Thursday, June 11th, 2009
Exams are over, the sun came and went, I got a first (hurrah!), a job for a couple of months and now it’s just .. working out what now? Completing Chrono Trigger is my first priority :D
Spent some time moving the last.fm charts thing to Python, because Python is tasty, PHP is clumsy, and matplotlib is a superb piece of kit.
Here’s a histogram of the number of tracks I’ve listened to each week for the last few years:

(x is the number of tracks in a week.) I looked at a few friends’ and there seemed quite a split between those roughly following a Gaussian distribution and those following something rather more exponential. I should experiment with different features of matplotlib, maybe narrow those bins a little. I’ve lots of little plans for other graphs and combinations.
Finally, there’s a great little piece about a quirk of the number 1/89 here. Sum the numbers of the Fibonacci Sequence in the following manner:
.01
.001
.0002
.00003
.000005
.0000008
.00000013
.000000021
.0000000034
.00000000055
.000000000089
.0000000000144
.
+ .
.
----------------
.01123595505... = 1/89
The link has an outline proof about why it’s true.
Wednesday, April 29th, 2009
Revising for an exam on machine learning and pattern recognition bitsandpieces on Friday and I came across a paper titled ‘An Introduction to the Conjugate Gradient Method Without the Agonizing Pain‘. Which is awesome.
The Conjugate Gradient Method is the most prominent iterative method for solving sparse systems of linear equations. Unfortunately, many textbook treatments of the topic are written with neither illustrations nor intuition, and their victims can be found to this day babbling senselessly in the corners of dusty libraries. For this reason, a deep, geometric understanding of the method has been reserved for the elite brilliant few who have painstakingly decoded the mumblings of their forebears. Nevertheless, the Conjugate Gradient Method is a composite of simple, elegant ideas that almost anyone can understand. Of course, a reader as intelligent as yourself will learn them almost effortlessly.
Its keywords are conjugate gradient method, preconditioning, convergence analysis and agonizing pain, and it has a chapter called ‘Eigen do it if I try‘ which (brilliant and awful title aside) is the first intuitive explanation of eigenvectors I’ve read, hurrah.
Tuesday, March 24th, 2009
Just a note to say I updated Historical Charts to take advantage of Last.fm automatically correcting misspelled info.
Thursday, February 26th, 2009
Take a look at the URLs used to make the charts at the bottom of this page.
ithankYouGodformostthisamazingdayfortheleapinggreenlyspiritsof
treesandabluetruedreamofskyandforeverythingwhichisnatural
whichisinfinitewhichisyesithankYouGodformostthisamazingday
fortheleapinggreenlyspiritsoftreesandabluetruedreamofskyand
foreverythingwhichisnaturalwhichisinfinitewhichisyeseecummings
It’d be even cooler if the chart was at all attractive..

Thursday, February 5th, 2009
Forever ago, in the glory-days of Napster and Kazaa, I discovered Radiohead (hurrah!) and amidst the 28.8kb/s hunt for b-sides and rarities on other people’s computers found myself in possession of a song called Cogs. It was a weird and haunting song that seemed to fit right into the Kid A/Amnesiac theme but didn’t fit with GreenPlastic’s suggestion that Cogs was an alternate title for Last Flowers.
It became this anomaly in my collection, Radiohead but not, and I forgot about it until today, when I thought I’d scan it with Last.fm’s command line fingerprinter which told me:
<track confidence="0.245223">
<artist>Ennio Morricone</artist>
<title>Man With A Harmonica</title>
<url>http://www.last.fm/music/Ennio+Morricone/_/Man+With+A+Harmonica</url>
</track>
Which wasn’t what I expected at all.
But now a six-year odd mystery has been solved and I’d love to know how the fingerprinter works. Probably some hairy maths .. it’s impressive it can figure these things, especially now they’re automatically redirected.
It’s still an excellent song.
Wednesday, January 28th, 2009
He’s standing there on Platform 5 of London Bridge station. He always is. Always in the same spot, always in the same outfit, always staring at me, always. And I’m always here, watching him.
We started forty years ago. Little has happened since. Every day we are here, staring.
I know his eyes.
They’re dark blue and jealous and bitter. I tried to decipher what had happened to make them once, but their glare intensified and I was scared so I backed down.