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Customizing axes part 3

In the past two weeks I explained how HG2 (in R2014b) enables us to customize the axes rulers, baselines, box and grid-lines in ways that were previously impossible in HG1 (R2014a or earlier). Today I will describe other useful undocumented customizations of the HG2 axes:

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Categories: Handle graphics, Low risk of breaking in future versions, Stock Matlab function, Undocumented feature
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Customizing axes part 2

Last week I explained how HG2 (in R2014b) enables us to customize the axes rulers in ways that were previously impossible in HG1 (R2014a or earlier). Today I will describe other useful undocumented customizations of the HG2 axes:

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Categories: Handle graphics, Low risk of breaking in future versions, Stock Matlab function, Undocumented feature
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Customizing axes rulers

Over 4 years have passed since I’ve posted my scoop on Matlab’s upcoming new graphics system (a.k.a. HG2, Handle Graphics version 2). At that time HG2 was still far from usable, but that has changed when I posted my HG2 update last year. Numerous user feedbacks, by email and blog comments, were reported and the MathWorks developers have listened and improved the code. HG2 was finally released with Matlab R2014b last Friday, and it seems at first glance to be a beauty. I hope my posts and the feedbacks have contributed, but in any case the MathWorks dev group deserves big kudos for releasing a totally new system that provides important usability and aesthetic improvements [almost] without sacrificing performance or backward-compatibility. Trust me, it’s not an easy achievement.

Customized HG2 plot

Customized HG2 plot


One of the nice things that I like about HG2 is that it provides numerous new ways to customize the objects in ways that were impossible (or nearly so) in the old HG1. In R2014b, the leap was large enough that MathWorks wisely chose to limit the official new properties to a bare minimum, for maximal HG1 compatibility. I assume that this will remain also in R2015a, which I expect to be a release devoted to bug fixing and stabilization rather than to new features. I expect the new features to start becoming official in R2015b onward. Such a measured roadmap is to be expected from a responsible engineering company such as MathWorks. So in fact there is no need at all to be disappointed at the relative lack of new functional features. They are all there already, just not yet official, and this is just as it should be.

That being said, if we are aware of the risk that these features might change in the upcoming years until they become official (if ever), then we can start using them today. Experience with this blog has shown that the vast majority of such undocumented features remain working unchanged for years, and some of them eventually become documented. For example, uitab/uitabgroup, on which I posted over 4 years ago, and which has existed almost unchanged since 2005, finally became official in R2014b after many years of running in unofficial form.

In the next few weeks I intend to present a series of posts that highlight some of the undocumented customizations in HG2. I’ll start with some new axes features, followed by plotting aspects.
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Categories: Handle graphics, Low risk of breaking in future versions, Stock Matlab function, Undocumented feature
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Customizing combobox popups

Last week I explained how we can use display custom items in a standard Matlab combobox (popup/dropdown), using its underlying Java component. Today I will show how we can use this Java component for other nice customizations of the combobox’s popup:

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Categories: GUI, Java, Medium risk of breaking in future versions, UI controls, Undocumented feature
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Customizing listbox/combobox items

Last week I wrote about using a variety of techniques to customize listbox items with an attached checkbox icon. Some of these methods used a standard Matlab listbox uicontrol, others used other controls. Today I wish to extend the discussion and show how Matlab listbox and combobox (pop-up) items can be customized in a variety of ways.

To add icons to listbox/combobox items, we could use standard HTML, as I’ve shown last week. This is the simplest method, requires no Java knowledge, and it usually works well. The problem is that when a listbox/combobox has numerous items (hundreds or more), it may start getting sluggish. In such case it is faster to use a dedicated Java cell-renderer that sets the icon, font, colors, tooltip and other aspects on an item-by-item basis. This runs faster and enables far greater customizability than what is possible with HTML. The drawback is that it requires some Java programming. No free lunch…

Listbox and combobox cell-renderers need to extend javax.swing.ListCellRenderer, similarly to uitable cell-renderers. This is basically a simple Java class that minimally contains just an empty constructor and a getListCellRendererComponent() method with a predefined signature. getListCellRendererComponent() is automatically called by the Swing render engine separately for each listbox item, and gets as input args a JList reference, the item value (typically a string), an integer list index, a boolean flag indicating whether the item is currently selected, and another flag indicating whether the item is currently in focus. getListCellRendererComponent() uses these parameters to customize and return a java.awt.Component, which is typically (but not necessarily) a standard Swing JLabel.

