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2010-09-07

Perl vs PHP

• in /general/
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Longest line in a string, using no third-party code.

Perl

use List::Util;

my $longest = List::Util::max( map length, split /\n/, $str );

List::Util is core.

PHP

$longestLine = max(
    array_map(
        create_function('$a', 'return strlen($a);'), 
        explode("\n", $str)
    )
);

An added bonus is that create_function is a huge security hole and doesn't perform compile-time syntax checking.

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2010-05-07

Countdown Breakdown

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Countdown is a TV show in the UK. Two contestants take turns to ask the nice lady (Rachel Riley is hot) at the board to put up nine letters, which are set up in unsorted (randomly sorted) stacks below the board when the game starts. The players then have 30 seconds to construct the longest legal word they can from the letters. Legal words are not capitalised or hyphenated, and no letter can be used twice.

So I wondered, what is the best way of writing down the letters as they appear, in order to maximise your chances of finding words in them simply by sight? It follows to ask, what is the most common location for each letter in all of the legal words in the game? For example, if the letters I, N and G are in the mix, then it seems sensible to try to find -ing words with the rest of the letters.

perl -lne 'next if length($_) > 9 or length($_) < 3 or /^[A-Z]/ or /\x27/; print' \
/usr/share/dict/british-english > countdown-dict

montage *.png -geometry +0+0 -tile 3x9 countdown.png

Here is the spread.

It is not surprising that D, G, S and T are found at the ends of words, but what is surprising is the frequency difference. Plurals are allowed in Countdown, as are conjugations of verbs, which explains why the S graph increases so much at the end: most words with an S in can be reproduced with an S at the end, be they a verb or a noun. The same appies to T to a lesser extent, since it only applies to verbs, and this lesser extend is reflected in the increased frequency of T in other positions. But it does not explain D and G so much: these are letters that also only appear at the end of conjugations and not on plurals. And yet the D and G graphs resemble the S graph and not the T graph; thus it is clear that D and G are only as common as they are because of how they are used at the ends of words.

Another oddity is the graph for E. As the most common letter in the English language, it seems strangs that its use in words is more common towards the ends than the beginnings; hugely more frequent at the end than at the beginning, indeed.

Note also the graph for Q. No word in the Countdown dictionary ends in Q!

The thing that concerns me is that the centre of every graph appears to be a peak. I have a feeling that this is an algorithm artefact: there will be more words that have a letter at the 0.5 position then any other position, simply because the normalised location of the letters are spread out between 0 and 0.5 and 0.5 and 1, but every word with an odd number of letters will have a 0.5. The same is true for the 0 position and the 1 position. Every word has a 0 and a 1; half the words (assuming an even spread of lengths) have a 0.5; 1/3 will have a 0.33, etc ad nauseam.

I am considering how to improve the algorithm to accommodate this, which may involve a tame mathematician or two. Nevertheless, these charts may help Countdown enthusiasts by giving them clues as to where to put the letters that appear in order to make a collection of letters out of which words appear at a glance.

I think I will employ them tomorrow and we'll see how they do.