovered my first back-door and closed it. Such a pity…

Luckily, alternative #2 (which uses the underlying Java frame object) seems to still work, even on R2011a.

I still haven’t tested this on R2011b’s compiler (whose pre-release has become available for download yesterday), but hopefully the trick above will continue to work on R2011b and on subsequent releases – please tell me if you find out otherwise.

1. Minimize/maximize figure window Matlab figure windows can easily be maximized, minimized and restored using a bit of undocumented magic powder...
2. FindJObj – find a Matlab component’s underlying Java object The FindJObj utility can be used to access and display the internal components of Matlab controls and containers. This article explains its uses and inner mechanism....
3. Blurred Matlab figure window Matlab figure windows can be blurred using a semi-transparent overlaid window - this article explains how...
4. JMI wrapper – local MatlabControl part 2 An example using matlabcontrol for calling Matlab from within a Java class is explained and discussed...

The problem

Matlab figures can be maximized, minimized and restored by interactively clicking the corresponding icon (or menu item) on the figure window’s frame (the title bar). However, we often need to create maximized main-application windows, and wish to save the users the need to manually maximize the window. Moreover, we may sometimes even wish to prevent users from resizing a maximized main window.

Unfortunately, Matlab does not contain any documented or supported way to programmatically maximize, minimize or restore a figure window.

This is very strange considering the fact that these are such elementary figure operations. Moreover, these operations are supported internally (and have been for many releases already), as shown below. It is therefore difficult for me to understand why they were not added to the documented Matlab HG wrapper functionality a long time ago. I fail to understand why obscure features such as docking were added to the wrapper, but standard minimization and maximization were not.

Maximization

Several solutions have been presented to this problem over the years. Let us start with the pressing question of figure maximization:

Solutions that rely on documented Matlab features tend to compute the available screen size and resize the figure accordingly. The result is lacking in many respects: it does not account for the taskbar (neither in size nor in location, which is not necessarily at the bottom of the screen); it does not remove the window border as in regular maximized figures; and it often ignores extended desktops (i.e. an attached additional monitor).

The solutions that do work properly all rely on undocumented features: Some use platform-specific native Windows API in a mex-file (Jan Simon’s recent WindowAPI submission really pushes the limit in this and other regards). Alternately, we can easily use the platform-independent JavaFrame:

>> jFrame = get(handle(gcf),'JavaFrame')
jFrame =
com.mathworks.hg.peer.FigurePeer@cdbd96
 
>> jFrame.setMaximized(true);   % to maximize the figure
>> jFrame.setMaximized(false);  % to un-maximize the figure

Minimization

To the best of my knowledge, there are no solutions for minimizing figure windows that use documented Matlab features. Again, this can be done using either native Windows API, or the platform-independent JavaFrame:

>> jFrame.setMinimized(true);   % to minimize the figure
>> jFrame.setMinimized(false);  % to un-minimize the figure

Usage notes

Maximized and Minimized are mutually-exclusive, meaning that no more than one of them can be 1 (or true) at any time. This is automatically handled – users only need to be aware that a situation in which a window is both maximized and minimized at the same time is impossible (duh!).

There are several equivalent manners of setting jFrame‘s Maximized and Minimized property values, and your choice may simply be a matter of aesthetics and personal taste:

% Three alternative possibilities of setting Maximized:
jFrame.setMaximized(true);
set(jFrame,'Maximized',true);   % note interchangeable 1< =>true, 0< =>false
jFrame.handle.Maximized = 1;

jFrame follows Java convention: the accessor method that retrieves boolean values is called is<Propname>() instead of get<Propname>. In our case: isMaximized() and isMinimized():

flag = jFrame.isMinimized;        % Note: isMinimized, not getMinimized
flag = get(jFrame,'Minimized');
flag = jFrame.handle.Minimized;

In some old Matlab releases, jFrame did not possess the Maximized and Minimized properties, and their associated accessor methods. In this case, use the internal FrameProxy which has always contained them:

>> jFrameProxy = jFrame.fFigureClient.getWindow() 
jFrameProxy =
com.mathworks.hg.peer.FigureFrameProxy$FigureFrame[fClientProxyFrame,227,25,568x502,invalid,layout=java.awt.BorderLayout,title=Figure 1,resizable,normal,defaultCloseOperation=DO_NOTHING_ON_CLOSE,...]
 
>> % Three alternative possibilities of setting Minimized:
>> jFrameProxy.setMinimized(true);
>> set(jFrameProxy,'Minimized',true);
>> jFrameProxy.handle.Minimized = true;

Using FrameProxy for figure minimization and maximization works correctly on both old and new Matlab releases; using jFrame is slightly simpler but only works on recent Matlab releases. Depending on your needs you may choose to use either of these. They are entirely equivalent.

When either the Maximized or Minimized properties are changed back to false, the window is restored to regular mode, which is the FrameProxy‘s RestoredLocation and RestoredSize.

Use of the JavaFrame property

Note that all this relies on the undocumented hidden figure property JavaFrame, which issues a standing warning (since Matlab release R2008a) of becoming obsolete in some future Matlab release (HG2?):

>> jFrame = get(gcf,'JavaFrame')
Warning: figure JavaFrame property will be obsoleted in a future release.
For more information see the JavaFrame resource on the MathWorks web site.
(Type "warning off MATLAB:HandleGraphics:ObsoletedProperty:JavaFrame" to suppress this warning.) 

jFrame =
com.mathworks.hg.peer.FigurePeer@1ffbad6

To remove the above warning I have used (note the handle wrapper, as suggested by Donn Shull):

jFrame = get(handle(gcf),'JavaFrame')

If and when JavaFrame does become obsolete in some future Matlab version, be sure to look in this blog for workarounds.

You may also wish to inform MathWorks on the dedicated webpage that they have set up for specifically this reason (http://www.mathworks.com/javaframe), how you are using JavaFrame and why it is important for you. This may help them to decide whether to keep JavaFrame or possibly add the functionality using other means.

Do you have a smart use for the figure’s minimization or maximization feature? or another use for JavaFrame? If so, please share your ideas in a comment below.

