merged 592

packages/squiggle-lang/src/rescript/Distributions/DistributionOperation.res

@@ -146,7 +146,7 @@ let rec run = (~env, functionCallInfo: functionCallInfo): outputType => {
       }
     | ToDist(Normalize) => dist->GenericDist.normalize->Dist
     | ToScore(LogScore(answer, prior)) =>
-      GenericDist.Score.logScore(~estimate=GDist(dist), ~answer, ~prior)
+      GenericDist.Score.logScore(~estimate=Score_Dist(dist), ~answer, ~prior)
       ->E.R2.fmap(s => Float(s))
       ->OutputLocal.fromResult
     | ToBool(IsNormalized) => dist->GenericDist.isNormalized->Bool

packages/squiggle-lang/src/rescript/Distributions/DistributionTypes.res

@@ -92,7 +92,7 @@ module DistributionOperation = {
     | ToString
     | ToSparkline(int)
 
-  type genericDistOrScalar = GDist(genericDist) | GScalar(float)
+  type genericDistOrScalar = Score_Dist(genericDist) | Score_Scalar(float)
 
   type toScore = LogScore(genericDistOrScalar, option<genericDistOrScalar>)
 
@@ -165,35 +165,35 @@ module Constructors = {
     let inspect = (dist): t => FromDist(ToDist(Inspect), dist)
     module LogScore = {
       let distEstimateDistAnswer = (estimate, answer): t => FromDist(
-        ToScore(LogScore(GDist(answer), None)),
+        ToScore(LogScore(Score_Dist(answer), None)),
         estimate,
       )
       let distEstimateDistAnswerWithPrior = (estimate, answer, prior): t => FromDist(
-        ToScore(LogScore(GDist(answer), Some(prior))),
+        ToScore(LogScore(Score_Dist(answer), Some(prior))),
         estimate,
       )
       let distEstimateScalarAnswer = (estimate, answer): t => FromDist(
-        ToScore(LogScore(GScalar(answer), None)),
+        ToScore(LogScore(Score_Scalar(answer), None)),
         estimate,
       )
       let distEstimateScalarAnswerWithPrior = (estimate, answer, prior): t => FromDist(
-        ToScore(LogScore(GScalar(answer), Some(prior))),
+        ToScore(LogScore(Score_Scalar(answer), Some(prior))),
         estimate,
       )
       let scalarEstimateDistAnswer = (estimate, answer): t => FromFloat(
-        ToScore(LogScore(GDist(answer), None)),
+        ToScore(LogScore(Score_Dist(answer), None)),
         estimate,
       )
       let scalarEstimateDistAnswerWithPrior = (estimate, answer, prior): t => FromFloat(
-        ToScore(LogScore(GDist(answer), Some(prior))),
+        ToScore(LogScore(Score_Dist(answer), Some(prior))),
         estimate,
       )
       let scalarEstimateScalarAnswer = (estimate, answer): t => FromFloat(
-        ToScore(LogScore(GScalar(answer), None)),
+        ToScore(LogScore(Score_Scalar(answer), None)),
         estimate,
       )
       let scalarEstimateScalarAnswerWithPrior = (estimate, answer, prior): t => FromFloat(
-        ToScore(LogScore(GScalar(answer), Some(prior))),
+        ToScore(LogScore(Score_Scalar(answer), Some(prior))),
         estimate,
       )
     }

packages/squiggle-lang/src/rescript/Distributions/GenericDist.res

@@ -121,31 +121,13 @@ let toPointSet = (
 
 module Score = {
   type genericDistOrScalar = DistributionTypes.DistributionOperation.genericDistOrScalar
-  type psDistOrScalar = PSDist(PointSetTypes.pointSetDist) | PSScalar(float)
+  type pointSet_ScoreDistOrScalar = PSDist(PointSetTypes.pointSetDist) | PSScalar(float)
 
