Light cleanup of ReducerInterface_GenericDistribution
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18d742b63c
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@ -6,6 +6,9 @@ let makeTest = (str, result) => test(str, () => expectEvalToBe(str, result))
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describe("eval", () => {
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Only.describe("expressions", () => {
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makeTest("normal(5,2)", "Ok(Normal(5,2))")
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makeTest("5 to 2", "Error(TODO: Low value must be less than high value.)")
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makeTest("to(2,5)", "Ok(Lognormal(1.1512925464970227,0.278507821238345))")
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makeTest("to(-2,2)", "Ok(Normal(0,1.215913388057542))")
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makeTest("lognormal(5,2)", "Ok(Lognormal(5,2))")
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makeTest("mean(normal(5,2))", "Ok(5)")
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makeTest("mean(lognormal(1,2))", "Ok(20.085536923187668)")
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@ -21,6 +24,5 @@ describe("eval", () => {
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makeTest("3+normal(5,2)", "Ok(Point Set Distribution)")
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makeTest("add(3, 3)", "Ok(6)")
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makeTest("truncateLeft(normal(5,2), 3)", "Ok(Point Set Distribution)")
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makeTest("mean(add(3, normal(5,2)))", "Ok(8.004619792609384)")
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})
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})
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@ -228,7 +228,7 @@ let pointwiseCombinationFloat = (
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): result<t, error> => {
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let m = switch arithmeticOperation {
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| #Add | #Subtract => Error(GenericDist_Types.DistributionVerticalShiftIsInvalid)
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| (#Multiply | #Divide | #Exponentiate | #Log) as arithmeticOperation =>
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| (#Multiply | #Divide | #Exponentiate | #Logarithm) as arithmeticOperation =>
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toPointSetFn(t)->E.R2.fmap(t => {
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//TODO: Move to PointSet codebase
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let fn = (secondary, main) => Operation.Scale.toFn(arithmeticOperation, main, secondary)
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@ -20,7 +20,7 @@ module Operation = {
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| #Subtract
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| #Divide
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| #Exponentiate
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| #Log
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| #Logarithm
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]
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let arithmeticToFn = (arithmetic: arithmeticOperation) =>
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@ -30,7 +30,7 @@ module Operation = {
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| #Subtract => \"-."
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| #Exponentiate => \"**"
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| #Divide => \"/."
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| #Log => (a, b) => log(a) /. log(b)
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| #Logarithm => (a, b) => log(a) /. log(b)
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}
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type toFloat = [
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@ -1,13 +1,14 @@
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module ExpressionValue = ReducerInterface_ExpressionValue
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type expressionValue = ReducerInterface_ExpressionValue.expressionValue
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let env: GenericDist_GenericOperation.env = {
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let runGenericOperation = GenericDist_GenericOperation.run(
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~env={
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sampleCount: 1000,
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xyPointLength: 1000,
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}
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let runGenericOperation = GenericDist_GenericOperation.run(~env)
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},
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)
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module Helpers = {
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let arithmeticMap = r =>
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switch r {
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| "add" => #Add
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@ -15,13 +16,13 @@ let arithmeticMap = r =>
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| "subtract" => #Subtract
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| "dotSubtract" => #Subtract
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| "divide" => #Divide
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| "logarithm" => #Divide
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| "logarithm" => #Logarithm
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| "dotDivide" => #Divide
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| "exponentiate" => #Exponentiate
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| "dotExponentiate" => #Exponentiate
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| "multiply" => #Multiply
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| "dotMultiply" => #Multiply
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| "dotLogarithm" => #Divide
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| "dotLogarithm" => #Logarithm
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| _ => #Multiply
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}
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@ -58,23 +59,9 @@ let twoDiststoDistFn = (direction, arithmetic, dist1, dist2) => {
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dist1,
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)->runGenericOperation
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}
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let genericOutputToReducerValue = (o: GenericDist_GenericOperation.outputType): result<
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expressionValue,
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Reducer_ErrorValue.errorValue,
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> =>
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switch o {
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| Dist(d) => Ok(ReducerInterface_ExpressionValue.EvDistribution(d))
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| Float(d) => Ok(EvNumber(d))
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| String(d) => Ok(EvString(d))
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| GenDistError(NotYetImplemented) => Error(RETodo("Function not yet implemented"))
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| GenDistError(Unreachable) => Error(RETodo("Unreachable"))
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| GenDistError(DistributionVerticalShiftIsInvalid) =>
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Error(RETodo("Distribution Vertical Shift is Invalid"))
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| GenDistError(Other(s)) => Error(RETodo(s))
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}
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module SymbolicConstructor = {
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module SymbolicConstructors = {
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let oneFloat = name =>
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switch name {
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| "exponential" => Ok(SymbolicDist.Exponential.make)
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@ -87,6 +74,7 @@ module SymbolicConstructor = {
