Scientists are not programmers. Repeat that after me: scientists are not programmers. It’s not their fault; it’s just a lack of proper training.  If you are implementing some algorithm given you by a scientist, it’s important to know this and account for it.

Certain algorithms are not direct – most often for some process which is not easily reversible.  For example, I was given the task of implementing a way of finding the Wet-Bulb temperature, given the Dewpoint temperature, the Dry-Bulb temperature, and the Barometric Pressure.  Accompanying this task was some code, written by a scientist, in some form of BASIC.

To accomplish this, they started with an estimate (the DewPoint Temp) and worked forward, using the known equations to convert wet-bulb temp into dewpoint temp, then compared that result to the known dewpoint (Tdew).  If the result was less than the known dewpoint, they added a constant 0.05 degrees to the estimate, and tried again. When the result exceeded the dewpoint, they called it good and returned the latest estimate as the final answer.

Scientists are not programmers. If you asked them about this, they will say that it gets the right answer.  If you ask them how they came to choose 0.05 as the step size, after the blank stare (while they think about it), you will get an answer something like “Well, that’s the tolerance I want”. If you really press them, they will come up with “Well, any smaller and it’ll take too long – any larger and it’ll not be correct enough”, which is exactly true. That step size is somebody’s wild guess.

Being the obsessive speed freak that I am, I figured a better way.  What the scientist didn’t realize, is that you don’t have to have a constant step size.  With a modicum of further effort, you can adjust the step size dynamically, and get to the final answer much more quickly.

Simply start with a relatively large positive step, and do your estimates as before.  Afterward, make a decision – if you haven’t exceeded your target, step again in the same direction.  If you exceeded the target, don’t simply quit and call it good, REDUCE and REVERSE your step size and go again.  Now you’re heading negative. When you go BELOW your target, REDUCE and REVERSE your step size. Repeat this until the absolute value of your step size is below your tolerance.

In certain cases, this will take LONGER, but in the vast majority of cases where a fine tolerance is needed, this will get a more accurate answer in FEWER iterations.

You of course need to check things out and match your particular case. Use an iteration counter. You always want to reduce your step size when you reverse it: a factor of -1 would never converge and a factor of near -1 would converge slowly. But a factor of -0.01 would reduce your tolerance.  Best to use a factor of -0.1 to -0.4.

I have seen reductions of 100:1 in iteration counts between the original method and this improved search.  In cases where it was worse, it was around 15 vs. 10 iterations, in cases where it was better it was around  30 vs. 500 iterations.

Use your common sense, and don’t hold it against them.  Scientists are not programmers.

If you read the post about en masse operations, you might remember that I pointed out that you should know what is happening behind the scenes. Here is a particular case where what looks like simpler code actually takes longer to execute.  If you don’t take the time to think about what is actually going on, then you might be fooled.

Consider a pair of signals, each around 12000 samples. Regulations state that I am allowed to drop (delete) certain samples from those signals before performing statistical operations on them.  The number of points to be dropped might be 2-10%, or up  to 1200 of the points. I have the indexes to be dropped in a third array. For graphing purposes, I need to keep the dropped points in separate arrays.

Now every programmer worth his salt has fallen into the trap of deleting elements 3, 5, and 8 from an array: If you try the straightforward way, you find out that after you delete element 3, that element 5 is not in the same place it was before!  So  you either have to delete element 8 BEFORE you delete element 5 and then 3, or you have to delete element (3-0), then element (5-1), and then element (8-2).

Having fallen into that pothole my share of times many years ago, I avoided it this time by doing the reversing trick: My list of points to drop was known to be in ascending order, so I reversed it, and then did the deletions.  Because I needed the deleted points in proper order, I had to reverse those after the deletion.  Here’s the code:

That worked fine for some time, but while revisiting this code, it occurred to me that it might be faster to manipulate the index while deleting, and avoid the reversals and speed things up.  Here’s the code:

That’s certainly simpler, right?  As one should always do, I applied a Timing Measurement to it. And I was surprised.  I created two arrays of 12000 numbers and an array of 1200 random (0..11999) indexes.  It was consistently 5-6% MORE TIME this simpler way.