   let argsMake = (
     ~esti: genericDistOrScalar,
     ~answ: genericDistOrScalar,
     ~prior: option<genericDistOrScalar>,
   ): result<PointSetDist_Scoring.scoreArgs, error> => {
-// <<<<<<< HEAD
-//    let toPointSetFn = toPointSet(
-//      ~xyPointLength=MagicNumbers.Environment.defaultXYPointLength,
-//      ~sampleCount=MagicNumbers.Environment.defaultSampleCount,
-//      ~xSelection=#ByWeight,
-//    )
-//    let twoDists = PointSetDist_Scoring.twoGenericDistsToTwoPointSetDists
-//    let prior': option<result<psDistOrScalar, error>> = switch prior {
-//    | None => None
-//    | Some(GDist(d)) => toPointSetFn(d, ())->E.R2.fmap(x => x->PSDist)->Some
-//    | Some(GScalar(s)) => s->PSScalar->Ok->Some
-//    }
-//    switch (esti, answ, prior') {
-//    | (GDist(esti'), GDist(answ'), None) =>
-//      twoDists(~toPointSetFn, esti', answ')->E.R2.fmap(((esti'', answ'')) =>
-//        {estimate: esti'', answer: answ'', prior: None}
-//        ->PointSetDist_Scoring.DistEstimateDistAnswer
-// =======
     let toPointSetFn = t =>
       toPointSet(
         t,
@@ -156,52 +138,53 @@ module Score = {
       )
     let prior': option<result<pointSet_ScoreDistOrScalar, error>> = switch prior {
     | None => None
-    | Some(Score_Dist(d)) => toPointSetFn(d)->E.R.bind(x => x->D->Ok)->Some
+    | Some(Score_Dist(d)) => toPointSetFn(d)->E.R.bind(x => x->PSDist->Ok)->Some
-    | Some(Score_Scalar(s)) => s->S->Ok->Some
+    | Some(Score_Scalar(s)) => s->PSScalar->Ok->Some
     }
-    let twoDists = (esti': t, answ': t): result<
+    let twoDists = (~toPointSetFn, esti': t, answ': t): result<
       (PointSetTypes.pointSetDist, PointSetTypes.pointSetDist),
       error,
     > => E.R.merge(toPointSetFn(esti'), toPointSetFn(answ'))
     switch (esti, answ, prior') {
     | (Score_Dist(esti'), Score_Dist(answ'), None) =>
-      twoDists(esti', answ')->E.R2.fmap(((esti'', answ'')) =>
+      twoDists(~toPointSetFn, esti', answ')->E.R2.fmap(((esti'', answ'')) =>
         {estimate: esti'', answer: answ'', prior: None}->PointSetDist_Scoring.DistEstimateDistAnswer
-// >>>>>>> origin/scoring-cleanup-refactor
       )
-    | (GDist(esti'), GDist(answ'), Some(Ok(PSDist(prior'')))) =>
+    | (Score_Dist(esti'), Score_Dist(answ'), Some(Ok(PSDist(prior'')))) =>
       twoDists(~toPointSetFn, esti', answ')->E.R2.fmap(((esti'', answ'')) =>
         {estimate: esti'', answer: answ'', prior: Some(prior'')}
         ->PointSetDist_Scoring.DistEstimateDistAnswer
       )
-    | (Score_Dist(_), _, Some(Ok(S(_)))) => DistributionTypes.Unreachable->Error
+    | (Score_Dist(_), _, Some(Ok(PSScalar(_)))) => DistributionTypes.Unreachable->Error
     | (Score_Dist(esti'), Score_Scalar(answ'), None) =>
       toPointSetFn(esti')->E.R.bind(esti'' =>
         {estimate: esti'', answer: answ', prior: None}
         ->PointSetDist_Scoring.DistEstimateScalarAnswer
         ->Ok
       )
-    | (Score_Dist(esti'), Score_Scalar(answ'), Some(Ok(D(prior'')))) =>
+    | (Score_Dist(esti'), Score_Scalar(answ'), Some(Ok(PSDist(prior'')))) =>
       toPointSetFn(esti')->E.R.bind(esti'' =>
         {estimate: esti'', answer: answ', prior: Some(prior'')}
-        ->PointSetDist_Scoring.DistEstimateScalarAnswer
+          ->PointSetDist_Scoring.DistEstimateScalarAnswer
+        -> Ok
       )
     | (Score_Scalar(esti'), Score_Dist(answ'), None) =>
       toPointSetFn(answ')->E.R.bind(answ'' =>
         {estimate: esti', answer: answ'', prior: None}
-        ->PointSetDist_Scoring.ScalarEstimateDistAnswer
+          ->PointSetDist_Scoring.ScalarEstimateDistAnswer
+        -> Ok
       )
-    | (Score_Scalar(esti'), Score_Dist(answ'), Some(Ok(S(prior'')))) =>
+    | (Score_Scalar(esti'), Score_Dist(answ'), Some(Ok(PSScalar(prior'')))) =>
       toPointSetFn(answ')->E.R.bind(answ'' =>
         {estimate: esti', answer: answ'', prior: Some(prior'')}
-        ->PointSetDist_Scoring.ScalarEstimateDistAnswer
+        ->PointSetDist_Scoring.ScalarEstimateDistAnswer->Ok
       )
-    | (GScalar(_), _, Some(Ok(PSDist(_)))) => DistributionTypes.Unreachable->Error
+    | (Score_Scalar(_), _, Some(Ok(PSDist(_)))) => DistributionTypes.Unreachable->Error
-    | (GScalar(esti'), GScalar(answ'), None) =>
+    | (Score_Scalar(esti'), Score_Scalar(answ'), None) =>
       {estimate: esti', answer: answ', prior: None}
       ->PointSetDist_Scoring.ScalarEstimateScalarAnswer
       ->Ok
-    | (GScalar(esti'), GScalar(answ'), Some(Ok(PSScalar(prior'')))) =>
+    | (Score_Scalar(esti'), Score_Scalar(answ'), Some(Ok(PSScalar(prior'')))) =>
       {estimate: esti', answer: answ', prior: prior''->Some}
       ->PointSetDist_Scoring.ScalarEstimateScalarAnswer
       ->Ok

