20 years of "...Adventures beyond the Ultraworld"

The_orb_-_adventures_beyond_the_ultraworld

It's 20 years since the release of The Orb's "...Adventures beyond the Ultraworld". This album has a special significance for me as it was one of the first "ambient" albums I bought and made me realise that this electronic music stuff could be cool. I vividly remember where I first heard it: Tower Records in Glasgow (just by Central Station. "Don't go looking for it - it's not there anymore"). I was up in the jazz / classical floor (such a pseud!) and there was this weird music playing that seemed to mesh classical with dance beats. Most odd.. It was "Into the fourth dimension" from the album featuring a sample of Allegri's "Miserere" and a Vivaldi Violin Concerto. I stuck around in the shop to hear the end of the track... 

I'm not exactly sure whether I bought it there and then. I'm also not sure when I heard "Little Fluffy Clouds" for the first time, but I CERTAINLY remember hearing "A huge evergrowing pulsating brain that rules form the center of the Ultraworld (Loving You)". John Peel's Festive 50 in 1990 featured a Peel Sessions version of the track and in those days I used to like listening to the radio late at night and taping anything from the Peel show that took my fancy. Because it was Festive 50, there was lots to snag on that night and I recall Peel announcing this track, and then listening in for a bit to see what it would do, hitting the record button a couple of minutes in, then switching it off after 5 minutes, then being aware 15 minutes later that it was STILL going on. Amazing stuff. (That's the 20:14 version which ends with a nice rendition of "Oh I do like to be beside the seaside" on a Wurlitzer organ).

"Little Fluffy Clouds" was the "hit" from the album (topping the charts at #87) and probably the track that gets most airplay. It was this track that introduced me to "Electric Counterpoint" by Steve Reich, since the track features a huge list of samples, some known and some unknown. This track has since passed into the stuff of legend, remix and parody...

I think this album led me on to Orbital - Orbital 1 (Green album), which got me firmly into all things bleepy... And the rest, as they say, is history. Without "...Adventures" there would be none of my weird ambient wibbling on the net. And I probably would still be trying to learn Geddy Lee licks on the bass. Which would be a shame.

Desert Island Albums

Changing the format of the original idea a little - these are albums that I'd like to accompany me on my desert island. They're not necessarily my favourites but rather are interesting enough to sustain several repeated listenings... I hope I never get bored with any of these.
Spotify playlist

  1. The Blue Nile - A walk across the rooftops. To be honest it's a toss up between this album and "Hats" - they're both wonderful - but this album sneeks in by virtue of being more interesting. There's a wonderful sparseness to the sound which makes it a very contemplative listen.
  2. The Cinematic Orchestra - Every Day. When you get bored of Zero 7 or Air then try The Cinematic Orchestra. They have an additional lushness in arrangements and sounds that sets them apart, and yet they still maintain a lazy, sunny day, new-jazz feel. This is a great album that combines jazzy instrumentals with vocal tunes.
  3. DJ Shadow - Endtroducing. Hip-hop sampling taken a whole new level. Great tunes. Very inventive sounds and soundscapes. This is one album in particular that I don't rate as a "favourite" per se. But it is one that I could keep listening to again and again and hear more and more layers. 
  4. Goldfrapp - Seventh Tree. I love the arrangements on this Goldfrapp album. They've left the electro-pop of the previous two albums and gone back to the more atmospheric, cinematic tracks of "Felt Mountain".
  5. Imogen Heap - Ellipse. Fabulous noises on this one. And great arrangements. And superb engineering (clarity of sounds, mix etc.). All done by Imogen herself. Great songs too... The special edition also shows off the instrumental tracks without the singing is also great for hearing the detail.
  6. Jon Hopkins - Insides. Jon Hopkins is a genius. All his albums are worth listening to (over and over) but the breadth of styles, sounds, mixing, arranging on this album means that it's never far from the play button. Love it. Deeply.
  7. Jon Hopkins & King Creosote - Diamond Mine. I guess it's not the done thing to have more than one album from a particular artist in this kind of list, but if I'm stuck on a desert island I'm going to have to insist that this album accompanies me. It's just too brilliant to ignore.
  8. Lusine - A certain distance. I loves my electronica. And this is really good electronica. Last year this album, Four Tet's "There is love in you" and Gold Panda's "Lucky Shiner" (along with Jon Hopkins' "Insides") were on heavy rotation. They're all great, but the Lusine album is the more interesting one to bring to a desert island...
  9. The Orb - ...Adventures beyond the Ultraworld. Twenty years on and it still sounds brilliant. This album first got me interested in electronica and ambient music (even though much of it is dub, rather than either of those). Again, another album that I can listen to a lot.
  10. Orbital - Orbital 2 (Brown Album). Epic electronica. Moves on from the first album and inserts weird samples (Australian pedestrian crossing, Star Trek, Withnail and I). Great sweeping tunes, fantastic arrangements, forward momentum. What more do you want from an album? Oh yeah, and Orbital were one of the first electronica bands that proved that you can take these sounds out on the road and not just play exactly the same arrangement night after night. Wonderful.
  11. Pixies - Doolittle. I don't need to justify this one. It's perfect.
  12. Radiohead - OK Computer. How many albums am I allowed? Who cares, this one's coming. I didn't get into OK Computer until fairly recently. I had "The Bends" which I really love, but hadn't gone past that, since I hadn't really liked "Karma Police" when I had heard it. But revisiting the album recently I discovered that there's lots to like. A very varied album with loud bits, quiet bits, guitar bits, electronic bits, weird bits, lovely bits. Something to get yer noodle around... Proper good.
  13. Steve Lawson - Not dancing for chicken. I love Steve's music, and I wouldn't like being on a desert island without this; especially the track "Jimmy James" which is one of my all time favourite pieces of music. 
  14. Teenage Fanclub - Songs from Northern Britain. I love Teenage Fanclub. Jingly-jangly guitars, close harmony, great songs, lovely (lack of) attitude. Perfick. This album is almost as good as it gets from TFC. Love everything on it.
  15. Zoe Keating - One Cello (x16). Zoe's album is that lovely mix of organic and electronic sounds. Except every sound is produced from her cello... But the sensibility of this album sits very much within the electronica world. There are spiky moments, lush moments, soaring melodies, woody rhythms. It's pretty damn fine, and I'd like to be able to listen to it many times. Undisturbed.