1. Enable/disable entire figure window Disabling/enabling an entire figure window is impossible with pure Matlab, but is very simple using the underlying Java. This article explains how....
2. Transparent Matlab figure window Matlab figure windows can be made fully or partially transparent/translucent or blurred - this article explains how...
3. Blurred Matlab figure window Matlab figure windows can be blurred using a semi-transparent overlaid window - this article explains how...
4. Detecting window focus events Matlab does not have any documented method to detect window focus events (gain/loss). This article describes an undocumented way to detect such events....

The basic idea

The basic idea, as reader Mory pointed out in a comment, is to overlay a semi-transparent empty figure window, having just the right size and position, on top of the main (disabled) figure window:

+ =

Main (unblurred) window + semi-transparent window = blurred window effect

In addition to ensuring the correct figure size and position, there are several other things we should care for: We need to synchronize the figure/blurring color, menubar/toolbar, and title. We also need to handle docking, resizing and figure movement. Finally we need to connect the two figures so that whenever one is closed then so is the other.

blurFigure

My blurFigure utility on the Matlab File Exchange attempts to handle all these setups for the user. The utility is quite simple to use:

blurFigure(hFig) blurs figure hFig and prevents interaction with it. The only interaction possible is with user-created controls on the blurring panel (see below).

hFigBlur = blurFigure(hFig) returns the overlaid blurred figure pane. This is useful to present a progress bar or other GUI controls, for user interaction during the blur phase (see the demo below).

blurFigure(hFig,STATE) sets the blur status of figure hFig to STATE, where state is ‘on’,'off’,true or false (default=’on’/true). blurFigure(hFig,’on’) or blurFigure(hFig,true) is the same as: blurFigure(hFig); blurFigure(hFig,’off’) or blurFigure(hFig,false) is the same as: close(hFigBlur).

blurFigure(‘demo’) displays a simple demo of the blurring. In fact, this runs the following simple code:

% Create the main (blurred) figure window
hFigMain = figure;
 
% Display some GUI controls in the main window
try oldWarn = warning('off','MATLAB:uitree:MigratingFunction'); catch, end
hTree = uitree('root','c:\');
drawnow;
try hTree.getTree.expandRow(0); catch, end
try warning(oldWarn); catch, end
uicontrol('string','click me!', 'units','pixel', 'pos',[300,50,100,20]);
axes('parent',gcf, 'units','pixel', 'pos',[230,100,300,300]);
surf(peaks);
set(gcf,'ToolBar','figure');  % restore the toolbar that was removed by the uicontrol() call above
 
% Call blurFigure() to add a semi-transparent overlaid window
hFigBlurTemp = blurFigure(hFigMain);
 
% Add some non-blurred controls on top of the blur
uicontrol('parent',hFigBlurTemp, 'style','text', 'units','pixel', 'pos',[130,85,390,80], ...
          'string','Processing - please wait...', 'FontSize',12, 'FontWeight','bold','Fore','red','Back','yellow');
jProgressBar = javacomponent('javax.swing.JProgressBar', [180,115,310,20], hFigBlurTemp);
jProgressBar.setValue(67);
uicontrol('parent',hFigBlurTemp, 'string','Cancel', 'pos',[280,90,100,20], 'Callback','close(gcbf)');

Non-blurred controls displayed over a blurred figure window

Do you have some other interesting uses for window transparency in Matlab? If so, please share your thought in a comment.

1. Transparent Matlab figure window Matlab figure windows can be made fully or partially transparent/translucent or blurred - this article explains how...
2. Minimize/maximize figure window Matlab figure windows can easily be maximized, minimized and restored using a bit of undocumented magic powder...
3. Enable/disable entire figure window Disabling/enabling an entire figure window is impossible with pure Matlab, but is very simple using the underlying Java. This article explains how....
4. Detecting window focus events Matlab does not have any documented method to detect window focus events (gain/loss). This article describes an undocumented way to detect such events....

Matlab figure window transparency

Following an idea I got from Malcolm Lidierth’s MUtilities submission on the Matlab File Exchange, the solution for setting Matlab figure window transparency is quite simple: Get the figure’s underlying Java window reference handle, as in last week’s article. Then use Java’s setWindowOpacity method to set the window’s transparency value. Actually, setWindowOpacity sets the opacity level, rather than transparency, but they are obviously complementary and I personally find “transparency” to be more easily understandable.

By default, windows are created with an opacity of 1.0 (= not transparent). They can be set to any floating-point value between 0.0-1.0, where an opacity of 0.0 means full transparency, and any value in between means partial transparency (i.e., translucency):

jFigPeer = get(handle(gcf),'JavaFrame');
jWindow = jFigPeer.fFigureClient.getWindow;
com.sun.awt.AWTUtilities.setWindowOpacity(jWindow,0.7)

Semi-transparent (translucent) Matlab figure (click to enlarge)

Similarly, you can set the entire Matlab Desktop’s transparency/opacity value:

jDesktop = com.mathworks.mde.desk.MLDesktop.getInstance.getMainFrame;
com.sun.awt.AWTUtilities.setWindowOpacity(jDesktop, 0.8);

Note that the com.sun.awt.AWTUtilities class also enables other GUI effects that would make a Matlab GUI developer’s mouth to start drooling: shaped windows, per-pixel transparency values, mirroring/reflection, window shadows, gradients etc. Perhaps I’ll explore their adaptation for Matlab figures someday.

Fade-in / fade-out

Window fade-in/fade-out effects can easily be achieved using transparency: Simply invoke the setWindowOpacity method several times, with progressively higher or lower values. This is easily done in a simple blocking loop. For example, to fade-out a window:

for stepIdx = 1 : 5
   newAlpha = 1.0 - 0.2*stepIdx;
   com.sun.awt.AWTUtilities.setWindowOpacity(jWindow,newAlpha);
   jWindow.repaint;
   pause(0.2);  % seconds
end

Gradual window fade-out

A more general example dynamically computes the opacity step size/duration and also enables non-blocking fade effects using an asynchronous timer:

% Compute the required opacity-setting steps
fadeDuration = 1.5;  % seconds
oldAlpha = com.sun.awt.AWTUtilities.getWindowOpacity(jWindow);
newAlpha = 0.0;
deltaAlpha = newAlpha - oldAlpha;
maxStepAlpha = 0.03;
steps = fix(abs(deltaAlpha) / maxStepAlpha) + 1;
stepAlpha = deltaAlpha / steps;
stepDuration = fadeDuration / (steps-1);
 
