Listeners – Undocumented Matlab Charting Matlab's unsupported hidden underbelly Thu, 19 Jul 2018 20:59:48 +0000 en-US hourly 1 Blocked wait with timeout for asynchronous events Sun, 13 May 2018 20:22:08 +0000
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Readers of this website may have noticed that I have recently added an IQML section to the website’s top menu bar. IQML is a software connector that connects Matlab to DTN’s IQFeed, a financial data-feed of live and historic market data. IQFeed, like most other data-feed providers, sends its data in asynchronous messages, which need to be processed one at a time by the receiving client program (Matlab in this case). I wanted IQML to provide users with two complementary modes of operation:

IQML's IQFeed-Matlab connectivity

  • Streaming (asynchronous, non-blocking) – incoming server data is processed by internal callback functions in the background, and is made available for the user to query at any later time.
  • Blocking (synchronously waiting for data) – in this case, the main Matlab processing flows waits until the data arrives, or until the specified timeout period has passed – whichever comes first.

Implementing streaming mode is relatively simple in general – all we need to do is ensure that the underlying connector object passes the incoming server messages to the relevant Matlab function for processing, and ensure that the user has some external way to access this processed data in Matlab memory (in practice making the connector object pass incoming data messages as Matlab callback events may be non-trivial, but that’s a separate matter – read here for details).

In today’s article I’ll explain how we can implement a blocking mode in Matlab. It may sound difficult but it turns out to be relatively simple.

I had several requirements/criteria for my blocked-wait implementation:

  1. Compatibility – It had to work on all Matlab platforms, and all Matlab releases in the past decade (which rules out using Microsoft Dot-NET objects)
  2. Ease-of-use – It had to work out-of-the-box, with no additional installation/configuration (which ruled out using Perl/Python objects), and had to use a simple interface function
  3. Timeout – It had to implement a timed-wait, and had to be able to tell whether the program proceeded due to a timeout, or because the expected event has arrived
  4. Performance – It had to have minimal performance overhead

The basic idea

The basic idea is to use Matlab’s builtin waitfor, as I explained in another post back in 2012. If our underlying connector object has some settable boolean property (e.g., Done) then we can set this property in our event callback, and then waitfor(object,'Done'). The timeout mechanism is implemented using a dedicated timer object, as follows:

% Wait for data updates to complete (isDone = false if timeout, true if event has arrived)
function isDone = waitForDone(object, timeout)
    % Initialize: timeout flag = false
    % Create and start the separate timeout timer thread
    hTimer = timer('TimerFcn',@(h,e)object.setDone(true), 'StartDelay',timeout);
    % Wait for the object property to change or for timeout, whichever comes first
    % waitfor is over - either because of timeout or because the data changed
    % To determine which, check whether the timer callback was activated
    isDone = isvalid(hTimer) && hTimer.TasksExecuted == 0;
    % Delete the timer object
    try stop(hTimer);   catch, end
    try delete(hTimer); catch, end
    % Return the flag indicating whether or not timeout was reached
end  % waitForDone

where the event callback is responsible for invoking object.setDone(true) when the server data arrives. The usage would then be similar to this:

if isBlockingMode
   % Blocking mode - wait for data or timeout (whichever comes first)
   isDone = waitForDone(object, 10.0);  % wait up to 10 secs for data to arrive
   if ~isDone  % indicates a timeout
      fprintf(2, 'No server data has arrived within the specified timeout period!\n')
   % Non-blocking (streaming) mode - continue with regular processing

Using a stand-alone generic signaling object

But what can we do if we don’t have such a Done property in our underlying object, or if we do not have programmatic access to it?

We could create a new non-visible figure and then waitfor one of its properties (e.g. Resize). The property would be initialized to 'off', and within both the event and timer callbacks we would set it to 'on', and then waitfor(hFigure,'Resize','on'). However, figures, even if non-visible, are quite heavy objects in terms of both memory, UI resources, and performance.

It would be preferable to use a much lighter-weight object, as long as it abides by the other criteria above. Luckily, there are numerous such objects in Java, which is bundled in every Matlab since 2000, on every Matlab platform. As long as we choose a small Java object that has existed forever, we should be fine. For example, we could use a simple javax.swing.JButton and its boolean property Enabled:

hSemaphore = handle(javax.swing.JButton);  % waitfor() expects a handle() object, not a "naked" Java reference
% Wait for data updates to complete (isDone = false if timeout, true if event has arrived)
function isDone = waitForDone(hSemaphore, timeout)
    % Initialize: timeout flag = false
    % Create and start the separate timeout timer thread
    hTimer = timer('TimerFcn',@(h,e)hSemaphore.setEnabled(true), 'StartDelay',timeout);
    % Wait for the object property to change or for timeout, whichever comes first
    % waitfor is over - either because of timeout or because the data changed
    % To determine which, check whether the timer callback was activated
    isDone = isvalid(hTimer) && hTimer.TasksExecuted == 0;
    % Delete the timer object
    try stop(hTimer);   catch, end
    try delete(hTimer); catch, end
    % Return the flag indicating whether or not timeout was reached
end  % waitForDone

In this implementation, we would need to pass the hSemaphore object handle to the event callback, so that it would be able to invoke hSemaphore.setEnabled(true) when the server data has arrived.

Under the hood, note that Enabled is not a true “property” of javax.swing.JButton, but rather exposes two simple public getter/setter methods (setEnabled() and isEnabled()), which Matlab interprets as a “property”. For all intents and purposes, in our Matlab code we can treat Enabled as a property of javax.swing.JButton, including its use by Matlab’s builtin waitfor function.

There is a light overhead to this: on my laptop the waitfor function returns ~20 mSecs after the invocation of hSemaphore.setEnabled(true) in the timer or event callback – in many cases this overhead is negligible compared to the networking latencies for the blocked data request. When event reactivity is of utmost importance, users can always use streaming (non-blocking) mode, and process the incoming data events immediately in a callback.

Of course, it would have been best if MathWorks would add a timeout option and return value to Matlab’s builtin waitfor function, similar to my waitForDone function – this would significantly simplify the code above. But until this happens, you can use waitForDone pretty-much as-is. I have used similar combinations of blocking and streaming modes with multiple other connectors that I implemented over the years (Interactive Brokers, CQG, Bloomberg and Reuters for example), and the bottom line is that it actually works well in practice.

Let me know if you’d like me to assist with your own Matlab project or data connector, either developing it from scratch or improving your existing code. I will be visiting Boston and New York in early June and would be happy to meet you in person to discuss your specific needs.

]]> 0
Auto-scale image colors Wed, 21 Feb 2018 18:06:23 +0000
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I deal extensively in image processing in one of my consulting projects. The images are such that most of the interesting features are found in the central portion of the image. However, the margins of the image contain z-values that, while not interesting from an operational point-of-view, cause the displayed image’s color-limits (axes CLim property) to go wild. An image is worth a thousand words, so check the following raw image (courtesy of Flightware, Inc.), displayed by the following simple script:

hImage = imagesc(imageData); colormap(gray); colorbar;

Raw image with default Matlab CLim

Raw image with default Matlab CLim

Rescaling the axes color-limits

As you can see, this image is pretty useless for human-eye analysis. The reason is that while all of the interesting features in the central portion of the image have a z-value of ~-6, the few pixels in the margins that have a z-value of 350+ screw up the color limits and ruin the perceptual resolution (image contrast). We could of course start to guess (or histogram the z-values) to get the interesting color-limit range, and then manually set hAxes.CLim to get a much more usable image:

hAxes = hImage.Parent; hAxes.CLim = [-7.5,-6];

Raw image with a custom CLim

Raw image with a custom CLim

Auto-scaling the axes color-limits

Since the z-values range and distribution changes between different images, it would be better to automatically scale the axes color-limits based on an analysis of the image. A very simple technique for doing this is to take the 5%,95% or 10%,90% percentiles of the data, clamping all outlier data pixels to the extreme colors. If you have the Stats Toolbox you can use the prctile function for this, but if not (or even if you do), here’s a very fast alternative that automatically scales the axes color limits based on the specified threshold (a fraction between 0-0.49):

% Rescale axes CLim based on displayed image portion's CData
function rescaleAxesClim(hImage, threshold)
    % Get the displayed image portion's CData
    CData = hImage.CData;
    hAxes = hImage.Parent;
    XLim = fix(hAxes.XLim);
    YLim = fix(hAxes.YLim);
    rows = min(max(min(YLim):max(YLim),1),size(CData,1)); % visible portion
    cols = min(max(min(XLim):max(XLim),1),size(CData,2)); % visible portion
    CData = CData(unique(rows),unique(cols));
    CData = CData(:);  % it's easier to work with a 1d array
    % Find the CLims from this displayed portion's CData
    CData = sort(CData(~isnan(CData)));  % or use the Stat Toolbox's prctile()
    thresholdVals = [threshold, 1-threshold];
    thresholdIdxs = fix(numel(CData) .* thresholdVals);
    CLim = CData(thresholdIdxs);
    % Update the axes
    hAxes.CLim = CLim;

Note that a threshold of 0 uses the full color range, resulting in no CLim rescaling at all. At the other extreme, a threshold approaching 0.5 reduces the color-range to a single value, basically reducing the image to an unusable B/W (rather than grayscale) image. Different images might require different thresholds for optimal contrast. I believe that a good starting point for the threshold is a value of 0.10, which corresponds to the 10-90% range of CData values.

Dynamic auto-scaling of axes color-limits

This is very nice for the initial image display, but if we zoom-in, or pan a sub-image around, or update the image in some way, we would need to repeat calling this rescaleAxesClim() function every time the displayed image portion changes, otherwise we might still get unusable images. For example, if we zoom into the image above, we will see that the color-limits that were useful for the full image are much less useful on the local sub-image scale. The first (left) image uses the static custom color limits [-7.5,-6] above (i.e., simply zooming-in on that image, without modifying CLim again); the second (right) image is the result of repeating the call to rescaleAxesClim(), which improves the image contrast:

Zoomed-in image with a custom static CLim

Zoomed-in image with a custom static CLim

Zoomed-in image with a re-applied custom CLim

Zoomed-in image with a re-applied custom CLim

We could in theory attach the rescaleAxesClim() function as a callback to the zoom and pan functions (that provide such callback hooks). However, we would still need to remember to manually call this function whenever we modify the image or its containing axes programmatically.

A much simpler way is to attach our rescaleAxesClim() function as a callback to the image’s undocumented MarkedClean event:

% Instrument image: add a listener callback to rescale upon any image update
addlistener(hImage, 'MarkedClean', @(h,e)rescaleAxesClim(hImage,threshold));

In order to avoid callback recursion (potentially caused by modifying the axes CLim within the callback), we need to add a bit of code to the callback that prevents recursion/reentrancy (details). Here’s one simple way to do this:

% Rescale axes CLim based on displayed image portion's CData
function rescaleAxesClim(hImage, threshold)
    % Check for callback reentrancy
    inCallback = getappdata(hImage, 'inCallback');
    if ~isempty(inCallback), return, end
        setappdata(hImage, 'inCallback',1);  % prevent reentrancy
        % Get the displayed image portion's CData
        ...  (copied from above)
        % Update the axes
        hAx.CLim = CLim;
        drawnow; pause(0.001);  % finish all graphic updates before proceeding
    setappdata(hImage, 'inCallback',[]);  % reenable this callback

The result of this dynamic automatic color-scaling can be seen below:

Zoomed-in image with dynamic CLim

Zoomed-in image with dynamic CLim

autoScaleImageCLim utility

I have created a small utility called autoScaleImageCLim, which includes all the above, and automatically sets the specified input image(s) to use auto color scaling. Feel free to download this utility from the Matlab File Exchange. Here are a few usage examples:

autoScaleImageCLim()           % auto-scale the current axes' image
autoScaleImageCLim(hImage,5)   % auto-scale image using 5%-95% CData limits
autoScaleImageCLim(hImage,.07) % auto-scale image using 7%-93% CData limits

(note that the hImage input parameter can be an array of image handles)

Hopefully one day the so-useful MarkedClean event will become a documented and fully-supported event for all HG objects in Matlab, so that we won’t need to worry that it might not be supported by some future Matlab release…

]]> 1
Enabling user callbacks during zoom/pan Wed, 28 Oct 2015 12:42:03 +0000
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An annoying side-effect of Matlab figure uimodes (zoom, pan and rotate3d) is that they disable the user’s figure-wide callbacks (KeyPressFcn, KeyReleaseFcn, WindowKeyPressFcn, WindowKeyReleaseFcn, WindowButtonUpFcn, WindowButtonDownFcn and WindowScrollWheelFcn). In most cases, users will indeed expect the mouse and keyboard behavior to change when these modes are active (selecting a zoom region with the mouse for instance). However, in certain cases we may need to retain our custom callback behavior even when the modes are active. This is particularly relevant for the keyboard callbacks, which are not typically used to control the modes and yet may be very important for our figure’s interactive functionality. Unfortunately, Matlab’s mode manager installs property listeners that prevent users from modifying these callback when any mode is active:

>> hFig=figure; plot(1:5); zoom on
>> set(hFig, 'KeyPressFcn', @myKeyPressCallback)
Warning: Setting the "KeyPressFcn" property is not permitted while this mode is active.
(Type "warning off MATLAB:modes:mode:InvalidPropertySet" to suppress this warning.)
> In matlab.uitools.internal.uimodemanager>localModeWarn (line 211)
  In matlab.uitools.internaluimodemanager>@(obj,evd)(localModeWarn(obj,evd,hThis)) (line 86) 
>> get(hFig, 'KeyPressFcn')  % the KeyPressFcn callback set by the mode manager
ans = 
    [1x1 matlab.uitools.internal.uimode]
    {1x2 cell                          }

The question of how to override this limitation has appeared multiple times over the years in the CSSM newsgroup (example1, example2) and the Answers forum, most recently yesterday, so I decided to dedicate today’s article to this issue.

In Matlab GUI, a “mode” (aka uimode) is a set of defined behaviors that may be set for any figure window and activated/deactivated via the figure’s menu, toolbar or programmatically. Examples of predefined modes are plot edit, zoom, pan, rotate3d and data-cursor. Only one mode can be active in a figure at any one time – this is managed via a figure’s ModeManager. Activating a figure mode automatically deactivates any other active mode, as can be seen when switching between plot edit, zoom, pan, rotate3d and data-cursor modes.

This mode manager is implemented in the uimodemanager class in %matlabroot%/toolbox/matlab/uitools/+matlab/+uitools/internal/@uimodemanager/uimodemanager.m and its sibling functions in the same folder. Until recently it used to be implemented in Matlab’s old class system, but was recently converted to the new MCOS (classdef) format, without an apparent major overhaul of the underlying logic (which I think is a pity, but refactoring naturally has lower priority than fixing bugs or adding new functionality).

Anyway, until HG2 (R2014b), the solution for bypassing the mode-manager’s callbacks hijacking was as follows (credit: Walter Roberson):

% This will only work in HG1 (R2014a or earlier)
hManager = uigetmodemanager(hFig);
set(hManager.WindowListenerHandles, 'Enable', 'off');
set(hFig, 'WindowKeyPressFcn', []);
set(hFig, 'KeyPressFcn', @myKeyPressCallback);

In HG2 (R2014b), the interface of WindowListenerHandles changed and the above code no longer works:

>> set(hManager.WindowListenerHandles, 'Enable', 'off');
Error using set
Cannot find 'set' method for event.proplistener class.

