Casting to Integers Considered Harmful August 6th, 2009
Patrick Stein


Many years back, I wrote some ambient music generation code. The basic structure of the code is this: Take one queen and twenty or so drones in a thirty-two dimensional space. Give them each random positions and velocities. Limit the velocity and acceleration of the queen more than you limit the same for the drones. Now, select some point at random for the queen to target. Have the queen accelerate toward that target. Have the drones accelerate toward the queen. Use the average distance from the drones to the queens in the i-th dimension as the volume of the i-th note where the notes are logarithmically spaced across one octave. Clip negative volumes to zero. Every so often, or when the queen gets close to the target, give the queen a new target.

It makes for some interesting ambient noise that sounds a bit like movie space noises where the lumbering enemy battleship is looming in orbit as its center portion spins to create artificial gravity within.

I started working on an iPhone application based on this code. The original code was in C++. The conversion to Objective C was fairly straightforward and fairly painless (as I used the opportunity to try to correct my own faults by breaking things out into separate functions more often).

Visualization troubles

The original code though chose random positions and velocities from uniform distributions. The iPhone app is going to involve visualization as well as auralization. The picture at the right here is a plot of five thousand points with each coordinate selected from a uniform distribution with range [-20,+20]. Because each axis value is chosen independently, it looks very unnatural.

What to do? The obvious answer is to use Gaussian random variables instead of uniform ones. The picture at the right here is five thousand points with each coordinate selected from a Gaussian distribution with a standard-deviation of 10. As you can see, this is much more natural looking.

How did I generate the Gaussians?

I have usually used the Box-Muller method of generating two Gaussian-distributed random variables given two uniformly-distributed random variables:

(defun random-gaussian ()
  (let ((u1 (random 1.0))
        (u2 (random 1.0)))
    (let ((mag (sqrt (* -2.0 (log u1))))
          (ang (* 2.0 pi u2)))
      (values (* mag (cos ang))
              (* mag (sin ang))))))

But, I found an article online that shows a more numerically stable version:

(defun random-gaussian ()
  (flet ((pick-in-circle ()
           (loop as u1 = (random 1.0)
                as u2 = (random 1.0)
                as mag-squared = (+ (* u1 u1) (* u2 u2))
                when (< mag-squared 1.0)
                return (values u1 u2 mag-squared))))
    (multiple-value-bind (u1 u2 mag-squared) (pick-in-circle)
      (let ((ww (sqrt (/ (* -2.0 (log mag-squared)) mag-squared))))
        (values (* u1 ww)
                (* u2 ww))))))

For a quick sanity check, I thought, let’s just make sure it looks like a Gaussian. Here, I showed the code in Lisp, but the original code was in Objective-C. I figured, If I just change the function declaration, I can plop this into a short C program, run a few thousand trials into some histogram buckets, and see what I get.

The trouble with zero

So, here comes the problem with zero. I had the following main loop:

#define BUCKET_COUNT 33
#define STDDEV       8.0
#define ITERATIONS   100000

  for ( ii=0; ii < ITERATIONS; ++ii ) {
    int bb = val_to_bucket( STDDEV * gaussian() );
    if ( 0 <= bb && bb < BUCKET_COUNT ) {
      ++buckets[ bb ];

I now present you with three different implementations of the val_to_bucket() function.

int val_to_bucket( double _val ) {
  return (int)_val + ( BUCKET_COUNT / 2 );

int val_to_bucket( double _val ) {
  return (int)( _val + (int)( BUCKET_COUNT / 2 ) );

int val_to_bucket( double _val ) {
  return (int)( _val + (int)( BUCKET_COUNT / 2 ) + 1 ) - 1;

As you can probably guess, after years or reading trick questions, only the last one actually works as far as my main loop is concerned. Why? Every number between -1 and +1 becomes zero when you cast the double to an integer. That’s twice as big a range as any other integer gets. So, for the first implementation, the middle bucket has about twice as many things in it as it should. For the second implementation, the first bucket has more things in it than it should. For the final implementation, the non-existent bucket before the first one is the overloaded bucket. In the end, I used this implementation instead so that I wouldn’t even bias non-existent buckets:

int val_to_bucket( double _val ) {
  return (int)lround(_val) + ( BUCKET_COUNT / 2 );

Apple Missed Their Own Boat On iPhone Backups May 28th, 2009
Patrick Stein

We’ve been able to rearrange apps on our iPhones for a year now, right? We’ve been able to move apps around to different screens.

For even longer than that, we’ve been able to reload our iPhones from backups.

Why, oh why, does a backup not contain the information about which app icons are where? How hard is this? I have 96 apps on my iPhone. Every single one of them still remembers its data despite the fact that I had to wipe the phone and start over yesterday. Sadly, the phone didn’t remember where any of the apps belong.

I spent the better (or worse as the case may be) part of an hour putting my apps back into a useful order. I can find several tutorials on the iPhone developer site that demonstrate how one might save such data in a location that gets backed up. Seriously….

Kindle App Makes Progress May 26th, 2009
Patrick Stein

Last month, I wrote about Four Ways eReader Beats Kindle on the iPhone. It looks like the 1.1 release of the Kindle iPhone app addresses the first of those four ways.

They now let you select between portrait or landscape mode. It lets you turn pages by tapping or swiping. And, it lets you change the background and text colors a bit.

I’m not terribly fond of its mechanism for letting you lock in landscape or portrait mode, but at least you can do it now. And, I don’t have free range on color choices, but at least I have some choice.

I hope they tackle my other three points in later releases.

eReader 2.1: The Unbotching May 11th, 2009
Patrick Stein

I mentioned earlier that eReader totally dropped the ball on free content by dropping support for and other free eBook sites.

I am happy to say that this functionality is restored in the latest version of eReader. I just tested it again to make sure it works. It seems peppier than before, too. It used to be a real pain to navigate around from within eReader. Now, it uses’s mobile site. It’s a much better experience.

Kindle Content Trumps eReader April 30th, 2009
Patrick Stein

Until the most recent releases of eReader, content was a close call between the Kindle app and eReader on the iPhone. Now, eReader dropped the ball, and Kindle scored on them.

What eReader Botched

Until the most recent release, eReader let you add books to your bookshelf from places like that provide free books in eReader format. I am hoping it was just an oversight when they wove in their own site a bit tighter. We shall see. It is obvious from the app reviews that the customers are annoyed.

The Kindle Advantage

You can download the free books mentioned above for the Kindle as well. You just have to jump through some hoops and re-upload them to Amazon before you can get them onto the Kindle app.

In addition to this, the new content available on Amazon is newer and cheaper than the content on the eReader site. It has always seemed wrong to pay full paperback prices for a book at eReader. eBooks for the Kindle seem to run between half and two thirds of the paperback prices.

Where To Go From Here

At the moment, I am stuck using both apps. I bought and got quite a few books in my eReader bookshelf, and it’s a better app anyway. But, there’s some newer, cheaper content at Amazon. And, now, if I want Project Gutenberg books or other free books, I’m going to have jump through Amazon’s hoops.


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