/*
This is the most basic file in our invariants family of tests. 

Validate that the addition of means equals the mean of the addition, similar for subtraction and multiplication. 

Details in https://deploy-preview-251--squiggle-documentation.netlify.app/docs/internal/invariants/

Note: epsilon of 1e3 means the invariants are, in general, not being satisfied. 
*/

open Jest
open Expect
open TestHelpers

module Internals = {
  let epsilon = 1e3

  let mean = GenericDist_Types.Constructors.UsingDists.mean

  let expectImpossiblePath: string => assertion = algebraicOp =>
    `${algebraicOp} has`->expect->toEqual("failed")

  let distributions = list{
    normalMake(0.0, 1e0),
    betaMake(2e0, 4e0),
    exponentialMake(1.234e0),
    uniformMake(7e0, 1e1),
    // cauchyMake(1e0, 1e0),
    lognormalMake(1e0, 1e0),
    triangularMake(1e0, 1e1, 5e1),
    Ok(floatMake(1e1)),
  }
  let pairsOfDifferentDistributions = E.L.combinations2(distributions)

  let runMean: DistributionTypes.genericDist => float = dist => {
    dist->mean->run->toFloat->E.O2.toExn("Shouldn't see this because we trust testcase input")
  }

  let testOperationMean = (
    distOp: (
      DistributionTypes.genericDist,
      DistributionTypes.genericDist,
    ) => result<DistributionTypes.genericDist, DistributionTypes.error>,
    description: string,
    floatOp: (float, float) => float,
    dist1': SymbolicDistTypes.symbolicDist,
    dist2': SymbolicDistTypes.symbolicDist,
    ~epsilon: float,
  ) => {
    let dist1 = dist1'->DistributionTypes.Symbolic // ->DistributionTypes.Other
    let dist2 = dist2'->DistributionTypes.Symbolic // ->DistributionTypes.Other
    let received =
      distOp(dist1, dist2)->E.R2.fmap(mean)->E.R2.fmap(run)->E.R2.fmap(toFloat)->E.R.toExn
    let expected = floatOp(runMean(dist1), runMean(dist2))
    switch received {
    | None => expectImpossiblePath(description)
    | Some(x) => expectErrorToBeBounded(x, expected, ~epsilon)
    }
  }
}

let {
  algebraicAdd,
  algebraicMultiply,
  algebraicDivide,
  algebraicSubtract,
  algebraicLogarithm,
  algebraicPower,
} = module(DistributionOperation.Constructors)

let algebraicAdd = algebraicAdd(~env)
let algebraicMultiply = algebraicMultiply(~env)
let algebraicDivide = algebraicDivide(~env)
let algebraicSubtract = algebraicSubtract(~env)
let algebraicLogarithm = algebraicLogarithm(~env)
let algebraicPower = algebraicPower(~env)

let {testOperationMean, distributions, pairsOfDifferentDistributions, epsilon} = module(Internals)

describe("Means invariant", () => {
  describe("for addition", () => {
    let testAdditionMean = testOperationMean(algebraicAdd, "algebraicAdd", \"+.", ~epsilon)

    testAll("of two of the same distribution", distributions, dist => {
      E.R.liftM2(testAdditionMean, dist, dist)->E.R.toExn
    })

    testAll("of two different distributions", pairsOfDifferentDistributions, dists => {
      let (dist1, dist2) = dists
      E.R.liftM2(testAdditionMean, dist1, dist2)->E.R.toExn
    })

    testAll("of two difference distributions", pairsOfDifferentDistributions, dists => {
      let (dist1, dist2) = dists
      E.R.liftM2(testAdditionMean, dist2, dist1)->E.R.toExn
    })
  })

  describe("for subtraction", () => {
    let testSubtractionMean = testOperationMean(
      algebraicSubtract,
      "algebraicSubtract",
      \"-.",
      ~epsilon,
    )

    testAll("of two of the same distribution", distributions, dist => {
      E.R.liftM2(testSubtractionMean, dist, dist)->E.R.toExn
    })

    testAll("of two different distributions", pairsOfDifferentDistributions, dists => {
      let (dist1, dist2) = dists
      E.R.liftM2(testSubtractionMean, dist1, dist2)->E.R.toExn
    })

    testAll("of two different distributions", pairsOfDifferentDistributions, dists => {
      let (dist1, dist2) = dists
      E.R.liftM2(testSubtractionMean, dist2, dist1)->E.R.toExn
    })
  })

  describe("for multiplication", () => {
    let testMultiplicationMean = testOperationMean(
      algebraicMultiply,
      "algebraicMultiply",
      \"*.",
      ~epsilon,
    )

    testAll("of two of the same distribution", distributions, dist => {
      E.R.liftM2(testMultiplicationMean, dist, dist)->E.R.toExn
    })

    testAll("of two different distributions", pairsOfDifferentDistributions, dists => {
      let (dist1, dist2) = dists
      E.R.liftM2(testMultiplicationMean, dist1, dist2)->E.R.toExn
    })

    testAll("of two different distributions", pairsOfDifferentDistributions, dists => {
      let (dist1, dist2) = dists
      E.R.liftM2(testMultiplicationMean, dist2, dist1)->E.R.toExn
    })
  })
})