Luckily, in MathWorks’ refactoring to MCOS, the property name WindowListenerHandles was not changed, nor its status as a public read-only hidden property. So we can still access it directly. The only thing that changed is its meta-properties, and this is due not to any change in the mode-manager’s code, but rather to a much more general change in the implementation of the event.proplistener class:

>> hManager.WindowListenerHandles(1)
ans = 
  proplistener with properties:
       Object: {[1x1 Figure]}
       Source: {7x1 cell}
    EventName: 'PreSet'
     Callback: @(obj,evd)(localModeWarn(obj,evd,hThis))
      Enabled: 0
    Recursive: 0

In the new proplistener, the Enabled meta-property is now a boolean (logical) value rather than a string, and was renamed Enabled in place of the original Enable. Also, the new proplistener doesn’t inherit hgsetget, so it does not have set and get methods, which is why we got an error above; instead, we should use direct dot-notation.

In summary, the code that should now be used, and is backward compatible with old HG1 releases as well as new HG2 releases, is as follows:

% This should work in both HG1 and HG2:
hManager = uigetmodemanager(hFig);
    set(hManager.WindowListenerHandles, 'Enable', 'off');  % HG1
    [hManager.WindowListenerHandles.Enabled] = deal(false);  % HG2
set(hFig, 'WindowKeyPressFcn', []);
set(hFig, 'KeyPressFcn', @myKeyPressCallback);

During an active mode, the mode-manager disables user-configured mouse and keyboard callbacks, in order to prevent interference with the mode’s functionality. For example, mouse clicking during zoom mode has a very specific meaning, and user-configured callbacks might interfere with it. Understanding this and taking the proper precautions (for example: chaining the default mode’s callback at the beginning or end of our own callback), we can override this default behavior, as shown above.

Note that the entire mechanism of mode-manager (and the related scribe objects) is undocumented and might change without notice in future Matlab releases. We were fortunate in the current case that the change was small enough that a simple workaround could be found, but this may possibly not be the case next time around. It’s impossible to guess when such features will eventually break: it might happen in the very next release, or 20 years in the future. Since there are no real alternatives, we have little choice other than to use these features, and document the risk (the fact that they use undocumented aspects). In your documentation/comments, add a link back here so that if something ever breaks you’d be able to check if I posted any fix or workaround.

For the sake of completeness, here is a listing of the accessible properties (regular and hidden) of both the mode-manager as well as the zoom uimode, in R2015b:

>> warning('off', 'MATLAB:structOnObject');  % suppress warning about using structs (yes we know it's not good for us...)
>> struct(hManager)
ans = 
                    CurrentMode: [1x1 matlab.uitools.internal.uimode]
                  DefaultUIMode: ''
                       Blocking: 0
                   FigureHandle: [1x1 Figure]
          WindowListenerHandles: [1x2 event.proplistener]
    WindowMotionListenerHandles: [1x2 event.proplistener]
                 DeleteListener: [1x1 event.listener]
            PreviousWindowState: []
                RegisteredModes: [1x1 matlab.uitools.internal.uimode]
>> struct(hManager.CurrentMode)
ans = 
    WindowButtonMotionFcnInterrupt: 0
                UIControlInterrupt: 0
                   ShowContextMenu: 1
                         IsOneShot: 0
                    UseContextMenu: 'on'
                          Blocking: 0
               WindowJavaListeners: []
                    DeleteListener: [1x1 event.listener]
              FigureDeleteListener: [1x1 event.listener]
                    BusyActivating: 0
                              Name: 'Exploration.Zoom'
                      FigureHandle: [1x1 Figure]
             WindowListenerHandles: [1x2 event.proplistener]
                   RegisteredModes: []
                       CurrentMode: []
               ModeListenerHandles: []
               WindowButtonDownFcn: {@localWindowButtonDownFcn  [1x1 matlab.uitools.internal.uimode]}
                 WindowButtonUpFcn: []
             WindowButtonMotionFcn: {@localMotionFcn  [1x1 matlab.uitools.internal.uimode]}
                 WindowKeyPressFcn: []
               WindowKeyReleaseFcn: []
              WindowScrollWheelFcn: {@localButtonWheelFcn  [1x1 matlab.uitools.internal.uimode]}
                     KeyReleaseFcn: []
                       KeyPressFcn: {@localKeyPressFcn  [1x1 matlab.uitools.internal.uimode]}
                      ModeStartFcn: {@localStartZoom  [1x1 matlab.uitools.internal.uimode]}
                       ModeStopFcn: {@localStopZoom  [1x1 matlab.uitools.internal.uimode]}
                  ButtonDownFilter: []
                     UIContextMenu: []
                     ModeStateData: [1x1 struct]
                WindowFocusLostFcn: []
          UIControlSuspendListener: [1x1 event.listener]
      UIControlSuspendJavaListener: [1x1 handle.listener]
                   UserButtonUpFcn: []
               PreviousWindowState: []
                 ActionPreCallback: []
                ActionPostCallback: []
           WindowMotionFcnListener: [1x1 event.listener]
                       FigureState: [1x1 struct]
                        ParentMode: []
                     DefaultUIMode: ''
             CanvasContainerHandle: []
                            Enable: 'on'
]]> 9
Using linkaxes vs. linkprop Wed, 22 Jul 2015 20:30:04 +0000
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One of my clients recently asked me to solve a very peculiar problem: He had several axes and was using Matlab’s builtin linkaxes function to link their axis limits. However, it didn’t behave quite the way that he expected. His axes were laid out as 2×2 subplots, and he wanted the two columns to be independently linked in the X axis, and the two rows to be independently linked in the Y axis:

% Prepare the axes
ax(1,1) = subplot(2,2,1); 
ax(1,2) = subplot(2,2,2); 
ax(2,1) = subplot(2,2,3); 
ax(2,2) = subplot(2,2,4);
% Plot something
x = 0 : 0.01 : 10;
line(x, sin(x),   'Parent',ax(1,1));
line(x, sin(2*x), 'Parent',ax(1,2));
line(x, cos(x),   'Parent',ax(2,1));
line(x, cos(5*x), 'Parent',ax(2,2));
% Link the relevant axes
linkaxes(ax(:,1),'x');  % left column
linkaxes(ax(:,2),'x');  % right column
linkaxes(ax(1,:),'y');  % top row
linkaxes(ax(2,:),'y');  % bottom row

The problem was that the plots didn’t behave as expected: when zooming in on the bottom-left axes, for example, only the bottom-right axes was updated (Y-limits synced), whereas the top-left axes’ X-limits remained unchanged:

Badly-synced axes limits

Badly-synced axes limits

Apparently, the second set of two linkaxes commands (to sync the rows’ Y-limits) overrode the first set of two linkaxes commands (to sync the columns’ X-limits).


The reason for this unexpected behavior is that under the hood, linkaxes attaches property-change listeners to the corresponding axes, and stores these listeners in the axes’ hidden ApplicationData property (which is typically accessible via the getappdata / setappdata / isappdata / rmappdata set of functions). Specifically, up to a certain Matlab release (R2013b?), the listeners were placed in a field called ‘listener__’, and since then in a field called ‘graphics_linkaxes’. In either case, the field name was constant.

Therefore, when we placed the first set of linkaxes commands, the axes were correctly synced vertically (ax(1,1) with ax(2,1) in their X-limits, and similarly ax(1,2) with ax(2,2)). But when we placed the second set of linkaxes commands, the internal field in the axes’ ApplicationData property was overriden with the new listeners (that synced the rows’ Y-limits).

It so happens that Matlab listeners have a very nasty feature of being deleted when they are no longer referenced anywhere (within a workspace variable or object property). So when we overrode the first set of listener handles, we effectively deleted them, as if they were never set in the first place.

Some people may possibly complain about both issues at this point:

  • That Matlab listeners get deleted so easily without so much as a console warning, and certainly against naive intuition.
  • That repeated calls to linkaxes should override (rather than complement) each other.

As a side note, the addlistener function creates a listener and then persists it in the object’s hidden AutoListeners__ property. However, unlike the linkaxes behavior, addlistener‘s listener handles are always appended to AutoListeners__‘s contents, rather than replacing it. This ensures that all listeners are accessible and active until their container is deleted or they are specifically modified/removed. I wish that linkaxes used this mechanism, rather than its current ApplicationData one.

Workaround: linkprop

Luckily, there is a very easy and simple workaround, namely to use linkprop rather than linkaxes. The linkprop function is a lower-level function that creates a property-change listener that syncs corresponding properties in any specified array of object handles. In fact, linkaxes uses linkprop in order to create the necessary listeners. In our case, we can use linkprop directly, to independently attach such listeners to the axes’ XLim and YLim properties. We just need to ensure that all these listeners remain accessible to Matlab throughout the corresponding objects’ life-cycle. This is easily done using ApplicationData, as is done by linkaxes.m but in a smarter manner that does not override the previous values. The benefit of this is that when the axes are deleted, then so are the listeners; as long as the axes are accessible then so are the listeners. We just need to ensure that we don’t override these listener values:

setappdata(ax(1,1), 'YLim_listeners', linkprop(ax(1,:),'YLim')); 
setappdata(ax(2,1), 'YLim_listeners', linkprop(ax(2,:),'YLim'));
setappdata(ax(1,1), 'XLim_listeners', linkprop(ax(:,1),'XLim'));
setappdata(ax(1,2), 'XLim_listeners', linkprop(ax(:,2),'XLim'));

This results in the expected behavior:

properly-linked axes

properly-linked axes


The design decision by MathWorks to automatically delete Matlab listeners as soon as their reference count is zeroed and they get garbage-collected, causes a myriad of unexpected run-time behaviors, one of which is exemplified in today’s post on linkaxes. This would still have not caused any problem had the developers of linkaxes been aware of this listener feature and taken care to store the linked listener handles in an accumulating repository (e.g., adding the listener handle to an array of existing handles, rather than replacing a scalar handle).

Luckily, now that we know how Matlab listeners behave, we can easily identify abnormal behavior that results from listener handles going out of scope, and can easily take steps to persist the handles somewhere, so that they will remain active.

I wish to stress here that the listeners’ limited scope is fully documented in several places in the documentation (e.g., here as well as the linkprop doc page). The non-additive behavior of linkaxes is also documented, albeit in an almost-invisible footnote on its doc-page.

However, I humbly contend that the fact that these behaviors are documented doesn’t meant that they are correct. After all, figure windows or timers aren’t deleted when their handle goes out of scope, are they? At the very least, I hope that MathWorks will improve the relevant doc pages, to highlight these non-intuitive behaviors, and in the case of linkaxes to present a linkprop usage example as a workaround.

If you are interested in the topic of Matlab listeners, note that I’ve written quite a few listener-related posts over the years (about property-change listeners as well as event listeners). I urge you to take a look at the list of related articles presented below, or to use the search box at the top of the page.

]]> 5
Undocumented HG2 graphics events Wed, 27 May 2015 17:20:10 +0000
Related posts:
  1. Matlab’s HG2 mechanism HG2 is presumably the next generation of Matlab graphics. This article tries to explore its features....
  2. Introduction to UDD UDD classes underlie many of Matlab's handle-graphics objects and functionality. This article introduces these classes....
  3. Multi-column (grid) legend This article explains how to use undocumented axes listeners for implementing multi-column plot legends...
  4. Draggable plot data-tips Matlab's standard plot data-tips can be customized to enable dragging, without being limitted to be adjacent to their data-point. ...
R2014b brought a refreshing new graphics engine and appearance, internally called HG2 (the official marketing name is long and impossible to remember, and certainly not as catchy). I’ve already posted a series of articles about HG2. Today I wish to discuss an undocumented aspect of HG2 that I’ve encountered several times over the past months, and most recently today. The problem is that while in the previous HG1 system (R2014a and earlier) we could add property-change listener callbacks to practically any graphics object, this is no longer true for HG2. Many graphics properties, that are calculated on-the-fly based on other property values, cannot be listened-to, and so we cannot attach callbacks that trigger when their values change.

Property-change listeners in HG1

Take for example my post about setting axes tick labels format from 3 years ago: the idea there was to attach a Matlab callback function to the PropertyPostSet event of the XTick, YTick and/or ZTick properties, so that when they change their values (upon zoom/pan/resize), the corresponding tick-labels would be reformatted based on the user-specified format:

Formatted labels, automatically updated Formatted labels, automatically updated

Formatted labels, automatically updated

A simple HG1 usage might look as follows:

addlistener(handle(hAxes), 'YTick', 'PostSet', @reformatTickLabels);
function reformatTickLabels(hProperty, eventData)
        hAxes = eventData.AffectedObject;
        hAxes = ancestor(eventData.Source,'Axes');
    tickValues = get(hAxes, 'YTick');
    tickLabels = arrayfun(@(x)(sprintf('%.1fV',x)), tickValues, 'UniformOutput',false);
    set(hAxes, 'YTickLabel', tickLabels)

I prepared a utility called ticklabelformat that automates much of the set-up above. Feel free to download this utility from the Matlab File Exchange. Its usage syntax is as follows:

ticklabelformat(gca,'y','%.6g V')  % sets y axis on current axes to display 6 significant digits
ticklabelformat(gca,'xy','%.2f')   % sets x & y axes on current axes to display 2 decimal digits
ticklabelformat(gca,'z',@myCbFcn)  % sets a function to update the Z tick labels on current axes
ticklabelformat(gca,'z',{@myCbFcn,extraData})  % sets an update function as above, with extra data

Property-change listeners in HG2

Unfortunately, this fails in HG2 when trying to listen to automatically-recalculated (non-Observable) properties such as the Position or axes Tick properties. We can only listen to non-calculated (Observable) properties such as Tag or YLim. Readers might think that this answers the need, since the ticks change when the axes limits change. This is true, but does not cover all cases. For example, when we resize/maximize the figure, Matlab may decide to modify the displayed ticks, although the axes limits remain unchanged.

So we need to have a way to monitor changes even in auto-calculated properties. Luckily this can be done by listening to a set of new undocumented HG2 events. It turns out that HG2’s axes ( objects) have no less than 17 declared events, and 14 of them are hidden in R2015a:

>> events(gca)   % list the non-hidden axes events
Events for class
>> mc = metaclass(gca)
mc = 
  GraphicsMetaClass with properties:
                     Name: ''
              Description: 'TODO: Fill in Description'
      DetailedDescription: ''
                   Hidden: 0
                   Sealed: 1
                 Abstract: 0
              Enumeration: 0
          ConstructOnLoad: 1
         HandleCompatible: 1
          InferiorClasses: {0x1 cell}
        ContainingPackage: [1x1 meta.package]
             PropertyList: [414x1]
               MethodList: [79x1 meta.method]
                EventList: [17x1 meta.event]    EnumerationMemberList: [0x1 meta.EnumeratedValue]
           SuperclassList: [7x1 meta.class]
>> mc.EventList(10)
ans = 
  event with properties:
                   Name: 'MarkedClean'
            Description: 'description'
    DetailedDescription: 'detailed description'
                 Hidden: 1
           NotifyAccess: 'public'
           ListenAccess: 'public'
          DefiningClass: [1x1]
>> [{mc.EventList.Name}; ...
    {mc.EventList.ListenAccess}; ...
    arrayfun(@mat2str, [mc.EventList.Hidden], 'Uniform',false)]'
ans = 
    'LocationChanged'             'public'       'true' 
    'SizeChanged'                 'public'       'true' 
    'ClaReset'                    'public'       'true' 
    'ClaPreReset'                 'public'       'true' 
    'Cla'                         'public'       'true' 
    'ObjectBeingDestroyed'        'public'       'false'  % not hidden
    'Hit'                         'public'       'true' 
    'LegendableObjectsUpdated'    'public'       'true' 
    'MarkedDirty'                 'public'       'true' 
    'MarkedClean'                 'public'       'true' 
    'PreUpdate'                   'protected'    'true' 
    'PostUpdate'                  'protected'    'true' 
    'Error'                       'public'       'true' 
    'Reparent'                    'public'       'true' 
    'Reset'                       'public'       'true' 
    'PropertyAdded'               'public'       'false'  % not hidden
    'PropertyRemoved'             'public'       'false'  % not hidden

Similar hidden events exist for all HG2 graphics objects. The MarkedDirty and MarkedClean events are available for practically all graphic objects. We can listen to them (luckily, their ListenAccess meta-property is defined as ‘public’) to get a notification whenever the corresponding object (axes, or any other graphics component such as a plot-line or axes ruler etc.) is being redrawn. We can then refresh our own properties. It makes sense to attach such callbacks to MarkedClean rather than MarkedDirty, because the property values are naturally stabled and reliable only after MarkedClean. In some specific cases, we might wish to listen to one of the other events, which luckily have meaningful names.

