Posts Tagged ‘Semi-documented function’

Matlab and the Event Dispatch Thread (EDT)

Wednesday, March 10th, 2010

Once again I welcome guest blogger Matt Whitaker, with the long awaited EDT article.

Java Swing’s Event Dispatch Thread (EDT)
or: why does my GUI foul up?

Matlab for the most part is a single threaded environment. That is, all commands are executed sequentially along a single execution thread. The main exception to this are the Handle Graphics (GUI) components whose operations execute on the Java Event Dispatch Thread (EDT). EDT effects are reflected even in mundane Matlab GUI operations.

If we execute the code below we will probably see nothing until the loop completes and the figure appears with the text label showing ‘10000′:

h = figure;
txt = uicontrol('Parent',h, 'Style','text', 'String','1');
for n = 1:10000
    set(txt,'String',int2str(n))
end %for

By adding a couple of drawnow commands we get the figure and text label to render and then we see the count progress to 10000.

h = figure;
txt = uicontrol('Parent',h, 'Style','text', 'String','1');
drawnow;
for n = 1:10000
    set(txt,'String',int2str(n));
    drawnow;
end %for

The drawnow function allows the EDT queue to be flushed and the pending graphics operations to be evaluated. This will also happen with pause and several other commands.

If we want to use Swing (or AWT) components in our user interfaces we need to take this multi-threaded environment into account. The Swing toolkit designers decided to make all the Swing components thread un-safe in order to decrease their complexity. As a consequence, all access to Swing components should be done from the event dispatch thread (EDT), to ensure the operations are executed sequentially, at the exact order in which they were dispatched. Any action on a Swing component done on another thread (Matlab’s main processing thread in our case) risks a race-condition or deadlock with the EDT, which could (and often does) result in weird, non-deterministic and non-repetitive behavior – all of which should be avoided in any application which should behave in a precisely deterministic manner.

In Java, the usual pattern to accomplish EDT dispatching is to create a Runnable object, encapsulate the GUI code in the run method of the Runnable object, then pass the Runnable object to the static EventQueue.invokeLater (or EventQueue.invokeAndWait if we need to block operations to get a return value) method.

Runnable runnable = new Runnable()
{
    public void run()
    {
        //GUI Code here
    }
}
 
EventQueue.invokeLater(runnable);

There are several functions in Matlab that implement this programming pattern for us: javaObjectEDT, javaMethodEDT, awtinvoke, awtcreate and javacomponent. JavaMethodEDT and javaObjectEDT were introduced in version R2008b (7.7) and are minimally and only partially documented although they have reasonably complete help comments. The other three are semi-documented (meaning they are unsupported but if you edit or type their m-file you’ll see a fairly detailed help section), and although there is some overlap in their functionality they are still available.

javaObjectEDT and javaMethodEDT

javaObjectEDT is the the preferred method since R2008b of creating swing components to be used on the EDT. An object created with javaObjectEDT will have all of its subsequent method calls run on the EDT. This is termed Auto Delegation. Auto-delegation greatly simplifies and increases the readability of code. Note that objects created as a result of method calls may not be implemented on the EDT.

If you have an existing Java object, you can pass it to javaObjectEDT at any time - all its subsequent calls will then onward run on the EDT. Note that this useful functionality is an under-documented javaObjectEDT feature: it is not mentioned in the main help section but only implied from the example.

% Create a button on the EDT
btn = javaObjectEDT('javax.swing.JButton');
% this will run on EDT since btn was javaObjectEDT-created
btn.setText('Button');
 
% Create a button NOT on the EDT
btn2 = javax.swing.JButton;
% Dangerous! call will run on main Matlab thread
btn2.setText('Button2');
% modify btn2 so its methods will start running on the EDT
javaObjectEDT(btn2);
btn2.setText('Button2');

The following example shows the use of javaObjectEDT and javaMethodEDT in a more complex situation using a JTable:

function tableExample
hFig = figure;
drawnow; %need to get figure rendered
 
%use Yair's createTable to add a javax.swing.JTable
%http://www.mathworks.com/matlabcentral/fileexchange/14225-java-based-data-table
%wrap ceateTable in javaObjectEDT to put the ensuing method calls on the EDT
f = java.awt.Font(java.lang.String('Dialog'),java.awt.Font.PLAIN,14);
headers = {'Selected','File','Analysis Routine','Task Status'};
tbl = javaObjectEDT(createTable(hFig,headers,[],false,'Font',f));
 
