some of the comments
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@ -146,7 +146,7 @@ let rec run = (~env, functionCallInfo: functionCallInfo): outputType => {
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}
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| ToDist(Normalize) => dist->GenericDist.normalize->Dist
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| ToScore(LogScore(answer, prior)) =>
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GenericDist.Score.logScore(~estimate=Score_Dist(dist), ~answer, ~prior)
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GenericDist.Score.logScore(~estimate=GDist(dist), ~answer, ~prior)
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->E.R2.fmap(s => Float(s))
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->OutputLocal.fromResult
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| ToBool(IsNormalized) => dist->GenericDist.isNormalized->Bool
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@ -68,7 +68,7 @@ module Constructors: {
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~env: env,
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genericDist,
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genericDist,
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DistributionTypes.DistributionOperation.scoreDistOrScalar,
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DistributionTypes.DistributionOperation.genericDistOrScalar,
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) => result<float, error>
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@genType
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let distEstimateScalarAnswer: (~env: env, genericDist, float) => result<float, error>
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@ -77,7 +77,7 @@ module Constructors: {
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~env: env,
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genericDist,
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float,
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DistributionTypes.DistributionOperation.scoreDistOrScalar,
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DistributionTypes.DistributionOperation.genericDistOrScalar,
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) => result<float, error>
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@genType
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let scalarEstimateDistAnswer: (~env: env, float, genericDist) => result<float, error>
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@ -86,7 +86,7 @@ module Constructors: {
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~env: env,
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float,
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genericDist,
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DistributionTypes.DistributionOperation.scoreDistOrScalar,
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DistributionTypes.DistributionOperation.genericDistOrScalar,
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) => result<float, error>
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@genType
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let scalarEstimateScalarAnswer: (~env: env, float, float) => result<float, error>
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@ -95,7 +95,7 @@ module Constructors: {
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~env: env,
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float,
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float,
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DistributionTypes.DistributionOperation.scoreDistOrScalar,
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DistributionTypes.DistributionOperation.genericDistOrScalar,
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) => result<float, error>
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}
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@genType
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@ -92,9 +92,9 @@ module DistributionOperation = {
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| ToString
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| ToSparkline(int)
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type scoreDistOrScalar = Score_Dist(genericDist) | Score_Scalar(float)
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type genericDistOrScalar = GDist(genericDist) | GScalar(float)
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type toScore = LogScore(scoreDistOrScalar, option<scoreDistOrScalar>)
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type toScore = LogScore(genericDistOrScalar, option<genericDistOrScalar>)
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type fromDist =
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| ToFloat(toFloat)
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@ -165,35 +165,35 @@ module Constructors = {
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let inspect = (dist): t => FromDist(ToDist(Inspect), dist)
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module LogScore = {
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let distEstimateDistAnswer = (estimate, answer): t => FromDist(
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ToScore(LogScore(Score_Dist(answer), None)),
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ToScore(LogScore(GDist(answer), None)),
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estimate,
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)
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let distEstimateDistAnswerWithPrior = (estimate, answer, prior): t => FromDist(
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ToScore(LogScore(Score_Dist(answer), Some(prior))),
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ToScore(LogScore(GDist(answer), Some(prior))),
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estimate,
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)
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let distEstimateScalarAnswer = (estimate, answer): t => FromDist(
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ToScore(LogScore(Score_Scalar(answer), None)),
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ToScore(LogScore(GScalar(answer), None)),
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estimate,
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)