For example, in my ticklabelformat utility I’ve implemented the following code (simplified here for readability – download the utility to see the actual code), which listens to the MarkedClean event on the axes’ YRuler property:

    % HG1 (R2014a or older)
    hAx = handle(hAxes);
    hProp = findprop(hAx, 'YTick');
    hListener = handle.listener(hAx, hProp, 'PropertyPostSet', @reformatTickLabels);
    setappdata(hAxes, 'YTickListener', hListener);  % must be persisted in order to remain in effect
    % HG2 (R2014b or newer)
    addlistener(hAx, 'YTick', 'PostSet', @reformatTickLabels);
    % *Tick properties don't trigger PostSet events when updated automatically in R2014b
    %addlistener(hAx, 'YLim', 'PostSet', @reformatTickLabels);  % this solution does not cover all use-cases
    addlistener(hAx.YRuler, 'MarkedClean', @reformatTickLabels);
% Adjust tick labels now

In some cases, the triggered event might pass some useful information in the eventData object that is passed to the callback function as the second input parameter. This data may be different for different events, and is also highly susceptible to changes across Matlab releases, so use with care. I believe that the event names themselves (MarkedClean etc.) are less susceptible to change across Matlab releases, but they might.

Performance aspects

The MarkedClean event is triggered numerous times, from obvious triggers such as calling drawnow to less-obvious triggers such as resizing the figure or modifying a plot-line’s properties. We therefore need to be very careful that our callback function is (1) non-reentrant, (2) is not active too often (e.g., more than 5 times per sec), (3) does not modify properties unnecessarily, and in general (4) executes as fast as possible. For example:

function reformatTickLabels(hProperty, eventData)
    persistent inCallback
    if ~isempty(inCallback),  return;  end
    inCallback = 1;  % prevent callback re-entry (not 100% fool-proof)
    % Update labels only every 0.2 secs or more
    persistent lastTime
        tnow = datenummx(clock);  % fast
        tnow = now;  % slower
    ONE_SEC = 1/24/60/60;
    if ~isempty(lastTime) && tnow - lastTime < 0.2*ONE_SEC
        inCallback = [];  % re-enable callback
    lastTime = tnow;
    % This is the main callback logic
        hAxes = eventData.AffectedObject;
        hAxes = ancestor(eventData.Source,'Axes');
    prevTickValues = getappdata(hAxes, 'YTick');
    tickValues = get(hAxes, 'YTick');
    if ~isequal(prevTickValues, tickValues)
        tickLabels = arrayfun(@(x)(sprintf('%.1fV',x)), tickValues, 'UniformOutput',false);
        set(hAxes, 'YTickLabel', tickLabels)
    inCallback = [];  % re-enable callback

Unfortunately, it seems that retrieving some property values (such as the axes’s YTick values) may by itself trigger the MarkedClean event for some reason that eludes my understanding (why should merely getting the existing values modify the graphics in any way?). Adding callback re-entrancy checks as above might alleviate the pain of such recursive callback invocations.

A related performance aspect is that it could be better to listen to a sub-component’s MarkedClean than to the parent axes’ MarkedClean, which might be triggered more often, for changes that are entirely unrelated to the sub-component that we wish to monitor. For example, if we only monitor YRuler, then it makes no sense to listen to the parent axes’ MarkedClean event that might trigger due to a change in the XRuler.

In some cases, it may be better to listen to specific events rather than the all-encompassing MarkedClean. For example, if we are only concerned about changes to the Position property, we should listen to the LocationChanged and/or SizeChanged events (more details).

Additional graphics-related performance tips can be found in my Accelerating MATLAB Performance book.

Have you used MarkedClean or some other undocumented HG2 event in your code for some nice effect? If so, please share your experience in a comment below.

]]> 14
Property value change listeners Wed, 13 Aug 2014 14:12:55 +0000
Related posts:
  1. HG2 update HG2 appears to be nearing release. It is now a stable mature system. ...
  2. Performance: accessing handle properties Handle object property access (get/set) performance can be significantly improved using dot-notation. ...
  3. Adding dynamic properties to graphic handles It is easy and very useful to attach dynamic properties to Matlab graphics objects in run-time. ...
  4. Graphic sizing in Matlab R2015b Matlab release R2015b's new "DPI-aware" nature broke some important functionality. Here's what can be done... ...
For performance reasons, it is almost always better to respond to events (asynchronously), than to continuously check a property value (synchronous polling). Therefore, if we wish to do something when some property value is changed (e.g., log the event, shut down the system, liquidate the portfolio, call the police, …), then it is preferable to attach a property-change listener callback.

The standard (documented) way of attaching a value-change listener to Matlab class properties is via the addlistener function. This only works for handle (not value) classes, and only to those properties that have the SetObservable and/or GetObservable attribute turned on:

addlistener(hClassObject, propertyName, 'PostSet', @myCallbackFcn);

This is all nice and well for Matlab class properties, but what about HG (handle Graphics: plots & GUI) properties? Can we similarly listen to changes in (say) the axes limits? Until now this has been possible, but undocumented. For example, this will trigger myCallbackFcn(hAxes,eventData) whenever the axes limits change (due to zoom, pan, plotting etc.):

addlistener(gca, 'YLim', 'PostSet', @(hAxes,eventData) myCallbackFcn(hAxes,eventData));
% Or (shorter equivalent):
addlistener(gca, 'YLim', 'PostSet', @myCallbackFcn);

This could be very useful when such properties could be modified from numerous different locations. Rather than updating all these location to call the relevant callback function directly, we simply attach the callback to the property-change listener. It could also be useful in cases where for some reason we cannot modify the source of the update (e.g., third-party or legacy code).

In addition to PostSet, we could also set listeners for PreSet. Also, we could set listeners on PostGet and PreGet – this could be useful for calculating dynamic (dependent) property values.

Under the hood

The HG1 variant of addlistener is basically equivalent to the following low-level UDD-based code snippet, as explained here:

% Create the listener object
hAxes = handle(gca);  % a UDD axes class object
hProp = findprop(hAxes,'YLim');  % a schema.prop class object
hListener = handle.listener(hAxes, hProp, 'PropertyPostSet', @myCallbackFcn);
% persist the listener in memory for as long as the source object (hAxes) is alive
setappdata(hAxes, 'listener__', hListener);

(in old Matlab releases, addlistener was a regular m-function that placed the listeners in the source handle’s ApplicationData property, as the code above shows; newer releases reimplemented addlistener as an internal built-in function and the listener is now stored somewhere in the DLL’s inaccessible memory, rather than in the ApplicationData property)

In HG2, handle.listener no longer works. Fortunately, we don’t need it since we have addlistener that works the same way for both HG1 (UDD objects) and HG2 (MCOS objects). Kudos on the backward-compatibility aspect, MathWorks!

]]> 9
Disabling menu entries in deployed docked figures Wed, 14 Nov 2012 18:00:46 +0000
Related posts:
  1. setPrompt – Setting the Matlab Desktop prompt The Matlab Desktop's Command-Window prompt can easily be modified using some undocumented features...
  2. Docking figures in compiled applications Figures in compiled applications cannot officially be docked since R2008a, but this can be done using a simple undocumented trick....
  3. 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....
  4. Matlab callbacks for Java events Events raised in Java code can be caught and handled in Matlab callback functions - this article explains how...
Last week I presented an article explaining how to solve an issue with deployed (compiled) Matlab applications. Today I’d like to welcome guest blogger Alexander Mering, who will explain how to disable standard Matlab menu items in deployed docked Matlab figures. Alexander has been an avid follower of this blog, and from his CSSM posts we can tell that he’s been heavily using advanced GUI features presented in this blog. His article today nicely shows how we can use different building-blocks presented in different articles in this blog, to achieve something new and useful.

As Yair pointed out in many occasions, the power of Matlab could be greatly enhanced using the underlying Java mechanism. To me, while developing a larger standalone tool for technical calculations, these hints are worth a mint (as I guess for many of you).

One of these very useful hints is the ability to dock figure windows in standalone applications. This perfectly fits to my understanding of a “clean desktop”, i.e., having as less as possible separate windows. Since in many calculations dozens of figures are generated, the desktop gets up crowded very fast – if these are not grouped. So docking is essential (at least for me). Unfortunately there seems to be a serious problem with the resulting menu entries (at least in R2011b on Win XP), leading to a crash of the standalone application. Based on the posts by Yair, I will sketch a possible route to avoid this issue.

The symptom

In the compiled application, docking could be accomplished by accessing the figure frame’s underlying Java level:

% get java frame for sophisticated modifications
jframe = get(handle(figure_handle), 'JavaFrame');
% allow docking

Using this modification, the user is now allowed to dock and undock the figures manually. For initial docking of the figure,


could be used during figure creation. Unfortunately, there are menu entries in the Figures container which are either unwanted (since not usable) or even directly crash the standalone applications:

Useless Debug menu items in deployed applications

Useless Debug menu items in deployed applications

Menu items crashing deployed applications

Menu items crashing deployed applications

Since crashing menu entries will be found and used by end-users (though these are somehow hidden), these prohibit the usage of the docking feature as long as these could be invoked. So how can we disable / remove these menu items?

The unsuccessful solution

Unfortunately, the straight forward solution of getting the handle to the Figures containers’ menu bar and remove the unwanted items does not work. The reason for this is the (to me unexpected behavior) that the menu bar seems to be rebuilt whenever a figure is docked/undocked.

This is actually the same behavior that automatically rebuilds the Editor’s menu bar whenever an editor file is added/removed. The Editor container is basically the same docking container as the Figures container, as shown by Yair’s setFigDockGroup utility:

Docking a figure in the Editor container (group)

Docking a figure in the Editor container (group)

Therefore, removing unwanted menu items only helps until the next figure docking/undocking. To make it even worse: also pressing any of the buttons within the document bar (if having more than one figure) somehow rebuilds the entire menu structure, reverting our changes. So the solution becomes a bit more complex.

The working solution

For the working solution, many pieces presented by Yair should be put together. The first piece results from the question how to detect a dock/undock event. Since no such callback is defined, we need to use a property listener as Yair showed in his post about the continuous slider callback:

% listen to the WindowStyle property to detect docking / undocking events
hProp = findprop(handle(figure_handle),'WindowStyle');  % a schema.prop object
% if the event occurs, invoke the callback
hlistener = handle.listener(handle(figure_handle), hProp, 'PropertyPostSet',{@(source, event) Callback_DockingFcn});
% attach listener to the GUI since it needs to be known (as long as the figure exists)
setappdata(figure_handle, 'Handle_Listener', hlistener);

Now, whenever the figure’s WindowStyle property (which controls the docking state) is changed, our docking callback is invoked.

The next piece of the puzzle takes care of the menu rebuild whenever any document bar button is pressed. To overcome this behavior, the idea is to define the MousePressed callback of theses buttons to (again) invoke the docking callback. This is necessary for two reasons: First, pressing the button (i.e., changing the current figure) rebuilds the menu, overwriting our changed menu entries. Secondly, all other buttons are also somehow rebuilt and the callbacks are removed if a new figure is docked.

The handles to the document bar buttons could be found using Yair’s findjobj utility. We have already seen that the Editor container is analogous to the Figures docking container. So let’s use the method described by Yair for accessing the Editor container, to access the Figures container:

figures_container = javaObjectEDT(matlab_instance.getGroupContainer('Figures'));
figures_frame = javaObjectEDT(figures_container.getTopLevelAncestor);

Once we get the Java Frame for the Figures container, the buttons could be found by digging through its children. This finally allows to set the callback using

DTDocumentBar = javaObjectEDT(figures_frame.getRootPane.getLayeredPane.getComponent(1).getComponent(1).getComponent(0).getComponent(0).getComponent(1).getComponent(0));
ContentPanel = javaObjectEDT(DTDocumentBar.getComponent(0).getComponent(0).getViewport.getView);
if ~isempty(ContentPanel.getComponents) % less than two documents are open and no DTDocumentbar exists
    drawnow; pause(0.05)
    GroupPanel = javaObjectEDT(ContentPanel.getComponent(0));
    GroupPanel_Elements = javaObjectEDT(GroupPanel.getComponents);
    % change the MousePressed Callback for each of the buttons to invoke the function which disables the menu
    for n = 1 : GroupPanel.getComponentCount
        thisElement = GroupPanel_Elements(n);
        if isequal(char(thisElement.getClass.toString), 'class com.mathworks.widgets.desk.DTDocumentBar$DocumentButton')
            set(handle(thisElement, 'CallbackProperties'), 'MousePressedCallback', {@(source, event) Cbrake_Callback_Diagrams_DockingFcn})
    drawnow; pause(0.05)

where the loop runs through the current buttons in the document bar.

As the last step of our procedure, we finally remove (or disable) the menu entries which are unwanted. This is achieved by extracting the handle to the Figures menu by:

figures_menu = javaObjectEDT(figures_frame.getJMenuBar);

Running through the menu items, searching for the unwanted entries (as long as they have pre-defined menu-item names) at the end sets us into the position to take care of the menu items:

% run through top-level menu items
for n = 1 : figures_menu.getMenuCount
    % completely deactivate Debugging options
    if isequal(char(figures_menu.getMenu(n-1).getName), 'DesktopDebugMenu')
        DesktopDebugMenuPos = n - 1;
    % Remove some items from the Desktop menu
    if isequal(char(figures_menu.getMenu(n-1).getName), 'DesktopMenu')
        desktop_menu = javaObjectEDT(figures_menu.getMenu(n-1));
        DeletePos = [];
        for m = 1: desktop_menu.getMenuComponentCount
            if ismember({char(desktop_menu.getMenuComponent(m-1).getName)}, ...
                        {'ToggleFigure PaletteCheckBoxMenuItem', 'TogglePlot BrowserCheckBoxMenuItem', 'ToggleProperty EditorCheckBoxMenuItem'})
                DeletePos(end+1) = m - 1;
        for m = length(DeletePos) : -1 : 1
% finally remove the "Debug" menu
if ~isempty(DesktopDebugMenuPos)

Since this callback is invoked whenever a figure is docked/undocked, or the currently shown figure is changed (by pressing the document bar button), all unwanted menu items within the Figures menu could be removed.

As a result, the new Figures container menu looks like:

Deployed menu without unwanted items

Deployed menu without unwanted items


I must admit that above solution is still imperfect. For instance, sometimes there is a larger delay between the docking (or button press event) and the removing of the menu item. Nevertheless, this solution allows me to distribute my standalone with docked figures without having menu items directly leading to a fatal error.

Obviously, the solution has some positive side effects:

  • As could be seen from the screen shot, the Matlab desktop becomes available also within your compiled applications. This might be wanted. If not, it could be removed the same way as the other menu items. One drawback of making the desktop available should be mentioned: In my tests, the standalone Matlab desktop shows the whole list of recent files I have in the Matlab editor at compile time. This is somehow ugly but not that problematic.
  • Additional menu items could be added, giving more possibilities for modifications.

I have uploaded a first version of the docking and creation functions, together with a small test project, to the Matlab file Exchange. Readers are welcome to download the code and send me improvement suggestions. Or you could simply leave a comment below.