%set column 1 to use check boxes and set up a change callback
tbl.setCheckBoxEditor(1);
jtable = javaObjectEDT(tbl.getTable); %get the underlying Java Table. IMPORTANT: we need to put jtable on the EDT
columnModel = javaObjectEDT(jtable.getColumnModel); %now we can now do direct calls safely on jtable
selectColumn = javaObjectEDT(columnModel.getColumn(0));
selectColumnCellEditor = selectColumn.getCellEditor;
chk = javaMethodEDT('getComponent',selectColumnCellEditor);
set(chk,'ItemStateChangedCallback',@chkChange_Callback);
 
%make column three a combo drop down
analysisTable = {'Analysis1';'Analysis2';'Analysis3'};
cb = javaObjectEDT('com.mathworks.mwswing.MJComboBox',analysisTable);
cb.setEditable(false);
cb.setFont(f);
set(cb,'ItemStateChangedCallback',@cbChange_Callback);
editor = javaObjectEDT('javax.swing.DefaultCellEditor',cb);
analysisColumn = javaObjectEDT(columnModel.getColumn(2));
analysisColumn.setCellEditor(editor);
 
%set some column with restrictions
selectColumn.setMaxWidth(100);
analysisColumn.setPreferredWidth(300);
 
%set the data
SELECTED = java.awt.event.ItemEvent.SELECTED;
tbl.setData({false,'file1','Analysis2','Analysis2';...
             true,'file2','Analysis3','Analysis3'});
drawnow;
 
    function cbChange_Callback(src,ev) %#ok
        jRow = jtable.getSelectedRow;
        stateChange = javaMethodEDT('getStateChange',ev);
        if stateChange == SELECTED
            newData = javaMethodEDT('getItem',ev);
            model = jtable.getModel;
            javaMethodEDT('setValueAt',model,newData,jRow,3);
        end %if
    end %cbChange
 
    function chkChange_Callback(src,ev) %#ok
        chkBox = javaMethodEDT('getItem',ev);
        if logical(javaMethodEDT('isSelected',chkBox))
            beep; %put useful code here
        else
            beep;
            pause(0.1)
            beep; %put useful code here
        end %if
    end %chkChange_Callback
 
end %tableExample

If you are running Matlab R2008a or later, javacomponent uses the javaObjectEDT function to create the returned objects so you do not have to do anything further to these objects to have their calls dispatched on the EDT. Users need to take care that objects added directly to the components created by javacomponent are on the EDT as well as specialized sub-components (e.g. CellRenderers and CellEditors). The overhead of calling javaMethodEDT is fairly small so if in doubt, use it.

javaObjectEDT and its kin first appeared in R2008a, although they only became supported in R2008b. Unfortunately, using them on R2008a sometimes causes hangs and all sorts of other mis-behaviors. This problem was fixed in the R2008b release, when javaObjectEDT became a fully-supported function. The problem with using javaObjectEDT in our application is that if it ever runs on an R2008a platform it might hang! (on Matlab release R2007b and earlier we will get an informative message saying that the javaObjectEDT function does not exist)

For this reason, I am using the following method in my projects:

function result = javaObjEDT(varargin)
%Placeholder of Matlab's buggy javaObjectEDT function on R2008a
 
% Programmed by Yair M. Altman: altmany(at)gmail.com
% $Revision: 1.2 $  $Date: 2009/01/25 11:31:08 $
 
  try
      try
          result = varargin{1};
      catch
          result = [];
      end
      v = version;
      if str2double(v(1:3)) > 7.6
          result = builtin('javaObjectEDT',varargin{:});
      end
  catch
      % never mind
  end
end

Note that javaMethodEDT has the method name as its first input argument, and the object name or reference as its second arg. This is inconsistent with many other Matlab/Java functions, which normally accept the target object as the first argument (compare: invoke, awtinvoke, notify etc.). It also means that we cannot use the familiar obj.javaMethodEDT(methodName) format.

One final note: when javaObjectEDT and javaMethodEDT first appeared in R2008a, they were complemented by the javaObjectMT and javaMethodMT functions, which create and delegate Java objects on the main Matlab computational thread. Their internal documentation says that there are cases when execution must occur on the MT rather than EDT, although I am personally not aware of any such case.

awtcreate and awtinvoke

For users with versions prior to R2008b the user must use the awtcreate function to create objects on the EDT. One huge disadvantage of this older function is that if you have to pass java objects in the parameter list you must use the very cumbersome JNI style notation. For example, for the simple task of setting a button label, one has to use:

btn = awtcreate('javax.swing.JButton');
awtinvoke(btn,'setText(Ljava/lang/String;)','click me')

The other disadvantage is that creating the object using awtcreate does not ensure that its subsequent method calls will be executed on the EDT. The awtinvoke function must be used for each call.