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let distEstimateScalarAnswerWithPrior = (estimate, answer, prior): t => FromDist(
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ToScore(LogScore(Score_Scalar(answer), Some(prior))),
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ToScore(LogScore(GScalar(answer), Some(prior))),
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estimate,
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)
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let scalarEstimateDistAnswer = (estimate, answer): t => FromFloat(
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ToScore(LogScore(Score_Dist(answer), None)),
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ToScore(LogScore(GDist(answer), None)),
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estimate,
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)
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let scalarEstimateDistAnswerWithPrior = (estimate, answer, prior): t => FromFloat(
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ToScore(LogScore(Score_Dist(answer), Some(prior))),
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ToScore(LogScore(GDist(answer), Some(prior))),
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estimate,
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)
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let scalarEstimateScalarAnswer = (estimate, answer): t => FromFloat(
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ToScore(LogScore(Score_Scalar(answer), None)),
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ToScore(LogScore(GScalar(answer), None)),
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estimate,
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)
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let scalarEstimateScalarAnswerWithPrior = (estimate, answer, prior): t => FromFloat(
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ToScore(LogScore(Score_Scalar(answer), Some(prior))),
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ToScore(LogScore(GScalar(answer), Some(prior))),
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estimate,
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)
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}
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@ -120,72 +120,64 @@ let toPointSet = (
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}
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module Score = {
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type scoreDistOrScalar = DistributionTypes.DistributionOperation.scoreDistOrScalar
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type genericDistOrScalar = DistributionTypes.DistributionOperation.genericDistOrScalar
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type psDistOrScalar = PSDist(PointSetTypes.pointSetDist) | PSScalar(float)
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type pointSet_ScoreDistOrScalar = D(PointSetTypes.pointSetDist) | S(float)
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let argsMake = (
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~esti: scoreDistOrScalar,
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~answ: scoreDistOrScalar,
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~prior: option<scoreDistOrScalar>,
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~esti: genericDistOrScalar,
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~answ: genericDistOrScalar,
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~prior: option<genericDistOrScalar>,
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): result<PointSetDist_Scoring.scoreArgs, error> => {
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let toPointSetFn = toPointSet(
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~xyPointLength=MagicNumbers.Environment.defaultXYPointLength,
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~sampleCount=MagicNumbers.Environment.defaultSampleCount,
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~xSelection=#ByWeight,
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)
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let prior': option<result<pointSet_ScoreDistOrScalar, error>> = switch prior {
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let twoDists = PointSetDist_Scoring.twoGenericDistsToTwoPointSetDists
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let prior': option<result<psDistOrScalar, error>> = switch prior {
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| None => None
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| Some(Score_Dist(d)) => toPointSetFn(d, ())->E.R.bind(x => x->D->Ok)->Some
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| Some(Score_Scalar(s)) => s->S->Ok->Some
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| Some(GDist(d)) => toPointSetFn(d, ())->E.R2.fmap(x => x->PSDist)->Some
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| Some(GScalar(s)) => s->PSScalar->Ok->Some
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}
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let twoDists = (esti': t, answ': t): result<
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(PointSetTypes.pointSetDist, PointSetTypes.pointSetDist),
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error,
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> => E.R.merge(toPointSetFn(esti', ()), toPointSetFn(answ', ()))
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switch (esti, answ, prior') {
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| (Score_Dist(esti'), Score_Dist(answ'), None) =>
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twoDists(esti', answ')->E.R.bind(((esti'', answ'')) =>
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| (GDist(esti'), GDist(answ'), None) =>
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twoDists(~toPointSetFn, esti', answ')->E.R2.fmap(((esti'', answ'')) =>
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{estimate: esti'', answer: answ'', prior: None}
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->PointSetDist_Scoring.DistEstimateDistAnswer
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->Ok
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)
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| (Score_Dist(esti'), Score_Dist(answ'), Some(Ok(D(prior'')))) =>
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twoDists(esti', answ')->E.R.bind(((esti'', answ'')) =>
