logScore on records now interprets almost every which way we're

interested in

Value: [1e-3 to 9e-1]

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

@@ -148,8 +148,8 @@ let rec run = (~env, functionCallInfo: functionCallInfo): outputType => {
       GenericDist.Score.klDivergence(dist, t2, ~toPointSetFn)
       ->E.R2.fmap(r => Float(r))
       ->OutputLocal.fromResult
-    | ToScore(LogScore(prediction, answer)) =>
-      GenericDist.Score.logScoreWithPointResolution(Some(dist), prediction, answer, ~toPointSetFn)
+    | ToScore(LogScore(answer, prior)) =>
+      GenericDist.Score.logScoreWithPointResolution(dist, answer, prior, ~toPointSetFn)
       ->E.R2.fmap(r => Float(r))
       ->OutputLocal.fromResult
     | ToBool(IsNormalized) => dist->GenericDist.isNormalized->Bool
@@ -266,8 +266,8 @@ module Constructors = {
   let normalize = (~env, dist) => C.normalize(dist)->run(~env)->toDistR
   let isNormalized = (~env, dist) => C.isNormalized(dist)->run(~env)->toBoolR
   let klDivergence = (~env, dist1, dist2) => C.klDivergence(dist1, dist2)->run(~env)->toFloatR
-  let logScore = (~env, prior, prediction, answer) =>
-    C.logScoreWithPointResolution(prior, prediction, answer)->run(~env)->toFloatR
+  let logScoreWithPointResolution = (~env, prediction, answer, prior) =>
+    C.logScoreWithPointResolution(prediction, answer, prior)->run(~env)->toFloatR
   let toPointSet = (~env, dist) => C.toPointSet(dist)->run(~env)->toDistR
   let toSampleSet = (~env, dist, n) => C.toSampleSet(dist, n)->run(~env)->toDistR
   let fromSamples = (~env, xs) => C.fromSamples(xs)->run(~env)->toDistR

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

@@ -62,7 +62,12 @@ module Constructors: {
   @genType
   let klDivergence: (~env: env, genericDist, genericDist) => result<float, error>
   @genType
-  let logScore: (~env: env, genericDist, genericDist, float) => result<float, error>
+  let logScoreWithPointResolution: (
+    ~env: env,
+    genericDist,
+    float,
+    option<genericDist>,
+  ) => result<float, error>
   @genType
   let toPointSet: (~env: env, genericDist) => result<genericDist, error>
   @genType

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

@@ -91,7 +91,7 @@ module DistributionOperation = {
     | ToString
     | ToSparkline(int)
 
-  type toScore = KLDivergence(genericDist) | LogScore(genericDist, float)
+  type toScore = KLDivergence(genericDist) | LogScore(float, option<genericDist>)
 
   type fromDist =
     | ToFloat(toFloat)
@@ -120,7 +120,7 @@ module DistributionOperation = {
     | ToFloat(#Sample) => `sample`
     | ToFloat(#IntegralSum) => `integralSum`
     | ToScore(KLDivergence(_)) => `klDivergence`
-    | ToScore(LogScore(_, x)) => `logScore against ${E.Float.toFixed(x)}`
+    | ToScore(LogScore(x, _)) => `logScore against ${E.Float.toFixed(x)}`
     | ToDist(Normalize) => `normalize`
     | ToDist(ToPointSet) => `toPointSet`
     | ToDist(ToSampleSet(r)) => `toSampleSet(${E.I.toString(r)})`