Also, both awtcreate and awtinvoke have some limitations due to bugs in the private parseJavaSignature function (for example, invoking methods which accept a java.lang.Object) which forces one to use the direct call to the method, using the main Matlab thread. This can result in the undesired effects described above. In this situation the best workaround is to call pause(0.01) to allow the event queue to clear.

Versions of javacomponent earlier than R2008a use awtcreate and objects created by these versions must have their subsequent methods called by awtinvoke to be used on the EDT.

A very rare CSSM thread discusses the usage of awtcreate and awtinvoke with some very interesting remarks by MathWorks personnel.

There is an interesting option in awtinvoke that was not carried over into the newer javaMethodEDT. This option allows the user to pass a function handle in the argument list along with its parameters. This option creates an undocumented com.mathworks.jmi.Callback object that has a delayed callback. The delayed callback is dispatched on the EDT so that it will be called once the java method used in awtinvoke is finished. Note that the actual function will still execute on the main Matlab thread the delayed callback will just control when it is called. However this may be useful at times. It is possible to put this functionality into a separate function we can call to delay execution until the event queue is cleared.

%CALLBACKONEDTQUEUE will place a callback on the EDT to asynchronously
%run a function.
%CALLBBACKONEDTQUEUE(FCN) will run function handle FCN once all previous
%methods dispatched to the EDT have completed.
%CALLBBACKONEDTQUEUE(FCN,ARG1,ARG2,...) ill run function handle FCN with
%arguments ARG1,ARG2...once all previous methods dispatched to the EDT
%have completed.
%Note that the function is still executing on the main Matlab thread. This
%function just delays when it will be called.
function callbackOnEDTQueue(varargin)
    validateattributes(varargin{1},{'function_handle'},{});
    callbackObj = handle(com.mathworks.jmi.Callback,'callbackProperties');
    set(callbackObj,'delayedCallback',{@cbEval,varargin(:)});
    callbackObj.postCallback;
 
    function cbEval(src,evt,args) %#ok
        feval(args{:});
    end %cbEval
end %callbackOnEDTQueue
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setPrompt - Setting the Matlab Desktop prompt

Monday, January 25th, 2010

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;
try
  cmdWin = jDesktop.getClient('Command Window');
  jTextArea = cmdWin.getComponent(0).getViewport.getComponent(0);
catch
  commandwindow;
  jTextArea = jDesktop.getMainFrame.getFocusOwner;
end
 
% Instrument the text area's callback
if nargin && ~isempty(newPrompt) && ~strcmp(newPrompt,'>> ')
  set(jTextArea,'CaretUpdateCallback',{@setPromptFcn,newPrompt});
else
  set(jTextArea,'CaretUpdateCallback',[]);
end

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 = jTextArea.java;  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);
    fprintf(fprintfStr);
    newLen = newLen + length(fprintfStr);
  end
 
  % The Command-Window text should be modified on the EDT
  awtinvoke(jTextArea,'replaceRange(Ljava.lang.String;II)',...
            newPrompt(end-2:end), newLen-3, newLen);
  awtinvoke(jTextArea,'repaint()');
end

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
  else
    return;
  end
 
  try
    % *** Prompt modification code goes here ***
 
    % force prompt-change callback to fizzle-out...
    pause(0.02);
  catch
    % Never mind - ignore errors...
  end
 
  % 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
try
  origNewPrompt = newPrompt;
  newPrompt = feval(newPrompt);
catch
  try
    newPrompt = eval(newPrompt);
  catch
    % Never mind - probably a string...
  end
end
if ~ischar(newPrompt) && ischar(origNewPrompt)
  newPrompt = origNewPrompt;
end

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:
stopPromptTimers;
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, ...
              'TimerFcn',{@setPromptTimerFcn,jTextArea}));
end
 
% Stop & delete any existing prompt timer(s)
function stopPromptTimers
  try
    timers = timerfindall('tag','setPromptTimer');
    if ~isempty(timers)
      stop(timers);
      delete(timers);
    end
  catch
    % Never mind...
  end
end  % stopPromptTimers
 
% Internal timer callback function
function setPromptTimerFcn(timerObj,eventData,jTextArea)
  try
    try jTextArea = jTextArea.java;  catch,  end  %#ok
    pos = getappdata(jTextArea,'setPromptPos');
    newPrompt = datestr(now);
    awtinvoke(jTextArea,'replaceRange(Ljava.lang.String;II)',...
              newPrompt, pos, pos+length(newPrompt));
    awtinvoke(jTextArea,'repaint()');
  catch
    % Never mind...
  end
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.