% If blocking, do the fade effect immediately
if blockingFlag || steps==1
   for stepIdx = 1 : steps
      newAlpha = oldAlpha + stepAlpha*stepIdx;
      com.sun.awt.AWTUtilities.setWindowOpacity(jWindow,newAlpha);
      jWindow.repaint;
      if stepIdx < steps,  pause(stepDuration);  end
   end
else
   % non-blocking: fade in/out asynchronously using a dedicated timer
   start(timer('ExecutionMode','fixedRate', 'Period',0.1, 'TasksToExecute',steps, ...
               'TimerFcn', {@timerFcn,jWindow,oldAlpha,stepAlpha}));
end
 
% Timer function for non-blocking fade-in/fade-out effect
function timerFcn(hTimer,eventData,jFrame,currentAlpha,stepAlpha)  %#ok<INUSL> eventData
  stepIdx = hTimer.TasksExecuted;
  newAlpha = currentAlpha + stepAlpha*stepIdx;
  com.sun.awt.AWTUtilities.setWindowOpacity(jFrame,newAlpha);
  jFrame.repaint;
  if stepIdx == hTimer.TasksToExecute
      stop(hTimer);
      delete(hTimer);
  end
end  % timerFcn

Of course, you can also fade-in/out to intermediate values such as 0.3 or 0.8. If you fade-out completely (i.e., to a value of 0.0), it might be a good idea to actually close the figure window once it gets the totally-transparent value of 0.0.

I’ve prepared a Matlab utility that contains all these options, including optional blocking/non-blocking fade effects, in my setFigTransparency utility, which is available for download on the Matlab File Exchange. You may also wish to use Malcolm Lidierth’s MUtilities, which also has similar functionalities (plus some other goodies).

Limitations

Setting a figure window’s transparency requires using Java Run-time Engine (JRE) 1.6.0_10 (also called “Java 6 update 10″) or higher. This means that it’s supported on Matlab release 7.9 (R2009b) and higher by default, and on earlier releases using a JRE retrofit.

If you are using an earlier Matlab release, consider a retrofit of JRE 1.6.0_10 or any later version (e.g., the latest available version today is 1.6 update 24). The JRE can be downloaded from here, and you can configure Matlab to use it according to the instructions here. As noted, Matlab R2009b (7.9) and onward, at least on Microsoft Windows, pre-bundle a JRE version that does support transparency/opacity and so do not require a retrofit.

You can check your current Java version in Matlab as follows:

>> version -java
ans =
Java 1.6.0_17-b04 with Sun Microsystems Inc. Java HotSpot(TM) Client VM mixed mode

Unfortunately, Matlab plot axes cannot be made transparent. If you have any axes in your GUI, the axes area will simply appear as a shaded axes, whose intensity depends on the selected alpha (transparency) value; the contents beneath the window will not be merged in the axes area as it is in the non-axes areas.

Finally, note that com.sun.awt.AWTUtilities is itself an undocumented Java class. It is bundled with the standard Java release since 2008 (1.6.0_10), and yet is not part of the official release because its API has not yet settled. In fact, in the upcoming Java 7 release, which is expected in a few months, and which I expect to be available in Matlab sometime in 2012, the set of transparency/opacity methods have migrated to the fully-documented java.awt.Window class.

Blurred figure window

So here’s a riddle for you: using figure window transparency, can you guess how to make a Matlab figure appear blurred for disabled figures (see the screenshot there)? There are several possible ways to do this – can you find the simplest? The first one to post a comment with a correct answer gets a smiley… My answer will appear in next week’s article.

Upgraded website

Also, did you notice my new website design? It’s supposed to be much more readable (yes – also on Android…). It now also runs on a multi-server cloud, which means more stability and faster response times. Do you like the new design? hate it? I would love to hear your feedback via comment or email.

1. Blurred Matlab figure window Matlab figure windows can be blurred using a semi-transparent overlaid window - this article explains how...
2. Minimize/maximize figure window Matlab figure windows can easily be maximized, minimized and restored using a bit of undocumented magic powder...
3. Enable/disable entire figure window Disabling/enabling an entire figure window is impossible with pure Matlab, but is very simple using the underlying Java. This article explains how....
4. Detecting window focus events Matlab does not have any documented method to detect window focus events (gain/loss). This article describes an undocumented way to detect such events....

Uiwait and uiresume

We start with a short review of the supported mechanism: We can use the built-in uiwait function to suspend Matlab processing until either the specified handle (typically a figure handle) is deleted/closed, a user callback programmatically calls uiresume, or Ctrl-C is pressed. A short example, adapted from uiwait‘s help section (the official help section has a bug, so if anyone reads this at TMW, please fix):

h = uicontrol('Position', [20 20 200 40], 'String', 'Continue', 'Callback', 'uiresume(gcbf)');
f = gcf;
disp('This will print immediately');
uiwait(f); 
disp('This will print after you click Continue or close the window');
 
% Close the figure (use try-catch in case f is already closed)
try close(f); catch, end

Unfortunately, the side effect is that uiwait blocks the regular (non-callback’ed) processing until the lock is released. This is great for simple cases where we require a user to respond to a popup window (e.g., message-box or input dialog) before being allowed to proceed. In more complex situations we may wish to suspend interaction on certain figure windows while continuing to process Matlab functionality – this is impossible to do using uiwait.

Matlab does not have any documented way to disable an entire figure window. You can set the figure’s WindowStyle property to ‘modal’ but this is not the same: (1) it removes the toolbar and menu-bar (2) it still enables interaction with all the figure’s GUI controls and (3) it prevents access to any other Matlab window or desktop until the modal figure is closed. This is certainly NOT what we need.

Of course, we could always loop over all the relevant GUI handles and set their Enable property to ‘inactive’ or ‘off’. But this is tedious, lengthy, and in complex GUIs that have multiple layers of nested panels, it also requires careful recursive programming. We also need to take care to disable hidden handles, toolbars, menu-bars, context-menus, Java components – all these have different ways of being accessed and disabled. And once we uiresume from the lock, we need to remember each handle’s pre-uiwait state, so that if it was disabled before the call to uiwait, it will remain so after uiresume. In short, this is not a trivial exercise at all.

