## Perl: I still love it

For the first time in a few years I am mucking about with Perl scripts.

I know the language is in decline and Perl 6 has become the ultimate in vapourware, but I have to report I still love it.

## Similarity, difference and compression

I am in York this week, being a student and preparing for the literature review seminar I am due to give on Friday – the first staging post on the PhD route, at which I have to persuade the department I have been serious about reading around my subject.

Today I went to a departmental seminar, presented by Professor Ulrike Hahne of Birkbeck College (and latterly of Cardiff University). She spoke on the nature of “similarity” – as is the nature of these things it was a quick rattle through a complex subject and if the summary that follows is inaccurate, then I am to blame and not Professor Hahne.

Professor Hahne is a psychologist but she has worked with computer scientists and so her seminar did cut into computer science issues. She began by stating that it was fair to say that all things are equally the same (or different) – in the sense that one can find an infinite number of things by which two things can be categorised in the same way (object A is weighs less that 1kg, object B weighs less than 1kg, they both weigh less than 2kgs and so on). I am not sure I accept this argument in its entirity – in what way is an object different from itself? But that’s a side issue, because her real point was that similarity and difference is a product of human cognition, which I can broadly accept.

So how do we measure similarity and difference? Well the “simplest” way is to measure the “distance” between two stimuli in the standard geometric way – this is how we measure the difference between colours in a colour space (about which more later) ie., the root of the sum of the squares of the distances. This concept has even been developed into the “universal law of generalisation”. This idea has achieved much but has major deficiencies.

Professor Hahne outlined some of the alternatives before describing her interest (and defence of) the idea that the key to difference was the number of mental transformations required to change one thing from another – for instance, how different is a square from a triangle? Two transformations are required, first to think of the triangle and then to replace the square with the triangle and so on.

In a more sophisticated way, the issue is the Kolmogorov complexity of the transformation. The shorter the program we can write to make the transformation, the more similar the objects are.

This, it strikes me, has an important application in computer science, or it least it could have. To go back to the colour space issue again – when I wrote the Perl module Image::Pngslimmer I had to write a lot of code that computed geometrical distances between colour points – a task that Perl is very poor at, maths is slow there. This was to implement the so-called “median cut” algorithm (pleased to say that the Wikipedia article on the median cut algorithm cites my code as an example, and it wasn’t even me who edited it to that, at least as far as I can remember!) where colours are quantised to those at the centre of “median cut boxes” in the colour space. Perhaps there is a much simpler way to make this transformation and so more quickly compress the PNG?

I asked Professor Hahne about this and she confirmed that her collaborator Professor Nick Chater of Warwick University is interested in this very question. When I have got this week out the way I may have a look at his published papers and see if there is anything interesting there.

## Betamax versus VHS in your browser

Everyone knows the story, even if, unlike me, they are not old enough to remember it: the video format VHS overcame the superior Betamax format to dominate the home video market in the 80s and 90s.

Of course, the claims that Beta was superior are rather tendentious but the fact that video producers stuck with a Beta format for their own tapes long after the rest of us switched to a VHS monoculture must say something.

Now, inside your browser, the same thing has happened. As is noted in today’s Guardian, the 1987-vintage GIF format refuses to die. These days you see far fewer static GIFs than even a few years ago (though they are still out there in large numbers) – JPEG and PNG dominate. But you’ll have to look very hard for an MNG (the ‘official’ PNG analogue of the animated GIF) or even APNGs, the unofficial but more widely used attempt to animate PNGs.

A few years ago I wrote a Perl PNG module – Image::Pngslimmer – which replicated many of the functions of the C libpng library, so I could use some of that in CGI code without having to switch from Perl to C and back again. Then – this was 2006 or so – PNG support was quite weak in browsers and GIFs were far more plentiful.

PNG is a superior format to GIF (especially for line drawings and similar – for general photographs JPEG is the superior choice, unless you truly demand a lossless format) and it is a good thing that it has edged GIF out in many places. But it seems we will be stuck with GIFs for many years yet.

## Making sense of Android’s complex development process

Back in about 1997 I bought a book about this new programming environment – it seemed something bigger than a language but smaller than an operating system – called Java.

Back then the idea seemed great – write once, run anywhere – but there was a lot of scepticism and, of course, Microsoft tried to poison the well through the tactics of “embrace and extend” with their J++ offering. All of that made it look as though Java was going nowhere.

