MATLAB Compatibility: nominal() and ordinal() objects since R2013a are not compatible with R2012b and before

In the old days (before R2013a), nominal() and ordinal() were separate parallel classes with astoundingly similar structures. That means there’s a lot of copy-paste-mod going on. TMW improved on it by consolidating the ideas into a new categorical() class, which nominal() and ordinal() derives from it.

The documentation mentioned that nominal() and ordinal() might be deprecated in the future, but I contacted their support urging them not to. It’s not for compatibility reasons: nominal() and ordinal() captures the common use cases that these two ideas do not need to be unified, and the names themselves clearly encodes the intention.

If the user want to exploit the commonalities between the two, either it’s already taken care of by the parent’s public methods, or the object can be sliced to make it happen. I looked into the source code for nominal() and ordinal(): it’s pretty much a wrapper over categorical’s methods yet the interface (input arguments) are much simpler and intuitive because we don’t have to consider all the more general cases.

Back to the titled topic. Because categorical()’s properties (members) are different from pre R2013a’s nominal() and ordinal() objects, the objects created in R2012b or before cannot be loaded correctly in newer versions. That means the backward compatibility is completely broken for nominal()/ordinal() as far as saved objects are concerned.

There’s no good incentive to solve this problem on the TMWs side because the old nominal()/ordinal() is short-lived and they always want everybody to upgrade. Since I use nominal() most of the time and the ones that really need to be saved are all nominal(), I recommend the converting (‘casting’) them to cellstr by

>> A = nominal({'a','a','b','c'});
>> A = cellstr(A)
A = 
    'a'    'a'    'b'    'c'

Remember, nominal() is pretty much compressing a ton of cellstr into a few unique items and mapping the indices. No information is lost going back and forth between cellstr() and nominal(). It’s just a little extra computations for the conversion.

As for ordinal(), I rarely need to save it because order/level assignment is almost the very last thing in the processing chain because it changes so frequently (e.g. how would you draw the lines for six levels of fatness?), I might as well just not save it and reprocess the last step (where the code with ordinal() sits) when I need it.

Nonetheless, if you still want to save ordinals() instead of re-crunching it, this time you’ll want to save it as numerical levels by casting the ordinal() into double():

>> A = ordinal([1 2 3; 3 2 1; 2 1 3],{'low' 'medium' 'high'}, [3 1 2])
A = 
     medium      high        low    
     low         high        medium 
     high        medium      low    
>> D = double(A)
D =
     2     3     1
     1     3     2
     3     2     1
>> U = unique(A)
U = 
     low 
     medium 
     high 
>> L = cellstr(U)
L = 
    'low'
    'medium'
    'high'
>> I = double(U)
I =
     1
     2
     3
>> A_reconstructed = ordinal(D, L, I)
A_reconstructed = 
     medium      high        low    
     low         high        medium 
     high        medium      low

You’ll save (D, L, I) from old MATLAB and load it and reconstruct it with the triplets from the new MATLAB (I’d suggest using structs to keep track of the triplets). I know it’s a hairy mess!

 

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MATLAB Gotchas: Adding whitespace in strcat()

strcat() is a very handy function in MATLAB that allows you to combine strings using a mixture of cellstr() and char strings and it will auto-expand the char strings to match the cellstr() if necessary.

However, by design intention, strcat() removes trailing white spaces by internally applying deblank() to all char string inputs. It does NOT deblank cellstr() inputs. So if you want to combine date and time with a space, you have to use {‘ ‘} instead of ‘ ‘:

date = '2000-01-01';
time = '00:00:01';
>> strcat(date, ' ', time)  % The ' ' is ignored
ans =
2000-01-0100:00:01
>> strcat(date, {' '}, time)  % The ' ' is ignored
ans = 
    '2000-01-01 00:00:01'
>>

I find this more confusing than helpful. Including myself and other users, we naturally resort to processing line by line using cellfun() or other tricks just to get around the deblank() problem without taking a second look at the documentation because

  • rolling our own implementation is marginally as annoying as the deblank()
  • we expect cellstr() to match the dimensions without auto-expanding. I naturally thought it would expand only if it’s a char string.

Well, somebody asked this question on the newsgroup before, so obviously it’s not an intuitive design. It make sense to do it the way MATLAB designed strcat() because we need some way to tell MATLAB whether I want my inputs deblanked or not.

I think it’s more intuitive to have MATLAB’s default strcat() not to deblank() char strings at all and have a strcat_deblanked() that deblanks the inputs before feeding into strcat().

Unfortunately this behavior is there for a long time, so it’s too late to change it without affecting compatibility. Might as well live with it, but this is one of the very few unnatural (or slightly illogical design choice) of MATLAB to keep in mind.

