Monday, 19 September 2016

Music as code talks

I've been giving talks about music theory and code for a few years now, so I thought I'd collect them all together in one place. They are based on Overtone and my Leipzig music composition library.
  1. Functional Composition, about music theory from sine waves through to canons, given at Lambda Jam 2013 (code).
  2. Kolmogorov Music, about music and complexity theory, given at Strange Loop 2015 (code).
  3. Dueling Keyboards, about temperament and tuning systems, given at Clojure eXchange 2015 (code).
  4. Klangmeister, about my online live coding environment, given at FlatMap 2016 (code).
  5. African Polyphony and Polyrhythm, about music from the Central African Republic, given at Strange Loop 2016 (code). Slides are online.
If you're interested in my personal music, check out Whelmed (code).

Sunday, 3 July 2016

Falsehoods programmers believe about music

In the spirit of Patrick McKenzie's great post on falsehoods programmers believe about names, I am trying to write an equivalent one for music. Any false assumption that might be made in codifying music is a candidate for inclusion. Suggestions are very welcome.
  1. Music can be written down.
  2. Okay, maybe not with European notation, but there'll be a specialist notation for that kind of music.
  3. Music is finite in duration.
  4. Music has a composer.
  5. Music is about harmony.
  6. Music uses scales.
  7. Music uses equal temperament.
  8. Music uses tones and semitones.
  9. Music and dance are separate activities.
  10. Playing and listening to music are separate activities.
  11. Musicians can play their part separately from the overall composition.
  12. Music is performed by professional musicians.

Sunday, 26 June 2016


Douglas Hofstadter's Godel, Escher, Bach is one of my favourite books. Commonly referred to as GEB, this book is a mesmerising meditation on consciousness, mathematics and creativity. The central idea is that of a "strange loop", in which the same message is interpreted on multiple semantic levels.

GEB was the first place I came across the idea of a musical canon. A canon is a beautifully austere form of composition that was popular in the Baroque period. A canon consists of a dux part which sets out the base melody accompanied by a comes part which is some kind of transformation of the dux.

Here is the structure of a canon described using the programming language Clojure. f stands for the transformation selected by the composer.

(defn canon [f notes]
  (->> notes
       (with (f notes))))

For example, the comes might be formed by delaying the dux by a bar and raising every note by a third. In my talk Functional Composition I show how computer code can be used to explain music theory, focussing on JS Bach's Canone alla Quarta from the Goldberg Variations. Canone alla Quarta is an unusually complex and beautiful canon where the transformation is composed of a delay of three beats (a simple canon), a reflection (a mirror canon) and a pitch transposition down a fourth (an interval canon).

Here is the transformation from Canone alla Quarta written in Clojure. comp is a Clojure function for composing multiple transformations together.

(defn canone-alla-quarta [notes]
  (->> notes
         (comp (interval -3) mirror (simple 3)))))

I was working on a talk for last year's Strange Loop programming conference (itself a reference to Hofstadter's work) and I decided that I wanted to create my own canon as a tribute to GEB as a finale. Rather than use an ordinary musical transformation for my comes, I wanted to pick something that spoke to the idea of composing music with computer code. I also wanted to incorporate GEB's theme of interpreting messages on multiple levels.

I took the letters G, E and B, and used the ASCII codes that represent these letters as though they were MIDI pitch codes. This gave me my dux. I then took the same three letters and interpreted them as the musical notes G, E and B. This gave me my comes. I had obtained a canon based not on musical concepts like delay or transposition, but on encoding schemes used in computer programming.

(defn canone-alla-geb [notes]
  (->> notes
         #(where :pitch ascii->midi %))))

I elaborated the harmonies provided by this canon into a complete track, composed via computer code. The dux and the comes are joined by various other parts, some using polyrhythms to generate apparent complexity from underlying simplicity.

Eventually, the dux and the comes are accompanied by a third canonic voice, in which the names of Godel, Escher and Bach are read out by a text-to-speech program. So the theme of three notes G, E and B becomes a canon of three voices musical, technical and allusive to the three great creative spirits Godel, Escher and Bach.

