fix: PointSetDist_Scoring.WithScalarAnswer.scoreWithPrior

Done in pair coding with Quinn.
Value::[0.3 to 0.9]

packages/squiggle-lang/__tests__/Distributions/Scoring/WithScalarAnswer_test.res

@@ -0,0 +1,81 @@
+// Bring up a discrete distribution
+open Jest
+open Expect
+open TestHelpers
+open GenericDist_Fixtures
+
+// WithDistAnswer -> in the KL divergence test file.
+
+// WithScalarAnswer
+describe("WithScalarAnswer: discrete -> discrete -> float", () => {
+  let mixture = a => DistributionTypes.DistributionOperation.Mixture(a)
+  let pointA = mkDelta(3.0)
+  let pointB = mkDelta(2.0)
+  let pointC = mkDelta(1.0)
+  let pointD = mkDelta(0.0)
+
+  test("score: agrees with analytical answer when finite", () => {
+    let prediction' = [(pointA, 0.25), (pointB, 0.25), (pointC, 0.25), (pointD, 0.25)]->mixture->run
+    let prediction = switch prediction' {
+    | Dist(PointSet(a'')) => a''
+    | _ => raise(MixtureFailed)
+    }
+
+    let answer = 2.0 // So this is: assigning 100% probability to 2.0
+    let result = PointSetDist_Scoring.WithScalarAnswer.score(~estimate=prediction, ~answer)
+    switch result {
+    | Ok(x) => x->expect->toEqual(-.Js.Math.log(0.25 /. 1.0))
+    | _ => raise(MixtureFailed)
+    }
+  })
+
+  test("score: agrees with analytical answer when finite", () => {
+    let prediction' = [(pointA, 0.75), (pointB, 0.25)]->mixture->run
+    let prediction = switch prediction' {
+    | Dist(PointSet(a'')) => a''
+    | _ => raise(MixtureFailed)
+    }
+    let answer = 3.0 // So this is: assigning 100% probability to 2.0
+    let result = PointSetDist_Scoring.WithScalarAnswer.score(~estimate=prediction, ~answer)
+    switch result {
+    | Ok(x) => x->expect->toEqual(-.Js.Math.log(0.75 /. 1.0))
+    | _ => raise(MixtureFailed)
+    }
+  })
+
+  test("scoreWithPrior: ", () => {
+    let prior' = [(pointA, 0.5), (pointB, 0.5)]->mixture->run
+    let prediction' = [(pointA, 0.75), (pointB, 0.25)]->mixture->run
+
+    let prediction = switch prediction' {
+    | Dist(PointSet(a'')) => a''
+    | _ => raise(MixtureFailed)
+    }
+
+    let prior = switch prior' {
+    | Dist(PointSet(a'')) => a''
+    | _ => raise(MixtureFailed)
+    }
+
+    let answer = 3.0 // So this is: assigning 100% probability to 2.0
+    let result = PointSetDist_Scoring.WithScalarAnswer.scoreWithPrior(
+      ~estimate=prediction,
+      ~answer,
+      ~prior,
+    )
+    switch result {
+    | Ok(x) => x->expect->toEqual(-.Js.Math.log(0.75 /. 1.0) -. -.Js.Math.log(0.5 /. 1.0))
+    | _ => raise(MixtureFailed)
+    }
+  })
+})
+
+// WithDistAnswer
+/*
+describe("WithScalarAnswer: discrete -> discrete -> float", () => {
+})
+
+// TwoScalars
+describe("WithScalarAnswer: discrete -> discrete -> float", () => {
+})
+*/

packages/squiggle-lang/src/rescript/Distributions/PointSetDist/PointSetDist_Scoring.res

@@ -115,11 +115,20 @@ module WithScalarAnswer = {
       }
     _score(~estimatePdf, ~answer)
   }
+  /*
+  let score1 = (~estimate: pointSetDist, ~answer: scalar): result<score, Operation.Error.t> => {
+    let probabilityAssignedToAnswer = Ok(1.0)
+  }
+ */
 
   let scoreWithPrior = (~estimate: pointSetDist, ~answer: scalar, ~prior: pointSetDist): result<
     score,
     Operation.Error.t,
   > => {
+    E.R.merge(score(~estimate, ~answer), score(~estimate=prior, ~answer))->E.R2.fmap(((s1, s2)) =>
+      s1 -. s2
+    )
+    /*
     let _scoreWithPrior = (
       ~estimatePdf: float => float,
       ~answer: scalar,
@@ -132,7 +141,6 @@ module WithScalarAnswer = {
       } else if numerator == 0.0 || priorDensityOfAnswer == 0.0 {
         infinity->Ok
       } else {
-        minusScaledLogOfQuotient(~esti=numerator, ~answ=priorDensityOfAnswer)
       }
     }
 
@@ -149,6 +157,7 @@ module WithScalarAnswer = {
       | Mixed(prio) => Mixed.T.xToY(x, prio)->sum
       }
     _scoreWithPrior(~estimatePdf, ~answer, ~priorPdf)
+ */
   }
 }