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Customizing print setup

Wednesday, November 25th, 2009

Last week, while consulting a client, I watched him use a Matlab application that processed data and presented the results in a figure window. I saw that he constantly needed to go to File/Print-Preview menu option to customize the figure’s print setup before being able to print. He would constantly click the “Fill Page” button, then go to the Color tab and set RGB rather than Black-and-White, and finally go to the Advanced tab to prevent printing UI controls. Only then would he actually print the figure using the menu (File/Print) or the toolbar Print button.

Print Preview window

Print Preview window

This is absurd, I thought to myself - there must be a better way. Unfortunately, Matlab only supports two documented ways to modify the print setup:

  • the print function enables setting print settings when actually printing the figure. It accepts a long list of optional parameters that specify a wide range of printing options. But if I want to allow users to print at their own time, using the default figure menu/toolbar, I need to separate the actions of (1) setting the print setup and (2) doing the actual printout action. Since print does both of these together, we can’t use it. Moreover, if we don’t call print, the setup remains at the default settings and the menu/toolbar printouts use this default setup.
  • the printopt.m file stores the user’s default print setup. This file can be modified (use the printopt function). However, it affects all Matlab printouts, and cannot be configured on a figure-by-figure basis.

Of course, lack of a documented method never stopped us before. Sure enough, after a short search I discovered the hidden potential of the undocumented/unsupported setprinttemplate function. This function, called internally by Matlab’s print-related functions, is responsible for setting the figure’s initial print setup. Once I had this key, unlocking the problem was easy. Here is the bottom line:

The figure’s default print setup is stored in the figure’s hidden ApplicationData property, accessible via the getappdata and setappdata functions or directly via get/set, as explained in a previous post. More importantly, the figure-specific setup is stored in another hidden property, PrintTemplate. Both of these setup data are stored in structure format, which is not available when a figure is first created, but only after printing or print-preview. Note that printtemplate.m contains detailed explanations about the meaning of some fields - to see them, simply display the file:

>> type printtemplate.m  % or: edit printtemplate.m

Unless we set PrintTemplate ourselves (or call print or printpreview to do this), printing the figure will use the default print setup. To set a non-standard setup, we just need to create the PrintTemplate structure with our non-default setup options. Matlab will then automatically use them when printing the figure. Here is a checklist for doing so:

  1. First, create a figure and get its default print setup data. Since this data is unavailable in newly-created figures, simply open the figure’s Print-Preview window without changing anything - this will create the missing print setup structure that we can retrieve:

    % Create a simple figure
    >> hFig = figure;  surf(peaks);
     
    % Open the print-preview window to create setup data
    >> printpreview(hFig);
     
    % Retrieve the original (default) print setup data
    >> oldSetup = get(hFig,'PrintTemplate')
    oldSetup = 
           VersionNumber: 2
                    Name: ''
               FrameName: ''
             DriverColor: 1
         AxesFreezeTicks: 0
               tickState: {}
        AxesFreezeLimits: 0
                limState: {}
                   Loose: 0
                    CMYK: 0
                  Append: 0
               Adobecset: 0
                 PrintUI: 1
                Renderer: 'auto'
          ResolutionMode: 'auto'
                     DPI: 0
                FileName: 'untitled'
             Destination: 'printer'
             PrintDriver: ''
               DebugMode: 0
              StyleSheet: 'default'
                FontName: ''
                FontSize: 0
            FontSizeType: 'screen'
               FontAngle: ''
              FontWeight: ''
               FontColor: ''
               LineWidth: 0
           LineWidthType: 'screen'
            LineMinWidth: 0
               LineStyle: ''
               LineColor: ''
            PrintActiveX: 0
               GrayScale: 0
                 BkColor: 'white'
                 FigSize: [14.8054083333333 11.10405625]
  2. Next, go to the File/Print-Preview menu option and modify the setup according to your specific needs, and retrieve the new (modified setup):
    >> newSetup = get(hFig,'PrintTemplate');
  3. Now compare the two structures and retrieve only the modified setup options. This can be done in several ways - I personally use the objdiff utility. In our case, we modified the DriverColor (B&W => color), FigSize (for “Fill page”), and PrintUI (for hiding UI controls) fields:
    >> objdiff(oldSetup,newSetup)
    ans = 
        DriverColor: {[0]  [1]}
            FigSize: {[14.8054083333333 11.10405625]  [2x1 double]}
            PrintUI: {[1]  [0]}
         StyleSheet: {'default'  'modified'}
           limState: {{}  ''}
          tickState: {{}  ''}
  4. Finally, use the undocumented printtemplate and setprinttemplate functions to prepare the default setup sub-structure, and override with the modified options that you have just discovered. Place this in the figure’s _OpeningFcn function (for GUIDE-generated figures) or in your figure’s initialization function (for non-GUIDE figures). For example, if we have a GUIDE-generated figure called “MyFig”, then place this code in the MyFig_OpeningFcn function in MyFig.m:
    function MyFig_OpeningFcn(hObject, eventdata, handles, varargin)
      ...
      % This was adapted from initprintexporttemplate.m
      pt = printtemplate;
      pt.StyleSheet = 'modified';
      pt.VersionNumber = 2;   % important (Note #1 below)
      pt.FigSize = [38.1, 21.0];
      pt.DriverColor = 1;
      pt.PrintUI = 0;
      % we must set the paper size *before* setprinttemplate
      set(hObject, 'PaperPositionMode','manual', ...
                   'PaperPosition',[0 0.5 29.5 20], ...
                   'PaperSize',[29.68 20.98], ...
                   'PaperType','A4');
      setprinttemplate(hObject, pt);
     