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

@@ -132,7 +132,7 @@ module WithScalarAnswer = {
       } else if numerator == 0.0 || priorDensityOfAnswer == 0.0 {
         infinity->Ok
       } else {
-        minusScaledLogOfQuot(~esti=numerator, ~answ=priorDensityOfAnswer)
+        minusScaledLogOfQuotient(~esti=numerator, ~answ=priorDensityOfAnswer)
       }
     }
 
@@ -172,7 +172,7 @@ module TwoScalars = {
     }
 }
 
-let twoGenericDistsToTwoPointSetDists = (~toPointSetFn, estimate, answer): result<(t, t), 'e> =>
+let twoGenericDistsToTwoPointSetDists = (~toPointSetFn, estimate, answer): result<(pointSetDist, pointSetDist), 'e> =>
   E.R.merge(toPointSetFn(estimate, ()), toPointSetFn(answer, ()))
 
 let logScore = (args: scoreArgs, ~combineFn, ~integrateFn, ~toMixedFn): result<

packages/squiggle-lang/src/rescript/ReducerInterface/ReducerInterface_GenericDistribution.res

@@ -214,12 +214,12 @@ let dispatchToGenericOutput = (
   | ("normalize", [EvDistribution(dist)]) => Helpers.toDistFn(Normalize, dist, ~env)
   | ("klDivergence", [EvDistribution(estimate), EvDistribution(answer)]) =>
     Some(
-      DistributionOperation.run(FromDist(ToScore(LogScore(GDist(answer), None)), estimate), ~env),
+      DistributionOperation.run(FromDist(ToScore(LogScore(Score_Dist(answer), None)), estimate), ~env),
     )
   | ("klDivergence", [EvDistribution(estimate), EvDistribution(answer), EvDistribution(prior)]) =>
     Some(
       DistributionOperation.run(
-        FromDist(ToScore(LogScore(GDist(answer), Some(GDist(prior)))), estimate),
+        FromDist(ToScore(LogScore(Score_Dist(answer), Some(Score_Dist(prior)))), estimate),
         ~env,
       ),
     )