feat: Fix remaining scoring errors with Quinn
Value::0.3 to 0.9
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@ -14,7 +14,7 @@ describe("WithScalarAnswer: discrete -> discrete -> float", () => {
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let pointC = mkDelta(1.0)
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let pointD = mkDelta(0.0)
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test("score: agrees with analytical answer when finite", () => {
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test("WithScalarAnswer.score: agrees with analytical answer when finite", () => {
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let prediction' = [(pointA, 0.25), (pointB, 0.25), (pointC, 0.25), (pointD, 0.25)]->mixture->run
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let prediction = switch prediction' {
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| Dist(PointSet(a'')) => a''
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@ -29,7 +29,7 @@ describe("WithScalarAnswer: discrete -> discrete -> float", () => {
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}
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})
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test("score: agrees with analytical answer when finite", () => {
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test("WithScalarAnswer.score: agrees with analytical answer when finite", () => {
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let prediction' = [(pointA, 0.75), (pointB, 0.25)]->mixture->run
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let prediction = switch prediction' {
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| Dist(PointSet(a'')) => a''
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@ -43,7 +43,7 @@ describe("WithScalarAnswer: discrete -> discrete -> float", () => {
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}
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})
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test("scoreWithPrior: ", () => {
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test("WithScalarAnswer.scoreWithPrior: ", () => {
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let prior' = [(pointA, 0.5), (pointB, 0.5)]->mixture->run
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let prediction' = [(pointA, 0.75), (pointB, 0.25)]->mixture->run
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@ -70,7 +70,91 @@ describe("WithScalarAnswer: discrete -> discrete -> float", () => {
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})
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})
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// WithDistAnswer
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describe("TwoScalars: float -> float -> float", () => {
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test("TwoScalars.score: ", () => {
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let scalar1 = 1.0 // 100% of probability mass 1.0
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let scalar2 = 2.0 // 100% of probability mass to 2.0
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let score = PointSetDist_Scoring.TwoScalars.score(~estimate=scalar1, ~answer=scalar2)
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switch score {
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| Ok(x) => x->expect->toEqual(infinity)
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| _ => raise(MixtureFailed)
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}
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})
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test("TwoScalars.score: ", () => {
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let scalar1 = 1.5 // 100% of probability mass 1.0
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let scalar2 = 1.5 // 100% of probability mass to 2.0
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let score = PointSetDist_Scoring.TwoScalars.score(~estimate=scalar1, ~answer=scalar2)
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switch score {
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| Ok(x) => x->expect->toEqual(0.0)
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| _ => raise(MixtureFailed)
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}
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})
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test("TwoScalars.scoreWithPrior: ", () => {
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let scalar1 = 1.5 // 100% of probability mass 1.0
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let scalar2 = 1.5 // 100% of probability mass to 2.0
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let scalar3 = 1.0 // 100% of probability mass to 2.0
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let score = PointSetDist_Scoring.TwoScalars.scoreWithPrior(
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~estimate=scalar1,
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~answer=scalar2,
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~prior=scalar3,
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)
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switch score {
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| Ok(x) => x->expect->toEqual(-.infinity)
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| _ => raise(MixtureFailed)
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}
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})
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test("TwoScalars.scoreWithPrior: ", () => {
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let scalar1 = 1.5 // 100% of probability mass 1.0
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let scalar2 = 1.5 // 100% of probability mass to 2.0
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let scalar3 = 1.5 // 100% of probability mass to 2.0
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let score = PointSetDist_Scoring.TwoScalars.scoreWithPrior(
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~estimate=scalar1,
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~answer=scalar2,
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~prior=scalar3,
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)
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switch score {
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| Ok(x) => x->expect->toEqual(0.0)
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| _ => raise(MixtureFailed)
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}
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})
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test("TwoScalars.scoreWithPrior: ", () => {
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let scalar1 = 1.0 // 100% of probability mass 1.0
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let scalar2 = 1.5 // 100% of probability mass to 2.0
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let scalar3 = 1.0 // 100% of probability mass to 2.0
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let score = PointSetDist_Scoring.TwoScalars.scoreWithPrior(
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~estimate=scalar1,
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~answer=scalar2,
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~prior=scalar3,
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)
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switch score {
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| Ok(x) => x->expect->toEqual("Error: Really dumb forecasters") // unclear what this case should give; could be smth else, or undefined
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| _ => raise(MixtureFailed)
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}
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})
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test("TwoScalars.scoreWithPrior: ", () => {
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let scalar1 = 1.0 // 100% of probability mass 1.0
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let scalar2 = 1.0 // 100% of probability mass to 2.0
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let scalar3 = 1.0 // 100% of probability mass to 2.0
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let score = PointSetDist_Scoring.TwoScalars.scoreWithPrior(
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~estimate=scalar1,
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~answer=scalar2,
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~prior=scalar3,
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)
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switch score {
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| Ok(x) => x->expect->toEqual(0.0)
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| _ => raise(MixtureFailed)
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}
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})
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})
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/*
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describe("WithScalarAnswer: discrete -> discrete -> float", () => {
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})
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@ -129,7 +129,7 @@ module WithScalarAnswer = {
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s1 -. s2
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)
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/*
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let _scoreWithPrior = (
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let _scoreWithPrior = (
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~estimatePdf: float => float,
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~answer: scalar,
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~priorPdf: float => float,
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@ -141,6 +141,7 @@ 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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//
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}
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}
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@ -157,11 +158,30 @@ module WithScalarAnswer = {
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| Mixed(prio) => Mixed.T.xToY(x, prio)->sum
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}
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_scoreWithPrior(~estimatePdf, ~answer, ~priorPdf)
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*/
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*/
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}
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}
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// For mixed discrete answer
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// (prediction, answer) => sum(answer.map(a => a.probability * WithScalarAnswer.score(prediction, a.value)))
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module TwoScalars = {
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// You will almost never want to use this.
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let score = (~estimate: scalar, ~answer: scalar) => {
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if estimate == answer {
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0.0->Ok
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} else {
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infinity->Ok // - log(0)
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}
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}
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let scoreWithPrior = (~estimate: scalar, ~answer: scalar, ~prior: scalar) => {
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E.R.merge(score(~estimate, ~answer), score(~estimate=prior, ~answer))->E.R2.fmap(((s1, s2)) =>
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s1 -. s2
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)
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// unclear what this should give if both are wrong: infinity-infinity. Maybe some warning??
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}
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/*
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let score = (~estimate: scalar, ~answer: scalar) =>
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if answer == 0.0 {
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0.0->Ok
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@ -179,6 +199,7 @@ module TwoScalars = {
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} else {
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minusScaledLogOfQuotient(~esti=estimate /. prior, ~answ=answer)
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}
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*/
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}
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let twoGenericDistsToTwoPointSetDists = (~toPointSetFn, estimate, answer): result<
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