Uisuspend and uirestore

To complicate things, the fully-documented and supported uiwait and uiresume functions have the semi-documented unsupported built-in counterparts uisuspend and uirestore, which are very similar in functionality and name. It is important not to confuse between these two function sets, and most importantly, not to confuse between uiresume and uirestore after using their counterparts earlier in the code – odd things might happen if you do…

Hopefully, in a nearby Matlab release these inconsistencies between the two function sets will disappear and they will be merged, because the current situation is prone to errors and confusion. For backward compatibility considerations, I hope that uisuspend and uirestore would not be discontinued but rather be modified to simply call uiwait and uiresume.

Note that in Matlab releases up to R2010b, uirestore had a minor bug in that it overwrites the figure’s WindowScrollWheelFcn callback with the WindowKeyPressFcn value. This bug was finally fixed in R2011a.

How to enable/disable a figure window

So going back to the main question, we want to find a way to disable an entire figure window, in one simple stroke, and without blocking the Matlab processing.

As usual, we turn to Java and the solution is trivially simple:

First, get the figure window’s underlying Java reference. Note that we need the top-level container reference, rather than the proxy peer handle returned by the JavaFrame hidden property:

>> jFigPeer = get(handle(gcf),'JavaFrame')
jFigPeer =
com.mathworks.hg.peer.FigurePeer@1ffbad6
 
>> jWindow = jFigPeer.fFigureClient.getWindow
ans =
com.mathworks.hg.peer.FigureFrameProxy$FigureFrame[...]

Now remember that all Java GUI components (on which Matlab GUI is based) contain an Enabled property. So, simply set this property on the jWindow reference to true or false:

jWindow.setEnabled(false);  % or true
 
% an equivalent alternative
set(handle(jWindow),'Enabled',false)  % or true

By the way, if you only need to disable the figure’s content area (i.e., not the toolbar and menu bar), simply use a different reference handle:

jFigPeer.getFigurePanelContainer.setEnabled(false);  % or true

Notes:

• While the window looks the same when it is disabled, in reality none of its GUI elements can be clicked or activated (try it!). If you also want the figure to appear blurred you could try using something like a JXLayer semi-translucent glass pane.
• The Java components’ property is called Enabled, not Enable as in pure-Matlab Handle-Graphics controls. Also, the Java property expects true/false (or 0/1), rather than Matlab’s ‘on’/'off’ (there are some fine details here that are release-specific so I will skip them)
• For docked windows the top-level window is the figure’s group container window or the desktop window, which we do not want to disable. Detecting this is easy (check whether the figure’s WindowStyle is ‘docked’), and in such cases simply disable/enable the figure’s content area as shown above.

Use of the JavaFrame property

Note that all this relies on the undocumented hidden figure property JavaFrame, which issues a standing warning (since Matlab release R2008a) of becoming obsolete in some future Matlab release (HG2?):

>> jFigPeer = get(gcf,'JavaFrame')
Warning: figure JavaFrame property will be obsoleted in a future release.
For more information see the JavaFrame resource on the MathWorks web site.
(Type "warning off MATLAB:HandleGraphics:ObsoletedProperty:JavaFrame"
to suppress this warning.) 

jFigPeer =
com.mathworks.hg.peer.FigurePeer@1ffbad6

To remove the above warning I have used (note the handle wrapper, as suggested by Donn Shull):

jFigPeer = get(handle(gcf),'JavaFrame')

If and when JavaFrame does become obsolete in some future Matlab version, be sure to look in this blog for workarounds.

You may also wish to inform MathWorks on the dedicated webpage that they have set up for specifically this reason (http://www.mathworks.com/javaframe), how you are using JavaFrame and why it is important for you. This may help them to decide whether to keep JavaFrame or possibly add the functionality using other means.

The enableDisableFig utility

In 2007, I created the enableDisableFig utility that wraps the above code in an easy-to-use Matlab utility that I have uploaded to the File Exchange.

enableDisableFig returns the current state of the specified figure handle (or gcf if no handle is specified), and optionally sets the figure’s enabled/disabled state to a new value (‘on’,'off’, true or false):

>> oldState = enableDisableFig(gcf, 'on')
oldState =
on
 
>> enableDisableFig(oldState);
>> enableDisableFig(true);  % an alternative

enableDisableFig also provides some sanity checks and error handling that should always appear in any real-world application. In this blog I generally tend to provide only bare-bones code snippets (as above). But in any respected application we must check the validity of input arguments and return values, catch run-time errors, compensate for incompatibilities with older Matlab release and so on. Take a look at enableDisableFig‘s source code to see how I have done this.

Visual aid

When any GUI control is disabled, the accepted convention is to shade it in a gray color as a visual aid to the user that the control is currently disabled. This is automatically done by Matlab when any control’s Enable property is set to ‘off’. In our case, it would be very helpful to display a similar blurring effect for the disabled figure window.

Would you be very surprised if I told you that this is impossible to do with regular Matlab, but trivially easy to achieve using a tiny bit of Java magic powder? I’ll expand on this in my next post, but here’s something to keep you waiting:

A blurred disabled figure

Server upgrade

This weekend (9-10 April, 2011) I plan to upgrade the website. This will entail moving to a different webserver, database, upgraded blogging application, new design etc. This site may be down or “goofy” for quite a few hours. Hopefully all will be back to normal by Monday and I hope you will like the new design.

1. Minimize/maximize figure window Matlab figure windows can easily be maximized, minimized and restored using a bit of undocumented magic powder...
2. Transparent Matlab figure window Matlab figure windows can be made fully or partially transparent/translucent or blurred - this article explains how...
3. Blurred Matlab figure window Matlab figure windows can be blurred using a semi-transparent overlaid window - this article explains how...
4. Detecting window focus events Matlab does not have any documented method to detect window focus events (gain/loss). This article describes an undocumented way to detect such events....

The need: load a FIG without displaying it

In data-processing applications, we often present data in graphs that can then be manipulated and saved for later use. In Matlab, saving is done interactively (via the figure’s File/Save menu option or via the figure’s Save toolbar button), or programmatically (via the hgsave function). In all cases, the data is stored in a *.FIG file (the FIG extension can actually be changed, but I really don’t see why).

The point is that in order to re-load the stored data, we need to use hgload, which has a nasty side-effect of actually displaying the stored figure.

This is bad in terms of performance and memory, especially for heavily-laden GUI figures, not to mention the fact that sometimes we do not want to display the GUI at all. We often just need to extract a sub-set of the stored information (for example, the plot values), without having to display the figure.