      % Choose default command line output for MyFig
      handles.output = hObject;
     
      % Update handles structure
      guidata(hObject, handles);

That’s all there is to it. So easy once we know how, isn’t it? The most annoying pain-in-the-so-and-so sometimes have simple solutions…

Note #1: it is very important to set pt.VersionNumber to 2, otherwise some modifications will not take effect.

Note #2: the internal implementation of printtemplate as well as the internal setup fields have changed between Matlab releases. These were often minor backward-compatible changes, but at least once this was a major change (VersionNumber 1=>2, I think around Matlab 7.2, but I’m not sure). Therefore, carefully test your code on the oldest release which is supposed to run it. Also, if you plan the code to run in future Matlab releases, you should note that the entire setup functionality might break without prior notice, since it is an internal unsupported implementation.

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Undocumented mouse pointer functions

Thursday, September 24th, 2009

Matlab contains several well-documented functions and properties dealing with the mouse pointer. However, for some reason, some very-useful functions have remained undocumented and unsupported despite having a very long history (as far back as Matlab 6, a decade ago).

getptr, setptr, moveptr and overobj are all semi-documented functions (help section available, but online doc and official support not) which are used for internal Matlab purposes and relate to the mouse pointer. All these files are pure-Matlab non-Java files, which can be edited and modified. getptr and setptr (%Matlabroot\toolbox\matlab\uitools\getptr.m and setptr.m) access the pointer shape for a figure; moveptr (%Matlabroot\toolbox\shared\controllib\moveptr.m) moves the pointer across the screen; overobj (%Matlabroot\toolbox\matlab\uitools\overobj.m) determines which figure component is currently beneath the pointer.

getptr and setptr

While undocumented Java code is needed for setting component-specific pointer shapes, figure-wide shapes can be set using pure-Matlab. Setting the mouse pointer shape is normally achieved by modifying the figure’s Pointer property, which is fully documented. The following pointer shapes are supported: ‘arrow’ (the default Matlab pointer), ‘crosshair’, ‘fullcrosshair’ (used for ginput), ‘ibeam’, ‘watch’, ‘topl’, ‘topr’, ‘botl’, ‘botr’, ‘left’, ‘top’, ‘right’, ‘bottom’, ‘circle’, ‘cross’, ‘fleur’, and ‘custom’. For example:

set(hFig, 'Pointer', 'crosshair');

Using setptr enables access to a far greater variety of pointer shapes, in addition to all the standard shapes above: ‘hand’, ‘hand1′, ‘hand2′, ‘closedhand’, ‘glass’, ‘glassplus’, ‘glassminus’, ‘lrdrag’, ‘ldrag’, ‘rdrag’, ‘uddrag’, ‘udrag’, ‘ddrag’, ‘add’, ‘addzero’, ‘addpole’, ‘eraser’, ‘help’, ‘modifiedfleur’, ‘datacursor’, and ‘rotate’. It also has a few entirely-undocumented shapes: ‘forbidden’, and ‘file’ (which expects a cursor data filepath as the following argument):

setptr(gcf, 'hand');
setptr(gcf, 'file', 'my137byteFile.data');

getptr returns a cell array of parameter name/value pairs that can be stored and later used to restore the pointer shape for a specified figure:

ptr = getptr(gcf);
% do some stuff...
set(gcf, ptr{:});

moveptr

moveptr is used to move the mouse pointer programmatically across a specific plot axes. This function is poorly and incorrectly documented and contains quite a few bugs (as of R2008b). However, with minor fixes and slight attention to usage, it can be quite useful.