But if you stop and think about what’s going on, the reason is clear.  Suppose your signal array contains [0, 1, 2, 3, 4, 5] and you want to delete elements [1, 3, 4 ]

Using method A you reverse the list to get [4, 3, 1 ].
You delete element 4.  {that moves element 5 down – 1 move}
You delete element 3.  {that moves element 5 down – 1 more move}
You delete element 1. {that moves elements 2, 5 down – 2 more moves}
That’s 4 moves that were made in the shuffling process.

Now consider the “simpler” method:
You delete element [1-0].  {that moves elements 2,3,4,5 down = 4 moves }
You delete element [3-1].  {that moves elements 4,5 down = 2 moves}
You delete element [4-2].  {that moves element 5 down = 1 move }
That’s a total of SEVEN moves that were made.

So even though we eliminated three REVERSAL operations, we actually take LONGER because we are doing more work.  The increased amount of data-shuffling was enough to overcome the benefit of removing the reversals.

This was done using a random list of indexes to drop; I’d bet that there are possible scenarios where this wouldn’t hold true (for example if the points to drop were few, and confined to the end of the signal), but given that neither of those will be true in my case, I’m sticking with the original plan – on average it will be faster.

But don’t assume that fewer operations on the diagram means less work !

As mentioned earlier, a compiled LabVIEW application behaves similarly to the development system when terminating.  Namely, it leaves the main window on the screen, waiting for you to close it.  That’s handy in the DevSys, because you usually want to work some more on the program after quitting.

But in an executable, it’s not so good, because the user doesn’t understand why the window hangs around.

The earlier article offered a way to have it both ways by simply detecting whether or not you were running with the main VI from an LLB, or something else, and performing a QUIT LABVIEW if it was something else.

With the advent of LabVIEW 2009, the scheme of detecting whether you were in an LLB or not was broken, because LV2009 started putting VIs into an EXE using the folder structure that they came from.  Before 2009, an EXE was a container for ALL VIs in the program, regardless of their folder structure on disk.  It was like having one folder.

Using THIS VI’s PATH would point to one of those VIs, stripping it ONCE would point to the container, and stripping it TWICE would refer to the containing folder.

With LV2009 and later, we can no longer use that logic.  What we do instead is to examine the path to MAIN:

• If we find an “.EXE”  in it, then we are in an executable, and we strip twice to get the containing folder
• else if we find “.LLB” in it, we are in a library, and we strip twice (from the point of the LLB) to get the containing folder
• else if we find “.VI” in it, we are in a stand-alone VI and strip ONCE to get to the containing folder

The attached VI is a replacement for the ROOT FOLDER vi mentioned in the earlier article, and is in LV 2009 format  (works in LV2010, too).

Use it when you’re ready to quit – see this snippet:

Click to download the Root Folder.vi .

By using the NOT IN LIBRARY signal as an input for QUIT LABVIEW, you can run the same code unmodified in an app, or in the DevSys, and it does the right thing either way.

“Fragile” code is code that breaks in one place because of changes you make in some other place. It’s most aggravating when you’re due to ship a new version tomorrow and you need to make one last tweak at 11:30 PM, or your client is looking over your shoulder and this little “harmless” change shows up as a smoldering heap during the demo.

In this case, “break” doesn’t ONLY mean “broken arrow” , or uncompilable code (at least you can chase those down easily enough). Here, “break” also means “operates incorrectly” or “completely wrecks itself like it never did before” or somewhere in between.

These sorts of breaks come from unrecognized dependencies, and they’re all too easy to make: the header size has been 3 for months and months now, so when you add a new function that needs it, it’s easy to stick in a constant 3 and be done with it.

DON’T DO IT.

If you’re an old-hand bit-banging cycle counter like me, it’s easy to think of saving a few cycles and adding up the bytes in this cluster, and using a constant of 53 when you need the size of it.

DON’T DO IT.

The problem is, or course, then when (not if, but when) these things change, then you will have to track down ALL the instances where you use this number and change them.  Not a good plan.  The compiler won’t complain – the code is still valid.  But reading thee bytes when you should be reading four will not get you where you want to go.

