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a framework for describing and running cellular automata
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This is a small framework to describe and run cellular automata


project demo / description page

basic docs

There are two classes: Cell and World. Cells describe a rule set for a particular kind of member. Cells are virtually placed within a world, by default in a von-neuman neighborhood.

To describe a cell's transition rules in the simplest case, you must implement the abstract method:

step(number: number): State

Cells have a generic render method that you will likely want to implement to render in some way, somewhere.

static render(value: State): R

If you'd like to make more interesting cells, it's useful to break out of 'pure' cellular automata and allow von-neuman / oop type computation over a cell's state and the current state of the world. The convenience hatch that allows for this is a prepare pass that runs over all cells in the world before the step pass runs. This is your chance to save arbitrary state to the cell's ontology by running some computation before the state of the world changes in the current transition iteration.

The World api lets you compose an arrangement of cells. By default cells are in VN lattice (8 neighbors). Composition follows a fluent api, e.g:

// An iterated prisoner's dilemma world generator
const Prisoners = (width: number, height: number) => {
  return new World({ width, height })
      { class: Prisoner, distribution: 25, options: { strategy: 'ALL-D' } },
      { class: Prisoner, distribution: 25, options: { strategy: 'ALL-C' } },
      { class: Prisoner, distribution: 0, options: { strategy: 'RAND' } },
      { class: Prisoner, distribution: 25, options: { strategy: 'TFT' } },
      { class: Prisoner, distribution: 25, options: { strategy: 'PAV' } },

// Or, something more complicated, like a wolfram CA world generator
const Rule = (rule: number) => (width: number, height: number): World<boolean, RGBA> => {
  // top layer of cells run the CA rule
  // and the bottom layers are a history buffer of past state
  const k = NeighborRule(rule);
  const cp = Copy('top', false);
  return new World({ width, height: 1 })
    .populateWith([{ class: k, distribution: 100 }])
    .extendDown(height - 1)
    .terraform((c, x, y) => (c === undefined ? new cp(x, y) : c))

The examples directory has some sample cells and worlds, including things like wolfram CAs, forest fires, caves, highways, jazz, and iterated prisoner's dilemma.

While your render can just be numbers that you print out to a console, it's likely that you want to render in some graphics paradigm. In the unlikely case that you have some strange reason to use three.js: this gist is a sample of a world renderer that also exposes a fluent api:

new CellAutomata(Prisoners(110, 70), { maxSteps: 1000, cellSize: 8 }).noBorder().start();
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