The regular and fully documented/supported method of moving the mouse pointer across the screen is by modifying the root (0) handle’s PointerLocation property. In many cases we may wish to programmatically move the pointer from to a specific location in a plot axes. This can be done of course by computing the figure’s dimensions and position in screen pixel coordinates, and the internal figure components dimensions/position within the figure, and their internal components and so on, not forgetting to translate data or normalized coordinates into screen pixel units, and taking care of logarithmic and reverse axes. After adding all these up, and assuming we’ve made no mistake in the computation (no easy task), we can now set the root handle’s PointerLocation property.

Comes moveptr to the rescue: moveptr accepts a handle(hAxes) as first parameter (note that handle(hAxes) must be passed, not hAxes!), and one of the following; either ‘init’ to initialize the move (creating a transformation from local axes data units to screen pixels), or ‘move’ followed by X,Y (axes data units) to actually move the mouse pointer. X and Y may well be outside the axes boundaries:

moveptr(handle(gca),'init');
moveptr(handle(gca),'move',-5,7);  % so easy

moveptr is only available in Matlab 7, not Matlab 6. moveptr also has a bug/limitation (fixed in R2008a) in that it expects the supplied axes to be a direct child of the figure. Finally, it accepts handle(hAxes) as first parameter – not the regular numeric hAxes handle as its help section would have us believe. These may not of course be the case in a more general case. Note that R2008a’s fix for the direct-figure-child limitation, using hgconvertunits (another semi-documented function), is incompatible with Matlab 6, which did not have this function. The fix for all these issues, which accepts both hAxes and handle(hAxes), removes the direct-figure-child limitation and also works on Matlab 6, is outlined below:

%% Moveptr replacement for Matlab 6 compatibility
function moveptr(hAx, x, y)
    % Compute normalized axis coordinates
    NormX = getNormCoord(hAx, 'x', x);
    NormY = getNormCoord(hAx, 'y', y);
 
    % Compute the new coordinates in screen units
    Transform = axis2Screen(hAx);
    NewLoc = Transform(1:2) + Transform(3:4) .* [NormX NormY];
 
    % Move the pointer
    set(0,'PointerLocation',NewLoc);
%end  % moveptr
 
%% Get normalized axis coordinates
function normCoord = getNormCoord(hAx, axName, curPos)
    limits = get(hAx, [axName 'Lim']);
    if strcmpi(get(hAx,[axName 'Scale']), 'log')
        normCoord = (log2(curPos) - log2(limits(1))) /diff(log2(limits));
    else
        normCoord = (curPos-limits(1)) / diff(limits);
    end
%end  % getNormCoord
 
%% Axis to screen coordinate transformation
function T = axis2Screen(ax)
    % computes a coordinate transformation T = [xo,yo,rx,ry] that
    % relates normalized axes coordinates [xa,ya] of point [xo,yo]
    % to its screen coordinate [xs,ys] (in the root units) by:
    %     xs = xo + rx * xa
    %     ys = yo + ry * ya
    % Note: this is a modified internal function within moveptr()
    % Get axes normalized position in figure
    T = getPos(ax,'normalized');
    % Loop all the way up the hierarchy to the root
    % Note: this fixes a bug in Matlab 7's moveptr implementation
    parent = get(ax,'Parent');
    while ~isempty(parent)
        % Transform normalized axis coords -> parent coords
        if isequal(parent,0)
            parentPos = get(0,'ScreenSize');  % Save screen units
        else
            parentPos = getPos(parent, 'normalized'); % Norm units
        end
        T(1:2) = parentPos(1:2) + parentPos(3:4) .* T(1:2);
        T(3:4) = parentPos(3:4) .* T(3:4);
        parent = get(parent,'Parent');
    end
%end  % axis2Screen

overobj and hittest

overobj is a related semi-documented function. It returns a handle to the first visible element beneath the mouse pointer that has visible handles (i.e., can be found with findobj , as opposed to hidden handles that can only be found using findall). The mandatory Type argument specifies the requested handle’s Type property value.

There are several overobj usage samples in CSSM. Here is an example for modifying the mouse cursor over axes:

% Modify mouse pointer over axes
hAxes = overobj('axes');
if ~isempty(hAxes)
    set(gcf,'Pointer','fleur');
else
    set(gcf,'Pointer','arrow');
end

A CSSM reader has noted that since overobj uses the findobj function, it is rather slow. Therefore, do not use overobj in a complex figure’s WindowButtonMotionFcn callback.