And by the way, if you want to hear Steve or Zoe's albums, go listen on Bandcamp and buy them from there. Artist gets the biggest possible slice of the cash that way and you can listen to more than just a paltry 30 seconds. In fact in Steve's case, you can download and listen to the whole flippin' album for no money, at no cost and completely free. Even in super-high-res.

What is my luxury item? Well, I'd like a flipping huge-munguous PA please. Hi-fi sound quality. VERY loud. After all, it's not like my neighbours are going to object. And some of these albums need a certain decibel level... ;-)

Desert Island Discs #3

Teenage Fanclub - Ain't That Enough

Teenage Fanclub feature heavily in my music collection. I first heard "A Catholic Education" while on a trip to the US (!) in 1990. That first album didn't grab me initially, sounding to my untutored ears as slightly sloppy and shambolic. However the close harmonies certainly did have something... Teenage Fanclub (TFC / The Fannies) were around a lot while I was at University - I saw them many times unwittingly, either supporting other bands or cropping up at festivals and they seemed to have a residency at King Tuts Wah Wah Hut in Glasgow during the early 90s. For a long time I have to confess I still didn't get it. With "Bandwagonesque" they finally clicked (I'm a slow learner) and I got it. Their music has been the soundtrack to much of my life ever since. I love their very un-rock-star presence and humility while on stage... Very ordinary guys playing extraordinary music.

This particular track has resonance for me since it came out in June 1997 while I was spending a (rather difficult) year working in the US. My girlfriend (now wife) was in the UK and this track got a lot of airplay on the radio in the UK that summer. She told me that I had to listen out for it. There's something about the jangly guitars, perfect harmony, beautiful lyrics... Brings a tear every time.

Many songs gain a place in our hearts because of the context of what was going on when we first remember hearing them. I guess with this one the context propels it into my favourites list, but I also like to think that the music and lyrics themselves would have got it there regardless...

(There are at least 6 other Teenage Fanclub tracks that could easily make it onto this Desert Island. If you haven't listened to TFC much, then I exhort you to go and take a listen on SpotifyLast.FM, iTunes)

Statistics without Maths

I got an interesting message from Chris Atherton the other day who has offered to do a workshop at the Technical Communications UK conference on statistics and data visualisation. The problem is that for some tech writers, their understanding of statistics is limited and she wanted to do a primer that wouldn't be too scary for them while still engaging the more quantitative members of the audience. How to meet the needs of both groups? 

