Older blog entries for welisc (starting at number 30)

12 Dec 2001 (updated 9 Jan 2002 at 20:11 UTC) »

There's an interesting interview with Lincoln Stein on perl.com. He says that computer scientists find it much harder to learn biology than biologists do to learn computer science because computer scientists need to learn a new paradigm while biologists are just picking up another skill.

He makes it sound so easy. I tell you it is not.

tk pointed me to Psyco, a compiler designed to execute Python at near the speed of compiled languages. Erann Gat proposed Lisp as an Alternative to Java; Psyco offers the prospect of being able to propose Python as an alternative to C but it'd be worthwhile even it only allowed Python to be substituted for Java . Python is attractive because the Pmv project is using Python to develop components for structural bioinformatics.

11 Dec 2001 (updated 9 Jan 2002 at 20:14 UTC) »

It's occurred to me - after a mere four years - that I've spent much more time writing code for extracting propensity tables and loop modelling than I have actually running it. Since the output of the programs is what I'm really interested in, it's obvious that I should be trying to minimise the development time.

Using Perl or Python would certainly reduce development times but at a cost in terms of performance. However, if it saves a lot of development time, this might actually offset the increased running time to the extent of reducing the overall time to get results. And there's always the option of using SWIG to drop down into C for the heavy-lifting bits.

This of course still means having to write the heavy-lifting bits in C or C++.

I really like functional languages: they let you write high-level code and write it quickly, and then compile it to get optimal performance. The problem with functional languages is that the paradigm is very different to imperative programming so there might be problems persuading coworkers that they're a good idea. There's also the perennial problem of people not wanting to use lesser-used languages that add little or no value to a CV.

I suspect I'm going to end up with a compromise solution such as gcj-compiled Java, a language whose only selling point for me is that it eliminates a lot of the complexity of C++ (while also eliminating some of the good features of C++).

7 Dec 2001 (updated 9 Jan 2002 at 20:14 UTC) »

Reading Structure and Interpretation of Computer Programs and working through the exercises in Accelerated C++. C++ is certainly an improvement on C but Scheme makes it look like a supercharged assembly language.

16 Nov 2001 (updated 9 Apr 2003 at 09:21 UTC) »

IT job market imploding. Interest in structural biology reviving. First sighting of Lisp in a bioinformatics job ad [This was at the EBI].

My first attempt to read Damian Conway's Exegesis 3 left me with a spinning head and serious doubts about Perl 6. Piers Cawley's Not just for Damians acknowledges that a lot of people feel the same way but makes a good case for the new features and inspired me to have another go at Exegesis 3. I liked what I found: the features discussed in the Exegesis have a distinctly functional flavour to them that will make it possible to write Perl code that is more concise but also more readable.

18 Oct 2001 (updated 7 Dec 2001 at 20:47 UTC) »

The O'Reilly book (in French) about O'Caml is online. I skimmed through it and was surprised to find I could follow it pretty well. This seems likes an interesting, if slightly unusual, way to brush up on my technical French. A volunteer project to translate it into English has completed about 70 % of the text.

8 Sep 2001 (updated 17 Oct 2001 at 18:18 UTC) »
The results of the Fourth ICFP programming contest are out. First place went to Haskell Carrots. The Dylan Hackers came second, with most of the team using Gwyddion Dylan, which would indicate that the current version is in a very usable state. Dylan is interesting for the reason outlined in the contest write-up:
A major design goal of Dylan is to produce a language in which complex programs can be rapidly prototyped in the same way as with dynamically-typed languages such as Smalltalk or Lisp or "scripting" languages, while at the same time enabling performance comparable to statically typed languages such as C or ML.

Having problems building DrScheme and Bigloo from source using gcc 3.0. Luckily, I still had the (very) old installation of gcc 2.91.66, which compiles them without a problem.

Spent half the afternoon tracking down a mysterious segfault caused by one little line:

static char *sort_phen1 = NULL,*sort_phen2 = NULL;
static int initialised = FALSE;

/* lots of code */

static int sort_comp_phen(Ind *s1, Ind *s2)

char *sort_phen1,*sort_phen2;
if (!initialised){
sort_phen1 = chrom_string();
sort_phen2 = chrom_string();
initialised = TRUE;

strcpy(sort_phen1,chrom_phenotype(s1->chrom)); strcpy(sort_phen2,chrom_phenotype(s2->chrom));
return strcmp(sort_phen1,sort_phen2);


Strange how you can never see something that's staring you in the face. Compiling with the -Wshadow flag would've caught it.

24 Aug 2001 (updated 24 Aug 2001 at 13:25 UTC) »
Bruce Eckel isn't impressed by Ruby. I've tinkered with Ruby and I like the pure OO design but there are two reasons why I don't see myself doing much with it. First, it's not as concise as Perl for writing small scripts (neither is Python). Second, and more significantly, there are no Ruby libraries that make it worth my while learning it. By contrast, there are at least two Python molecular modelling projects, Pmv and MMTK, each of which is fairly mature and featureful. Even if I didn't care about Python having a cleaner design than Perl, these two libraries would be a compelling reason to learn it.

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