Last weekend I was listening to Enon's High Society with the idea I'd post a review of it here on my blog. Music blogs typically report on the newest, usually not-even-released albums, but I'd rather discuss the stuff I'm listening to and why I like it (or don't).
I listened to each track of the album, and when I was finished, I couldn't really figure the album out because it seemed like it was several different records. The John Schmersal tracks served up a couple musical styles, and those sung by Toko Yasuda seemed totally different. So I didn't post.
Earlier today on good hodgkins he wrote about the same album and said pretty much the same thing, although he identifies only two different styles (Dayton-rock and bass-driven dance-punk) and closes his review with: "This is one of my favorite albums of the decade."
Anyway, here's what I wrote, unedited from that listening session:
Old Dominion -- Pretty much straight up rock with a strong guitar driving the song. A great start to the album.
Count Sheep -- Slower song, more electronic stuff going on in the background. Sharp drums, slow extended guitar parts. Dark feel.
In This City -- Upbeat dancy drums, nice bass and synthesizer melodies in the background really compliment Toko Yasuda's voice. Surprising pop sound after the first two more rock numbers with John Schmersal on vocal.
Window Display -- Another Schmersal tune very much in the Pavement, lazily sung indie-rock mold.
Native Numb -- Strange vocal process effect as another instrument, dark, heavy song. More solid drumming driving the song. Lots going on in the background.
Leave It To Rust -- More mellow song, like Count Sheep with a nice melody.
Disposable Parts -- The second upbeat dancy drum song sung by Yasuda with synthesizers and the processed vocals. Definately a different style than the other songs.
Sold! -- Almost sounds like The Cars with solo vocals to start the song, and other instruments coming in as the song progresses.
Shoulder -- Lots of synthesizer effects, droning guitars and a strong beat backing up Yasuda. Slower than her other songs on the record.
Pleasure and Privilege -- Punk, britpop sound. Great driving drums and loud guitars behind Schmersal's shouted lyrics (and screaming).
Natural Disasters -- Slacker indie sound like Window Display. Not as loud or driven as much of the record.
Carbonation -- Reminds me a bit of Love and Rockets for some reason maybe because of the way Schmersal is singing and the bass driving the song. Great lyrics.
Salty -- Third upbeat dancy song sung by Yasuda, but more rock than dance. Reminds me of a more techno version of Magnapop.
High Society -- More of the slacker indie sound. Maybe it's more about the strength of the vocals in the mix and the slower beat and more acoustic sound that's making me think Pavement. This one has a bunch of strings in it too, and a Morphine-esque saxiphone.
Diamond Raft -- Slow song with a synth loop pulling the song along. Ends before it really begins.
Excellent drumming, nice mixture of guitars, synthesizers and lots of effects. Yasuda has a striking voice. Schmersal can sing straight up rock, punk, as well as slacker-indie.Overall:
Great record, but quite varied in style. If the songs were in a different order you might think you were listening to three (or four!) different bands.
Anyway, I don't think it's one of the best of the decade like Ryan does, but it's pretty damned good if you can get past the variety of styles.
Back in April I wrote about some methods for seeing who is connected to your iTunes library and what they're listening to. Or downloading. There's actually a much easier way to see what's been accessed, at least if you're on a Mac. (Note that this might work under Cygwin on a Windows machine if the Windows filesystem stores access time.)
In Unix all files have three dates associated with them; creation time, last time modified, and last time accessed. You can see all of these times for a particular file by using the stat command. For example, in a terminal window:
$ stat The Jesus Lizard/Down/01 Fly On The Wall.m4a 234881026 2016664 -rw-r--r-- 1 0 4733250 "Aug 22 14:22:57 2006" "May 12 07:45:03 2006" "May 12 07:45:03 2006"
(I've edited the result slightly)
The three times shown are the last accessed, last modified, and the creation date. For this file, you can see that it was accessed earlier today. Since I wasn't playing any music with iTunes today, someone else accessed this file through my shared iTunes library.
There's an easier way to, ahem, find this information:
$ find ~/Music -type f -amin -360
This command shows all the files in the Music directory (where your iTunes music is stored by default) that were accessed in the last 6 hours. Students have just started showing up for the fall semester here at UAF, and when I ran this command at the end of the day, it yielded 451 tracks that other people on campus listened to. I also had my watch_itunes.py Python script running for part of the day, and it was clear from watching, that most of these "listeners" were actually downloading these tracks.
I wonder how long before this becomes a problem for the Recording Industry Association of America? Seems like Apple has created their own P2P filesharing network by allowing iTunes to share tracks in the same network block. Apple can claim it's not their problem because purchased tracks with their FairPlay DRM won't play on anyone else's computer. But what about all those ripped M4A and MP3's files that will play anywhere? It's a free-for-all, thanks to Apple.
Me says to RIAA lawyer: Talk to Apple. I'm just using iTunes, nothing more.
A couple posts ago I showed a hand-made similarity diagram for The Magnetic Fields, where I started at the last.fm similarity page and followed the top two most similar artists until I'd made a diagram. At the time I wondered how hard it would be to generate these things automatically.