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

@@ -68,18 +68,18 @@ module Score = {
   }
 
   let logScoreWithPointResolution = (
-    prior,
     prediction,
     answer,
+    prior,
     ~toPointSetFn: toPointSetFn,
   ): result<float, error> => {
     switch prior {
     | Some(prior') =>
       E.R.merge(toPointSetFn(prior'), toPointSetFn(prediction))->E.R.bind(((a, b)) =>
         PointSetDist.T.logScoreWithPointResolution(
-          a->Some,
           b,
           answer,
+          a->Some,
         )->E.R2.errMap(x => DistributionTypes.OperationError(x))
       )
     | None =>
@@ -87,9 +87,9 @@ module Score = {
       ->toPointSetFn
       ->E.R.bind(x =>
         PointSetDist.T.logScoreWithPointResolution(
-          None,
           x,
           answer,
+          None,
         )->E.R2.errMap(x => DistributionTypes.OperationError(x))
       )
     }

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

@@ -26,9 +26,9 @@ let toFloatOperation: (
 module Score: {
   let klDivergence: (t, t, ~toPointSetFn: toPointSetFn) => result<float, error>
   let logScoreWithPointResolution: (
-    option<t>,
     t,
     float,
+    option<t>,
     ~toPointSetFn: toPointSetFn,
   ) => result<float, error>
 }

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

@@ -279,7 +279,7 @@ module T = Dist({
     )
     newShape->E.R2.fmap(x => x->make->integralEndY)
   }
-  let logScoreWithPointResolution = (prior: option<t>, prediction: t, answer: float) => {
+  let logScoreWithPointResolution = (prediction: t, answer: float, prior: option<t>) => {
     let priorPdf = prior->E.O2.fmap((shape, x) => XYShape.XtoY.linear(x, shape.xyShape))
     let predictionPdf = x => XYShape.XtoY.linear(x, prediction.xyShape)
     PointSetDist_Scoring.LogScoreWithPointResolution.score(~priorPdf, ~predictionPdf, ~answer)

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

@@ -229,7 +229,7 @@ module T = Dist({
       answer,
     )->E.R2.fmap(integralEndY)
   }
-  let logScoreWithPointResolution = (prior: option<t>, prediction: t, answer: float) => {
+  let logScoreWithPointResolution = (prediction: t, answer: float, prior: option<t>) => {
     Error(Operation.NotYetImplemented)
   }
 })

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

@@ -34,7 +34,7 @@ module type dist = {
   let mean: t => float
   let variance: t => float
   let klDivergence: (t, t) => result<float, Operation.Error.t>
-  let logScoreWithPointResolution: (option<t>, t, float) => result<float, Operation.Error.t>
+  let logScoreWithPointResolution: (t, float, option<t>) => result<float, Operation.Error.t>
 }
 
 module Dist = (T: dist) => {

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

@@ -306,7 +306,7 @@ module T = Dist({
     let klContinuousPart = Continuous.T.klDivergence(prediction.continuous, answer.continuous)
     E.R.merge(klDiscretePart, klContinuousPart)->E.R2.fmap(t => fst(t) +. snd(t))
   }
-  let logScoreWithPointResolution = (prior: option<t>, prediction: t, answer: float) => {
+  let logScoreWithPointResolution = (prediction: t, answer: float, prior: option<t>) => {
     Error(Operation.NotYetImplemented)
   }
 })

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

@@ -203,11 +203,11 @@ module T = Dist({
     | (m1, m2) => Mixed.T.klDivergence(m1->toMixed, m2->toMixed)
     }
 
-  let logScoreWithPointResolution = (prior: option<t>, prediction: t, answer: float) => {
+  let logScoreWithPointResolution = (prediction: t, answer: float, prior: option<t>) => {
     switch (prior, prediction) {
     | (Some(Continuous(t1)), Continuous(t2)) =>
-      Continuous.T.logScoreWithPointResolution(t1->Some, t2, answer)
-    | (None, Continuous(t2)) => Continuous.T.logScoreWithPointResolution(None, t2, answer)
+      Continuous.T.logScoreWithPointResolution(t2, answer, t1->Some)
+    | (None, Continuous(t2)) => Continuous.T.logScoreWithPointResolution(t2, answer, None)
     | _ => Error(Operation.NotYetImplemented)
     }
   }