Here is a simple example that displays a folder of icon files in a Matlab listbox and combobox. Each item is the filename, with a customization that if the file is an icon, then this icon is displayed next to the file name, otherwise the name appears in red italic without an icon. For illustration, we’ll use Matlab’s builtin icons folder: %matlabroot%/toolbox/matlab/icons/:

Custom listbox cell-renderer    Custom combobox cell-renderer

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

Several years ago I blogged about using a checkbox-tree in Matlab. A few days ago there was a question on the Matlab Answers forum asking whether something similar can be done with Matlab listboxes, i.e. add checkboxes next to each list item. There are actually several alternatives for this and I thought this could be a good opportunity to discuss them:

MathWorks CheckBoxList

MathWorks CheckBoxList


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Categories: GUI, Java, Medium risk of breaking in future versions, UI controls, Undocumented feature
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savezip utility

A few months ago I wrote about Matlab’s undocumented serialization/deserialization functions, getByteStreamFromArray and getArrayFromByteStream. This could be very useful for both sending Matlab data across a network (thus avoiding the need to use a shared file), as well as for much faster data-save using the -V6 MAT format (save -v6 …).

As a followup to that article, in some cases it might be useful to use ZIP/GZIP compression, rather than Matlab’s proprietary MAT format or an uncompressed byte-stream.

Unfortunately, Matlab’s compression functions zip, gzip and tar do not really help run-time performance, but rather hurt it. The reason is that we would be paying the I/O costs three times: first to write the original (uncompressed) file, then to have zip or its counterparts read it, and finally to save the compressed file. tar is worst in this respect, since it does both a GZIP compression and a simple tar concatenation to get a standard tar.gz file. Using zip/gzip/tar only makes sense if we need to pass the data file to some external program on some remote server, whereby compressing the file could save transfer time. But as far as our Matlab program’s performance is concerned, these functions bring little value.

In contrast to file-system compression, which is what zip/gzip/tar do, on-the-fly (memory) compression makes more sense and can indeed help performance. In this case, we are compressing the data in memory, and directly saving to file the resulting (compressed) binary data. The following example compresses int8 data, such as the output of our getByteStreamFromArray serialization:
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Categories: High risk of breaking in future versions, Java, Undocumented function
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Inter-Matlab data transfer with memcached

Once again I welcome guest blogger Mark Mikofski. Mark has written here last year about JGIT-Matlab integration and earlier this year on JSON-Matlab integration. Today, Mark shows how to use the well-known open-source memcached library for data transfer between separate Matlab processes. Readers are also referred to Mark’s article on his blog. I have already written about various ways to communicate between separate Matlab processes – today’s article is an important complement to these methods.

Downloads

Stringpool's memcached tutorialThe memcached open-source library is great for sending objects from process to process. It is typically used to cache large data objects from databases or in a distributed environment, but we can also use it as a simple distributed shared memory system, which stores data in key-value pairs (as in a hashtable).

I was able to use memcached to set and retrieve objects from two different instances of Matlab. Both the Java and .NET variants of memcached can be used for this. memcached requires two components: server and client: The server comes precompiled, while the client needs to be compiled by us.

The memcached server was compiled by Trond Norbye from Couchbase (previously Membase and Northscale) for 32-bit and 64-bit Windows OS. See below how to run it as a service using the Python PyWin32 package.

I compiled Windows binaries of memcached-client libraries for both the Java and .NET using Java-1.7 and Visual Studio 2010 and zipped them up here.

Note: additional (non-memcached) shared-memory implementations used in Matlab include Joshua Dillon’s sharedmatrix (also see here), and Kevin Stone’s SharedMemory utilities, which use POSIX shared-memory and the Boost IPC library. Rice University’s TreadMarks library is another example of a shared-memory approach that has been used with Matlab, in the MATmarks package (note that the current availability of MATmarks is unclear).
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Categories: Guest bloggers, Low risk of breaking in future versions
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Property value change listeners

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.
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Categories: GUI, Handle graphics, Listeners, Low risk of breaking in future versions, Stock Matlab function, Undocumented feature
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Online (web-based) Matlab

For many years I searched for a good solution for deploying Matlab applications in online web-pages. There used to be a solution over a decade ago but it was taken off the market. We could use the Java Builder to wrap our Matlab apps in a JAR that could be called by a Java-based application server, but we’d still need to develop the front-end web GUI as well as the middle-tier plumbing. A similar limitation exists if we wish to use the new Matlab Production Server (MSP). Developing this front-end and middle-tier is by no means a trivial exercise, as much as MathWorks presentations would like it to appear. Not to mention the fact that the Builder and the MSP are relatively costly (~$5-7K and ~$30K respectively).

I was thrilled to see the answer in the recent Matlab Computational Finance Conference, London. I presented at last year’s conference, so I was excited to review this year’s presentations when I came across a nugget in Kevin Shea’s keynote presentation on new Matlab developments. Note that there were two separate Matlab computational-finance events in 2014 – in London (June 24) and NY (April 9); the interesting piece is from London. Unlike the NY conference, the London conference proceedings do not include a video recording, only the slides (perhaps the video will be added to the proceedings page later, after all it takes some time to process). The last slide of Kevin’s presentation shows a screenshot of a Chrome browser displaying what appears to be a full-fledged Matlab desktop (Workspace, Editor, Command Window, figures) at https://matlab.mathworks.com:

Matlab Online (click to zoom)
Matlab Online (click to zoom)

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Categories: Desktop, Medium risk of breaking in future versions, Semi-documented feature
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