]]> 14
Waiting for asynchronous events Wed, 18 Jul 2012 18:50:57 +0000
Related posts:
  1. setPrompt – Setting the Matlab Desktop prompt The Matlab Desktop's Command-Window prompt can easily be modified using some undocumented features...
  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. Uitable sorting Matlab's uitables can be sortable using simple undocumented features...
  4. Disabling menu entries in deployed docked figures Matlab's standard menu items can and should be removed from deployed docked figures. This article explains how. ...
It often happens that we need our program to wait for some condition to occur. This condition may depend on some external process that updates the condition asynchronously, meaning in a non-predictable (non-specific) time. A typical example is user mouse or keyboard actions in a GUI dialog window, or a specific signal that is received from hardware.

waitfor and other built-in functions

Matlab has a couple of built-in functions for blocking Matlab’s main processing thread until certain asynchronous GUI events occurs. waitfor is documented to block code execution until either the specified GUI handle object is deleted, or is updated (possibly to a specified value), or Ctrl-C is pressed in matlab’s Command Window. uiwait similarly blocks execution, until a specified figure handle is deleted/closed, or a separate processing thread (typically, a callback function) calls the corresponding uiresume (I discussed uiwait/uiresume, together with their uisuspend/uirestore siblings, last year). uiwait, unlike waitfor, has an optional timeout parameter; on the other hand, uiwait cannot wait for a non-deletion event on a regular uicontrol property, as waitfor can.

Other related built-in Matlab functions are waitforbuttonpress, pause (which awaits user mouse/keyboard clicks), and ginput, gtext, rbbox, dragrect (which awaits mouse clicks in a plot/image axes). Some toolboxes have other similar blocking functions, for example roipoly in the Image Processing toolbox.

Waiting for events on non-HG objects

But what if we need to wait for an event to happen on a non-Matlab (HG) object? Say on an ActiveX control property or even on a non-graphical Java object?

It turns out that waitfor can also be used in these cases. Although not documented, waitfor actually accepts handles not only of HG objects (e.g., figure handles) but also of other types of handles, such as regular Java reference handles. The usage is the same as for regular HG handles:

waitfor(objectHandleOrReference, 'propertyName', propertyValue);

For example, to wait for data to be available in a java.util.Hashtable object, which has a public boolean isEmpty() method and therefore returns a value of ‘on’ or ‘off’ for get(object,’Empty’):

waitfor(javaHashTableReference, 'Empty', 'off');

(Note that Matlab automatically converts a Java boolean into ‘on’/’off’ in such cases, so we need to use ‘on’/’off’ rather than true/false; this is not always the case – a counter-case is presented immediately below)

Setting a timeout on waitfor

To set a timeout on our blocked wait, a feature of uiwait that is missing in the built-in waitfor, we can use a dedicated one-time timer object. Timer callbacks use a separate thread from the main Matlab processing thread, and are therefore processed even when the Main thread is blocked. The implementation is quite easy, as shown below:

% Wait for data updates to complete (isDone = false if timeout, true if data ok)
function isDone = waitForDone(object,timeout)
    % Initialize: timeout flag = false
    % Create and start the separate timeout timer thread
    hTimer = timer('TimerFcn',@(h,e)object.setDone(true), 'StartDelay',timeout);
    % Wait for the object property to change or for timeout, whichever comes first
    % waitfor is over - either because of timeout or because the data changed
    % To determine which, check whether the timer callback was activated
    isDone = (hTimer.TasksExecuted == 0);
    % Delete the time object
    try stop(hTimer);   catch, end
    try delete(hTimer); catch, end
    % Return the flag indicating whether or not timeout was reached
end  % waitForDone


In some cases (for example, waiting on a specific field value within a struct, which waitfor does not support), we need to revert to using plain-ol’ polling, rather than the more efficient blocked wait. In such cases, I strongly advice to place a certain pause within the polling loop:

delay = 0.01;  % 10 milliseconds
while ~object.isDone  % set by the callback
    pause(delay);  % a slight pause to let all the data gather

Or, a variant with timeout:

delay = 0.01;
for idx = 1 : (timeout/delay)  % wait up to N secs before giving up
    if object.isDone  % set by the callback
    pause(delay);  % a slight pause to let all the data gather

The reason we need this deliberate pause is to enable the CPU to process other processing threads, namely that thread which is responsible for updating the field value in due time. Without this pause, it would take the CPU much longer (if at all) to get to that thread, and our overall application performance will actually degrade, since the event will take longer to get processed.

Adding deliberate pause delays as a mechanism to improve overall performance may sound counter-intuitive, but this is in fact the case here. Performance tuning can indeed be counter-intuitive sometimes, until you learn the underlying reasons when it becomes clear (I’ve shown several examples of this in the past, here, here, here and here).

We should take care not to set too high a pause delay, since that will unnecessarily delay processing of the incoming event; on the other hand, setting it too low will return the thread-starvation issue explained above. A pause value of 5-50 millisecs (0.005-0.05) should be about right for the vast majority of applications. Note that different platforms run your application at different speeds, so be careful not to over-tune this delay to a particular computer.

Interested in learning more Matlab performance or advanced programming tricks? Then consider joining my Matlab Performance Tuning, Advanced Matlab GUI and/or Matlab-Java programming seminars in Geneva on August 21-23, 2012 – email me (altmany at gmail dot com) for details.

]]> 33
Setting axes tick labels format Wed, 18 Apr 2012 18:00:17 +0000
Related posts:
  1. Introduction to UDD UDD classes underlie many of Matlab's handle-graphics objects and functionality. This article introduces these classes....
  2. Inactive Control Tooltips & Event Chaining Inactive Matlab uicontrols cannot normally display their tooltips. This article shows how to do this with a combination of undocumented Matlab and Java hacks....
  3. New information on HG2 More information on Matlab's new HG2 object-oriented handle-graphics system...
  4. Multi-column (grid) legend This article explains how to use undocumented axes listeners for implementing multi-column plot legends...
Have you ever tried to customize the way in which tick labels appear in Matlab plot axes?

For example, setting the numerical precision of the labels, or adding some short descriptive text (for example, the units)? If you have, then I bet that you have encountered the following dilemma: Once we modify the tick labels (for discussion sake, let’s assume the Y axis, so this is done by updating the YTickLabel property), then the corresponding YTickLabelMode property changes from ‘auto’ to ‘manual’ and loses its relationship to the tick values (YTick). So, if we now zoom or pan the plot, our new labels remain unchanged although the tick values have changed, causing much panic and frustration… If we also set the tick values manually, this solves that problem but leaves us with another: now, when we zoom or pan, we no longer see any ticks or tick labels at all!

Original plot Manual labels, auto ticks Manual labels, manual ticks

Original plot (left)
Manual labels, auto ticks (center)
Manual labels, manual ticks (right)

Of course, we can always trap the zoom and pan callback functions to update the tick labels dynamically while keeping the tick values automatically. This will work for these cases, but we need to do it separately for zoom and pan. Also, if we modify the axes limits explicitly (via the corresponding YLim property) or indirectly (by modifying the displayed plot data), then the callbacks are not called and the labels are not updated.

The solution – using a property change listener

A better way to solve this problem is to simply trap changes to the displayed tick values, and whenever these occur to call our dedicated function to update the labels according to the new tick values. This can be done by using UDD, or more precisely the ability to trap update events on any property (in our case, YTick). Such a mechanism was already demonstrated here in 2010, as one way to achieve continuous slider feedback. The idea is to use the built-in handle.listener function with the PropertyPostSet event, as follows:

hhAxes = handle(hAxes);  % hAxes is the Matlab handle of our axes
hProp = findprop(hhAxes,'YTick');  % a schema.prop object
hListener = handle.listener(hhAxes, hProp, 'PropertyPostSet', @myCallbackFunction);
setappdata(hAxes, 'YTickListener', hListener);

Note that we have used setappdata to store the hListener handle in the axes. This ensures that the listener exists for exactly as long as the axes does. If we had not stored this listener handle somewhere, then Matlab would have immediately deleted the listener hook and our callback function would not have been called upon tick value updates. Forgetting to store listener handles is a common pitfall when using them. If you take a look at the addlistener function’s code, you will see that it also uses setappdata after creating the listener, for exactly this reason. Unfortunately, addlistsner cannot always be used, and I keep forgetting under which circumstances, so I generally use handle.listener directly as above: It’s simple enough to use that I find I never really need to use the simple addlistener wrapper, but you are welcome to try it yourself.

That’s all there is to it: Whenever YTick changes its value(s), our callback function (myCallbackFunction) will automatically be called. It is quite simple to set up. While we cannot use TeX in tick labels yet (this will change in the upcoming HG2), using sprintf formatting does enable quite a bit of flexibility in formatting the labels. For example, let’s say I want my tick labels to have the format ‘%.1fV’ (i.e., always one decimal, plus the Volts units):

function myCallbackFunction(hProp,eventData)    %#ok - hProp is unused
   hAxes = eventData.AffectedObject;
   tickValues = get(hAxes,'YTick');
   newLabels = arrayfun(@(value)(sprintf('%.1fV',value)), tickValues, 'UniformOutput',false);
   set(hAxes, 'YTickLabel', newLabels);
end  % myCallbackFunction

Manual labels, automatically updated Manual labels, automatically updated

Manual labels, automatically updated

Handling duplicate tick labels

Of course, ‘%.1fV’ may not be a good format when we zoom in to such a degree that the values differ by less than 0.1 – in this case all the labels will be the same. So let’s modify our callback function to add extra decimals until the labels become distinct:

function myCallbackFunction(hProp,eventData)    %#ok - hProp is unused
   hAxes = eventData.AffectedObject;
   tickValues = get(hAxes,'YTick');
   %newLabels = arrayfun(@(value)(sprintf('%.1fV',value)), tickValues, 'UniformOutput',false);
   digits = 0;
   labelsOverlap = true;
   while labelsOverlap
      % Add another decimal digit to the format until the labels become distinct
      digits = digits + 1;
      format = sprintf('%%.%dfV',digits);
      newLabels = arrayfun(@(value)(sprintf(format,value)), tickValues, 'UniformOutput',false);
      labelsOverlap = (length(newLabels) > length(unique(newLabels)));
      % prevent endless loop if the tick values themselves are non-unique
      if labelsOverlap && max(diff(tickValues))< 16*eps
   set(hAxes, 'YTickLabel', newLabels);
end  % myCallbackFunction

non-distinct labels distinct labels

Non-distinct labels                   distinct labels


Based on a file that I received from an anonymous reader a few years ago, I have prepared a utility called ticklabelformat that automates much of the set-up above. Feel free to download this utility and modify it for your needs – it’s quite simple to read and follow. The usage syntax is as follows:

ticklabelformat(gca,'y','%.6g V')  % sets y axis on current axes to display 6 significant digits
ticklabelformat(gca,'xy','%.2f')   % sets x & y axes on current axes to display 2 decimal digits
ticklabelformat(gca,'z',@myCbFcn)  % sets a function to update the Z tick labels on current axes
ticklabelformat(gca,'z',{@myCbFcn,extraData})  % sets an update function as above, with extra data

Addendum for HG2 (R2014b or newer releases)

As I’ve indicated in my comment response below, in HG2 (R2014b or newer) we need to listen to the HG object’s MarkedClean event, rather than to a property change event.

I’ve updated my ticklabelformat utility accordingly, so that it works with both HG1 (pre-R2014a) and HG2 (R2014b+). Use this utility as-is, and/or look within its source code for the implementation details.

]]> 17
Blurred Matlab figure window Wed, 20 Apr 2011 18:58:12 +0000
Related posts:
  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. Customizing menu items part 2 Matlab menu items can be customized in a variety of useful ways using their underlying Java object. ...
  4. Customizing menu items part 3 Matlab menu items can easily display custom icons, using just a tiny bit of Java magic powder. ...
Following my post two weeks ago about disabling an entire Matlab figure window, and my article last week about setting the transparency of a figure window, I would like to combine these two functionalities into a blurred-window effect for a disabled window.

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

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.


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:\');
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]);
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);
uicontrol('parent',hFigBlurTemp, 'string','Cancel', 'pos',[280,90,100,20], 'Callback','close(gcbf)');

Non-blurred controls displayed over a blurred figure window

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.

]]> 2
UDD and Java Wed, 23 Mar 2011 21:04:35 +0000
Related posts:
  1. Matlab callbacks for Java events Events raised in Java code can be caught and handled in Matlab callback functions - this article explains how...
  2. setPrompt – Setting the Matlab Desktop prompt The Matlab Desktop's Command-Window prompt can easily be modified using some undocumented features...
  3. Introduction to UDD UDD classes underlie many of Matlab's handle-graphics objects and functionality. This article introduces these classes....
  4. Types of undocumented Matlab aspects This article lists the different types of undocumented/unsupported/hidden aspects in Matlab...
Once again I welcome Donn Shull, who concludes his series on Matlab’s undocumented UDD mechanism with a discussion of the UDD-Java relationship.

Introduction to the UDD-Java relationship

Over the course of this series we have mentioned connections between UDD and Java. In UDD Events and Listeners we described how in Matlab each Java object can have a UDD companion. In Hierarchical Systems with UDD we briefly noted that a UDD hierarchy may be passed to Java. This suggests that there is a two way relationship between between UDD and Java.

In this article we will use some undocumented built-in methods such as java and classhandle to explore the UDD-Java relationship. We have used built-in methods for UDD objects before. We have also mentioned the importance of studying code from The MathWorks. When you come across something that looks like it may be a UDD method you can check with the which command:

>> which java -all
java is a built-in method                               % method
java is a built-in method                               % ui.figure method
java is a built-in method                               % hg2utils.HGHandle method
java is a built-in method                               % JavaVisible method
java is a built-in method                               % hg.figure method
java is a built-in method                               % hg.GObject method
java is a built-in method                               % schema.class method
java is a built-in method                               % handle.handle method
java is a built-in method                               % schema.method method
C:\MATLAB\R2010b\toolbox\rptgen\rptgen\@sgmltag\java.m  % sgmltag method

If you find schema.class in the comments for built-in methods, then the method is a general UDD method.

UDD javahandle companions for Java object

Whenever a Java class is instantiated in Matlab, it is possible to create a companion UDD object. The created companion can be in either the javahandle or the javahandle_withcallbacks package. The primary reason for creating the companion object is to avoid memory leaks when attaching a Matlab callback to a callback property. It makes sense in general to use the javahandle_withcallbacks package.