Listen to the recording.

Read the code.

Watch the talk.

Sunday, 17 May 2015

Lanham on explicit data dependencies

Who's kicking who?

- Richard Lanham, Revising Prose

Tuesday, 20 January 2015

Korzybski on story points

The map is not the territory.

- Alfred Korzybski

Sunday, 19 October 2014

Types don't substitute for tests

When reading discussions about the benefits of types in software construction, I've come across the following claim:
When I use types, I don't need as many unit tests.
This statement is not consistent with my understanding of either types or test-driven design. When I've inquired into reasoning behind the claim, it often boils down to the following:
Types provide assurance over all possible arguments (universal quantification). Unit tests provide assurance only for specific examples (existential quantification). Therefore, when I have a good type system I don't need to rely on unit tests.
This argument does not hold in my experience, because I use types and unit tests to establish different kinds of properties about a program.

Types prove that functions within a program will terminate successfully for all possible inputs (I'm ignoring questions of totality for the sake of simplifying the discussion).

Unit tests demonstrate that functions yield the correct result for a set of curated inputs. The practice of test-driven design aims to provide confidence that the inputs are representative of the function's behaviour through the discipline of expanding a function's definition only in response to an example that doesn't yet hold.

All of the examples that I use in my practice of test-driven design are well-typed, whether or not I use a type system. I do not write unit tests that exercise the behaviour of the system in the presence of badly-typed input, because in an untyped programming language it would be a futile exercise and in a typed programming language such tests would be impossible to write.

If I write a program using a type system, I still require just as many positive examples to drive my design and establish that the generalisations I've created are faithful to the examples that drove them. Simply put, I can't think of a unit test that I would write in the absence of a type system that I would not have to write in the presence of one.

I don't use a type system to prove that my functions return the output I intend for all possible inputs. I use a type system to prove that there does not exist an input, such that my functions will not successfully terminate (again, sidestepping the issue of non-total functions). In other words, a type checker proves the absence of certain undesirable behaviours, but it does not prove the presence of the specific desirable behaviours that I require.

Type systems are becoming more sophisticated and are capable of proving increasingly interesting properties about programs. In particular, dependently typed programming languages like Idris can be used to establish that lists are always non-empty or the parity of addition.

But unless the type system proves that there is exactly one inhabitant of a particular type, I still require a positive example to check that I've implemented the right well-typed solution. And even if the type provably has only one inhabitant, I would still likely write a unit test to help explain to myself how the abstract property enforced by the type system manifests itself.

A type system is complementary to unit tests produced by test-driven design. The presence of a type system provides additional confidence as to the correctness of a program, but as I write software it does not reduce the need for examples in the form of unit tests.

Sunday, 12 October 2014

Hiding the REPL

I depend heavily on Clojure's REPL, because it's where I write music. Over time, however, I've become less focused on directly interacting with the REPL, and pushed it more and more into the background.

I use Vim Fireplace, which gives me the ability to evaluate forms in a buffer by sending them to an nREPL instance. There's also a REPL available within Fireplace, but I find I only use it for simple commands like stopping a piece of music or printing a data structure.

Speaking to Aidy Lewis on Twitter today, I've come to realise that there may be two different models for REPL-driven development.

Aidy described a model where the REPL is ever-present in a split-window. This brings the REPL to the foreground, and makes it conveniently available for experimentation. I would describe this as a side-by-side model.

On the other hand, I treat the buffer itself as my REPL. I write and refine forms, evaluating them as I go. If I want to experiment, I do so by writing code in my buffer and either evolving it or discarding it. My navigation and interaction are as they would be in any other Vim session, punctuated by occasional re-evaluation of something I've changed. This seems to me more like a layered model, with my buffer on the surface and the REPL below.

The reason I value this mode of interaction is it makes me feel more like I'm directly interacting with my code. When I make a change and re-evaluate the form, I have the sense that I'm somehow touching the code. I don't have a mental separation between my code-as-text and the state of my REPL session. Rather they're two ways of perceiving the same thing.