squiggle/packages/squiggle-lang/__tests__/Distributions/Scale_test.res

open Jest
open Expect
open TestHelpers

describe("Scale logarithm", () => {
  //   test("mean of the base e scalar logarithm of an exponential(10)", () => {
  //    let rate = 10.0
  //    let scalelog = DistributionOperation.Constructors.scaleLogarithm(~env, mkExponential(rate), MagicNumbers.Math.e)
  //
  //    let meanResult = E.R2.bind(DistributionOperation.Constructors.mean(~env), scalelog)
  //    let meanAnalytical = Js.Math.log(rate /. MagicNumbers.Math.e)
  //    switch meanResult {
  //      | Ok(meanValue) => meanValue -> expect -> toBeCloseTo(meanAnalytical)
  //      | Error(err) => err -> expect -> toBe(DistributionTypes.OperationError(DivisionByZeroError))
  //    }
  //  })
  let low = 10.0
  let high = 100.0
  let scalelog = DistributionOperation.Constructors.scaleLogarithm(~env, mkUniform(low, high), 2.0)

  test("mean of the base 2 scalar logarithm of a uniform(10, 100)", () => {
    //For uniform pdf `_ => 1 / (b - a)`, the expected value of log of uniform is `integral from a to b of x * log(1 / (b -a)) dx`
    let meanResult = E.R2.bind(DistributionOperation.Constructors.mean(~env), scalelog)
    let meanAnalytical = -.Js.Math.log2(high -. low) /. 2.0 *. (high ** 2.0 -. low ** 2.0) // -. Js.Math.log2(high -. low)
    switch meanResult {
    | Ok(meanValue) => meanValue->expect->toBeCloseTo(meanAnalytical)
    | Error(err) => err->expect->toEqual(DistributionTypes.OperationError(NegativeInfinityError))
    }
  })
})