>> % creage a java instance and the companion UDD object
>> javaFrame = javax.swing.JFrame;
>> % dot notation
>> javaFrameUDD = javaFrame.handle('CallbackProperties');
>> % or Matlab notation
>> javaFrameUDD = handle(javaFrame,'CallbackProperties');

We can use the built-in classhandle method to inspect our UDD companion object. This can be used, for example, to obtain a list of the events that the Java class generates:

>> % use classhandle to list a java classes events
>> jch = javaFrame.handle.classhandle;
>> for index = 1:numel(jch.Events), disp(jch.Events(index).Name); end
>> % Use one of the object's callbacks
>> set(javaFrameUDD,'WindowGainedFocusCallback',@myCallbackFcn);

If we do not wish to use callback properties, then we can create our UDD companion in the javahandle package and use handle.listener to respond to events.

javaFrame = javax.swing.JFrame;
javaFrameUDD = javaFrame.handle;
lis = handle.listener(javaFrameUDD,'WindowGainedFocus',@myCallbackFcn);

Passing UDD objects to Java code

You can pass any UDD object to your Java classes in Matlab. Matlab will create a Java bean adapter for the UDD object. The bean adapter created is a subclass of com.MathWorks.jmi.bean.UDDObject. UDDObject implements the Java interfaces com.MathWorks.jmi.bean.DynamicProperties, com.MathWorks.jmi.bean.MTObject, com.MathWorks.jmi.bean.TreeObject, and

The generated bean adapter will have the methods of the parent class the methods of the UDD class, as well as set and get methods for the class properties. To understand how this works, let’s start with our simple.object and use the java method to inspect the bean adapter:

>> myObj = simple.object('myObj', 2);
>> % using dot notation with the java method 
ans =
class objectBeanAdapter0
Methods for class objectBeanAdapter0:
acquireReference                    createNullMatlabObjectListener      lastDown                            
addBelow                            createNullPropertyChangeListener    left                                
addBrowseableListener               dialog                              notify                              
addFirstBelow                       disp                                notifyAll                           
addLeft                             dispose                             objectBeanAdapter0                  
addMatlabObjectListener             equals                              releaseReference                    
addObjectPropertyChangeListener     findProperty                        removeBrowseableListener            
addRight                            firstDown                           removeMatlabObjectListener          
browseableCanHaveChildren           getChildAt                          removeObjectPropertyChangeListener  
browseableChild                     getChildCount                       right                               
browseableChildCount                getClass                            setDirtyFlag                        
browseableChildFetchCount           getClassName                        setDynamicPropertyValue             
browseableChildren                  getDynamicProperties                setName                             
browseableDataObject                getDynamicPropertyValue             setPropertyValue                    
browseableDisplayObject             getIndex                            setThreadSafetyCheckLevel           
browseableHasChildren               getIndexOfChild                     setValue                            
browseableNChildren                 getName                             toString                            
browseableNextNSiblings             getNewInstance                      up                                  
browseableNextSibling               getPropertyValue                    updateCache                         
browseableParent                    getValue                            updateChildCount                    
browseablePrevNSiblings             hashCode                            updateIndex                         
browseablePrevSibling               isDirty                             wait                                
checkThreadSafety                   isLeaf                              
clearDirtyFlag                      isObservable                        
compareTo                           isValid

The parent class has added a large number of methods to the bean adapter for our original class. By looking at the list we can see our dialog and disp methods. There are also getName, setName, getValue, and setValue methods for our classes properties. The rest of the methods were inherited from the base UDDObject superclass. We can use any superclass method directly with the bean adapter object. For example:

ans =

Java interface class

To be able to use our UDD object in user-written Java code, we need a Java interface class for it. While we could manually write an interface file, UDD provides a very handy convenience method to automatically create the interface file. For this, we use the classhandle method again. The schema.class object obtained using classhandle has a method called createJavaInterface that takes two string arguments: the Java interface classname, and the folder in which to place the interface file. The steps to create and use this interface file are:

  1. Create and test your UDD class
  2. Create a Java interface file using schema.class‘s CreateJavaInterface
  3. Modify your UDD class definition file (schema.m) to reference the Java interface file
  4. Create the Java code that uses your class

For example, to create a Java interface file for the simple object we created above, use the following commands in Matlab:

classH = classhandle(myObj);

This will create the following file in the current working directory:

public interface simpleObjectInterface 
       extends com.mathworks.jmi.bean.TreeObject
    /* Properties */
    public java.lang.String getName();
    public void setName(java.lang.String value);
    public double getValue();
    public void setValue(double value);
    /* Methods */
    public void dialog();
    public void disp();

The interface file contains set and get accessor methods for our UDD object properties, and Java prototypes for the UDD methods (in our case, dialog and disp).

The next step is to modify our class definition file (schema.m) to reference the Java interface file we have created. This modification provides the information that Matlab needs to create the bean adapter that implements the Java interface:

simpleClass = schema.class(simplePackage, 'object');
simpleClass.JavaInterfaces = { 'simpleObjectInterface' };

We can verify that the generated bean adapter implements the interface using Java Reflection techniques. As always when we have made changes to the class definition file, we need to use the clear classes command, and then recreate our objects:

>> myObj = simple.object('myObj', pi)
myObj =
  Name: myObj
 Value: 3.141593
>> myObjBean = java(myObj) 
myObjBean =
  Name: myObj
 Value: 3.141593
>> interfaces = myObjBean.getClass.getInterfaces 
interfaces =
>> interfaces(1) 
ans =
interface simpleObjectInterface

Using UDD in Java

Let’s create a simple Java class that illustrates passing a UDD object to Java. Here we will just have two methods: The first gets the Value property from a class instance and doubles it; the second launches the class instance dialog:

public class accessUDDClass 
  double localValue;
  public void accessUDDClass() { 
  public void doubleValue(simpleObjectInterface UDDObj) {
    localValue = UDDObj.getValue();
  public void launchDialog(simpleObjectInterface UDDObj) {

If we have set up the Java compiler and environment variables correctly, we can compile our interface and Java class files from inside Matlab using the system command (alternately, we can compile using any external Java compiler or IDE):

>> system('javac')
ans =

Now test our simple Java class with the UDD object created earlier:

>> javaObj = accessUDDClass
javaObj =
>> javaObj.doubleValue(myObj)  % pi => 2*pi
>> myObj
myObj =
  Name: myObj
 Value: 6.283185

This concludes the UDD series. I would like to thank Yair for his help in preparing and presenting this information.

Editor’s note

I would like to thank Donn for his enourmously detailed work on UDD, and for preparing it in easy-to-follow articles. I can personally attest to the huge time investment it has taken him. I trully believe he deserves a warm “thank you” from the Matlab community. Please visit Donn’s website, or add a short comment below.

In the following weeks, I return to the regular stuff that made this website famous: solving day-to-day Matlab problems using simple undocumented built-in Matlab gems.
– Yair

]]> 4
UDD Events and Listeners Wed, 16 Mar 2011 18:43:16 +0000
Related posts:
  1. Introduction to UDD UDD classes underlie many of Matlab's handle-graphics objects and functionality. This article introduces these classes....
  2. Creating a simple UDD class This article explains how to create and test custom UDD packages, classes and objects...
  3. UDD Properties UDD provides a very convenient way to add customizable properties to existing Matlab object handles...
  4. Multi-column (grid) legend This article explains how to use undocumented axes listeners for implementing multi-column plot legends...
Donn Shull continues his exploration of the undocumented UDD mechanism, today discussing the important and extremely useful topic of UDD events

The UDD event model

The UDD event model is very similar to the MCOS event model. There is an excellent discussion of the MCOS event model in Matlab’s official documentation. Most of the MCOS information also applies to UDD if you make the following substitutions:

MCOS Event ModelUDD Event Model
events blockschema.event
PreGet, PreSetPropertyPreGet, PropertPreSet
PostGet, PostSetPropertyPostGet, PropertyPostSet

Event handler functions

To begin the UDD event model discussion we will start at the end, with the event handler. The event handler function requires at least two input arguments: the source object which triggered the event, and an object of type handle.EventData or a subclass of handle.EventData.

To demonstrate how this works, let’s write a simple event handler function. This event handler will display the class of the source event and the class of the event data:

function displayEventInfo(source, eventData)
%DISPLAYEVENTINFO display the classes of source, data objects
%   of the source object and the event data object
%       SOURCE    : the event source
%       EVENTDATA : the event data
  if ~isempty(source)
    fprintf(1, 'The source object class is: %s',class(source));
  if ~isempty(eventData)
    fprintf(1, 'The event data class is: %s',class(eventData));

Creating a listener

In the section on Creating a Simple UDD Class we used schema.event in our simple.object class definition file to create a simpleEvent event. We now create an instance of simple.object, then use handle.listener to wait (“listen”) for the simpleEvent event to occur and call the displayEventInfo event handler function:

a = simple.object('a', 1);
hListener = handle.listener(a,'simpleEvent',@displayEventInfo);
setappdata(a, 'listeners', hListener);

Important: The hListener handle must remain stored somewhere in Matlab memory, or the listener will not be used. For this reason, it is good practice to attach the listener handle to the listened object, using the setappdata function, as was done above. The listener will then be alive for exactly as long as its target object is alive.

Creating an EventData object

Next, create the handle.EventData object. The handle.EventData object constructor requires two arguments: an instance of the events source object, and the name of the event:

evtData = handle.EventData(a, 'simpleEvent')

Generating an event

The last step is actually triggering an event. This is done by issuing the send command for the specified object, event name and event data:

>> a.send('simpleEvent', evtData)
The source object class is: simple.object
The event data class is: handle.EventData

If there is other information that you wish to pass to the callback function you can create a subclass of the handle.EventData. Add properties to hold your additional information and use your subclass as the second argument of the send method.

Builtin UDD events

The builtin handle package has six event data classes which are subclasses of the base handle.EventData class. Each of these classes is paired with specific UDD events that Matlab generates. Actions that trigger these events include creating/destroying an object, adding/removing objects from a hierarchy, and getting/setting property values. The following table lists the event names and handle.*EventData data types returned for these events:

event data typeevent trigger
handle.ChildEventDataObjectChildAdded, ObjectChildRemoved
handle.PropertyEventDataPropertyPreGet, PropertyPostGet
handle.PropertySetEventDataPropertyPreSet, PropertyPostSet

As an example of some of these events let’s look at a question recently asked on the CSSM newsgroup. The basic idea is that we want to monitor an axis, automatically make any added lines to be green in color, and prevent patches from being added.

The solution is to monitor the ObjectChildAdded event for an axis. We will write an event handler which checks the handle.ChildEventData to see what type of child was added. In the case of lines we will set their color to green; patch objects will be deleted from the axis. Here is our event handler function:

function modifyAxesChildren(~, eventData)
%MODIFYAXESCHILDREN monitor and axis and modify added children
%   change newly-added lines to green and remove added patches
%       EVENTDATA : handle.ChildEventData object
   switch eventData.Child.classhandle.Name
      case 'line'
         eventData.Child.set('Color', 'green');
         disp('Color changed to green.')
      case 'patch'
         disp('Patch removed.')

Next create an axis, and a listener which is triggered when children are added:

% create a new axes and get its handle
a = hg.axes;
% create the listener
listen = handle.listener(a, 'ObjectChildAdded', @modifyAxesChildren);
% add a line
>> hg.line;
Color changed to green.
% try to add a patch
>> hg.patch;
Patch removed.

Removing a child with either the delete or the disconnect method generates an ObjectChildRemoved event. The delete method also generates the ObjectBeingDestroyed event. Changing a child’s parent with the up method generates an ObjectParentChanged event.

Reading an object’s properties with either dot notation or with the get method generates PropertyPreGet and PropertyPostGet events.

Changing the value of a property generates the PropertyPreSet and PropertyPostSet events. As we saw in the section on UDD properties, when the AbortSet access flag is ‘on’, property set events are only generated when a set operation actually changes the value of the property (as opposed to leaving it unchanged).

Note that the handle.listener syntax is slightly different for property events:

hProp = findprop(a, 'Value');
hListener = handle.listener(a,hProp,'PropertyPreGet',@displayEventInfo);

Java events

The final specialized event data object in the handle package is handle.JavaEventData. In Matlab, Java classes are not UDD classes, but each Java instance can have a UDD peer. The peer is created using the handle function. The Java peers are created in either UDD’s javahandle package or the javahandle_withcallbacks package. As their names imply, the latter enables listening to Java-triggered events using a Matlab callback.

To illustrate how this works we will create a Java Swing JFrame and listen for MouseClicked events:

% Create the Java Frame
javaFrame = javax.swing.JFrame;
javaFrame.setSize(200, 200);;
% Create a UDD peer for the new JFrame (two alternatives)
javaFramePeer = javaFrame.handle('CallbackProperties');  % alternative #1
javaFramePeer = handle(javaFrame, 'CallbackProperties');  % alternative #2
% Create the a listener for the Java MouseClicked event
listen = handle.listener(javaFramePeer, 'MouseClicked', @displayEventInfo);

a simple Java Swing JFrame

a simple Java Swing JFrame

When we click on the JFrame, our UDD peer triggers the callback:

The source object class is: javahandle_withcallbacks.javax.swing.JFrame
The event data class is: handle.JavaEventData

Since we created our peer in the javahandle_withcallbacks package, it is not necessary to create a listener using handle.listener. If we place our callback function handle in the MouseClickedCallback property it will be executed whenever the MouseClicked event is triggered. Such *Callback properties are automatically generated by Matlab when it creates the UDD peer (details).

clear listen
javaFramePeer.MouseClickedCallback = @displayEventInfo

This will work the same as before without the need to create and maintain a handle.listener object. If we had created our UDD peer in the javahandle package rather than javahandle_withcallbacks, we would not have the convenience of the MouseClickedCallback property, but we could still use the handle.listener mechanism to monitor events.

Creating callback properties for custom UDD classes

It is easy to add callback properties to user created UDD objects. The technique involves embedding a handle.listener object in the UDD object. To illustrate this, we add a SimpleEventCallback property to our simple.object, then use a SimpleEventListener property to hold our embedded handle.listener. Add the following to simple.object‘s schema.m definition file:

   % Property to hold our callback handle
   prop = schema.prop(simpleClass, 'SimpleEventCallback', 'MATLAB callback');
   prop.setFunction = @setValue;
   % hidden property to hold the listener for our callback
   prop = schema.prop(simpleClass, 'SimpleEventListener', 'handle');
   prop.Visible = 'off';
function propVal = setValue(self, value)
   %SETVALUE function to transfer function handle from callback property to listener
   self.SimpleEventListener.Callback = value;
   propVal = value;

Next we add the following to our simple.object constructor file:

% set the hidden listener property to a handle.listener
simpleObject.SimpleEventListener = handle.listener(simpleObject, 'simpleEvent', []);

Now if we set the SimpleObjectCallback property to a function handle, the handle is transferred to the embedded handle.listener Callback property. When a simpleEvent event is generated, our SimpleEventCallback function will be executed.

This series will conclude next week with a look at the special relationship between UDD and Java.

]]> 32
Introduction to UDD Wed, 16 Feb 2011 18:00:09 +0000
Related posts:
  1. Creating a simple UDD class This article explains how to create and test custom UDD packages, classes and objects...
  2. UDD Events and Listeners UDD event listeners can be used to listen to property value changes and other important events of Matlab objects...
  3. New information on HG2 More information on Matlab's new HG2 object-oriented handle-graphics system...
  4. Multi-column (grid) legend This article explains how to use undocumented axes listeners for implementing multi-column plot legends...
I would like to welcome guest blogger Donn Shull. Donn will present a series of articles about UDD classes and objects, on which many undocumented Matlab features and functions are based.

Background on UDD

Matlab has used objects for a long time. In R8 (Matlab 5.0), their first user accessible class system was introduced. Andy Register wrote a detailed reference on using this system. Although that original system is obsolete, it is still available in R24 (R2010b).

UDD objects (also referred to as schema objects) were introduced with R12 (Matlab 6.0). UDD has been a foundation platform for a number of core Matlab technologies. MathWorks have consistently maintained that UDD is only meant for internal development and not for Matlab users. So, while UDD has no formal documentation, there are plenty of examples and tools to help us learn about it.

It is somewhat odd that despite Matlab’s new object-oriented system (MCOS)’s introduction 3 years ago, and the ongoing concurrent development of HG2 classes, the older-technology UDD is still being actively developed, as evidenced by the increasing number of UDD classes in recent releases. More background on the differences between these different sets of classes can be found here.

Why should we bother learning UDD?

There are some things to consider before deciding if you want to spend the time to learn about the UDD class system:

The case against studying UDD classes

  • There is no documentation from The MathWorks for these classes
  • You will not get any help from The MathWorks in applying these classes
  • The UDD system is now more than a decade old and may be phased out in future Matlab releases (perhaps in HG2?)

The case for studying UDD classes

  • UDD is currently the foundation of handle graphics, Java integration, COM, and Simulink
  • The m code versions of UDD may be considered a forerunner of the newer MCOS class system
  • To avoid memory leaks when using Callbacks in GUI applications you currently need to use UDD
  • UDD techniques facilitate Matlab interaction with Java GUIs
  • UDD directly supports the Matlab style method invocation as well as dot notation for methods without the need to write subsasgn and subsref routines

Tools for Learning about UDD

We start by describing some undocumented Matlab tools that will help us investigate and understand UDD classes.