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| (GDist(esti'), GDist(answ'), Some(Ok(PSDist(prior'')))) =>
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twoDists(~toPointSetFn, esti', answ')->E.R2.fmap(((esti'', answ'')) =>
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{estimate: esti'', answer: answ'', prior: Some(prior'')}
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->PointSetDist_Scoring.DistEstimateDistAnswer
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->Ok
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)
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| (Score_Dist(_), _, Some(Ok(S(_)))) => DistributionTypes.Unreachable->Error
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| (Score_Dist(esti'), Score_Scalar(answ'), None) =>
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| (GDist(_), _, Some(Ok(PSScalar(_)))) => DistributionTypes.Unreachable->Error
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| (GDist(esti'), GScalar(answ'), None) =>
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toPointSetFn(esti', ())->E.R.bind(esti'' =>
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{estimate: esti'', answer: answ', prior: None}
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->PointSetDist_Scoring.DistEstimateScalarAnswer
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->Ok
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)
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| (Score_Dist(esti'), Score_Scalar(answ'), Some(Ok(D(prior'')))) =>
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toPointSetFn(esti', ())->E.R.bind(esti'' =>
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| (GDist(esti'), GScalar(answ'), Some(Ok(PSDist(prior'')))) =>
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toPointSetFn(esti', ())->E.R2.fmap(esti'' =>
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{estimate: esti'', answer: answ', prior: Some(prior'')}
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->PointSetDist_Scoring.DistEstimateScalarAnswer
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->Ok
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)
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| (Score_Scalar(esti'), Score_Dist(answ'), None) =>
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toPointSetFn(answ', ())->E.R.bind(answ'' =>
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| (GScalar(esti'), GDist(answ'), None) =>
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toPointSetFn(answ', ())->E.R2.fmap(answ'' =>
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{estimate: esti', answer: answ'', prior: None}
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->PointSetDist_Scoring.ScalarEstimateDistAnswer
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->Ok
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)
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| (Score_Scalar(esti'), Score_Dist(answ'), Some(Ok(S(prior'')))) =>
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toPointSetFn(answ', ())->E.R.bind(answ'' =>
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| (GScalar(esti'), GDist(answ'), Some(Ok(PSScalar(prior'')))) =>
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toPointSetFn(answ', ())->E.R2.fmap(answ'' =>
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{estimate: esti', answer: answ'', prior: Some(prior'')}
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->PointSetDist_Scoring.ScalarEstimateDistAnswer
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->Ok
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)
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| (Score_Scalar(_), _, Some(Ok(D(_)))) => DistributionTypes.Unreachable->Error
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| (Score_Scalar(esti'), Score_Scalar(answ'), None) =>
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| (GScalar(_), _, Some(Ok(PSDist(_)))) => DistributionTypes.Unreachable->Error
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| (GScalar(esti'), GScalar(answ'), None) =>
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{estimate: esti', answer: answ', prior: None}
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->PointSetDist_Scoring.ScalarEstimateScalarAnswer
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->Ok
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| (Score_Scalar(esti'), Score_Scalar(answ'), Some(Ok(S(prior'')))) =>
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| (GScalar(esti'), GScalar(answ'), Some(Ok(PSScalar(prior'')))) =>
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{estimate: esti', answer: answ', prior: prior''->Some}
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->PointSetDist_Scoring.ScalarEstimateScalarAnswer
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->Ok
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@ -194,9 +186,9 @@ module Score = {
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}
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let logScore = (
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~estimate: scoreDistOrScalar,
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~answer: scoreDistOrScalar,
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~prior: option<scoreDistOrScalar>,
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~estimate: genericDistOrScalar,
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~answer: genericDistOrScalar,
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~prior: option<genericDistOrScalar>,
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): result<float, error> =>
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argsMake(~esti=estimate, ~answ=answer, ~prior)->E.R.bind(x =>
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x->PointSetDist.logScore->E.R2.errMap(y => DistributionTypes.OperationError(y))
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@ -26,9 +26,9 @@ let toFloatOperation: (
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module Score: {
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let logScore: (
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~estimate: DistributionTypes.DistributionOperation.scoreDistOrScalar,
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~answer: DistributionTypes.DistributionOperation.scoreDistOrScalar,