overobj has other annoying limitations: it only searches direct figure children, not inner descendants. Therefore, anything contained within a uipanel, uibuttongroup etc. cannot be found. Also, it assumes the root and figure units are both ‘pixel’: often they are not. Also, it only searches visible objects: hidden axes are not retrieved. Finally, it would be a great benefit to have an overobj variant in which the Type argument is optional, so the function would return the handle of the first object found, of whichever type. Here’s this variant overobj2, adapted from Matlab’s overobj. Note that overobj and overobj2 only work on objects having a Position property, and so cannot be used for axes plot children:

function h = overobj2(varargin)
%OVEROBJ2 Get handle of object that the pointer is over.
%   H = OVEROBJ2 searches all objects in the PointerWindow
%   looking for one that is under the pointer. Returns first
%   object handle it finds under the pointer, or empty matrix.
%
%   H = OVEROBJ2(FINDOBJ_PROPS) searches all objects which are
%   descendants of the figure beneath the pointer and that are
%   returned by FINDOBJ with the specified arguments.
%
%   Example:
%       h = overobj2('type','axes');
%       h = overobj2('flat','visible','on');
%
%   See also OVEROBJ, FINDOBJ
 
% Ensure root units are pixels
oldUnits = get(0,'units');
set(0,'units','pixels');
 
% Get the figure beneath the mouse pointer and mouse pointer pos
fig = get(0,'PointerWindow'); 
p = get(0,'PointerLocation');
set(0,'units',oldUnits);
 
% Look for quick exit (if mouse pointer is not over any figure)
if fig==0,  h=[]; return;  end
 
% Compute figure offset of mouse pointer in pixels
figPos = getpixelposition(fig);
x = (p(1)-figPos(1));
y = (p(2)-figPos(2));
 
% Loop over all figure descendents
c = findobj(get(fig,'Children'),varargin{:});
for h = c',
   % If descendent contains the mouse pointer position, exit
   r = getpixelposition(h);
   if ( (x>r(1)) && (x<r(1)+r(3)) && (y>r(2)) && (y<r(2)+r(4)) )
      return
   end
end
h = [];

An alternative to overobj or overobj2 is to use the undocumented hittest built-in function – separate cases may dictate preferring one alternative to the other:

hObj = hittest(hFig);

p.s. - while most of Matlab’s undocumented stuff indeed lies in the Java domain, there are quite a few non-Java pearls to be exposed, as in this article. From time to time I will take time off from Java and describe these aspects.

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Figure toolbar components

Thursday, August 27th, 2009

Toolbars are by now a staple of modern GUI design. An unobtrusive list of small icons enables easy access to multiple application actions without requiring large space for textual descriptions. Unfortunately, the built-in documented support for the Matlab toolbars is limited to adding icon buttons via the uipushtool and uitoggletool functions, and new toolbars containing them via the uitoolbar function. In this post I will introduce several additional customizations that rely on undocumented features.

This article will only describe figure toolbars. However, much of the discussion is also relevant to the desktop (Comand Window) toolbars and interested users can adapt it accordingly.

Accessing toolbar buttons - undo/redo

Let’s start by adding undo/redo buttons to the existing figure toolbar. I am unclear why such an elementary feature was not included in the default figure toolbar, but this is a fact that can easily be remedied. In a future post I will describe uiundo, Matlab’s semi-documented support for undo/redo functionality, but for the present let’s assume we already have this functionality set up.

First, let’s prepare our icons, which are basically a green-filled triangle icon and its mirror image:

% Load the Redo icon
icon = fullfile(matlabroot,'/toolbox/matlab/icons/greenarrowicon.gif');
[cdata,map] = imread(icon);
 
% Convert white pixels into a transparent background
map(find(map(:,1)+map(:,2)+map(:,3)==3)) = NaN;
 
% Convert into 3D RGB-space
cdataRedo = ind2rgb(cdata,map);
cdataUndo = cdataRedo(:,[16:-1:1],:);

Now let’s add these icons to the default figure toolbar:

% Add the icon (and its mirror image = undo) to the latest toolbar
hUndo = uipushtool('cdata',cdataUndo, 'tooltip','undo', 'ClickedCallback','uiundo(gcbf,''execUndo'')');
hRedo = uipushtool('cdata',cdataRedo, 'tooltip','redo', 'ClickedCallback','uiundo(gcbf,''execRedo'')');

Undo/redo buttons

Undo/redo buttons

In the preceding screenshot, since no figure toolbar was previously shown, uipushtool added the undo and redo buttons to a new toolbar. Had the figure toolbar been visible, then the buttons would have been added to its right end. Since undo/redo buttons are normally requested near the left end of toolbars, we need to rearrange the toolbar buttons:

hToolbar = findall(hFig,'tag','FigureToolBar');
%hToolbar = get(hUndo,'Parent');  % an alternative
hButtons = findall(hToolbar);
set(hToolbar,'children',hButtons([4:end-4,2,3,end-3:end]));
set(hUndo,'Separator','on');