  • findpackage – All UDD Classes are defined as members of a package. findpackage takes the package name as an input argument and returns a schema.package object which provides information about the package
  • findclass – This method of the schema.package object returns a schema.class object of the named class if the class exists in the package
  • classhandle – For a given UDD object classhandle returns a schema.class object with information about the class. classhandle and findclass are two ways of getting the same information about a UDD class. findclass works with a schema.package object and a class name and does not require an instance of the class. classhandle works with an instance of a class
  • findprop – This method of the schema.class object returns a schema.prop object which contains information about the named property
  • findevent – This method of the schema.class object returns a schema.prop object which contains information about the named event
  • handle – handle is a multifaceted and unique term for The MathWorks. There are both UDD and MCOS handle classes. There is a UDD handle package. In terms of the tools we need, handle is also an undocumented function which converts a numeric handle into a UDD handle object. Depending on your background you may want to think of handle as a cast operator which casts a numeric handle into a UDD object.
  • methods – This is used to display the methods of an object
  • methodsview – Provides a graphic display of an objects methods
  • uiinspect – Yair Altman’s object inspection tool, which can be used for COM, Java and Matlab classes (uiinspect will be described in a separate article in the near future).

Before we apply these tools we need to discuss the basic structure of UDD classes. Let’s compare them with the newer, well documented MCOS classes:

MCOS classes can be defined simply as a standalone class or scoped by placing the class in a package or a hierarchy of packages. With UDD, all classes must be defined in a package. UDD Packages are not hierarchical so a UDD package may not contain other packages. UDD classes can always be instantiated with syntax of packageName.className. By default MCOS classes are value classes. With MCOS you can subclass the handle class to create handle classes. UDD classes are handle classes by default, but it is possible to create UDD value classes.

Exploring some important built-in UDD Classes

The current versions of Matlab include a number of built-in UDD packages. We will use our new tools to see what we can learn about these packages. Let us begin by inspecting the two packages that form the basis of the UDD class system.

The schema package

The built-in schema package contains the classes for creating user written UDD classes. It also is used to provide meta information about UDD classes. Using findpackage we will obtain a schema.package object for the schema package and then use it obtain information about the classes it contains:

>> pkg = findpackage('schema')
pkg =
>> pkg.get
               Name: 'schema'
    DefaultDatabase: [1x1 handle.Database]
            Classes: [9x1 schema.class]
          Functions: [0x1 handle]
        JavaPackage: ''
         Documented: 'on'

Note that here we have used the dot-notation pkg.get – we could also have used the Matlab notation get(pkg) instead.

We have now learned that that there are nine classes in the schema package. The information about them in a schema package’s Classes property. To see the information about individual classes we inspect this property:

>> pkg.Classes(1).get
               Name: 'class'
            Package: [1x1 schema.package]
        Description: ''
        AccessFlags: {0x1 cell}
             Global: 'off'
             Handle: 'on'
       Superclasses: [0x1 handle]
    SuperiorClasses: {0x1 cell}
    InferiorClasses: {0x1 cell}
            Methods: [4x1 schema.method]
         Properties: [13x1 schema.prop]
             Events: []
     JavaInterfaces: {0x1 cell}

Not surprisingly, the first class in the schema.package is ‘class’ itself. Here we can see that schema.class has 4 methods and 13 properties. We can also see that the schema.class objects have a Name property. Let’s use that information to list all the classes in the schema package:

>> names = cell(numel(pkg.Classes), 1);
>> for index = 1:numel(names), names{index} = pkg.Classes(index).Name; end;
>> names
names =

These are the base classes for the UDD package schema. To illustrate a different way to get information, let’s use the findclass method of schema.package to get information about the schema.prop class:

>> p = findclass(pkg, 'prop')
p =
>> get(p)
               Name: 'prop'
            Package: [1x1 schema.package]
        Description: ''
        AccessFlags: {0x1 cell}
             Global: 'off'
             Handle: 'on'
       Superclasses: [0x1 handle]
    SuperiorClasses: {0x1 cell}
    InferiorClasses: {0x1 cell}
            Methods: [2x1 schema.method]
         Properties: [9x1 schema.prop]
             Events: []
     JavaInterfaces: {0x1 cell}

The handle package

The second basic UDD package is the handle package. Handle holds a special place in Matlab and has multiple meanings: Handle is a type of Matlab object that is passed by reference; handle is a function which converts a numeric handle to an object; handle is an abstract object in the new MCOS class system and handle is also a UDD package as well as the default type for UDD objects.

There is an interesting connection between UDD and MCOS that involves handle. In Matlab releases R12 through R2007b, the UDD handle package had up to 12 classes and did not have any package functions (package functions are functions which are scoped to a package; their calling syntax is [outputs] = packageName.functionName(inputs)).

Beginning with the formal introduction of MCOS in R2008a, the abstract MCOS class handle was introduced. The MCOS handle class has 12 methods. It also turns out that beginning with R2008a, the UDD handle package has 12 package functions which are the MCOS handle methods.

The 12 UDD classes in the handle package fall into two groups: The database and transaction classes work with the schema.package to provide a UDD stack mechanism; the listener and family of EventData classes work with schema.event to provide the UDD event mechanism:

>> pkg = findpackage('handle')
pkg =
>> pkg.get
               Name: 'handle'
    DefaultDatabase: [1x1 handle.Database]
            Classes: [12x1 schema.class]
          Functions: [12x1 schema.method]
        JavaPackage: ''
         Documented: 'on'
>> names = cell(numel(pkg.Classes), 1);
>> for index = 1:numel(names), names{index} = pkg.Classes(index).Name; end
>> names
names =

The hg package

Arguably the most important UDD package in Matlab is the handle graphics package hg. Among the built-in UDD packages, hg is unique in several respects. As Matlab has evolved from R12 through R2011a, the number of default classes in the hg package has nearly doubled going from 17 classes to 30 (UDD has a mechanism for automatically defining additional classes as needed during run-time).

The hg package contains a mixture of Global and non Global classes. These classes return a numeric handle, unless they have been created using package scope. The uitools m-file package provides a great example of extending built-in UDD classes with user written m-file UDD classes.

The UDD class for a Handle-Graphics object can be obtained either by explicitly creating it with the hg package, or using the handle function on the numeric handle obtained from normal hg object creation. Using figure as an example, you can either use figh = hg.figure or fig = figure followed by figh = handle(fig):

>> pkg = findpackage('hg')
pkg =
>> pkg.get
               Name: 'hg'
    DefaultDatabase: [1x1 handle.Database]
            Classes: [30x1 schema.class]
          Functions: [0x1 handle]
        JavaPackage: 'com.mathworks.hg'
         Documented: 'on'
>> for index = 1:numel(names), names{index} = pkg.Classes(index).Name; end
>> names
names =

So far we have just explored the very basic concepts of UDD. You may well be wondering what the big fuss is about, since the information presented so far does not have any immediately-apparent benefits.

The following set of articles will describe more advanced topics in UDD usage and customizations, using the building blocks presented today. Hopefully you will quickly understand how using UDD can help achieve some very interesting stuff with Matlab.

]]> 7
Multi-column (grid) legend Mon, 07 Feb 2011 18:00:04 +0000
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  3. Controlling plot data-tips Data-tips are an extremely useful plotting tool that can easily be controlled programmatically....
  4. getundoc – get undocumented object properties getundoc is a very simple utility that displays the hidden (undocumented) properties of a specified handle object....
I would like to welcome guest blogger Adrian Cherry. Adrian will describe a very handy utility that shows how basic built-in Matlab functions can be improved and customized by just a bit of fiddling under Matlab’s hood.

Legend Plotting

Whilst I enjoy using the many time saving features of Matlab, one area where I feel it suffers is the technical plotting and annotation. This tale relates the development of a legend plotting routine, gridLegend, in an effort to improve the presentation.

In my day job we have a requirement to condense a large quantity of data onto summary charts. However, there is only so much data consolidation possible before you start losing the information required. We often need to plot 40 or 50 lines of test data to visualize trends or outliers, using the legend to identify the number of test hours against each test specimen.

Using the standard Matlab legend function resulted in a long legend over twice the size of the associated plot:

Standard Matlab legend

Standard Matlab legend

I wanted some way of generating a more compact legend format.

Fortunately earlier in the year, an entry on Matlab Central allowing a multi-column legend to be generated was posted, columnlegend. Although lacking some features, columnlegend gave me a good start on developing what I wanted for a multi column legend, culminating in gridLegend:

Multi-column legend

Multi-column legend

Delving into the Undocumented Matlab

So where is the link with undocumented Matlab?

As mentioned in the original columnlegend entry, it was relatively simple to redraw the legend as required on the screen. However, as soon as the figure was printed or exported to an image file, internal Matlab workings would redraw the figure, including the legend, thereby undoing my careful legend crafting, squeezing it back into one column (Yuck!):

Matlab-reverted multi-column legend

Matlab-reverted multi-column legend

As we wanted to automatically output images files, I had to delve into the hidden areas of Matlab to try to solve this problem.

My initial thought was to find out where the figure got redrawn for printing or export and override the standard legend call with a call to my new function. I couldn’t find the obvious culprit, stepping as far as I could through the print function there didn’t appear to be any call to the legend function.

In my search for information on how the legend worked I found the undocumented Matlab article about generating dynamic legends. This dynamic-legend post covered details about attaching a listener to a child of the legend axes, in Matlab the legend function creates its own set of axes on the figure to display the legend.

Armed with the information that legend axes objects could have listeners attached, I considered that these might be the source of redrawing the legend for printing. So with the legend I had generated I took a look at what listeners were attached, using the undocumented hidden axes property ScribeLegendListeners:

>> legendListener = get(gca,'ScribeLegendListeners')
legendListener = 
        fontname: [1x1 handle.listener]
        fontsize: [1x1 handle.listener]
      fontweight: [1x1 handle.listener]
       fontangle: [1x1 handle.listener]
       linewidth: [1x1 handle.listener]
         deleted: [1x1 handle.listener]
    proxydeleted: [1x1 handle.listener]

The font size and line positioning were all being redrawn for printing so this was potentially the source of my problem. However I’d not looked at a handle.listener before, so a little further digging was required:

K>> get(legendListener.fontname)
      SourceObject: [1x1 schema.prop]
         Container: [1x1 axes]
         EventType: 'PropertyPostSet'
          Callback: {2x1 cell}
    CallbackTarget: []
           Enabled: 'on'

The option Enabled immediately drew my attention, and so the following lines were added to my gridLegend function to switch off these listeners and apply it back to the legend:

LL = get(gca,'ScribeLegendListeners');

Finally allowing me to output the image files with a multi-column legend:

Printed multi-column legend

Printed multi-column legend

So my thanks to the contributors on Matlab Central who enabled me to get started on gridLegend and to Yair for collating the many nuggets of information on Undocumented Matlab which allowed me to complete the function and get it posted on Matlab Central.

Multi-column legend in action

Multi-column legend in action

]]> 5
Matlab callbacks for Java events Tue, 30 Nov 2010 22:09:35 +0000
Related posts:
  1. setPrompt – Setting the Matlab Desktop prompt The Matlab Desktop's Command-Window prompt can easily be modified using some undocumented features...
  2. UDD and Java UDD provides built-in convenience methods to facilitate the integration of Matlab UDD objects with Java code - this article explains how...
  3. Types of undocumented Matlab aspects This article lists the different types of undocumented/unsupported/hidden aspects in Matlab...
  4. Disabling menu entries in deployed docked figures Matlab's standard menu items can and should be removed from deployed docked figures. This article explains how. ...
A few days ago, a user posted a question on StackOverflow asking whether it is possible to trap a Java-based event in a Matlab callback.IB-Matlab connectivity (Matlab and TWS may be on separate computers)

It so happens that only a few weeks ago I completed a consulting project which required exactly this. The project was to integrate a Matlab computational engine with a Java interface to Interactive Brokers (IB) – a well-known online brokerage firm. The idea was to use the Java interface to fetch real-time data about securities (stocks, bonds, options etc.), use a Matlab processing utility, then use the Java interface again to send Buy or Sell orders back to IB.

If you are interested in the final result (IB-Matlab, a complete and field-tested Matlab-IB interface), look here.

The challenge

A big challenge in this project (aside from handling quite a few IB interface quirks), was to propagate events from the Java interface to the Matlab application. This had to be done asynchronously, since events such as order execution can occur at any time following the order placement. Moreover, even simple requests such as retrieving security information (bid/ask prices for example) is handled by IB via Java events, not as simple function return values.

Handling Java-based events in Matlab is not a trivial task. Not only merely undocumented, but it is also not intuitive. I have spent quite a few hours trying to crack this issue. In fact, I believe it was one of my more challenging tasks in figuring out the undocumented aspects of the Matlab-Java interface. Few other challenges were as difficult, yet with a happy ending (Drag & Drop is a similar issue – I will describe it in another article sometime).

The solution

Fast-forward all the fruitless attempted variations, here is the bottom line. Refer to the following simple Java class example:

public class EventTest
    private java.util.Vector data = new java.util.Vector();
    public synchronized void addMyTestListener(MyTestListener lis) {
    public synchronized void removeMyTestListener(MyTestListener lis) {
    public interface MyTestListener extends java.util.EventListener {
        void testEvent(MyTestEvent event);
    public class MyTestEvent extends java.util.EventObject {
        private static final long serialVersionUID = 1L;
        public float oldValue,newValue;        
        MyTestEvent(Object obj, float oldValue, float newValue) {
            this.oldValue = oldValue;
            this.newValue = newValue;
    public void notifyMyTest() {
        java.util.Vector dataCopy;
        synchronized(this) {
            dataCopy = (java.util.Vector)data.clone();
        for (int i=0; i < dataCopy.size(); i++) {
            MyTestEvent event = new MyTestEvent(this, 0, 1);

When compiling, three class files are created: EventTest.class, EventTest$MyTestEvent.class and EventTest$MyTestListener.class. Place them on Matlab’s Java static classpath, using edit(‘classpath.txt’) (using the dynamic classpath causes many problems that using the static classpath solves). They can now be accessed as follows:

>> which EventTest
EventTest is a Java method  % EventTest constructor
>> evt = EventTest
evt =
>> evt.get
	Class = [ (1 by 1) java.lang.Class array]
	TestEventCallback = 
	TestEventCallbackData = []
	BeingDeleted = off
	ButtonDownFcn = 
	Children = []
	Clipping = on
	CreateFcn = 
	DeleteFcn = 
	BusyAction = queue
	HandleVisibility = on
	HitTest = on
	Interruptible = on
	Parent = []
	Selected = off
	SelectionHighlight = on
	Tag = 
	Type = EventTest
	UIContextMenu = []
	UserData = []
	Visible = on
>> set(evt)
	TestEventCallback: string -or- function handle -or- cell array
>> set(evt,'TestEventCallback',@(h,e)disp(h))
>> get(evt)
	Class = [ (1 by 1) java.lang.Class array]
	TestEventCallback = [ (1 by 1) function_handle array]    % < = ok
	TestEventCallbackData = []
>> evt.notifyMyTest   % invoke Java event
              0.0009765625   % < = Matlab callback

Note how Matlab automatically converted the Java event testEvent, declared in interface MyTestListener, into a Matlab callback TestEventCallback (the first character is always capitalized). All Java events are automatically converted in this fashion, by appending a ‘Callback’ suffix. Here is a code snippet from R2008a’s \toolbox\matlab\uitools\@opaque\addlistener.m that shows this (slightly edited):

hSrc = handle(jobj,'callbackproperties');
allfields = sortrows(fields(set(hSrc)));
for i = 1:length(allfields)
   fn = allfields{i};
   if ~isempty(findstr('Callback',fn))
callback = @(o,e) cbBridge(o,e,response);
hdl = handle.listener(handle(jobj), eventName, callback);
function cbBridge(o,e,response)
   hgfeval(response, java(o), e.JavaEvent)

Note that hgfeval, which is used within the cbBridge callback function, is a semi-documented pure-Matlab built-in function, which I described a few weeks ago.