My idea is that you could motivate and teach statistics without having to resort to equations and mathematics. How? Lots of graphs. Like this:

(download)

Let's look at a sample of 10 observations. You can see the spread in the data. Since I generated this data, I know that the mean should be 0. For this sample it looks quite different. People sometimes get confused about the difference between standard deviation and standard error (of the mean). Standard deviation talks about the spread of the observed data. Roughly speaking, 2 standard deviations ought to cover 95% of the data - so most of the data should lie between the outer vertical red lines in the second graph.

(download)

If we increase the number of observations, we get a much better handle on what the mean value actually is. (Large samples give better confidence than small samples for making inferences). By the time we get to 1000 samples we can see that we the estimated mean and standard deviation really do match what I used to generate the data (mean = 0, std dev = 1).

Swm5

Our sample of 10 observations was only ONE trial though. If we repeat the exercise 10 times then we can see how variable the data is between trials, and that the mean changes from one trial to the next.

(download)

Going back to the first sample, we can construct the standard error of the mean, which tells us how certain we are about the estimate of the mean based on this data. (Actually in this example the interval estimate for the mean excludes zero, even though the true value is zero).

Bigger samples reduce our uncertainty in the mean, so the standard error of the mean is smaller and the interval estimate for the mean is narrower.

(download)

Now imagine we had two mechanisms generating the data so that what differs between them is the location of the distribution. We can estimate the means and look at how different they are. Of course, we now know that larger samples give better characterisation of the distribution and that results may differ across trials for the same sample size. This is true here too.

Finally, if we wanted to formally say whether the difference between populations that we see here is statistically significant what we need to do is to find out how likely this observation would be if there was NO difference between populations. So we take 100 trials of 10 samples from two populations both centred on zero, order these by how different the two samples are and see where our sample of two different populations lies. In this case there's no trial where the difference is bigger than we see between the two samples of 10 observations. That means the p-value is <0.01.

(download)

So. Did you get all that?

The lesson for the more quantitative folks? How you can describe stats without maths.

[Code]

Click here to download:
Stats_without_maths.doc (5 KB)
(download)

Desert Island Discs #2

The Cure - Friday I'm in Love

The Cure get a bad rap as gloomy, glum, Crown Princes of the Goth world, but there's something about this track that's really upbeat and uplifting. There has been some debate about the meaning of the lyrics, but you know what? I don't care. Every time I hear it I smile and feel better. Also, I hold this as a really great example of production. All instruments are beautifully clean and clear - you can hear great separation between the parts: acoustic guitar in the background and the picked lead guitar line, mahoosive bass and kick, hi-hat and claps / tambourine. If you're producing a track, slap this on to check how your mix compares (it won't!).

Desert Island Discs #1

Pixies – Debaser

I first heard this in my second year at University. I had spent much of the first year nursing a long-standing relationship with Rush. It wasn't until the second year that my good friend, and later my best man, Stuart handed me a cassette of Doolittle and quietly said "Here. Check this out." The rest, as they say, is history. I had discovered "Indie". Most shamefully though, I didn't discover the Pixies until the term AFTER they had toured Doolittle and played in the local student union directly across from the Maths and Statistics department.

This is the first track on Doolittle and grabs you right by the scruff of the neck. Loud, hard and completely uncompromising, for me it sets the standard by which all other "rock" is judged. Does band X "rock"? Well, if they make the hairs on the back of my neck stand up to the extent that this track does, then yes. If not, then I'm afraid it just doesn't cut it.

I've listened to this more times than I care to count. Every time it provokes that same visceral reaction that makes you want to leap around and cry "Chien!" at lung-busting volume every time it comes round.

The first time I got to see the Pixies play live was in Glasgow on the Planet of Sound tour where the band played three songs (including this one), the stage collapsed and the gig was cancelled. I like to think it was the crowd moshing, jumping and crying "Chien!" that made the stage give way. Maybe it was, maybe it wasn't. In my mind this is the only logical reason…

If I was marooned on a desert island I'd like to have this track (in fact the whole Doolittle album) with me. When things got tough, I could listen to this track, cry "Chien!" at the top of my lungs and maybe it would be cathartic enough for me to live on for another day.

type="n" graphs in R

Click here to download:
type n graph.R (2 KB)

One of the most useful graphs you can produce in R using the plot(...) function is one with nothing in it. Using the type="n" option, you get a blank canvas to which you can add points, lines, text, shaded regions and build up something that's really very useful. Other packages such as lattice and ggplot2 produce really nice graphics, but when it comes to annotating these graphs and tailoring them to your needs you have to delve into more complex options and programming (panel functions) and this has quite a steep learning curve. Keeping it simple with the plot(...) function and using lines(...), points(...), text(...), polygon(...) etc. allows you to build quite sophisticated graphs without too much hassle.

