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Plot legend title

This blog post was supposed to be a piece of cake: The problem description was that we wish to display a text title next to the legend box in plot axes. Sounds simple enough. After all, in HG1 (R2014a and earlier), a legend was a simple wrapper around a standard Matlab axes. Therefore, we can simply access the legend axes’s title handle, and modify its properties. This works very well in HG1:

hold all; 
hLine1 = plot(1:5); 
hLine2 = plot(2:6); 
hLegend = legend([hLine1,hLine2], 'Location','NorthWest');
hTitle = get(hLegend,'title');
set(hTitle, 'String','Plot types:', 'VerticalAlignment','middle', 'FontSize',8);

Matlab HG1 legend with title

Matlab HG1 legend with title


How hard then could a corresponding solution be in HG2 (R2014b+), right?

Well, it turns out that hard enough (at least for me)…
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Categories: Handle graphics, Low risk of breaking in future versions, Stock Matlab function, Undocumented feature
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Using Infiniband with Matlab Parallel Computing Toolbox

I would like to welcome guest blogger Brock Palen, who is the Associate Director for Advanced Research Computing at the University of Michigan. Brock worked in High Performance computing since 2004 and is also one half of the Research Computing podcast; Research Computing and Engineering. You can find him blogging at failureasaservice.com. This is an updated repost of Brock’s article on UMich’s Flux HPC blog. Additional information on the Parallel Computing Toolbox can be found in my book Accelerating MATLAB Performance.

In High Performance Computing (HPC) there are a number of network types commonly used, among these are: Ethernet, the common network found on all computer equipment. Infiniband, a specialty high performance low latency interconnect common on commodity clusters. There are also several propriety types and a few other less common types but I will focus on Ethernet and Infiniband.

Ethernet and really its mate protocol, TCP, are the most common supported MPI networks. Almost all computer platforms support this network type and can be as simple as using your home network switch. It is ubiquitous and easy to support. Networks like Infiniband though require special drivers, uncommon hardware but the effort is normally worth it.

The MATLAB Parallel Computing Toolbox provides a collection of functions that allow MATLAB users to utilize multiple compute nodes to work on larger problems. Many may not realize that MathWorks chose to use the standard MPI routines to implement this toolbox. MathWorks also chose, for ease of use, to ship MATLAB with the MPICH2 MPI library, and the version they use only supports Ethernet for communication between nodes.

Unfortunately, Ethernet is about the slowest common network used in parallel applications. The question is how much can this impact performance.

Mmmmm Data:

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Categories: Low risk of breaking in future versions, Stock Matlab function, Undocumented feature
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Frameless (undecorated) figure windows

All Matlab figures have a standard frame around them, consisting of a border and title bar. In some cases it could be useful to present a figure window, displaying only the contents without the border and title bar. Such a borderless (undecorated) window is not possible in Matlab. Well, at least not in supported/documented Matlab…

Readers of this blog and/or my Matlab-Java programming book are aware that Matlab’s GUI is based on Java Swing. In the end, every Matlab figure window is a simple Java JFrame, and JFrames have a setUndecorated(true) method that can be called to remove the border and title bar.

An undecorated Matlab figure window
An undecorated Matlab figure window

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Categories: Figure window, GUI, High risk of breaking in future versions, Java, Undocumented feature
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Transparent legend

I’ve been working lately on Matlab program for a client, which attempts to mimic the appearance and behavior of MetaTrader charts, which are extensively used by traders to visualize financial timeseries and analysis indicators.

Such charts are often heavily laden with information, and a legend can be handy to understand the meaning of the various plot lines. Unfortunately, in such heavily-laden charts the legend box typically overlaps the data. We can of course move the legend box around (programmatically or by interactive dragging). But in such cases it might be more useful to have the legend background become semi- or fully-transparent, such that the underlying plot lines would appear beneath the legend:

Matlab chart with a semi-transparent legend (click for details)
Matlab chart with a semi-transparent legend (click for details)

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Categories: Handle graphics, Medium risk of breaking in future versions, Stock Matlab function, Undocumented feature
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Customizing Matlab uipanels

The major innovation in Matlab release R2014b was the introduction of the new handle-based graphics system (HG2). However, this release also included a few other improvements to graphics/GUI that should not be overlooked. The most notable is that uitabs are finally officially documented/supported, following a decade or being undocumented (well, undocumented in the official sense, since I took the time to document this functionality in this blog and in my Matlab-Java book).