If several events have the same case-insensitive name, then the additional callbacks will have an appended underscore character (e.g., ‘TestEventCallback_’):

// In the Java class:
public interface MyTestListener extends java.util.EventListener
    void testEvent(MyTestEvent e);
    void testevent(TestEvent2 e);
% …and back in Matlab:
>> evt=EventTest; evt.get
	Class = [ (1 by 1) java.lang.Class array]
	TestEventCallback = 
	TestEventCallbackData = []
	TestEventCallback_ = 
	TestEventCallback_Data = [] 

To complete this discussion, it should be noted that Matlab also automatically defines corresponding Events in the Java object’s classhandle. Unfortunately, classhandle events are not differentiated in a similar manner – in this case only a single event is created, named Testevent. classhandle events, and their relationship to the preceding discussion, will be described in Donn Scull’s upcoming series on UDD.

An alternative to using callbacks on Java events, as shown above, is to use undocumented handle.listeners:

hListener = handle.listener(handle(evt),'TestEvent',callback);

There are several other odds and ends, but this article should be sufficient for implementing a fully-functional Java event handling mechanism in Matlab. Good luck!

p.s. – if you’re still stuck, consider hiring me for a short consulting project. I’ll be happy to help.

]]> 86
Inactive Control Tooltips & Event Chaining Wed, 24 Feb 2010 22:34:46 +0000
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  2. Customizing Matlab labels Matlab's text uicontrol is not very customizable, and does not support HTML or Tex formatting. This article shows how to display HTML labels in Matlab and some undocumented customizations...
  3. Continuous slider callback Matlab slider uicontrols do not enable a continuous-motion callback by default. This article explains how this can be achieved using undocumented features....
  4. The javacomponent function Matlab's built-in javacomponent function can be used to display Java components in Matlab application - this article details its usages and limitations...
Once again, I welcome guest blogger Matt Whitaker, who continues his series of articles.

In my last post I explored some tips on tooltips. One of these tips involved displaying tooltips on disabled uicontrols. I explained that displaying tooltips on inactive controls is problematic since Matlab appears to intercept mouse events to these inactive controls, so even setting the tooltip on the underlying Java object will not work: The java object appears not to receive the mouse-hover event and therefore does not “know” that it’s time to display the tooltip.

When Yair and I deliberated this issue, he pointed me to his comment on a previous article showing an undocumented Java technique (Java also has some…) for forcing a tooltip to appear using the ActionMap of the uicontrol’s underlying Java object to get at a postTip action. We discussed using a WindowButtonMotionFcn callback to see if the mouse was above the inactive control, then triggering the forced tooltip display. Yair then went on to remind me and I quote: “you’ll need to chain existing WindowButtonMotionFcn callbacks and take into account ModeManagers that override them.”

Frankly, having written code previously that handles callback chaining, I would rather poke myself in the eye with a fork!

The Image Processing Toolbox has the nice pair of iptaddcallback and iptremovecallback functions that largely handle these issues. But for general Matlab, there seemed to be no alternative until I remembered that events trigger callbacks. I decided to use a listener for the WindowButtonMotion event to detect the mouse motion. Event listeners were briefly explained two weeks ago and deserve a dedicated future article. The advantage of using an event listener is that we don’t disturb any existing WindowButtonMotionFcn callback. We still need to be somewhat careful that our listeners don’t do conflicting things, but it’s a lot easier than trying to manage everything through the single WindowButtonMotionFcn.

A demonstration of this appears below with some comments following (note that this code uses the FindJObj utility):

function inactiveBtnToolTip
  %Illustrates how to make a tooltip appear on an inactive control
  h = figure('WindowButtonMotionFcn',@windowMotion,'Pos',[400,400,200,200]);
  col = get(h,'color');
  lbl = uicontrol('Style','text', 'Pos',[10,160,120,20], ...
                  'Background',col, 'HorizontalAlignment','left');
  btn = uicontrol('Parent',h, 'String','Button', ...
                  'Enable','inactive', 'Pos',[10,40,60,20]);
  uicontrol('Style','check', 'Parent',h, 'String','Enable button tooltip', ...
            'Callback',@chkTooltipEnable, 'Value',1, ...
            'Pos',[10,80,180,20], 'Background',col);
  %create the tooltip and postTip action
  jBtn = findjobj(btn);
  import java.awt.event.ActionEvent;
  javaMethodEDT('setToolTipText',jBtn,'This button is inactive');
  actionMap = javaMethodEDT('getActionMap',jBtn);
  action = javaMethodEDT('get',actionMap,'postTip');
  actionEvent = ActionEvent(jBtn, ActionEvent.ACTION_PERFORMED, 'postTip');
  %get the extents plus 2 pixels of the control to compare to the mouse position
  btnPos = getpixelposition(btn)+[-2,-2,4,4]; %give a little band around the control
  left = btnPos(1);
  right = sum(btnPos([1,3]));
  btm = btnPos(2);
  top =  sum(btnPos([2,4]));
  % add a listener on mouse movement events
  tm = javax.swing.ToolTipManager.sharedInstance; %tooltip manager
  pointListener = handle.listener(h,'WindowButtonMotionEvent',@figMouseMove);
  %inControl is a flag to prevent multiple triggers of the postTip action
  %while mouse remains in the button
  inControl = false;
  function figMouseMove(src,evtData) %#ok
    %get the current point
    cPoint = evtData.CurrentPoint;
    if cPoint(1) >= left && cPoint(1) <= right &&...
       cPoint(2) >= btm  && cPoint(2) <= top
      if ~inControl %we just entered
        inControl = true;
        action.actionPerformed(actionEvent); %show the tooltip
      end %if
      if inControl %we just existed
        inControl = false;
        %toggle to make it disappear when leaving button
      end %if
    end %if
  end %gpMouseMove
  function windowMotion(varargin)
    %illustrate that we can still do a regular window button motion callback
    set(lbl,'String',sprintf('Mouse position: %d, %d',get(h,'CurrentPoint')));
  end %windowMotion
  function chkTooltipEnable(src,varargin)
    if get(src,'Value')
    end %if
  end %chkTooltipEnable
end %inactiveBtnToolTip

Tooltip on an inactive button

Tooltip on an inactive button

Comments on the code:

  1. The code illustrates that we can successfully add an additional listener to listen for mouse motion events while still carrying out the original WindowButtonMotionFcn callback. This makes chaining callbacks much easier.
  2. The handle.listener object has an Enable property that we can use to temporarily turn the listener on and off. This can be seen in the chkTooltipEnable() callback for the check box in the code above. If we wanted to permanently remove the listener we would simply use delete(pointListener). Note that addlistener adds a hidden property to the object being listened to, so that the listener is tied to the object’s lifecycle. If you create a listener directly using handle.listener you are responsible for it’s disposition. Unfortunately, addlistener fails for HG handles on pre-R2009 Matlab releases, so we use handle.listener directly.
  3. The code illustrates a good practice when tracking rapidly firing events like mouse movement of handling reentry into the callback while it is still processing a previous callback. Here we use a flag called inControl to prevent the postTip action being continuously fired while the mouse remains in the control.
  4. I was unable to determine if there is any corresponding action for the postTip to dismiss tips so I resorted to using the ToolTipManager to toggle its own Enable property to cleanly hide the tooltip as the mouse leaves the control.

Each Matlab callback has an associated event with it. Some of the ones that might be immediately useful at the figure-level are WindowButtonDown, WindowButtonUp, WindowKeyPress, and WindowKeyRelease. They can all be accessed through handle.listener or addlistener as in the code above.

Unfortunately, events do not always have names that directly correspond to the callback names. In order to see the list of available events for a particular Matlab object, use the following code, which relies on another undocumented function – classhandle. Here we list the events for gcf:

>> get(get(classhandle(handle(gcf)),'Events'),'Name')
ans = 

Note that I have made extensive use of the javaMethodEDT function to execute Java methods that affect swing components on Swing’s Event Dispatch Thread. I plan to write about this and related functions in my next article.

]]> 8
Continuous slider callback Mon, 08 Feb 2010 09:13:39 +0000
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Every few months, a CSSM forum reader asks how to set up a continuously-invoked slider callback: Matlab’s slider uicontrol invokes the user callback only when the mouse button is released, and not continuously while the slider’s thumb is dragged. This functionality was again referred-to yesterday, and I decided it merits a dedicated post.

There are three distinct simple ways to achieve continuous callbacks:

Using Java callbacks

As explained in an earlier article, Matlab uicontrols are basically Java Swing objects that possess a large number of useful callbacks. Matlab sliders’ underlying Java objects, which are really not JSliders but JScrollBars, have an AdjustmentValueChangedCallback property that is useful for our purposes and is accessible using the FindJObj utility. Simply download FindJObj from the File Exchange, and then:

hSlider = uicontrol('style','slider', ...);
jScrollBar = findjobj(hSlider);
jScrollBar.AdjustmentValueChangedCallback = @myCbFcn;
% or: set(jScrollBar,'AdjustmentValueChangedCallback',@myCbFcn)

Where myCbFcn is the Matlab callback function that will be invoked continuously when the arrow buttons are depressed or the slider’s thumb is dragged.

Using an event listener

An alternative to the Java route is to use Matlab’s undocumented handle.listener function to listen to the slider’s Action event, as follows:

hListener = handle.listener(hSlider,'ActionEvent',@myCbFcn);
setappdata(hSlider,'sliderListener',hListener);  % this is important - read below

This alternative is used by Matlab’s own imscrollpanel function:

if isJavaFigure
   % Must use these ActionEvents to get continuous events fired as slider
   % thumb is dragged. Regular callbacks on sliders give only one event
   % when the thumb is released.
   hSliderHorListener = handle.listener(hSliderHor,...
   hSliderVerListener = handle.listener(hSliderVer,...
      [hSliderHorListener hSliderVerListener]);
   % Unfortunately, the event route is only available with Java Figures,
   % so platforms without Java Figure support get discrete events only
   % when the mouse is released from dragging the slider thumb.

In this case, hScrollpanel is merely a handle to a panel in Matlab’s imscrollpanel code. You can use any Matlab control to store the listener handle, including hSlider itself, which would be simplest. It doesn’t matter where or how exactly you store hListener, since you will not use it directly in your program. The important thing is just to store it *anywhere*, so that it remains in persistent (heap) memory. As long as the reference handle is “alive”, the listener will keep working. This is explained here.

Addedndum 2014-08-20: In R2014a the event name has changed from ActionEvent to ContinuousValueChange. Also, handle.listener will not work in the upcoming HG2. Therefore, it would be best to use the following code snippet instead:

try    % R2013b and older
catch  % R2014a and newer

Using a property listener

The handle.listener function can also be used to listen to property value changes. In our case, set a post-set listener, that gets triggered immediately following Value property updates, as follows:

hhSlider = handle(hSlider);
hProp = findprop(hhSlider,'Value');
try    % R2014b and newer
   % hProp is a object
catch  % R2014a and older
   % hProp is a schema.prop object
   hListener = handle.listener(hhSlider,hProp,'PropertyPostSet',@myCbFcn);
   setappdata(hSlider,'sliderListener',hListener);  % this is important - read above

In addition to ‘PostSet’, we could also listen on ‘PreSet’, which is triggered immediately before the property is modified. There are also corresponding ‘*Get’ options.

Do you know of any other way to achieve continuous callbacks? If so, I would be delighted to hear in the comments section below.

]]> 56
setPrompt – Setting the Matlab Desktop prompt Mon, 25 Jan 2010 15:30:54 +0000
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A few days ago, a reader emailed me with a challenge to modify the standard matlab Command-Window prompt from “>> ” to some other string, preferably a dynamic prompt with the current timestamp. At first thought this cannot be done: The Command-Window prompts are hard-coded and to the best of my knowledge cannot be modified via properties or system preferences.

So the prompt can (probably) not be modified in advance, but what if it could be modified after being displayed? It is true that my cprintf utility modifies the Command-Window contents in order to display formatted text in a variety of font colors. But this case is different since cprintf runs once synchronously (user-invoked), whereas the prompt appears asynchronously multiple times.

There are two methods of handling multiple asynchronous events in Matlab: setting a callback on the object, and setting a PostSet handle.listener (or schema.listener) on the relevant object property. The first of these methods is a well-known Matlab practice, although we shall see that it uses an undocumented callback and functionality; the PostSet method is entirely undocumented and not well-known and shall be described in some later article. I decided to use the callback method to set the prompt – interested readers can try the PostSet method.

Setting the Command Window’s callback

The solution involved finding the Command-Window reference handle, and setting one of its many callbacks, in our case CaretUpdateCallback. This callback is fired whenever the desktop text is modified, which is an event we trap to replace the displayed prompt:

% Get the reference handle to the Command Window text area
jDesktop = com.mathworks.mde.desk.MLDesktop.getInstance;
  cmdWin = jDesktop.getClient('Command Window');
  jTextArea = cmdWin.getComponent(0).getViewport.getComponent(0);
  jTextArea = jDesktop.getMainFrame.getFocusOwner;
% Instrument the text area's callback
if nargin && ~isempty(newPrompt) && ~strcmp(newPrompt,'>> ')

Now that we have the Command-Window object callback set, we need to set the logic of prompt replacement – this is done in the internal Matlab function setPromptFcn. Here is its core code:

% Does the displayed text end with the default prompt?
% Note: catch a possible trailing newline
try jTextArea =;  catch,  end  %#ok
cwText = get(jTextArea,'Text');
pos = strfind(cwText(max(1,end-3):end),'>> ');
if ~isempty(pos)
  % Short prompts need to be space-padded
  newLen = jTextArea.getCaretPosition;
  if length(newPrompt)<3
    newPrompt(end+1:3) = ' ';
  elseif length(newPrompt)>3
    fprintfStr = newPrompt(1:end-3);
    newLen = newLen + length(fprintfStr);
  % The Command-Window text should be modified on the EDT
            newPrompt(end-2:end), newLen-3, newLen);

In this code snippet, note that we space-pad prompt string that are shorter than 3 characters: this is done to prevent an internal-Matlab mixup when displaying additional text – Matlab “knows” the Command-Window’s text position and it gets mixed up if it turns out to be shorter than expected.

Also note that I use the semi-documented awtinvoke function to replace the default prompt (and an automatically-appended space) on the Event-Dispatch Thread (more on this in a future article). Since Matlab R2008a, I could use the more convenient javaMethodEDT function, but I wanted my code to work on all prior Matlab 7 versions, where javaMethodEDT was not yet available.

Preventing callback re-entry

The callback snippet above would enter an endless loop if not changed: whenever the prompt is modified the callback would have been re-fired, the prompt re-modified and so on endlessly. There are many methods of preventing callback re-entry – here’s the one I chose:

function setPromptFcn(jTextArea,eventData,newPrompt)
  % Prevent overlapping reentry due to prompt replacement
  persistent inProgress
  if isempty(inProgress)
    inProgress = 1;  %#ok unused
    % *** Prompt modification code goes here ***
    % force prompt-change callback to fizzle-out...
    % Never mind - ignore errors...
  % Enable new callbacks now that the prompt has been modified
  inProgress = [];
end  % setPromptFcn

Handling multiple prompt types

I now wanted my function to handle both static prompt strings (like: ‘[Yair] ‘) and dynamic prompts (like: ‘[25-Jan-2010 01:00:51] ‘). This is done by accepting string-evaluable strings/functions:

% Try to evaluate the new prompt as a function
  origNewPrompt = newPrompt;
  newPrompt = feval(newPrompt);
    newPrompt = eval(newPrompt);
    % Never mind - probably a string...
if ~ischar(newPrompt) && ischar(origNewPrompt)
  newPrompt = origNewPrompt;

File Exchange submission

I then added some edge-case error handling and wrapped everything in a single utility called setPrompt that is now available on the File Exchange.

In the future, if I find time, energy and interest, maybe I’ll combine cprintf‘s font-styling capabilities, to enable setting colored prompts.