Working with multiple graphs in R

I'm trying out screencasting to help illustrate some tips and tricks with the statistics software package R, but also to hone my skills in this area.

I'm including the code for this example as an attachment to this post.

I'm in the process of preparing the next one, which will look at using the basic graphics function plot(...) but with the option type="n".

Click here to download:
Multiple graph example.R (0 Bytes)

This year I have been mostly listening to...

It's that time of year when we look back at the year that has just gone and make lists of our favourite things of 2010 and try to make sense of what has happened over the last 12 months. A lot of random stuff has happened this year and I've been pretty busy - so not so much music making for me, but LOTS of music listening. Thanks to a very lovely bunch of people who I follow on Twitter, the wonderful people at Spotify for providing a listening station for new music, and lots and lots of lovely people who actually MAKE the music, I've got a whole new list of artists that I've "discovered" this year.

Here's the list of what I've been listening to this year (courtesy of LastFM).

Screen_shot_2010-12-31_at_23

Artists on the Ghostly International roster (or formerly on their roster) have featured heavily this year).

Kiln - Fabulous ambient electronica. The album Dusker is especially recommended.

School of Seven Bells - MBV-esque band whose albums have that huge "wall of sound" of My Bloody Valentine but with beautiful harmonies and aesthetic. Unfortunately though, although I've seen them twice, they don't seem to be able to replicate that sound live. Still on heavy rotation on the old iPod though.

Teenage Fanclub, Pixies - saw both bands live this year (hurrah!). Particularly good to see Pixies after only 19 years hiatus. Wonderful bands, great music.

Steve Lawson -  Steve has had a prolific year releasing at least 3 albums and a uploading a whole bunch of new music for us to listen to FOR WHATEVER PRICE SEEMS REASONABLE (including no money at all!). His music is still the soundtrack to many of my days.

Lusine - Discovered the track "Gravity" via the excellent Create Digital Music blog and a free release soundtrack for a SyFy channel programme. Wonderful electronica with just the right amount of glitchyness. Highly recommended.

Goldfrapp - The orchestration and arrangements on Goldfrapp's albums just keeps me coming back for more. Haven't really given their new album much of a listen since it's returning to the electro-pop style. Love the grandiose soundtrack numbers though...

Jon Hopkins - Had the good fortune to see Jon Hopkins support sviib recently. Loved his music before. REALLY love it now. The man's a genius.

Zoe Keating - Avant-cellist Zoe released her album "Into the Trees" this year and it is a real corker. Love her electronica / ambient / cello / avant-something / neo-something else music. Again, the soundtrack to many days...

Christopher Willits / The Sight Below - Another couple of artists from the wonderful Ghostly International. Both seriously worth checking out. (The Sight Below = ambient guitar with 4/4 beats. Most wonderful).

lowercase noises - Can't say enough good things about this music. I loved the guitar-based ambient music of Rob W Jackson and this artist takes that into the next dimension. Perfect. Lovely. 

Four Tet - Really liked earlier work by Four Tet but the album "There is love in you" and the track Angel Echoes has been a revelation. Wonderful in every way.

I encourage you to look these up and have a listen. I don't think you'll be disappointed.

If you're interested in albums on my "Check this out" list or things that I recommend, then Spotify is the place to find me.

Is this good or bad programming?

If I come across this kind of code when I'm checking (QCing) code it makes me want to punch the programmer's face. I find that it's impossible to step through and check each dataset with the previous incarnation. Which is how I check what has happened in between lines. (In this case the changes are trivial, but the principle applies). However when I discussed it with a colleague recently he said "No, I think this is cool. Your final dataset is still called 'data' and you can easily see what changes have been made between the input and the final version ready for analysis."

data <- read.csv("foo.csv")
data <- data[data$STUDY == 1234,]
data <- data[!is.na(data$VAR),]
data <- data[data$VAR > 0,]
 data$VAR<- log(data$VAR)

So. Is this cool? Or really, really bad?