Models by berekuk

/*
 * via https://twitter.com/AISafetyMemes/status/1729892336782524676
 * TODO:
 * - represent distributions as beta distributions or truncate tp [0,1]
 * - links to sources with docstrings
 * 
 * Other implementations:
 * - https://aiopinions.org/questions/what-are-the-chances-that-ai-will-cause-human-extinction
 */

export autoTable(data) = {
  keys = List.flatten(data) -> map(Dict.keys) -> List.flatten -> List.uniq

  Table.make(
    data,
    { columns: keys -> map({|key| { name: key, fn: {|f| f[key]} }}) }
  )
}

@showAs(autoTable)

/* Squiggle doesn't allow naive recursion; f(x) = f(x-1) will fail.
 * But it's still possible to simulate recursion by passing a function to itself.
 * The simplest version of this trick, which would cause stack overflow, is this:
 * f(f) = f(f); f(f).
 *
 * This model shows how this can be useful in practice, by reimplementing
 * `List.reduce` in pure Squiggle.
 */
innerRecurse(state, halt, process, tail) = {
  newState = inspect(process(state))

export dropdownMenu(items) = Calculator.make(
  {
    fn: {|tab|List.find(items, {|item|item.name == tab}).value},
    inputs: [
      Input.select(
        {
          name: "tab",
          options: items -> map({|item|item.name}),
          default: items[0].name,
        }

utils = {
  choose(n, k) = Danger.factorial(n) /
    (Danger.factorial(n - k) * Danger.factorial(k))

  binomial(k, n, p) = if k <= n then choose(n, k) * p ^ k *
    (1 - p) ^ (n - k) else 0

  laplace(s, n) = (s + 1) / (n + 2)

  integrate(fun, min, max, epsilon) = {

// import from the old Relative Values UI, I didn't write this code -- berekuk

//Trying having one file here, to see if that makes editing easier. Will later move this around with some script or similar.
ss(t) = SampleSet.fromDist(t)
animalModule = {
  //Sentient Welfare
  average_qaly_per_year = ss(0.7 to 0.9)
  qalys_in_farming_per_year = ss(mx(-(0.2 to 100), 0.01 to 0.5, [0.7, 0.3]))
  lifespan_in_farming = ss(0.3 to 0.6)
  cow_qalys_per_human = ss(0.1 to 0.6)