The answer: FIGs are simply MATs in disguise

Here’s where the undocumented stuff enters:

It seems that a FIG file is simply a hierarchical structure of all the non-default properties of the stored figure and its descendant handles, all this stored within a simple MAT file.

This is hinted in several places, for example in hgsave‘s doc page, and in the MAT-file preferences panel:

MAT-file preferences (note the FIG clarification)

Knowing this, we can easily load the data, without displaying the figure, by using load(filename,’-mat’) rather than hgload. For example:

% Create and store a simple plot figure
>> figure('Name','Test #1');
>> plot(1:9, sqrt(1:9));
>> hgsave(gcf,'testFig');
 
% Load the figure data
>> d = load('testFig.fig','-mat')
d = 
    hgS_070000: [1x1 struct]   % a Matlab 7 figure
 
% Investigate the figure data
>> d.hgS_070000
ans = 
          type: 'figure'
        handle: 1
    properties: [1x1 struct]
      children: [1x1 struct]
       special: []
 
>> d.hgS_070000.children
ans = 
          type: 'axes'
        handle: 176.08251953125
    properties: [1x1 struct]
      children: [1x1 struct]
       special: [4x1 double]
 
>> d.hgS_070000.children.children
ans = 
          type: 'graph2d.lineseries'
        handle: 177.0830078125
    properties: [1x1 struct]
      children: []
       special: []
 
>> d.hgS_070000.children.children.properties
ans = 
              Color: [0 0 1]
              XData: [1 2 3 4 5 6 7 8 9]
              YData: [1 1.4142 1.7321 2 2.2361 2.4495 2.6458 2.8284 3]
    ApplicationData: [1x1 struct]
        XDataJitter: 0
          XDataMode: 'manual'
      ObeyXDataMode: 'auto'
                ...
 
% Extract plot data
>> YData = d.hgS_070000.children.children.properties.YData
YData =
  1.0000  1.4142  1.7321  2.0000  2.2361  2.4495  2.6458  2.8284  3.0000

We see a couple of interesting things in this simple example:

First, note that the top-level structure node is called “hgS_070000″ – we’ll dig into this next week. Basically, it indicates that the structure holds a Matlab 7 figure.

Secondly, we see hidden/undocumented properties of the stored objects (for example, the lineseries’ XDataJitter and ObeyXDataMode properties). ApplicationData is such a hidden handle, which is widely used as a substitute for any handle’s UserData property (the built-in setappdata and getappdata functions are simply wrappers for accessing this property using standard set and get functions).

Have you used the FIG/MAT feature for any useful functionality? If so, please do share your experience in a comment.

Next week, I will explain how looking under hgsave‘s hood leads to useful functions and to an interesting insight about Matlab’s future. Merry Christmas everybody!

1. Reading non-Latin text files A workaround that enables reading non-Latin text files in Matlab is shown...
2. Plot LimInclude properties The plot objects' XLimInclude, YLimInclude, ZLimInclude, ALimInclude and CLimInclude properties are an important feature, that has both functional and performance implications....
3. getundoc – get undocumented object properties getundoc is a very simple utility that displays the hidden (undocumented) properties of a specified handle object....
4. Modifying default toolbar/menubar actions The default Matlab figure toolbar and menu actions can easily be modified using simple pure-Matlab code. This article explains how....

Callback functionality

Both uisplittool and uitogglesplittool have a Callback property, in addition to the standard ClickedCallback property that is available in uipushtools and uitoggletools.

The standard ClickedCallback is invoked when the main button is clicked, while Callback is invoked when the narrow arrow button is clicked. uitogglesplittool, like uitoggletool, also has settable OnCallback and OffCallback callback properties.

The accepted convention is that ClickedCallback should invoke the default control action (in our case, an Undo/Redo of the topmost uiundo action stack), while Callback should display a drop-down of selectable actions.

While this can be done programmatically using the Callback property, this functionality is already pre-built into uisplittool and uitogglesplittool for our benefit. To access it, we need to get the control’s underlying Java component.

Accessing the underlying Java component is normally done using the findjobj utility, but in this case we have a shortcut: the control handle’s hidden JavaContainer property that holds the underlying com.mathworks.hg.peer.SplitButtonPeer (or .ToggleSplitButtonPeer) Java reference handle. This Java object’s MenuComponent property returns a reference to the control’s drop-down sub-component (which is a com.mathworks.mwswing.MJPopupMenu object):

>> jUndo = get(hUndo,'JavaContainer')
jUndo =
com.mathworks.hg.peer.SplitButtonPeer@f09ad5
 
>> jMenu = get(jUndo,'MenuComponent')  % or: =jUndo.getMenuComponent
jMenu =
com.mathworks.mwswing.MJPopupMenu[Dropdown Picker ButtonMenu,...]

Let’s add a few simple textual options:

jOption1 = jMenu.add('Option #1');
jOption1 = jMenu.add('Option #2');
set(jOption1, 'ActionPerformedCallback', 'disp(''option #1'')');
set(jOption2, 'ActionPerformedCallback', {@myCallbackFcn, extraData});

setting uisplittool & uitogglesplittool popup-menus

Popup-menus are described in more detail elsewhere (and in future articles). In the past I have already explained how icons and HTML markup can be added to menu items. Sub-menus can also be added.

A complete example

Let’s now use this information, together with last year’s set of articles about Matlab’s undocumented uiundo functionality, to generate a complete and more realistic example, of undo/redo toolbar buttons.

Undo and redo are actions that are particularly suited for uisplittool, since its main button enables us to easily undo/redo the latest action (like a simple toolbar button, by clicking the main uisplittool button) as well as select items from the actions drop-down (like a combo-box, by clicking the attached arrow button) – all this using a single component.

