393 relevant articles found:

Using SQLite in Matlab

MathWorks invests a huge amount of effort in recent years on supporting large distributed databases. The business case for this focus is entirely understandable, but many Matlab users have much simpler needs, which are often served by the light-weight open-source SQLite database (which claims to be the most widely-used database worldwide). Although SQLite is very widely used, and despite the fact that built-in support for SQLite is included in Matlab (for its internal use), MathWorks has chosen not to expose any functionality or wrapper function that would enable end-users to access it. In any case, I recently came across a need to do just that, when a consulting client asked me to create an interactive data-browser for their SQLite database that would integrate with their Matlab program:

SQLite data browser

In today’s post I will discuss several possible mechanisms to integrate SQLite in Matlab code, and you can take your pick among them. Except for the Database Toolbox, all the alternatives are free (open-source) libraries (even the commercial Database Toolbox relies on one of the open-source libraries, by the way).
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Categories: Java, Low risk of breaking in future versions, Undocumented feature
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PlotEdit context-menu customization

Last week, a Matlab user asked whether it is possible to customize the context (right-click) menu that is presented in plot-edit mode. This menu is displayed by clicking the plot-edit (arrow) icon on the standard Matlab figure toolbar, then right-clicking any graphic/GUI element in the figure. Unfortunately, it seems that this context menu is only created the first time that a user right-clicks in plot-edit mode – it is not accessible before then, and so it seems impossible to customize the menu before it is presented to the user the first time.

Customized plot-edit context-menu

Customized plot-edit context-menu

A few workarounds were suggested to the original poster and you are most welcome to review them. There is also some discussion about the technical reasons that none of the “standard” ways of finding and modifying menu items fail in this case.

In today’s post I wish to repost my solution, in the hope that it might help other users in similar cases.

My solution is basically this:
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Categories: Figure window, GUI, Handle graphics, Java, Low risk of breaking in future versions, Undocumented feature
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Builtin PopupPanel widget

8 years ago I blogged about Matlab’s builtin HelpPopup widget. This control is used by Matlab to display popup-windows with help documentation, but can also be used by users to display custom lightweight popups that contain HTML-capable text and even URLs of entire webpages. Today I’d like to highlight another builtin Matlab widget, ctrluis.PopupPanel, which can be used to display rich contents in a lightweight popup box attached to a specific Matlab figure:

Matlab's builtin PopupPanel widget

Matlab's builtin PopupPanel widget

As you can see, this popup-panel displays richly-formatted contents, having either an opaque or transparent background, with vertical scrollbars being applied automatically. The popup pane is not limited to displaying text messages – in fact, it can display any Java GUI container (e.g. a settings panel). This popup-panel is similar in concept to the HelpPopup widget, and yet much more powerful in several aspects.
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Categories: Figure window, GUI, High risk of breaking in future versions, Java, Undocumented feature
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Customizing uifigures part 3

As I have repeatedly posted in recent years, Matlab is advancing towards web-based GUI. The basic underlying technology is more-or-less stable: an HTML/Javascript webpage that is created-on-the-fly and rendered in a stripped-down browser window (based on Chromium-based jxBrowser in recent years). However, the exact mechanism by which the controls (“widgets”) are actually converted into visible components (currently based on the Dojo toolkit and its Dijit UI library) and interact with Matlab (i.e., the internal Matlab class structures that interact with the browser and Dojo) is still undergoing changes and is not quite as stable.

Customization hacks reported on this blog last year (part 1, part 2) may fail in some cases due to the changing nature of the undocumented internals. Some examples are the way by which we can extract the uifigure’s URL (which changed in R2017a), the ability to display and debug uifigures in a standard webbrowser with associated dev tools (which seems to have stopped working in R2017b), and the way by which we can extract the Dijit reference of displayed uicontrols.

Greatly assisting in this respect is Iliya Romm, who was the guest blogger for part 2 of this series last year. Iliya co-authored the open-source (GitHub) mlapptools toolbox, which enables accessing and customizing uifigure components using standard CSS, without users having to bother about the ugly hacks discussed in the previous parts of the series. This toolbox is really just a single Matlab class (mlapptools), contained within a single m-file (mlapptools.m). In addition to this class, the toolbox includes a README.md mark-down usage documentation, and two demo functions, DOMdemoGUI.m and TableDemo.m.

Here is the effect of using TableDemo, that shows how we can customize individual uitable cells (each uitable cell is a separate Dijit widget that can be customized individually):

CSS customizations of uifigure components

CSS customizations of uifigure components


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Categories: Figure window, GUI, High risk of breaking in future versions, UI controls, Undocumented feature
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Customizing contour plots part 2

A few weeks ago a user posted a question on Matlab’s Answers forum, asking whether it is possible to display contour labels in the same color as their corresponding contour lines. In today’s post I’ll provide some insight that may assist users with similar customizations in other plot types.

Matlab does not provide, for reasons that escape my limited understanding, documented access to the contour plot’s component primitives, namely its contour lines, labels and patch faces. Luckily however, these handles are accessible (in HG2, i.e. R2014b onward) via undocumented hidden properties aptly named EdgePrims, TextPrims and FacePrims, as I explained in a previous post about contour plots customization, two years ago.

Let’s start with a simple contour plot of the peaks function:

[X,Y,Z] = peaks;
[C,hContour] = contour(X,Y,Z, 'ShowText','on', 'LevelStep',1);

The result is the screenshot on the left:

Standard Matlab contour labels

Standard Matlab contour labels

 
Customized Matlab contour labels

Customized Matlab contour labels

In order to update the label colors (to get the screenshot on the right), we create a short updateContours function that updates the TextPrims color to their corresponding EdgePrims color:
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Categories: Handle graphics, Hidden property, High risk of breaking in future versions, Stock Matlab function
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The HotLinks feature

Back in 2010, I posted about Matlab’s undocumented feature function. One of the features that I mentioned was 'HotLinks'. A few days ago I had an occasion to remember this feature when a StackOverflow user complained that the headers of table outputs in the Matlab console appear with HTML tags (<strong>) in his diary output. He asked whether it was possible to turn off this automated headers markup.