A less-visible improvement occurred with uipanels: Panels are very important containers when designing GUIs. They enable a visual grouping of related controls and introduce order to an otherwise complex GUI. Unfortunately, until R2014b panels were drawn at the canvas level, and did not use a standard Java Swing controls like other uicontrols. This made it impossible to customize uipanels in a similar manner to other GUI uicontrols (example).

In R2014b, uipanels have finally become standard Java Swing controls, a com.mathworks.hg.peer.ui.UIPanelPeer$UIPanelJPanel component that extends Swing’s standard javax.swing.JPanel and Matlab’s ubiquitous com.mathworks.mwswing.MJPanel. This means that we can finally customize it in various ways that are not available in plain Matlab.

We start the discussion with a simple Matlab code snippet. It is deliberately simple, since I wish to demonstrate only the panel aspects:

figure('Menubar','none', 'Color','w');
hPanel = uipanel('Title','Panel title', 'Units','norm', 'Pos',[.1,.1,.6,.7]);
hButton = uicontrol('String','Click!', 'Parent',hPanel);

Standard Matlab uipanel

Standard Matlab uipanel

Notice the default ‘etchedin’ panel border, which I hate (note the broken edges at the corners). Luckily, Swing includes a wide range of alternative borders that we can use. I’ve already demonstrated customizing Matlab uicontrols with Java borders back in 2010 (has it really been that long? wow!). In R2014b we can finally do something similar to uipanels:
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Categories: GUI, Hidden property, Java, Medium risk of breaking in future versions, Stock Matlab function, UI controls
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Simulink Data Dictionary

Once again I wish to welcome guest blogger Donn Shull. Donn has previously written a series of articles on Matlab’s previous-generation class-object system (UDD). Today Donn explores a little-known yet quite useful aspect of Simulink.


In 2014, MathWorks introduced the Simulink Data Dictionary. This new feature provides the ability to store Data Types, Parameters, and Signals in database files. This is great news for embedded systems developers who want the flexibility of using data objects and want to avoid using the base workspace with its potential for data corruption.

In its initial implementation, the data dictionary interface is provided by the Simulink Model Explorer. The GUI interface is clean, intuitive, and easy to use. This interface supports importing and exporting dictionaries to m files and mat files.

Unfortunately, in production code generation environments there is frequently a need to interface this data with external tools such as software specification systems, documentation generators, and calibration tools. MathWorks have not published an API for accessing dictionaries from code, indicating that it may possibly be available in a future release. Today, we will look at some portions of the undocumented API for Simulink Data Dictionaries.

Simulink F14 model using data dictionary

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Categories: Guest bloggers, Medium risk of breaking in future versions, Stock Matlab function, Undocumented feature
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Accessing hidden HG2 plot functionality

I received two separate reader queries in the past 24 hours, asking how to access certain functionalities in HG2 (R2014b)’s new graphics system. These functionalities were previously accessible in HG1 (R2014a and earlier), but stopped being [readily] accessible in HG2. The functionalities have not disappeared, they have merely changed the way in which they can be accessed. Moreover, with the new graphics system they were even expanded in terms of their customizability.

In both cases, the general way in which I approached the problem was the same, and I think this could be used in other cases where you might need some HG1 functionality which you cannot find how to access in HG2. So try to read today’s article not as a specific fix to these two specific issues, but rather as a “how-to” guide to access seemingly inaccessible HG2 features.

Accessing contour fills

Contour fills were implemented in HG1 as separate HG objects that could be accessed using findall or allchild. This could be used to set various properties of the fills, such as transparency. This broke in HG2 as reported by reader Leslie: the contours are no longer regular HG children. No complaints there – after all, it was based on undocumented internal features of the data-brushing functionality.

It turns out that the solution for HG2 is not difficult, using the contour handle’s hidden FacePrims property:

[~, hContour] = contourf(peaks(20), 10);
drawnow;  % this is important, to ensure that FacePrims is ready in the next line!
hFills = hContour.FacePrims;  % array of matlab.graphics.primitive.world.TriangleStrip objects
for idx = 1 : numel(hFills)
   hFills(idx).ColorType = 'truecoloralpha';   % default = 'truecolor'
   hFills(idx).ColorData(4) = 150;   % default=255

Contour plot in HG2, with and without transparency

Contour plot in HG2, with and without transparency

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Categories: Handle graphics, Medium risk of breaking in future versions, Stock Matlab function, Undocumented feature
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Matlab compiler bug and workaround

I recently consulted at a client who uses R2010a and compiles his code for distribution. Debugging compiled code is often tricky, since we do not have the Matlab desktop to help us debug stuff (well, actually we do have access to a scaled-down desktop for minimal debugging using some undocumented internal hooks, but that’s a topic for a separate article). In my client’s case, I needed to debug a run-time error that threw an exception to the console:

Error using strtrim
Input should be a string or a cell array of strings.
Error in updateGUI (line 121)

Sounds simple enough to debug right? Just go to updateGUI.m line #121 and fix the call to strtrim(), correct?