One tip to solving this is to reduce the number of places that you use such numbers. Focus such procedures into a single VI if you can. But the real key to solving this is to recognize these things when you originate them.

Example #1

Here we need to receive a packet header, consisting of a cluster of a U8 enum command and a U16 integer.  It’s easy enough to count up to three bytes, and it would be easy to plop down a 3 constant.  However, it is safer to use a constant of the header’s typedef and calculate its size in code.  This might go against your instincts (it does mine), but in fact the extra time taken (to flatten into string and get string length) is trivial (measure it yourself if you have doubts). On top of a TCP READ operation, this burden is truly insignificant.

And the benefit is that when the integer needs to become an U32 or the command must become a U16, here’s one less thing YOU have to worry about.  Since the constant here is a TYPEDEF, and since you’re calculating the size every time, then it will keep on working.

Example #2

This example is similar – sending a packet header plus a payload thru a connection. Even if your payload is always the same size, it’s better to calculate it than to use a constant.  With any luck at all, the STRING LENGTH operation will get the same answer every time. and if you do change it at some point, then this code won’t break.

Some development environments have a concept called “watching”, where you choose a variable to watch and you see a continuous display of that variable in some window.  This is very useful during debugging, as you can step through your program and find out where this variable is being changed.

LabVIEW has no such built-in feature, but it doesn’t really need one.  You can construct your own watch windows, have them run independently of your main code and accomplish the same thing.

Simply make a new VI with a WHILE loop and a STOP button.  Add a WAIT for 200 mSec (or something) inside it (so you don’t hog the CPU).  Each time thru the loop, grab your watch variable, process it, and display it.

The “processing” can be unbundling a single item from a complicated cluster, or picking an element out of an array, or anything you need to display the item in question.  Perhaps you need to call a VI to get it. Perhaps you need to query an I/O port, or a TCP instrument. Whatever you need to do to watch your troublesome variable.

SUGGESTION:  When you’re done with it, save it in a folder called “Miscellaneous Stuff” or something, so you can get at it easy next time.  There will be a next time.

A question came up on the LabVIEW forum the other day about multiple connections, and how hard it was to have two connections transmitting at two different rates.  This surprised me a bit, because I have been doing just that for quite a few years.  The allegation was made also that TCP requires a minimum packet size of 32 bytes. That is also a surprise since I have been doing things contrary to that “rule” for quite a few years.

So, in an attempt to clarify things above and beyond the Beginner’s Guide to TCP/IP, I present this example with a CLIENT and a SERVER.

The SERVER should be run first and listens for four connections on four consecutive ports. It has four data generators, running at different rates.  When data is available, it transmits it over the connection  if there is one, or listens for one if there’s not.

The SERVER uses a re-entrant VI so that the same code can be executing in four instances at one time.  The four instances are given four different intervals. The WAITs do not conflict because of this reentrancy.

The CLIENT initiates four connections to these same ports, and waits for data in four loops.  I did not use reentrant VIs here, because of the connection to the charts.  Although you could pass a reference to the chart to four reentrant subVIs, I chose not to, thinking that the speed would be better with the direct approach.

Given that this is based on the mSec Timer in LabVIEW, I wouldn’t vouch for it’s accuracy as you approach 1000 Hz. But the basic techniques are sound and will work beyond that frequency.

Click here for a downloadable example of four-channel client server communications.

Just in case you thought I was kidding in the article on en masse operations, I decided to offer some proof of the speed advantages they can give you.

I used the Timing Template vi to measure the time it takes to multiply an array of DBLs by two, both with a loop, and without.  I set up the timing VI to create an array of 1000 random numbers, and then time the multiply operation.

First, the loop method, where you auto-index every value out of the array, multiply it, and auto-index it back in:

As you can see, this took 7.47 uSec per loop.  Not all that shabby.  But just removing the loop lets the en masse operation do it:

Holy Speed Demon, Batman!  That’s 0.77 uSec or about ONE TENTH the time!

Now, I’m not guaranteeing that all such operations will save you that much time, but if you have a chance to use them, then you should!

It’s easier on you and easier on the hardware!

En masse is a French term meaning “as a whole” or “all together”; treating a group of something as a single unit.   LabVIEW has the ability to treat arrays this way, which can greatly reduce your workload. If you come to LabVIEW from a text-based language, it’s easy to miss the capabilities that are right at your fingertips.