% Display our GUI
hEditbox = uicontrol('style','edit', 'position',[20,60,40,40]); 
set(hEditbox, 'Enable','off', 'string','0');
hSlider = uicontrol('style','slider','userdata',hEditbox);
set(hSlider,'Callback',@test_uiundo);  
 
% Display the figure toolbar that was hidden by the uicontrol function
set(gcf,'Toolbar','figure');
 
% Add the Undo/Redo buttons
hToolbar = findall(gcf,'tag','FigureToolBar');
hUndo = uisplittool('parent',hToolbar);
hRedo = uitogglesplittool('parent',hToolbar);
 
% Load the Redo icon
icon = fullfile(matlabroot,'/toolbox/matlab/icons/greenarrowicon.gif');
[cdata,map] = imread(icon);
 
% Convert white pixels into a transparent background
map(find(map(:,1)+map(:,2)+map(:,3)==3)) = NaN;
 
% Convert into 3D RGB-space
cdataRedo = ind2rgb(cdata,map);
cdataUndo = cdataRedo(:,[16:-1:1],:);
 
% Add the icon (and its mirror image = undo) to latest toolbar
set(hUndo, 'cdata',cdataUndo, 'tooltip','undo','Separator','on', ...
           'ClickedCallback','uiundo(gcbf,''execUndo'')');
set(hRedo, 'cdata',cdataRedo, 'tooltip','redo', ...
           'ClickedCallback','uiundo(gcbf,''execRedo'')');
 
% Re-arrange the Undo/Redo buttons  
jToolbar = get(get(hToolbar,'JavaContainer'),'ComponentPeer');
jButtons = jToolbar.getComponents;
for buttonIdx = length(jButtons)-3 : -1 : 7  % end-to-front
   jToolbar.setComponentZOrder(jButtons(buttonIdx), buttonIdx+1);
end
jToolbar.setComponentZOrder(jButtons(end-2), 5);    % Separator
jToolbar.setComponentZOrder(jButtons(end-1), 6);    % Undo
jToolbar.setComponentZOrder(jButtons(end), 7);      % Redo
jToolbar.revalidate;
 
% Retrieve redo/undo object
undoObj = getappdata(gcf,'uitools_FigureToolManager');
if isempty(undoObj)
   undoObj = uitools.FigureToolManager(gcf);
   setappdata(gcf,'uitools_FigureToolManager',undoObj);
end
 
% Populate Undo actions drop-down list
jUndo = get(hUndo,'JavaContainer');
jMenu = get(jUndo,'MenuComponent');
undoActions = get(undoObj.CommandManager.UndoStack,'Name');
jMenu.removeAll;
for actionIdx = length(undoActions) : -1 : 1    % end-to-front
    jActionItem = jMenu.add(undoActions(actionIdx));
    set(jActionItem, 'ActionPerformedCallback', @myUndoCallbackFcn);
end
jToolbar.revalidate;
 
% Drop-down callback function
function myUndoCallbackFcn(jActionItem,hEvent)
    % user processing needs to be placed here
end  % myUndoCallbackFcn

undo/redo buttons implemented using uisplittool

In a real-world application, the code-segment above that populated the drop-down list would be placed within the slider’s test_uiundo() callback function, and we would set a similar drop-down for the hRedu button. In addition, we would dynamically modify the button tooltips. As a final customization, we could modify the figure’s main menu. Menu customization will be discussed in a future separate set of articles.

Have you used uisplittool or uitogglesplittool in your GUI? If so, please tell us what use you have made of them, in a comment below.

1. uisplittool & uitogglesplittool Matlab's undocumented uisplittool and uitogglesplittool are powerful controls that can easily be added to Matlab toolbars - this article explains how...
2. Matlab callbacks for Java events Events raised in Java code can be caught and handled in Matlab callback functions - this article explains how...
3. Uicontrol callbacks This post details undocumented callbacks exposed by the underlying Java object of Matlab uicontrols, that can be used to modify the control's behavior in a multitude of different events...
4. Figure toolbar components Matlab's toolbars can be customized using a combination of undocumented Matlab and Java hacks. This article describes how to access existing toolbar icons and how to add non-button toolbar components....

>> which uisplittool
built-in (C:\Matlab\R2010b\toolbox\matlab\uitools\uisplittool)

These uitools are entirely undocumented, even today (R2010b). They puzzled me for a very long time. An acute reader (Jeremy Raymonds) suggested they are related to toolbars, like other uitools such as the uipushtool and uitoggletool. This turned out to be the missing clue that unveiled these useful tools:

So what are uisplittool and uitogglesplittool?

Both uisplittool and uitogglesplittool are basic Handle-Graphics building blocks used in Matlab toolbars, similarly to the well-documented uipushtool and uitoggletool.

uisplittool presents a simple drop-down, whereas uitogglesplittool presents a drop-down that is also selectable.

The Publish and Run controls on the Matlab Editor’s toolbar are examples of uisplittool, and so are the Brush / Select-Data control on the figure toolbar, and the plot-selection drop-down on the Matlab Desktop’s Workspace toolbar:

uisplittool in action in the Matlab Desktop

Adding uisplittool and uitogglesplittool to a toolbar

Adding a uisplittool and uitogglesplittool to a toolbar is done in a similar manner to adding uipushtools and uitoggletools:

hToolbar = findall(gcf,'tag','FigureToolBar');
hUndo=uisplittool('parent',hToolbar);       % uisplittool
hRedo=uitogglesplittool('parent',hToolbar); % uitogglesplittool

Like uipushtool and uitoggletool, uisplittool and uitogglesplittool also have unique Type property values, ‘uisplittool’ and ‘uitogglesplittool’ respectively. The handles can also be tested using the built-in isa function:

>> isa(handle(hUndo),'uisplittool')   % or: 'uitogglesplittool'
ans =
     1
>> class(handle(hUndo))
ans =
uisplittool

Just as with uipushtools and uitoggletools, the new buttons have an empty button-face appearance, until we fix their CData, Tooltip and similar settable properties:

% Load the Redo icon
icon = fullfile(matlabroot,'/toolbox/matlab/icons/greenarrowicon.gif');
[cdata,map] = imread(icon);
 
% Convert white pixels into a transparent background
map(find(map(:,1)+map(:,2)+map(:,3)==3)) = NaN;
 
% Convert into 3D RGB-space
cdataRedo = ind2rgb(cdata,map);
cdataUndo = cdataRedo(:,[16:-1:1],:);
 
% Add the icon (and its mirror image = undo) to latest toolbar
set(hUndo, 'cdata',cdataUndo, 'tooltip','undo','Separator','on', ...
           'ClickedCallback','uiundo(gcbf,''execUndo'')');
set(hRedo, 'cdata',cdataRedo, 'tooltip','redo', ...
           'ClickedCallback','uiundo(gcbf,''execRedo'')');

User-created uisplittool & uitogglesplittool toolbar buttons

Note that the controls can be created with these properties in a single command:

hUndo = uisplittool('parent',hToolbar, 'cdata',cdataRedo, ...);

Re-arranging the toolbar controls placement

Let us now re-arrange our toolbar buttons. Unfortunately, a bug causes uisplittools and uitogglesplittools to always be placed flush-left when the toolbar’s children are re-arranged (anyone at TMW reading this in time for the R2011a bug-parade selection?).