Well, not so fast… It turns out that updateGUI.m line #121 is an empty line surrounded on either side by one-line comments. This is certainly not the line that caused the error. The actual call to strtrim() only occurs in line #147!

What’s going on?

The answer is that the Matlab compiler has a bug with comment blocks – lines surrounded by %{ and %}:

15   %{
16       This is a comment block that is
17       ignored by the Matlab engine,
18       and causes a line-numbering
19       error in the Matlab compiler!
20   %}
22   a = strtrim(3.1416);  % this generates an error

In the example above, the 6-line comment block is ignored as expected by the Matlab engine in both interactive and compiled modes. However, whereas in interactive mode the error is correctly reported for line #22, in compiled mode it is reported for line #17. Apparently the compiler replaces any block comment with a single comment line before parsing the m-file.
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Categories: Low risk of breaking in future versions, Stock Matlab function, Toolbox, Undocumented feature
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I would like to introduce guest blogger Oliver Woodford. For the past several years Oliver has been a top contributor on the Matlab File Exchange, and several of his utilities have earned the prestigious distinction as “Pick of the Week”. This is no easy feat in a File Exchange that hosts ~23K utilities at latest count. For the past few years, excluding short spans of time, Oliver’s export_fig was the File Exchange’s most downloaded utility, by a wide margin. export_fig has improved the output quality of figures for so many numerous Matlab users that it is hard to imagine a Matlab File Exchange without it. Today, Oliver describes the basic technical mechanisms underlying export_fig.

Yair has very kindly agreed to take over maintenance of export_fig. For his benefit, and anyone else’s interest, I will briefly describe the layout and functionality of the toolbox.

Before starting, I always recommend that new users read the README file, to get a better understanding of the available options, how the functions perform, how to do certain frequently-asked things, and what problems still remain. The following excerpt comes from the README file (please do read the entire file):

If you’ve ever wondered what’s going on in the icon on the export_fig download page (reproduced below), then this explanation is for you: The icon is designed to demonstrate as many of export_fig‘s features as possible. Given a figure containing a translucent mesh (top right), export_fig can export to pdf (bottom center), which allows the figure to be zoomed in without losing quality (because it’s a vector graphic), but isn’t able to reproduce the translucency, and also, depending on the viewer, creates small gaps between the patches, which are seen here as thin white lines. By contrast, when exporting to png (top left), translucency is preserved (see how the graphic below shows through), the figure is anti-aliased, but zooming-in does not reveal more detail.

export_fig demo usage (click for details)

export_fig demo usage (click for details)

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Categories: Guest bloggers, Handle graphics, Medium risk of breaking in future versions
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Unorthodox checkbox usage

A few weeks ago, Robert Cumming explained how we can use a Matlab uicontrol’s CData property to provide an optical illusion of a transparent background. Today I will discuss another usage of this property, providing a simple checkbox control the unorthodox appearance of a split-pane divider.

The underlying problem description is easy: we wish to have the ability to split a Matlab uipanel into two or more sub-panels, separated by a draggable horizontal/vertical divider. Such split-panes are standard in any semi-decent GUI, but for some reason were never incorporated in official Matlab. This is a real pity, but not to worry as there are at least two alternatives we could use:


UISplitPane is a utility that I wrote back in 2009 that uses a Java JSplitPane divider and associates it with plain Matlab panels on both sides. This solves the problem of embedding Matlab axes in Java panels, such as the ones provided by the standard Java JSplitPane. A detailed description of the technique can be found in my dedicated post on this utility.

Two levels of UISplitPane, with customized dividers

Two levels of UISplitPane, with customized dividers

[hDown,hUp,hDiv1] = uisplitpane(gcf, 'Orientation','ver', 'dividercolor',[0,1,0]);
[hLeft,hRight,hDiv2] = uisplitpane(hDown, 'dividercolor','r', 'dividerwidth',3);
hax1=axes('Parent',hUp);    plot(t,sin(t));
hax2=axes('parent',hLeft);  plot(t,cos(t));
hax3=axes('parent',hRight); plot(t,tan(t));
hDiv1.DividerLocation = 0.75;    % one way to modify divider properties...
set(hDiv2,'DividerColor','red'); % ...and this is another way...

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Categories: GUI, Medium risk of breaking in future versions, UI controls
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