Undo/redo buttons in their expected positions

Undo/redo buttons in their expected positions

We would normally preserve hUndo and hRedo, and modify their Tooltip and Visible/Enable properties in run-time, based on the availability and name of the latest undo/redo actions:

% Retrieve redo/undo object
undoObj = getappdata(hFig,'uitools_FigureToolManager');
if isempty(undoObj)
   undoObj = uitools.FigureToolManager(hFig);
   setappdata(hFig,'uitools_FigureToolManager',undoObj);
end
 
% Customize the toolbar buttons
latestUndoAction = undoObj.CommandManager.peekundo;
if isempty(latestUndoAction)
   set(hUndo, 'Tooltip','', 'Enable','off');
else
   tooltipStr = ['undo' latestUndoAction.Name];
   set(hUndo, 'Tooltip',tooltipStr, 'Enable','on');
end

We can easily adapt the method I have just shown to modify/update existing toolbar icons: hiding/disabling them etc. based on the application needs at run-time.

Adding non-button toolbar components - undo dropdown

A more advanced customization is required if we wish to present the undo/redo actions in a drop-down (combo-box). Unfortunately, since Matlab only enables adding uipushtools and uitoggletools to toolbars, we need to use a Java component. The drawback of using such a component is that it is inaccessible via the toolbar’s Children property (implementation of the drop-down callback function is left as an exercise to the reader):

% Add undo dropdown list to the toolbar
jToolbar = get(get(hToolbar,'JavaContainer'),'ComponentPeer');
if ~isempty(jToolbar)
   undoActions = get(undoObj.CommandManager.UndoStack,'Name');
   jCombo = javax.swing.JComboBox(undoActions(end:-1:1));
   set(jCombo, 'ActionPerformedCallback', @myUndoCallbackFcn);
   jToolbar(1).add(jCombo,5); %5th position, after printer icon
   jToolbar(1).repaint;
   jToolbar(1).revalidate;
end
 
% Drop-down (combo-box) callback function
function myUndoCallbackFcn(hCombo,hEvent)
   itemIndex = get(hCombo,'SelectedIndex');  % 0=topmost item
   itemName  = get(hCombo,'SelectedItem');
   % user processing needs to be placed here
end

Undo dropdown list

Undo dropdown list

Note that the javax.swing.JComboBox constructor accepts a cell-array of strings (undoActions in the snippet above). A user-defined dropdownlist might be constructed as follows (also see a related CSSM thread):

...
dropdownStrings = {'here', 'there', 'everywhere'};
jCombo = javax.swing.JComboBox(dropdownStrings);
set(jCombo, 'ActionPerformedCallback', @myUndoCallbackFcn);
jToolbar(1).addSeparator;
jToolbar(1).add(jCombo);  % at end, following a separator mark
jToolbar(1).repaint;
jToolbar(1).revalidate;
...

A similar approach can be used to add checkboxes, radio-buttons and other non-button controls.

In next week’s post I will describe how the toolbar can be customized using undocumented functionality to achieve a non-default background, a floating toolbar (”palette”) effect and other interesting customizations. If you have any specific toolbar-related request, I’ll be happy to hear in the comments section below.

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Context-Sensitive Help

Wednesday, August 5th, 2009

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])';
set(gcf,'HelpFcn',Hfcn);
th = 0:0.314:2*pi;
plot(th,sin(th),'r-','linewidth',4);
uicontrol('units','normalized', 'position',[.45 .02 .1 .05]);
cshelp(gcf);
set(gcf,'CSHelpMode','on');

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''); ' ...
          'end'];
set(gcf,'keyPressFcn',keyFcn);
 
% Exit CSHelp mode at the end of the CSHelp callback
helpFcn = 'title([''Type :'' get(gco,''type'')]); set(gcbf,''CSHelpMode'',''off'');';
set(gcf,'HelpFcn',helpFcn);
 
% 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; ' ...
         'set(gcbf,''CSHelpMode'',get(gcbo,''checked''))'];
uimenu(helpMenu,'Label',csName,'Callback',cbFcn,'Separator','on');

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:

Hfcn=['helpview(get(gco,''HelpTopicKey''),''CSHelpWindow'');'...
      'set(gcbf,''CSHelpMode'',''off'');' ];
set(gcf,'HelpFcn',Hfcn);
th = 0:0.314:2*pi;
hLine = plot(th,sin(th),'r-','linewidth',4);
set(hLine,'HelpTopicKey','MyCSHelpFile.html#Line');
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.

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