Setting a continuously-updated timestamp prompt

Using the code above, we can now display a dynamic timestamp prompt, as follows:

setPrompt usage examples

setPrompt usage examples

However, the displayed timestamp is somewhat problematic in the sense that it indicates the time of prompt creation rather than the time that the associated Command-Window command was executed. In the screenshot above, [25-Jan-2010 01:29:42] is the time that the 234 command was executed, not the time that the setPrompt command was executed. This is somewhat misleading. It would be better if the last (current) timestamp was continuously updated and would therefore always display the latest command’s execution time. This can be done using a Matlab timer as follows:

% This is entered in the main function before setting the prompt:
if nargin && strcmpi(newPrompt,'timestamp')
  % Update initial prompt & prepare a timer to continuously update it
  newPrompt = @()(['[',datestr(now),'] ']);
  start(timer('Tag','setPromptTimer', 'Name','setPromptTimer', ...
              'ExecutionMode','fixedDelay', 'ObjectVisibility','off', ...
              'Period',0.99, 'StartDelay',0.5, ...
% Stop & delete any existing prompt timer(s)
function stopPromptTimers
    timers = timerfindall('tag','setPromptTimer');
    if ~isempty(timers)
    % Never mind...
end  % stopPromptTimers
% Internal timer callback function
function setPromptTimerFcn(timerObj,eventData,jTextArea)
    try jTextArea =;  catch,  end  %#ok
    pos = getappdata(jTextArea,'setPromptPos');
    newPrompt = datestr(now);
              newPrompt, pos, pos+length(newPrompt));
    % Never mind...
end  % setPromptTimerFcn

Can you come up with some innovative prompts? If so, please share them in a comment below.

Update 2010-Jan-26: The code in this article was updated since it was first published yesterday.

]]> 13
EditorMacro v2 – setting Command Window key-bindings Thu, 20 Aug 2009 13:02:54 +0000
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  3. R2009b keyboard bindings The new Matlab release R2009b includes the ability to customize keyboard bindings for the editor and Command Window. However, there are still some uses for the EditorMacro utility and its...
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Some weeks ago, I introduced my EditorMacro utility as a means of assigning user-defined text strings and runnable macros (callbacks) to keyboard shortcuts in the Matlab Editor. I later showed how EditorMacro can be used to set non-textual editor macros.

Since then, I was contacted by several users with questions, enhancement requests and improvement suggestions. Of these, the most notable was from Perttu Ranta-aho who suggested (and provided sample code for) using the editor’s built-in actions. The next logical step was to extend this to support the editor menus, and then extend again to support Command Window key-bindings. We bounced several increasingly-powerful versions of the utility between us, until arriving at the version I uploaded yesterday, which has the following significant improvements over the first version:

  • several fixes: bugs, edge cases, stability (EDT etc.) etc.
  • support for built-in (native) Editor actions
  • support for built-in (native) Command-Window actions

Built-in native actions

It turns out that the Editor and Command-Window both have some ~200 built-in (native) available actions, about half of them common. Actions are identified by name, which is a lowercase dash-separated description like ‘selection-up’ (this format is familiar to Emacs users). Altogether, there are over 300 unique built-in actions which can be used, but only ~100 of them are assigned a default key-bindings. A few dozen actions have multiple assigned key-bindings. For example, the ‘selection-up’ action is assigned to both ‘shift pressed UP’ (=<shift>-<up>) and ‘shift pressed KP_UP’ (=<shift>-<Keypad-up>):

>> [bindings, actions] = EditorMacro
actions = 
 'selection-page-down'     'shift pressed PAGE_DOWN'     'editor native action'
 'selection-page-up'       'shift pressed PAGE_UP'       'editor native action'
 'selection-previous-word'                   {2x1 cell}  'editor native action'
 'selection-up'                              {2x1 cell}  'editor native action'
 'set-read-only'                                     []  'editor native action'
 'set-writable'                                      []  'editor native action'
 'shift-insert-break'      'shift pressed ENTER'         'editor native action'
 'shift-line-left'         'ctrl pressed OPEN_BRACKET'   'editor native action'
 'shift-line-right'        'ctrl pressed CLOSE_BRACKET'  'editor native action'
 'shift-tab-pressed'       'shift pressed TAB'           'editor native action'
 'toggle-typing-mode'      'pressed INSERT'              'editor native action'
 'uncomment'               'ctrl pressed T'              'editor native action'
 'undo'                    'ctrl pressed Z'              'editor native action'
 'unselect'                'pressed ESCAPE'              'editor native action'
 'adjust-window-bottom'                              []  'cmdwin native action'
 'adjust-window-top'                                 []  'cmdwin native action'
 'beep'                    'ctrl pressed G'              'cmdwin native action'
 'break-interrupt'         'ctrl pressed CANCEL'         'cmdwin native action'
 'toggle-typing-mode'      'pressed INSERT'              'cmdwin native action'
 'unselect'                'ctrl pressed BACK_SLASH'     'cmdwin native action'
 'new-mfile'               'ctrl pressed N'              'editor menu action'  
 'Figure'                                            []  'editor menu action'  

Even more interesting, apparently some 200 actions do not have any pre-assigned default key-bindings, such as ‘set-read-only’ and ‘set-writable’ in the snippet above. Let’s take the ‘match-brace’ action for example. This sounded promising so I assigned it an unused key-binding and indeed found that it can be very useful: if your cursor is placed on a beginning or end of some code, clicking the assigned key-binding will jump the cursor to the other end, and then back again. This works nicely for (..), [..], for..end, try..end, if..end, etc.

>> % Ensure that <Alt>-M is unassigned
>> bindings = EditorMacro('alt m')
bindings = 
   Empty cell array: 0-by-4
>> % Assign the key-binding and verify
>> EditorMacro('alt m','match-brace','run');
>> bindings = EditorMacro('alt m')
b = 
  'alt pressed M'  'match-brace'  'run'  'editor native action'

Implementation details

Interested readers of this post are encouraged to look within EditorMacro’s source code and see how the native actions and keybindings were retrieved and modified for the editor, Command-Window and menus. In a nutshell, the native action names and key-bindings are stored in a Java Map object. Here’s a code snippet:

%% Get all available actions even those without any key-binding
function actionNames = getNativeActions(hEditorPane)
    actionNames = {};
    actionKeys = hEditorPane.getActionMap.allKeys;
    actionNames = cellfun(@char,cell(actionKeys),'Uniform',0);
    actionNames = sort(actionNames);
    % never mind...
%% Get all active native shortcuts (key-bindings)
function accelerators = getAccelerators(hEditorPane)
    accelerators = cell(0,2);
    inputMap = hEditorPane.getInputMap;
    inputKeys = inputMap.allKeys;
    accelerators = cell(numel(inputKeys),2);
    for ii = 1 : numel(inputKeys)
      thisKey = inputKeys(ii);
      thisAction = inputMap.get(thisKey);
      accelerators(ii,:) = {char(thisKey), char(thisAction)};
    accelerators = sortrows(accelerators,1);
    % never mind...

The menu retrieval was more difficult: while it is possible to directly access the menubar reference (jMainPane.getRootPane.getMenuBar), the menu items themselves are not visible until their main menu item is clicked (displayed). The only way I know to access menu actions/keybindings is to read them from the individual menu items (if anyone knows a better way please tell me – perhaps some central key-listener repository?). Therefore, a simulation of the menu-click events is done and the menu hierarchy is traveled recuresively to collect all its actions and key-bindings.

A final note relates to the use of EDT. EDT really deserves a separate post, but in a nutshell it means that any action that affects the GUI needs to be invoked asynchronously (via the EDT) rather than synchronously (on the main Matlab thread). This is no real problem in the editor, but it is indeed an issue in the Command Window: If we do not use EDT there, we get ugly red stack-trace exceptions thrown on the Command Window whenever we run our EditorMacro-assigned macro. Here’s the code snippet that solves this:

   % Matlab 7
   %jEditorPane.insert(caretPosition, macro);  % better to use replaceSelection() than insert()
      % Try to dispatch on EDT
      awtinvoke(, 'replaceSelection', macro);
      % no good - try direct invocation
   % Matlab 6
   %jEditorPane.insert(macro, caretPosition);  % note the reverse order of input args vs. Matlab 7...
      % Try to dispatch on EDT
      awtinvoke(, 'replaceRange', macro, jEditorPane.getSelStart, jEditorPane.getSelEnd);
      % no good - try direct invocation
      jEditorPane.replaceRange(macro, jEditorPane.getSelStart, jEditorPane.getSelEnd);

Known limitations

Some limitations remain in EditorMacro – here are the major ones:

  • Multi-key bindings are still not reported properly, nor can they be assigned. For example, the editor menu action ‘to-lower-case’ has a pre-assigned default key-binding of <Alt>-<U>-<L>, but this is reported as unassigned. Of course, you can always add another (single-key) assignment for this action, for example: <Alt>-<Ctrl>-<L>
  • Menus are dynamically recreated whenever the Editor is docked/undocked, or a separate type of file is edited (e.g., switching from an m-file to a c-file). Similarly, whenever the active desktop window changes from the Command Window to another desktop-docked window (e.g., Command History). In all these cases, the dynamically recreated menus override any conflicting key-binding previously done with EditorMacro.
  • Unfortunately, my Matlab 6-installed computer crashed, so while the first version of EditorMacro works on ML6, the new version might well not. If you have ML6 available, please email me so I can post a working version with your help. This also means I won’t be able to post much about undocumented ML6 stuff in the future. Perhaps this is Fate’s way of telling me to progress with the times…
  • Key bindings are sometimes lost when switching between a one-document editor and a two-document one (i.e., adding/closing the second doc)
  • Key bindings are not saved between editor sessions
  • In split-pane mode, when inserting a text macro on the secondary (right/bottom) editor pane, then both panes (and the actual document) are updated but the secondary pane does not display the inserted macro (the primary pane looks ok).

The first couple of limitations have a non-perfect workaround that Perttu came up with. He implemented this in his KeyBindings utility on the Matlab File Exchange. Perhaps one day Perttu or me will find the time to merge these utilities into one.

Have you designed some crafty user-defined macro? or found some important unassigned built-in action? Please share your experience using EditorMacro in the comments section below.

]]> 4
Context-Sensitive Help Wed, 05 Aug 2009 18:20:26 +0000
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A recent CSSM thread about implementing a system-wide GUI help system got me working on a post to present Matlab’s built-in hidden/unsupported mechanism for context-sensitive help. There are many different ways in which such a system can be implemented (read that thread for some ideas), so Matlab users are by no means limited to Matlab’s built-in implementation. However, the built-in system certainly merits consideration for its simplicity and usefulness.

We start with Matlab’s cshelp function (%matlabroot%\toolbox\matlab\uitools\cshelp.m). cshelp is semi-documented, meaning that it has a help section but no doc, online help or official support. This useful function was grandfathered (made obsolete) in Matlab 7.4 (R2007a) for an unknown reason and to my knowledge without any replacement. cshelp is entirely based on m-code (no hidden internal or Java code) and is surprisingly compact and readable.

cshelp basically attaches two new properties (CSHelpMode and CSHelpData) to the specified figure (this is done using the schema.prop mechanism which will be described in a separate post), temporarily disables all active uicontrols, modifies the figure’s WindowButtonDownFcn callback and sets the mouse cursor (using setptr – another semi-documented function) to an arrow with a question mark.

Clicking any object in the figure’s main area (beneath the toolbar), causes the modified WindowButtonDownFcn callback to run whatever is stored in the figure’s HelpFcn property (string, @function_handle or {@function_handle, params, …} format). Here is a simple example taken from CSSM (thanks Jérôme):

Hfcn = 'str=get(gco,''type''); title([''Type :'' str])';
th = 0:0.314:2*pi;
uicontrol('units','normalized', 'position',[.45 .02 .1 .05]);

Simple context-sensitive help system

Simple context-sensitive help system

In order to exit CSHelp mode, the figure’s CSHelpMode property must be set to ‘off’. However, remember that all the figure’s uicontrols are disabled in CSHelp mode. Therefore, the user may use one or more of the following methods (other tactics are also possible, but the ones below seem intuitive):

  • Set the figure’s KeyPressFcn callback property to catch events (e.g., <ESC> key presses) and reset the CSHelpMode property from within the callback
  • Reset the CSHelpMode property at the end of the HelpFcn callback
  • Add a CS Help entry/exit option to the figure’s Help main menu
  • Add a CS Help entry/exit button to the figure toolbar

The following code sample implements all of these suggested tactics (the code to synchronize the states of the menu item and toolbar button is not presented):

% Set the <ESC> key press to exit CSHelp mode
keyFcn = ['if strcmp(get(gcbf,''CurrentKey''),''escape''), ' ...
             'set(gcbf,''CSHelpMode'',''off''); ' ...
% Exit CSHelp mode at the end of the CSHelp callback
helpFcn = 'title([''Type :'' get(gco,''type'')]); set(gcbf,''CSHelpMode'',''off'');';
% Add a CSHelp button to the figure toolbar
% Note: retrieve the button icon from the CSHelp cursor icon
hToolbar = findall(allchild(gcf),'flat','type','uitoolbar');
oldPtr = getptr(gcf);
ptrData = setptr('help');
set(gcf, oldPtr{:});
icon(:,:,1) = ptrData{4}/2;  % Convert into RGB TrueColor icon
icon(:,:,2) = ptrData{4}/2;
icon(:,:,3) = ptrData{4}/2;
cbFcn = 'set(gcbf,''CSHelpMode'',get(gcbo,''state''))';
csName = 'Context-sensitive help';
uitoggletool(hToolbar,'CData',icon, 'ClickedCallback',cbFcn, 'TooltipString',csName);
% Add a CSHelp menu option to the Help main menu
% Note: unlike other main menus, the Help menu tag is empty, so
% ^^^^  findall(gcf,'tag','figMenuHelp') is empty... Therefore,
%       we find this menu by accessing the Help/About menu item
helpAbout = findall(gcf,'tag','figMenuHelpAbout');
helpMenu = get(helpAbout,'parent');
cbFcn = ['if strcmp(get(gcbo,''Checked''),''on''), ' ...
             'set(gcbo,''Checked'',''off''); ' ...
         'else, ' ...
             'set(gcbo,''Checked'',''on''); ' ...
         'end; ' ...

Figure with context-sensitive help action in the main toolbar & menu

Figure with context-sensitive help action in the main toolbar & menu

cshelp has an additional optional argument, accepting another figure handle. This handle, if specified and valid, indicates a parent figure whose CSHelpMode, HelpFcn and HelpTopicMap properties should be shared with this figure (this is done using the handle.listener mechanism which will be described in a separate post). This option is useful when creating a multi-window GUI-wide context-sensitive help system. The user may then activate context-sensitive help in figure A and select the requested context object in figure B.

cshelp would normally be coupled with Matlab’s help system for non-trivial GUI implementations. The undocumented and hidden properties HelpTopicKey (of all handles) and HelpTopicMap (of figures), enable easy tie-in to the CSHelp system. A simplified sample is presented below:

      'set(gcbf,''CSHelpMode'',''off'');' ];
th = 0:0.314:2*pi;
hLine = plot(th,sin(th),'r-','linewidth',4);
set(gca,  'HelpTopicKey','MyCSHelpFile.html#Axes');

cshelp is by no way limited to presenting Matlab documentation: Refer to helpview‘s help section for an in-depth description of help maps and help topics. In a nutshell, helpview accepts any HTML webpage filepath (or webpage internal (#) reference), followed by optional parameter ‘CSHelpWindow’ (that indicates that the specified help page should be displayed in a stand-alone popup window rather than in the desktop’s standard Help tab), and optional extra parameters specifying the popup window’s figure handle and position. The webpage filepath parameter may be replaced by two string parameters, HelpTopicMap filepath and HelpTopicKey. Note that helpview itself is another semi-documented function.

]]> 10