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MATLAB Features: Persistent Excel ActiveX (DCOM) for xlsread() and xlswrite() R2015b

xlsread() and everything that calls it, such as readtable(), is terribly slow, especially when you have a boatload of Excel files to process. The reason behind it is that xlsread() closes that DCOM handle (which closes the Excel COM session) after it finishes, and restart Excel (DCOM) again when you call xlsread() again to load another spreadsheet file.

That means there’s a lot of opening and closing of the Excel application if you process multiple spreadsheets. The better strategy, which is covered extensively in MATLAB’s File Exchange (FEX), is to have your program open one Excel handle, and process all the spreadsheets within the same DCOM handle before closing it.

This strategy is quite overwhelming for a beginner, and even if you use FEX entries, you still cannot get around the fact that you have to know there’s a handle that manages the Excel session and remember to close it after you are done with it. Nothing beats having xlsread() do it automatically for you.

Starting with R2015b, the Excel DCOM handle called by xlsread() is now persistent: that after you make the first call to xlsread(), Excel.exe will stay in the memory unless you explicitly clear persistent variables or exit MATLAB, so you can reuse them every time xlsread() or xlswrite() is called. Finally!

The code itself is pretty slick. You can find it in ‘matlab.io.internal.getExcelInstance()’. Well, I guess it’s not hard to come up with it, but I guess in TMW, they must have a heated debate about whether it’s a good idea to keep Excel around (taking up resources) when you are done with it. With the computation power required to run R2015b, an extra Excel.exe lying around should be insignificant. Good call!

 

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MATLAB Techniques: Who’s your daddy? Ask dbstack(). Unusual uses of dbstack()

Normally having your function know about its caller (other than through the arguments we pass onto the stack) is usually a very bad idea in program organization, because it introduces unnecessary coupling and hinders visibility.

Nonetheless, debugger is a built-in feature of MATLAB and it provides dbstack() so you have access to your call stack as part of your program. Normally, I couldn’t come up with legitimate uses of it outside debugging.

One day, I was trying to write a wrapper function that does the idiom (mentioned in my earlier blog post)

fileparts( mfilename('fullpath') );

because I want the code to be self-documenting. Let’s call the function mfilepath(). Turns out it’s a difficult problem because mfilename(‘fullpath’) reports the path of the current function executing it. In the case of a wrapper, it’s the path of the wrapper function, not its caller that you are hoping to extract its path from.

In other words, if you write a wrapper function, it’s the second layer of the stack that you are interested in. So it can be done with dbstack():

function p = mfullpath()
  ST = dbstack('completenames');
  try
    p = ST(2).file;
  catch
    p = '';
  end

Since exception handling is tightly knit into MATLAB (unlike C++, which you pay for the extra overhead), there aren’t much performance penalty to use a try…catch() block than if I checked if ST actually have a second layer (i.e. has a non-base caller). I can confidently do that because there is only one way for this ST(2).file access operation to fail: mfullpath() is called from the base workspace.

Speaking of catchy titles, I wonder why Loren Shure, a self-proclaimed lover of puns and the blogger of the Art of MATLAB, haven’t exploited the built-in functions ‘who’ and ‘whos’ in her April Fools jokes like

whos your daddy
who let the dogs out

Note that these are legitimate MATLAB syntax that won’t throw you an exception. Unless you have ‘your’, ‘daddy’, ‘let’, ‘the’, ‘dogs’, ‘out’ as variable names, the above will quietly show nothing. It’d be hilarious if they pass that as an easter egg in the official MATLAB. They already have ‘why’,

why not

Error using rng (line 125)
First input must be a nonnegative integer seed less than 2^32, 'shuffle', 'default', or generator settings captured previously using S = RNG.

Error in why (line 10)
 dflt = rng(n,'v5uniform');

 

 

 

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Ebay customer support’s on-hold music: Weird Al?!!

A couple of months ago, before this blog started, I called eBay’s customer support and I was put on hold for a whole hour. It would have made my day miserable, but the on-hold music they played made my day: it’s Weird Al Yankovic’s parody song eBay!

Couldn’t stop chuckling for the first half hour despite the gruesome wait … I just couldn’t get enough of it even if loops every minute or two! I kept thinking: this can’t be true!

Yes, the eBay’s official hotline plays Weird Al’s parody of eBay to their customers while they wait! They didn’t even bleep out the word “crap” as in “this crap, shows up in, bubble wrap, almost every day“. Well, I guess they have to, as “crap” is essential to the spirit of the entire parody!

I love these people. They really have a sense of humor, and they are willing to make fun of themselves!