There are several ways this problem can be solved, ranging from creating a custom table display function, to modifying the table’s internal disp method (%matlabroot%/toolbox/matlab/datatypes/@tabular/disp.m), to using this method’s second optional argument (disp(myTable,false)). Note that simply subclassing the table class to overload disp() will not work because the table class is Sealed, but we could instead subclass table‘s superclass (tabular) just like table does.

Inside the disp.m method mentioned above, the headers markup is controlled (around line 45, depending on your Matlab release) by matlab.internal.display.isHot. Unfortunately, there is no corresponding setHot() method, nor corresponding m- or p-code that can be inspected. But the term “Hot” rang a bell, and then I remembered my old post about the HotLinks feature, which is apparently reflected by matlab.internal.display.isHot.

feature('HotLinks',false);  % temporarily disable bold headers and hyperlinks (matlab.internal.display.isHot=false)
disp(myTable)
myTable        % this calls disp() implicitly
feature('HotLinks',true);   % restore the standard behavior (markup displayed, matlab.internal.display.isHot=true)

Searching for “isHot” or “HotLinks” under the Matlab installation folder, we find that this feature is used in hundreds of places (the exact number depends on your installed toolboxes). The general use appears to be to disable/enable output of hyperlinks to the Matlab console, such as when you display a Matlab class, when its class name is hyperlinked and so is the “Show all properties” message at the bottom. But in certain cases, such as for the table output above, the feature is also used to determine other types of markup (bold headers in this case).
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Categories: Desktop, High risk of breaking in future versions, Undocumented feature, Undocumented function
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Tips for accelerating Matlab performance

I’m proud to report that MathWorks has recently posted my article “Tips for Accelerating MATLAB Performance” in their latest newsletter digest (September 2017). This article is an updated and expanded version of my post about consulting work that I did for the Crustal Dynamics Research Group at Harvard University, where I helped speed-up a complex Matlab-based GUI by a factor of 50-500 (depending on the specific feature). You can read the full detailed technical article here.

Crustal dynamics visualization GUI

Crustal dynamics visualization GUI

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Categories: Handle graphics, Low risk of breaking in future versions
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Faster csvwrite/dlmwrite

Matlab’s builtin functions for exporting (saving) data to output files are quite sub-optimal (as in slowwwwww…). I wrote a few posts about this in the past (how to improve fwrite performance, and save performance). Today I extend the series by showing how we can improve the performance of delimited text output, for example comma-separated (CSV) or tab-separated (TSV/TXT) files.

The basic problem is that Matlab’s dlmwrite function, which can either be used directly, or via the csvwrite function which calls it internally, is extremely inefficient: It processes each input data value separately, in a non-vectorized loop. In the general (completely non-vectorized) case, each data value is separately converted into a string, and is separately sent to disk (using fprintf). In the specific case of real data values with simple delimiters and formatting, row values are vectorized, but in any case the rows are processed in a non-vectorized loop: A newline character is separately exported at the end of each row, using a separate fprintf call, and this has the effect of flushing the I/O to disk each and every row separately, which is of course disastrous for performance. The output file is indeed originally opened in buffered mode (as I explained in my fprintf performance post), but this only helps for outputs done within the row – the newline output at the end of each row forces an I/O flush regardless of how the file was opened. In general, when you read the short source-code of dlmwrite.m you’ll get the distinct feeling that it was written for correctness and maintainability, and some focus on performance (e.g., the vectorization edge-case). But much more could be done for performance it would seem.

This is where Alex Nazarovsky comes to the rescue.
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Categories: Low risk of breaking in future versions, Mex, Undocumented feature
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Runtime code instrumentation

I regularly follow the MathWorks Pick-of-the-Week (POTW) blog. In a recent post, Jiro Doke highlighted Per Isakson’s tracer4m utility. Per is an accomplished Matlab programmer, who has a solid reputation in the Matlab user community for many years. His utility uses temporary conditional breakpoints to enable users to trace calls to their Matlab functions and class methods. This uses a little-known trick that I wish to highlight in this post.

tracer4m utility uses conditional breakpoints that evaluate but never become live

tracer4m utility uses conditional breakpoints that evaluate but never become live

Matlab breakpoints are documented and supported functionality, and yet their documented use is typically focused at interactive programming in the Matlab editor, or as interactive commands that are entered in the Matlab console using the set of db* functions: dbstop, dbclear, dbstatus, dbstack etc. However, nothing prevents us from using these db* functions directly within our code.
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Categories: Medium risk of breaking in future versions, Stock Matlab function, Undocumented feature
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Advanced Matlab online webinars

Advanced Matlab training webinars at the comfort of your desk I have prepared the following online webinars on advanced Matlab topics I (click the webinar titles for a detailed description):

All webinars are highly technical, concise and to the point, making very effective use of your time. They are based on onsite training courses that I presented at multiple client locations (details).

These webinars could be a great way for you to improve your Matlab proficiency and efficiency. You will quickly learn how to produce higher quality, better looking, faster working, and more robust applications. Your effectiveness in writing Matlab programs will improve, saving you development time while improving the quality. And all this at the comfort and convenience of your office or home.

 Email me if you would like additional information or a group discount, or to inquire regarding an onsite training course, or for any other related query/suggestion.

Categories: Public presentation
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