I wrote a couple of applets – one was a “countdown” timer for Trevor Philips‘s mayoral election website in 1999, another was a SAX based parser for the largely Perl-based content management system I wrote for the Scottish Labour Party the following year, ahead of the 2001 election. But no one seemed to like applets much – it seems ridiculous now, but the 90K download needed for the SAX parser really slowed down the Scottish party’s site, even though I was pretty proud of the little newsticker it delivered (along with annoying teletype noises as it went). I forgot about Java.

But, of course, that was wrong. Java is programming language du jour these days, though Microsoft’s responses to the success of Java and the failure of J++, C# and .net, are also big.

Android is, of course, Java’s most prominent offer these days – literally millions of people will be running Android apps even as I write this and thousands of Android phones are being bought across the world daily. Time to get reacquainted, especially as my new job is once more about political communications.

But, as I discovered with C++ when I came back to it after over a decade for my MSc, Java has moved on a fair bit in that time and, unlike C++, I cannot say all the progress seems to be positive. Indeed Java seems to thrive on a particularly ugly idiom with developers being encouraged to write constructors of anonymous classes in the headers of functions – ugh.

I can certainly see the beauty of Groovy more clearly than ever, too. Though being an old time Perl hacker makes me resent Java’s heavy duty static typing in any case.

To help me through all this I have been reading O’Reilly‘s Programming Android: Java Programming for the New Generation of Mobile Devices. Now, usually O’Reilly’s books are all but guaranteed to be the best or close to the best of any on offer, but I have my doubts that is the case with this one – it seems to be sloppily edited (eg at different times it is difficult to follow whether one is being advised to use the Android SDK or the Eclipse editor) and falls between being a comprehensive introduction to Android programming and a guide for Java hackers to get on with it. It feels less than ordered, to be honest.

Now, maybe this is a function of the language and the complexity of the environment, I don’t know. But I would welcome any alternative recommendations if anyone has some.

## Writing more code to avoid writing any of the report?

I have managed to churn out 160 lines of working C today – which I think is quite good going, though, according to this, maybe I could have churned out 400 of C++ or even 960 of Perl (I love Perl but the mind boggles).

My program will tell you how pages pages are present or how many have been swapped (it has the ability to do a bit more too, but I have not exploited that even though it is essentially there) – you can fetch it from github here: valext (the name reflects the idea that this was going to be an extension to Valgrind but then I discovered/realised that was never going to work).

Anyway, what I now have to face up to is whether I am churning out code to avoid actually writing any of my MSc project report – I have a feeling that some of that is going on and think I need to start rereading Writing for Computer Science – which helped me greatly with the proposal.

## “Analyzing Computer System Performance with Perl::PDQ”

My MSc project is ambitious, sometimes it seems too ambitious: to test various ways in which the Linux VMM and scheduler could be modified to improve performance under high levels of stress.

Books are an essential guide in computer science, perhaps the essential guide, and having a book that helped me get to grips with issues such as measuring the Linux kernel’s use of the VM subsystem and how to design tests of application behaviour and page faulting rates and so on is increasingly important.

So, is Analyzing Computer System Performance with Perl::PDQ any good (found it through trawling round Amazon, but please send me any links to anything else from scientific paper upwards)? Anybody got some alternative suggestions?

## Smaller PNG graphic files from your LaTeX

I use LaTeX (LyX as the front end) to generate the occasional bits of mathematical script that appear here. Is it bad to admit it gives me a small thrill to see how the LaTex is transformed into something mathematical – makes me feel like a proper scientist/mathematician. Well, I’ve done it now…

WordPress.com will not display postscript natively (or if it can I have never been able to get it to work), so I usually open the .ps files in GIMP and convert them to a PNG – PNGs being optimised to handle things like line drawings and graphical images of text.

The PNGs that come out of this are of a reasonable size but they could be smaller. Some years ago I wrote some Perl code to do that (I needed something that worked in a CGI environment and while Perl is not so fast for even integer maths it was the best option).

That code is available on CPAN as Image::Pngslimmer and on a typical Linux/BSD (OSX too?) install (I am assuming you have perl and the cpan module installed) you should be able to get it on to your box with sudo cpan Image::Pngslimmer – which may ask you a lot of questions before it installs if you have never used CPAN but while YMMV the default answers should probably work.

You can write your own script or just use this quick and dirty one for PNGs of 64K or less:

#!/usr/bin/perl -w
use Image::Pngslimmer();
my \$srcfile = shift;
open INF, \$srcfile;
binmode INF;