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Title of this blog site

Initially I started with “TMI: Too Much Information” as the title of this blog, given that my plan was to put fragments of technical information or insights I came across that might be useful for solving problems. That means the blog posts contain more than what you want to know, unless you are looking to solve a specific problem with the help of the post or you are just outright nerdy.

But soon I realized I have some non-technical stuff like gags, music, and the technical stuff covers more than just electronic measurement instruments, so I need a title that’s less common and more catchy.

Today, I came across a reddit post, which user “llllIlllIllIlIRogue Sysadmin “says:

If you don’t they’ll just hear jargon and glaze over completely and not even try to follow you. If you draw a pretty layout of everything, though, they’ll make some token effort to follow along.

They’ll still get lost but now you’re not just a nerd rambling… you’re a rambling nerd with a plan.

Very catchy! Also, I liked the original comment because it covers:

  • Passion for geeky topics
  • It’s important to communicate well so that people will bother to follow what we have to say.

I did a google search with quotes “rambling nerd with a plan” and only one entry: the original post, showed up, so it’s not a commonly used phrase. I’ll take it 🙂

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MATLAB Quirks: struct with no fields are not empty

As far as struct() is concerned, I’m more inclined to using Struct of Array (SoA) over Array of Structs (AoS), unless all the use cases screams for SoA. Performance and memory overhead are the obvious reasons, but the true motivation for me to use SoA is that I’m thinking in terms of table-oriented programming (which I’ll discuss in later posts. See table() objects.): each field of a struct is a column in a table (heterogeneous array).

Since a table() is considered empty (by isempty()) if it has EITHER 0 rows INCLUSIVE OR 0 columns (no fields) and the default constructor creates a 0 \times 0 table, I thought struct() would do the same. NOT TRUE!

First of all, the default constructor of struct() gives ONE struct with NO FIELDS (so it’s supposed to correspond to a 1 \times 0 table). What’s even harder to remember is that struct2table(struct()) gives a 0 \times 0 table.

The second thing I missed is that a struct() with NO fields is NOT empty. You can have 3 structs with NO fields! So isempty(struct()) is always false!

I usually run into this problem when I want to seed the execution with an empty struct() and have the loop expand the fields if the file has contents in it, and I’ll check if the seeded struct was untouched to see if I can read data from the file. Next time I will remember to call struct([]) instead of struct(). What a trap!

At the end of the day, while struct is powerful, but I rarely find AoS necessary to do what I wanted once table() is out. AoS has pretty much the same restrictions as in table() that you cannot put different types in the same field across the AoS, but table allows you to index with variables (struct’s field) or rows (struct array index) without changing the data structure (AoS <-> SoA). So unless it’s a performance critical piece of the code, I’ll stick with tables() for most of my struct() needs.

 

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MATLAB Techniques: onCleanup() ‘destructor’

If your program opens a file, creates a timer(), or whatever resources that needs to be closed when they are no longer needed, before R2008a, you have to put your close resource calls at two places: one at the end of successful execution, the other at the exception handling in try…catch block:

FID = fopen('a.txt')
try
   // ... do something here
   fclose(FID);
catch
   fclose(FID);
end

Not only it’s messy that you have to duplicate your code, it’s also error prone when you add code in between. If your true intention is to close the resource whenever you exit the current program scope, there’s a better way for you: onCleanup() object. The code above can be simplified as:

FID = fopen('a.txt')
obj = onCleanup(@() fclose(FID));
// ... do something with FID here

The way onCleanup() works is that it creates an object which you define what its destructor (delete()) does on creation (by the constructor of course) by specifying a function handle. This way when ‘obj’ is cleared (either as it goes out of scope or your explicitly cleared it with ‘clear’), the destructor in ‘obj’ will be activated and do the cleanup actions you specified.

Due to copyright reasons, I won’t copy the simple code here. Just open onCleanup.m in MATLAB editor and you’ll see it that the code (excluding comments) has less words than the description above. Pretty neat!

Normally we use onCleanup() inside a function. The best place to put is is right after you opened a resource because anything in between can go wrong (i.e. might throw exceptions): you want ‘obj’ to be swept (i.e. its destructors called) when that happens.

Technically, you can make an onCleanup() object in the base (root) workspace (aka command window). The destructor will be triggered either when you clear the ‘obj’ explicitly using ‘clear’ or when you exit MATLAB. You can see for yourself with this:

obj = onCleanup(@() pause);

It kind of let you do a one-off cleanup on exit instead of a recurring cleanup in finish.m.

So the next time you open a resource that needs to be closed whether the program exits unexpectedly or not, use onCleanup()! It’s one of the elegant, smart uses of OOP.

 

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