So, we can’t re-arrange the buttons at the HG-children level. Luckily, we can re-arrange directly at the Java level (note that until now, the entire discussion of uisplittool and uitogglesplittool was purely Matlab-based):

jToolbar = get(get(hToolbar,'JavaContainer'),'ComponentPeer');
jButtons = jToolbar.getComponents;
for buttonId = length(jButtons)-3 : -1 : 7  % end-to-front
   jToolbar.setComponentZOrder(jButtons(buttonId), buttonId+1);
end
jToolbar.setComponentZOrder(jButtons(end-2), 5);   % Separator
jToolbar.setComponentZOrder(jButtons(end-1), 6);   % Undo
jToolbar.setComponentZOrder(jButtons(end), 7);     % Redo
jToolbar.revalidate;

Re-arranged uisplittool & uitogglesplittool toolbar buttons
(not as simple as it may sound)

Next week, I will combine the information in this article, with last year’s articles about uiundo, and show how we can create a dynamic figure toolbar drop-down of undo/redo events. Here is a preview to whet your appetite:

undo/redo buttons implemented using uisplittool

1. uisplittool & uitogglesplittool callbacks Matlab's undocumented uisplittool and uitogglesplittool are powerful toolbar controls - this article explains how to customize their behavior...
2. Figure toolbar components Matlab's toolbars can be customized using a combination of undocumented Matlab and Java hacks. This article describes how to access existing toolbar icons and how to add non-button toolbar components....
3. uiundo – Matlab’s undocumented undo/redo manager The built-in uiundo function provides easy yet undocumented access to Matlab's powerful undo/redo functionality. This article explains its usage....
4. Customizing uiundo This article describes how Matlab's undocumented uiundo undo/redo manager can be customized...

Saving brushed data to a variable

The said reader has specifically wanted programmatic access, rather than interactivity. The official answer is that data brushing was designed to be an interactive tool, and so this cannot be done. However, this has never stopped us before. So off I went to launch my favorite inspection tool, the UIInspect utility on the figure above (UIInspect will be described in a near-future article), which can be recreated with the following simple code:

t=0:0.2:25; plot(t,sin(t),'.-');
% Now brush some data points...
uiinspect(gca);

UIInspect-ion of a data-brushed plot (click for details)

A couple of alternative answers to the reader’s question were immediately apparent:

Directly accessing brushed data

First, we notice that data brushing added data-brushing context menus, both of which are called BrushSeriesContextMenu (the duplication is an internal Matlab bug, that does not affect usability as far as I can tell).

Also, an invisible scribe overlay axes has been added to hold the new annotations (data brushing is considered an annotation; scribe axes deserve a separate article, which they will indeed get someday).

More importantly for our needs, we see a new line item called ‘Brushing’, which displays the red lines and data points that we seek. We can now easily get the brushed data using this line’s XData and YData properties: non-brushed data points simply have NaN values:

UIInspect-ion of the data-brushing line

hBrushLine = findall(gca,'tag','Brushing');
brushedData = get(hBrushLine, {'Xdata','Ydata'});
brushedIdx = ~isnan(brushedData{1});
brushedXData = brushedData{1}(brushedIdx);
brushedYData = brushedData{2}(brushedIdx);
% and similarly for ZData in 3D plots

Accessing brushing callbacks

Yet another way of approaching the problem is to use the available callback functions built-into the data-brushing functionality. We can access either the BrushSeriesContextMenu or the figure’s Tools/Brushing menu. I will leave the former (context-menu) approach as an exercise to the reader, and just describe the figure’s menu approach.

As I have already explained in a dedicated article, figure menu-bar actions are accessible via their handles, and we can retrieve that using a unique tag (well, most of the time – read that article for details). In our case, the Tools/Brushing/Create-new-variable menu item has the unique tag ‘figDataManagerNewVar’. So let’s use it:

>> hNewVarMenuItem = findall(gcf,'tag','figDataManagerNewVar')
hNewVarMenuItem =
          742.000244140625
 
>> hNewVarCallback = get(hNewVarMenuItem,'callback')
hNewVarCallback = 
    @datamanager.newvar
 
>> hNewVarCallback(gcf)   % activate the callback
% => set 'ans' as the new variable holding the brushed data
 
>> ans
ans =
                       6.4         0.116549204850494
                       6.6         0.311541363513379
                       6.8         0.494113351138609
                         7         0.656986598718789
                       7.2         0.793667863849153
                       7.4         0.898708095811627
                       7.6         0.967919672031486
                       7.8         0.998543345374605
                       ...         ...

Of course, we could also have gone the hard way, via the scribe axes and the annotations route. For masochistic people like me it could even be a worthwhile challenge. But for all other normal people, why bother when there are such simple alternatives, if we only knew how to find them.

1. Controlling plot data-tips Data-tips are an extremely useful plotting tool that can easily be controlled programmatically....
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jMouseEmu and inputEmu are both available on the Matlab File Exchange. There is a large overlap between these utilities. As their name suggests, jMouseEmu is geared to control the mouse, while inputEmu emulates both mouse and keyboard inputs.

jMouseEmu

The jMouseEmu utility is an interface function to simplify the programmatic execution of mouse actions (movements, clicks and wheel scrolls). jmouseemu features include accepting relative position with regards to a specified Handle Graphics control, supporting the Shift and Control click modifier keys, supporting double clicking and mouse dragging, controlling mouse wheel turns and allowing multiple command execution with interval timing specification.

jmouseemu has two operating modes: single- or multi-command. In this respect, a single jmouseemu command consists of a cursor position and a click option – multiple such commands can be specified to jmouseemu in the multi-command mode.

In the single-command mode, the function takes the cursor position information and click options. The click options can be any of the possible SelectionType property strings, or “none” if no clicking is desired. For example,

jmouseemu([500,250],'normal');

places the mouse cursor at the coordinate (500, 250) with respect to the current figure (in Matlab coordinates) and then clicks the left mouse button. If no figure is currently open, the cursor is placed at (500,250) with respect to the bottom-left corner of the screen.