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

@@ -251,27 +251,34 @@ let rec dispatchToGenericOutput = (call: ExpressionValue.functionCall, _environm
   | ("normalize", [EvDistribution(dist)]) => Helpers.toDistFn(Normalize, dist)
   | ("klDivergence", [EvDistribution(a), EvDistribution(b)]) =>
     Some(runGenericOperation(FromDist(ToScore(KLDivergence(b)), a)))
-  | ("logScore", [EvDistribution(prior), EvDistribution(prediction), EvNumber(answer)])
   | (
-    "logScore",
-    [EvDistribution(prior), EvDistribution(prediction), EvDistribution(Symbolic(#Float(answer)))],
+    "logScoreWithPointResolution",
+    [EvDistribution(prediction), EvNumber(answer), EvDistribution(prior)],
+  )
+  | (
+    "logScoreWithPointResolution",
+    [EvDistribution(prediction), EvDistribution(Symbolic(#Float(answer))), EvDistribution(prior)],
   ) =>
-    runGenericOperation(FromDist(ToScore(LogScore(prediction, answer)), prior))->Some
-  | ("logScore", [EvRecord(r)]) =>
-    recurRecordArgs("logScore", ["prior", "prediction", "answer"], r, _environment)
-  | ("increment", [EvNumber(x)]) => (x +. 1.0)->DistributionOperation.Float->Some
-  | ("increment", [EvRecord(r)]) => recurRecordArgs("increment", ["incrementee"], r, _environment)
-  | ("logScoreAgainstImproperPrior", [EvDistribution(prediction), EvNumber(answer)])
+    runGenericOperation(FromDist(ToScore(LogScore(answer, prior->Some)), prediction))->Some
+  | ("logScoreWithPointResolution", [EvDistribution(prediction), EvNumber(answer)])
   | (
-    "logScoreAgainstImproperPrior",
+    "logScoreWithPointResolution",
     [EvDistribution(prediction), EvDistribution(Symbolic(#Float(answer)))],
   ) =>
-    runGenericOperation(
-      FromDist(
-        ToScore(LogScore(prediction, answer)),
-        Helpers.constructNonNormalizedPointSet(~supportOf=prediction, _ => 1.0),
+    runGenericOperation(FromDist(ToScore(LogScore(answer, None)), prediction))->Some
+  | ("logScore", [EvRecord(r)]) =>
+    [
+      recurRecordArgs(
+        "logScoreWithPointResolution",
+        ["estimate", "answer", "prior"],
+        r,
+        _environment,
       ),
-    )->Some
+      recurRecordArgs("klDivergence", ["estimate", "answer"], r, _environment),
+      recurRecordArgs("logScoreWithPointResolution", ["estimate", "answer"], r, _environment),
+    ]->E.A.O.firstSome
+  | ("increment", [EvNumber(x)]) => (x +. 1.0)->DistributionOperation.Float->Some // this tests recurRecordArgs function
+  | ("increment", [EvRecord(r)]) => recurRecordArgs("increment", ["incrementee"], r, _environment)
   | ("isNormalized", [EvDistribution(dist)]) => Helpers.toBoolFn(IsNormalized, dist)
   | ("toPointSet", [EvDistribution(dist)]) => Helpers.toDistFn(ToPointSet, dist)
   | ("scaleLog", [EvDistribution(dist)]) =>

packages/squiggle-lang/src/rescript/Utility/E.res

@@ -631,6 +631,17 @@ module A = {
         }
       }
     }
+    let rec firstSome = (optionals: array<option<'a>>): option<'a> => {
+      let optionals' = optionals->Belt.List.fromArray
+      switch optionals' {
+      | list{} => None
+      | list{x, ...xs} =>
+        switch x {
+        | Some(_) => x
+        | None => xs->Belt.List.toArray->firstSome
+        }
+      }
+    }
   }
 
   module R = {