Orange Orange (category:programming)

[music map, a classical music concert visualizer]

Ever ask yourself, I wonder where major-record-label classical concerts are taking place in the world? Does Deutsche Grammophon have more concerts in central U.S. than EMI does? (They don’t.) What about central Europe? Just check out my CS171 final project: “Where’s the music?” (If you’ve never asked yourself these questions before, well, now you don’t have to!)

A few technical details about the project if you’re curious. (more…)

[poem visualizer, designed by me]

One in the morning isn’t always the best time to embark on programming projects of indeterminate length and scope. I learned that last night when, after having spent most of the afternoon and evening on a take-home midterm for my visualization class, I was beset with the dilemma of the extra credit problem. “Design your own poetry visualization,” along the lines of Poetry on the Road. This is a series of graphic designs commissioned each year by the Internationales Literaturfestival Bremen, designed by a team of professional graphic artists led by Boris Müller. The two things that immediately struck me about these graphics were 1) their juxtaposition of visual complexity and conceptual simplicity, and 2) their obvious requirement of a vastly greater number of hours — and sheer programming virtuosity — than the 24 hour maximum allotted for my midterm.

I must’ve been struck with temporary amnesia, or just had an acute attack of masochism, because I promptly forgot about the 3 problem sets that I had been saving up my sleep-hours for later in the week, and proceeded to bang away at Processing (coolest programming language ever) for the next 3 hours. The result, humble by the standards of any legitimate computer artist — but hopefully not of my exam grader — is this, a grid of colored squares representing “The Wasteland” by T.S. Eliot. I chose the poem mainly because it was long enough to really show patterns in my algorithm, but not so long as to crash the program. (although I would like to run Paradise Lost or The Iliad through, just for kicks.)
(more…)

[via Context Free Art Gallery and Community of Variation]

For a computer science assignment last week I wrote a program with a friend in Scheme that generates sentences using context-free grammar. By specifying a few basic rules for parts of speech and including a simple word list, you can get some remarkably coherent results — coherent, that is, in a strictly grammatical, minimalist sense. There’s actually no attention paid to the meaning of the words used, or to their relationship with each other, a consequence of the grammar being “context-free.” We had a few laughs using our program to generate bogus math proofs, but instead of puzzling you with a slew of inside jokes and insomnia-induced geekiness, I’ll point your way to a much more impressive — not to mention amusing — application of the same algorithm, this time used to generate an entire scientific paper. You can even put your own name down as an author! Here’s an example passage:

We question the need for digital-to-analog converters. It should be noted that we allow DHCP to harness homogeneous epistemologies without the evaluation of evolutionary programming [2], [12], [14]. Contrarily, the lookaside buffer might not be the panacea that end-users expected. However, this method is never considered confusing. Our approach turns the knowledge-base communication sledgehammer into a scalpel.
[Stribling et. al (PDF)]

Not too bad for randomly generated babble, is it? (more…)

[via flight404]

I love shopping week at the beginning of every semester, because it is a time of beautiful leisure and carefree distraction.

Okay, so I skip class for a couple days. But consider this–other, much more ambitious students will go to 20 classes that they don’t end up taking. And guess what? I also end up not taking those same 20 classes! I’ve effectively simulated Ivy-league-grade ambition by sitting in my room and surfing YouTube, and nobody is the wiser. A pareto-efficient transaction of sorts, between myself and The Man. (Maybe you question the correctness of my econ verbiage here. Maybe you’re right. Maybe I never sat in on any econ classes.)

Ah! But even without me once having to go outside, that perfect someone or something (but actually some thing) still strikes me like a thunderbolt between the eyes. (more…)

Thanks to C.J. for sending me the following, incredibly cool link: 80 Million Tiny Images. It’s a mosaic of millions of online images corresponding to nouns in the English language, and the spatial arrangement of the images in the mosaic reflects their semantic relationship to each other–i.e. closer images represent words that are closer in meaning. From the page (which also contains a link to the research paper):

Each of the tiles in the mosaic is an arithmetic average of images relating to one of 53,463 nouns. The images for each word were obtained using Google’s Image Search and other engines. A total of 7,527,697 images were used, each tile being the average of 140 images. The average reveals the dominant visual characteristics of each word. For some, the average turns out to be a recognizable image; for others the average is a colored blob. The list of nouns was obtained from Wordnet, a database compiled by lexicographers which records the semantic relationship between words. Using this database, we extract a tree-structured semantic hierarchy which we use to arrange tiles within the poster. We tessellate the poster using the hierarchy so that the proximity of two tiles is given by their semantic distance.

The most interesting thing about the result is the remarkable degree of color agreement that they achieve. Despite the fact that each tile is the average of several photos of the same thing, the end result is often surprisingly recognizable, and close-by tiles tend to have the same color scheme. The overall mosaic, rather than appearing as a wash of meaningless color noise, has some fairly uniform blobs on it because of the semantic association of images. The one they give on the website (composed of 7.5 million images, it seems–not 8 million) almost looks like a hunched over figure of a person. I wonder what the full 80 million images put together looks like.

The real question is, when can I get this as a wall poster to put up in my room?