The reference graphics handle can be added as the first argument. For example, if hEdit is a uicontrol editbox handle, then

jmouseemu(hEdit,[],'open');
jmouseemu(hEdit,[],'normal');

provides a simple way to select the entire text in the edit box: the double-click jmouseemu call selects the first word, then the following single-click jmouseemu extends the selection to the entire text. If the position argument omitted, the cursor is placed on the upper-left hand corner of the object, unless hEdit=0, in which case the cursor stays at the current position.

To turn the mouse wheel 600 notches down (towards you), run:

jmouseemu(-600,'wheel');

Multi-command mode extends the single-command mode by accepting a cell array of commands along with the update interval T in seconds. The command array must have three columns, and its k-th row specifies the mouse command at time (k–1)T second.

Using the multi-command mode, the above example can be executed with a single jmouseemu call, placing the commands in a cell array:

jmouseemu({h,[],'open'; [],[],'normal'},0);  % T=0

Here, if you omit handles (i.e., the first column of command array) for the second or later commands, it defaults to the handle of the previous command.

Multi-command mode enables mouse cursor to follow a predefined path. For example, to make the mouse cursor travel in a full circle:

T = 0.01; % update every 10 milliseconds
x = pi * (0:T:2)';
pos = 100*[cos(x),sin(x)] + 250;
N = numel(x);
cmds = cell(N,3); % empty click option -> no click
cmds{1,1} = gcf; % position w.r.t. current figure
cmds(:,2) = mat2cell(pos,ones(N,1),2);
jmouseemu(cmds,T);

The command interval is realized by calling robot.delay(T*1e3) between commands. This example updates the mouse position every 10 msecs and completes the circle in 2 seconds.

In multi-command mode, there are two additional click options, “drag_on” and “drag_off”, available to enable mouse dragging. Dragging must be initiated and terminated within a single jmouseemu call, and “drag_off” and “none” are the only two acceptable click options during dragging.

Lastly, to pause mouse movement for a moment (longer than the update interval) , a “delay” command may be used:

jmouseemu({...; [],1.0,'delay'; ...}, T);  % pause for 1 second

Using jMouseEmu to trigger multiple Matlab HG callbacks

jmouseemu (or more broadly the Matlab handling of Java Robot commands) has a major drawback: If jmouseemu is used to trigger a Matlab GUI callback during a sequence of mouse maneuver, the callback will not be executed until the entire maneuver is completed. Moreover, since SelectionType property is not logged for every callback event, the incorrect SelectionType property may be reported during callback execution.

For example, add a double click at the beginning of the circular movement:

cmds{:,3} = 'open';
jmouseemu(cmds,T);

Running this code, you can observe the figure’s WindowsButtonDownFcn callback, which has been set to echo SelectionType property from earlier, does not kick in until the circle is completed. Now, introduce “extend” click at the end of the circle:

cmds{end,3} = 'extend';
jmouseemu(cmds,T);

Again, no callback displaying SelectionType echo occurs during the mouse movement. When the callbacks are finally executed, they return in the order – “normal”, “extend”, “open” – instead of expected “normal”, “open”, “extend”. To correct this behavior, jmouseemu must be called twice:

jmouseemu(cmds(1,:),T);
jmouseemu(cmds(2:end,:),T);

The key here is for each jmouseemu call to have only one callback triggering mouse click command and to place it at the end of the command sequence.

inputEmu

The inputEmu utility is similar to jMouseEmu, with extended support for keyboard inputs. The support for relative mouse cursor position with respect to an HG object, however, has been turned off in the current version of inputEmu (it may get turned on in a future version). Position information in inputEmu is always given in pixels with respect to the lower-left corner of the main display screen. Also, the user must note that the input arguments are flipped between jMouseEmu and inputEmu.

In addition to the left mouse click commands from jMouseEmu, inputEmu can emulate the right and middle mouse button clicks. For example, to perform the right click (e.g., to open a context menu):

inputemu({'right_down' []; 'right_up' []}'); % execute right button click

inputEmu’s main feature is keyboard support. There are 4 basic commands (the behavior may be somewhat different on non-windows platforms):

• key_normal – Normal key press
• key_ctrl - CONTROL + key press
• key_alt – ALT + key press
• key_win – WIN + key press

One other obvious key press, SHIFT + key press, is conspicuously missing from this list. This is because the SHIFT key is automatically pressed when a SHIFT modified character (e.g., an upper-case alphabet) is entered. For example, executing

inputemu('key_normal','Hello World'); % emulates typing "Hello World"

directly in Matlab prompt displays “Hello World” in the next command line. The text is first decoded to a sequence of key press and release pairs, including SHIFT key presses and releases as needed, then the sequence of key commands are sent to the java Robot object.

In addition to all the characters on the keyboard, non-character keys can be stroked by using escape characters:

• ‘\SHIFT’
• ‘\CTRL’
• ‘\ALT’
• ‘\WINDOWS’
• ‘\BACKSPACE’
• ‘\TAB’
• ‘\ENTER’
• ‘\ESC’
• ‘\PAGEUP’
• ‘\PAGEDOWN’
• ‘\END’
• ‘\HOME’
• ‘\LEFT’
• ‘\UP’
• ‘\RIGHT’
• ‘\DOWN’
• ‘\INSERT’
• ‘\DELETE’
• ‘\CAPSLOCK’
• ‘\NUMLOCK’
• ‘\SCROLLLOCK’
• ‘\PRINTSCREEN’
• ‘\PAUSE’

Also, use ‘\\’ for the forward slash character and ‘\F1′ – ‘\F12′ for the Function keys. For example, to execute a Matlab “ver” command automatically via command window, run

inputemu('key_normal','ver\ENTER'); % runs the ver command

Lastly, as mentioned in the previous article, java.awt.Robot is sensitive to the keyboard locale, and the inputEmu utility is programmed specifically for the US QWERTY keyboard. To use the inputEmu for another keyboard layout, the program has to be modified accordingly. If anyone’s interested using this utility for different keyboard layout, I’d be glad to provide assistance.

Do you use Java’s Robot class or any of the utilities above in your work? Yair and I would love to hear about your experience in a short comment below.

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