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~prior: option<DistributionTypes.DistributionOperation.scoreDistOrScalar>,
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~estimate: DistributionTypes.DistributionOperation.genericDistOrScalar,
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~answer: DistributionTypes.DistributionOperation.genericDistOrScalar,
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~prior: option<DistributionTypes.DistributionOperation.genericDistOrScalar>,
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) => result<float, error>
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}
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@ -9,7 +9,7 @@ type scoreArgs =
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| ScalarEstimateScalarAnswer(abstractScoreArgs<scalar, scalar>)
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let logFn = Js.Math.log // base e
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let minusScaledLogOfQuot = (~esti, ~answ): result<float, Operation.Error.t> => {
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let minusScaledLogOfQuotient = (~esti, ~answ): result<float, Operation.Error.t> => {
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let quot = esti /. answ
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quot < 0.0 ? Error(Operation.ComplexNumberError) : Ok(-.answ *. logFn(quot))
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}
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@ -26,7 +26,7 @@ module WithDistAnswer = {
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} else if estimateElement == 0.0 {
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Ok(infinity)
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} else {
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minusScaledLogOfQuot(~esti=estimateElement, ~answ=answerElement)
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minusScaledLogOfQuotient(~esti=estimateElement, ~answ=answerElement)
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}
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let rec sum = (~estimate: t, ~answer: t, ~combineFn, ~integrateFn, ~toMixedFn): result<
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@ -109,7 +109,7 @@ module WithScalarAnswer = {
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} else if numerator == 0.0 || priorDensityOfAnswer == 0.0 {
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infinity->Ok
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} else {
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minusScaledLogOfQuot(~esti=numerator, ~answ=priorDensityOfAnswer)
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minusScaledLogOfQuotient(~esti=numerator, ~answ=priorDensityOfAnswer)
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}
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}
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@ -151,7 +151,7 @@ module TwoScalars = {
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} else if estimate == 0.0 {
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infinity->Ok
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} else {
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minusScaledLogOfQuot(~esti=estimate, ~answ=answer)
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minusScaledLogOfQuotient(~esti=estimate, ~answ=answer)
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}
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let scoreWithPrior = (~estimate: float, ~answer: float, ~prior: float) =>
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@ -160,10 +160,13 @@ module TwoScalars = {
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} else if estimate == 0.0 || prior == 0.0 {
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infinity->Ok
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} else {
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minusScaledLogOfQuot(~esti=estimate /. prior, ~answ=answer)
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minusScaledLogOfQuotient(~esti=estimate /. prior, ~answ=answer)
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}
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}
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let twoGenericDistsToTwoPointSetDists = (~toPointSetFn, estimate, answer): result<(t, t), 'e> =>
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E.R.merge(toPointSetFn(estimate, ()), toPointSetFn(answer, ()))
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let logScore = (args: scoreArgs, ~combineFn, ~integrateFn, ~toMixedFn): result<
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float,
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Operation.Error.t,
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@ -214,15 +214,12 @@ let dispatchToGenericOutput = (
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| ("normalize", [EvDistribution(dist)]) => Helpers.toDistFn(Normalize, dist, ~env)
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| ("klDivergence", [EvDistribution(estimate), EvDistribution(answer)]) =>
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Some(
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DistributionOperation.run(
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FromDist(ToScore(LogScore(Score_Dist(answer), None)), estimate),
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~env,
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),
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DistributionOperation.run(FromDist(ToScore(LogScore(GDist(answer), None)), estimate), ~env),
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)
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| ("klDivergence", [EvDistribution(estimate), EvDistribution(answer), EvDistribution(prior)]) =>
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Some(
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DistributionOperation.run(
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FromDist(ToScore(LogScore(Score_Dist(answer), Some(Score_Dist(prior)))), estimate),
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FromDist(ToScore(LogScore(GDist(answer), Some(GDist(prior)))), estimate),
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~env,
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),
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)
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