For example, if you need to scale a series of readings into percent of the total (a procedure called normalizing),  then you tend to think:

I need to find the total:

• I need to start with a zero sum     sum = 0.0;
• I need to loop over every element  for (int i = 0; i < nElements; i++)
• I need to add this element to the sum   sum += array[i]

Now I need to divide each entry by the total, to get the fraction of the total:

• for (int i = 0; i < nElements; i++)
• array[i] /= sum;

Now I need to multiply by 100 to get percentages:

• for (int i = 0; i < nElements; i++)
• array[i] *= 100.0;

That’s all well and good, and you could translate that literally into LabVIEW and it will get you the answer you want to see.  But that’s not the LabVIEW way of thinking.

What newcomers often fail to realize is that most primitive numeric functions (the ones with yellowish icons) will accept an array of numbers directly. This goes for basic arithmetic (add,subtract, multiply, divide), comparisons (greater than, less than, MAX/MIN), and many other operations.  It will happily multiply an array of numbers by a single scaler number, to produce an array of numbers.

This has great power to reduce the work that you do as the programmer. Consider the literal translation of the above code:

If that’s as good as it gets then why should I go with LabVIEW?

Well, it does get better.  There is a function in the numeric palette called ADD ARRAY ELEMENTS.  If we replace the entire first loop with this function, then we get to this:

Now for the en masse parts: You can replace the entire second loop with a single operation as well:

Any guesses what we can do with the third loop?    Yes, that’s right:

Now you have SO much more room to add comments about what you’re doing!

Now THIS is what makes you more productive in LabVIEW than in C; your chances for error are far less when you let the en masse operators handle the details, and you don’t even have to think about the details.

But be aware of what’s going on, however; there is no magic here.  Under the hood there is still a loop somewhere.  It’s now hidden somewhat; it’s not as obvious, but the work is still being done.  Don’t let the simplicity obscure the real processing that’s going on.

Here is an example of the normalizing function in use, from the real LabVIEW example examples\general\graphs\charts.llb\Draw Stacked Graph.vi (in LabVIEW 8.6. anyway).

This amounts to the same as our last part above.  In the example, the array given contains five elements and this is executed only once, so efficiency is not a concern.

But consider if the array was 10,000 elements. Don’t forget that the first operation is doing 10,000 divide operations, and the second is doing 10,000 multiplications.  Can you improve things?

Well, certainly! What you have to realize is that, by the associative property of numbers, (X / sum) * 100 is equal to (100 / sum) * X.  You also have to realize that 100 / sum, in this context, is a constant, and therefore needs to be calculated only once.  In effect, you are dividing by sum and multiplying by 100, but you are doing it 10,000 times!

With any luck at all, you get the same answer every time, so you only need to do it once:

THIS is why we use LabVIEW!

NOTE:  En masse is my term for this feature, it is not an official LabVIEW term.

LabVIEW beginners often either don’t know about type definitions, or don’t appreciate their value. This article will attempt to explain their use and how they can save you boatloads of time and effort.

Suppose you have a cluster of items that’s very handy to your project. For the sake of discussion, we’ll call it a channel, and assume this is a data acquisition project. A channel might have these items:

• Channel Name
• Active switch
• Scale factor
• Units

So, suppose you have an array of these to match the channels on your MIO DAQ board.

You might develop a series of VIs that deal with channels:

• You need an editor, so the user can rename them, select which ones to use, and scale them;
• You need a VI that takes an array of channels, and configures the hardware;
• You need to print the setup, so a VI takes an array of channels and formats a page for printing;
• You need to export the data to a spreadsheet, so another VI takes the array of channels and produces a spreadsheet.

and so on. You’ve defined the cluster and all these subVIs and it all works.

Now, though, you realize that you need to add another item to the channel, namely OFFSET. You have a new 4-20mA transducer which produces a 1-5V signal when you use the right resistor. So, instead of the single SCALE FACTOR (which assumes 0.0EU at 0.0 Volts), you implement the standard linear equation Y = mX + b, where X is the measured voltage, m is the SCALE FACTOR (slope), b is the OFFSET, and Y is the resulting Engineering Units (EU). How do you go about it?