Not too hard, it turns out, but it took me several months to get it all working properly. I wrote a Python script that queries the last.fm database, loading and saving the similarity pages for the artists related to the original query. Because it saves the similarities locally, after a few runs there's not much traffic to the last.fm web site.
Once all the data is collected, it generates a text file of links in the DOT language. These files are processed by the graphviz suite of programs (unflatten and dot, in this case) to produce similarity diagrams like the one below (click on the image to download a full-size PDF, 17 KB).
The diagram was produced by:
./build_and_graph.py -a "The Olivia Tremor Control" -c 60 -r 1 \ | unflatten | dot -Tps > /tmp/graph.ps
Click on the image for a PDF version of the entire graph. The darker and redder the lines, the more similar the two artists are. The options passed to my script control what the initial similarity cutoff is, and what the r-value is for the logistic function that controls how similarity changes as you get farther from the initial artist. For these values, the cutoff starts at 60 for the artists directly connected to The Olivia Tremor Control, rises to 80, then 92, 97, 99 and finally 100. That's why the links all get darker as you move down the diagram, moving farther from the original artist at the top.
It's smart to be thoughtful when writing, carefully choosing your words, crafting perfect sentences, reading and re-reading to make sure you haven't written anything stupid. Did I use the same adjective twice? Am I too tentative with my words? Is it good, or worth anyone's time to read it? Especially when your words are out there on The Internets, carried by those imaginary trucks, err., tubes.
I've been thinking about this a lot, as I watch the date on my last post to this blog disappear into the distant past. May 21st? Why haven't I written anything since then? Is there really that little going on in my life?
I've been waiting for the perfect posting. I've been messing around with
graphviz, which will draw directed and undirected graphs (like in my Magnetic Fields Similarity diagram post), and have even written a Python script to automatically generate them for a particular artist. It's awesome. But it's not perfect yet, so I haven't posted, waiting until I've got it down.
In the interim I've gone dip netting (9 red salmon, 1 king, plenty of food for me and heads for the dogs), broke one of my ribs, got snowed on in June during the Monahan Breeding Bird Survey, cut and chopped more than a cord of wood, and finished hanging drywall on the inside of the watershed (not in that order).
And I've downloaded and enjoyed a lot of great music. Right now I'm really enjoying Alligator by The National. I had downloaded Mr. November (track 13) back when I first subscribed to eMusic, but didn't get any other tracks. I finally got the rest today, and it's been on repeat (with the occasional Tokyo Police Club listen, which I also got today) since then. I've got it on the stereo now (AirTunes rocks. . .) and it sounds even better filling a room than boucing around my head via headphones.
In my mind, it fits into a sonic class with Spoon, Interpol and Bloc Party, but I don't know how much of that would bear out in a similarity diagram or in a critical analysis by someone who actually knows something about music. Anyway, the band is tight, and I dig it.
Other things that I've really enjoyed since the last time I wrote are The Fiery Furnaces (can't wait for Matthew Friedberger's solo albums on Tuesday), Girl Talk, The Futureheads and Art Brut. Reading the blogs on the Pitchfork Festival really made me wish I'd taken a trip to Chicago to visit family and attend. Sounded like a blast.
So I started this post off talking about my reticence (I had to look that up to figure out the spelling) about just posting whatever, whenever. Well, here goes. Whatever.
But check out Alligator. It's good stuffs.
I've been listening to a lot of The Magnetic Fields recently and decided to see what sort of data I could collect from last.fm about similar artists. I started on the similarity page for The Magnetic Fields, and wrote down the first two artists. Then I went to each of those artists similarity pages and did the same thing, producing a tree of artists that are similar to one another. The tree of highest similarity led from The Magnetic Fields to Belle & Sebastian to The Arcade Fire, and finally to Bloc Party, which led back to The Arcade Fire. Including the second most similar artists yielded a total of thirteen artists before all the links led to artists I already listed.
Here's what the similarity diagram looks like (click on the diagram for a larger version).
Artists in black are those that were directly connected to The Magnetic Fields or related artists during my initial search, the dark blue arrows are links between the most similar artists and the lighter blue arrows are the number two links. The numbers near the artist boxes are the number of artists that point to them.
After I made the original diagram, I wanted to see where some of my other artists that I thought might fit into the diagram. I added Of Montreal, Architecture in Helsinki, The New Pornographers, and Spoon, again, looking for the top two most popular artists for the new groups. I was certainly right that these artists are similar, although none of them were directly connected to The Magnetic Fields. Of Montreal is only two links away (Of Montreal and The Magnetic Fields both point to Neutral Milk Hotel), and the others I added are three links away.
I think it would be really interesting to figure out some way to generate these sorts of diagrams automatically (since the connections will change as the listening habits of last.fm submitters change), and to add more levels. I used Metapost to build the diagram, so the diagrams could be built programmatically, but it would take some work to read and follow the appropriate links from the last.fm web site.