The brute force way to go about it is to open up every instance of the cluster you used, and add an OFFSET term to the cluster. OUCH! In the example, you have 4-8 instances; that’s painful enough, but imagine if you had 50!

A slightly (slightly) more civilized way is to add the OFFSET term to one cluster somewhere, then copy the cluster, and paste it over all the old instances.

One of the good things about LabVIEW is that you can follow all the broken RUN arrows and figure out the places you missed. But is this really what computers are for? After all, LabVIEW knows all these things are broken, it knows WHY they are broken, but it’s YOU that has to chase them all down. So, do this a few dozen times and you might start wishing for a better way.

A Better Way

Enter the TYPEDEF, short for Type Definition. A Typedef is a “master” control. To use it, you ask for a new custom control (File | New | Custom Control). Here’s where you define the cluster you want for a channel. The first time you would use the four items mentioned initially. You then set the control menu to STRICT TYPEDEF, and SAVE the file with a name like CHANNEL.ctl. Now, every time you want to use it, you use the SELECT A CONTROL option on the panel palette and choose that file. What you get is a cluster that looks just like the one you made originally. Place one on your VI for exporting, another on the VI for printing, etc., etc. You can copy and paste them just like anything else.

So far, there’s nothing different. Where the value come in is when you need to change it. You may notice that you can’t change the cluster on your export VI. Drag something on top of it, and the something just sits there, on top. It doesn’t get put “into” the cluster. If yuo really do want to change it, you open the CTL file. You can do this thru the FILE menu, or notice that every instance has an OPEN TYPE DEF entry in the pop-up menu now.

If you open the CTL file, you can add the OFFSET term there, and SAVE it. When you do, EVERY INSTANCE of that control/indicator updates to follow! Open any of your VIs that used it, and it will have the OFFSET term in it! You’ve just changed 4-8 (or 40-80) controls in one whack. This is convenient for this example, but on a larger program, it is absolutely essential.

Another use for them is in ENUMs. Suppose you have an ENUM for units, with the options “PSI, kPA, mmHG, InH2O”. You can create that, and copy and paste it wherever you need it, but if you have to add something to the list, you’re in the same boat as the cluster, above. The answer is the same, make it a TYPEDEF, and use the TYPEDEF wherever you need to. Then when it’s changing time, all the instances update at once.

Generally, you don’t do anything special in a LabVIEW program to quit; when it runs out of things to do, it terminates. (Quite clever, that). Your program has a loop waiting on the user to do something: when the QUIT button is clicked, the loop stops. If that is the last thing in your VI, then the VI terminates, and it’s left on the screen for you. Usually, that’s what you want; you quit because you’re ready to add the next feature, or because you decided that the purple font on the pink background was too gaudy, or because you need to find out why the temperature shows -1.33e+44 degrees.

But if you compile your program into an executable, the same thing happens (the main window hangs around), but that’s usually NOT what you want here.  The user pressed the QUIT button – why doesn’t it quit?  Most programs make their windows disappear when the user quits, and yours doesn’t do that.   You might understand that it really did quit and the window’s just hanging around waiting for you to close it, but unless you enjoy the tech support calls that result, you should consider doing something about it.

To get that window to close in an executable, you have to QUIT LABVIEW.  Find that function on the APPLICATION CONTROL palette and put it where it will execute when everything in your program is safely shut down.

The trouble is, it will ALSO quit LabVIEW when you’re in the development system.  That’s nice in the executable, as all your windows go away just like they’re supposed to. But in the development system, you don’t want to quit developing; you want to stop your program from running.

One easy way to satisfy both requirements is to use the ROOT FOLDER vi.  It has an output called NOT IN LIBRARY which connects to the QUIT? input on the QUIT LABVIEW function.  If you’re already using that VI to ascertain your root folder, then just remember the initial value of NOT IN LIBRARY.  Or call it again at quitting time; it’s small and fast.

That way, you close up the windows in an executable, but leave it ready in the development environment, and you don’t have to set conditionals, or remember to set a boolean flag in your code.  It works without change in either situation.