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| "uniform" => Ok(SymbolicDist.Uniform.make)
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| "beta" => Ok(SymbolicDist.Beta.make)
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| "lognormal" => Ok(SymbolicDist.Lognormal.make)
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| "to" => Ok(SymbolicDist.From90thPercentile.make)
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| _ => Error("impossible path")
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}
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@ -111,47 +99,65 @@ let dispatchToGenericOutput = (call: ExpressionValue.functionCall): option<
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let (fnName, args) = call
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switch (fnName, args) {
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| ("exponential" as fnName, [EvNumber(f1)]) =>
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SymbolicConstructor.oneFloat(fnName)
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SymbolicConstructors.oneFloat(fnName)
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->E.R.bind(r => r(f1))
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->SymbolicConstructor.symbolicResultToOutput
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| (("normal" | "uniform" | "beta" | "lognormal") as fnName, [EvNumber(f1), EvNumber(f2)]) =>
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SymbolicConstructor.twoFloat(fnName)
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->SymbolicConstructors.symbolicResultToOutput
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| (
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("normal" | "uniform" | "beta" | "lognormal" | "to") as fnName,
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[EvNumber(f1), EvNumber(f2)],
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) =>
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SymbolicConstructors.twoFloat(fnName)
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->E.R.bind(r => r(f1, f2))
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->SymbolicConstructor.symbolicResultToOutput
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->SymbolicConstructors.symbolicResultToOutput
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| ("triangular" as fnName, [EvNumber(f1), EvNumber(f2), EvNumber(f3)]) =>
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SymbolicConstructor.threeFloat(fnName)
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SymbolicConstructors.threeFloat(fnName)
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->E.R.bind(r => r(f1, f2, f3))
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->SymbolicConstructor.symbolicResultToOutput
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| ("sample", [EvDistribution(dist)]) => toFloatFn(#Sample, dist)
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| ("mean", [EvDistribution(dist)]) => toFloatFn(#Mean, dist)
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| ("normalize", [EvDistribution(dist)]) => toDistFn(Normalize, dist)
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| ("toPointSet", [EvDistribution(dist)]) => toDistFn(ToPointSet, dist)
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| ("cdf", [EvDistribution(dist), EvNumber(float)]) => toFloatFn(#Cdf(float), dist)
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| ("pdf", [EvDistribution(dist), EvNumber(float)]) => toFloatFn(#Pdf(float), dist)
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| ("inv", [EvDistribution(dist), EvNumber(float)]) => toFloatFn(#Inv(float), dist)
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->SymbolicConstructors.symbolicResultToOutput
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| ("sample", [EvDistribution(dist)]) => Helpers.toFloatFn(#Sample, dist)
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| ("mean", [EvDistribution(dist)]) => Helpers.toFloatFn(#Mean, dist)
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| ("normalize", [EvDistribution(dist)]) => Helpers.toDistFn(Normalize, dist)
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| ("toPointSet", [EvDistribution(dist)]) => Helpers.toDistFn(ToPointSet, dist)
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| ("cdf", [EvDistribution(dist), EvNumber(float)]) => Helpers.toFloatFn(#Cdf(float), dist)
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| ("pdf", [EvDistribution(dist), EvNumber(float)]) => Helpers.toFloatFn(#Pdf(float), dist)
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| ("inv", [EvDistribution(dist), EvNumber(float)]) => Helpers.toFloatFn(#Inv(float), dist)
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| ("toSampleSet", [EvDistribution(dist), EvNumber(float)]) =>
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toDistFn(ToSampleSet(Belt.Int.fromFloat(float)), dist)
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Helpers.toDistFn(ToSampleSet(Belt.Int.fromFloat(float)), dist)
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| ("truncateLeft", [EvDistribution(dist), EvNumber(float)]) =>
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toDistFn(Truncate(Some(float), None), dist)
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Helpers.toDistFn(Truncate(Some(float), None), dist)
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| ("truncateRight", [EvDistribution(dist), EvNumber(float)]) =>
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toDistFn(Truncate(None, Some(float)), dist)
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Helpers.toDistFn(Truncate(None, Some(float)), dist)
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| ("truncate", [EvDistribution(dist), EvNumber(float1), EvNumber(float2)]) =>
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toDistFn(Truncate(Some(float1), Some(float2)), dist)
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| (("add" | "multiply" | "subtract" | "divide" | "exponentiate") as arithmetic, [a, b] as args) =>
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catchAndConvertTwoArgsToDists(args)->E.O2.fmap(((fst, snd)) =>
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twoDiststoDistFn(Algebraic, arithmetic, fst, snd)
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Helpers.toDistFn(Truncate(Some(float1), Some(float2)), dist)
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| (("add" | "multiply" | "subtract" | "divide" | "exponentiate" | "log") as arithmetic, [a, b] as args) =>
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Helpers.catchAndConvertTwoArgsToDists(args)->E.O2.fmap(((fst, snd)) =>
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Helpers.twoDiststoDistFn(Algebraic, arithmetic, fst, snd)
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)
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| (
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("dotAdd" | "dotMultiply" | "dotSubtract" | "dotDivide" | "dotExponentiate") as arithmetic,
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("dotAdd" | "dotMultiply" | "dotSubtract" | "dotDivide" | "dotExponentiate" | "dotLogarithm") as arithmetic,
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[a, b] as args,
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) =>
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catchAndConvertTwoArgsToDists(args)->E.O2.fmap(((fst, snd)) =>
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twoDiststoDistFn(Pointwise, arithmetic, fst, snd)
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Helpers.catchAndConvertTwoArgsToDists(args)->E.O2.fmap(((fst, snd)) =>
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Helpers.twoDiststoDistFn(Pointwise, arithmetic, fst, snd)
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)
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| _ => None
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}
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}
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let genericOutputToReducerValue = (o: GenericDist_GenericOperation.outputType): result<
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expressionValue,
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Reducer_ErrorValue.errorValue,
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> =>
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switch o {
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| Dist(d) => Ok(ReducerInterface_ExpressionValue.EvDistribution(d))
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| Float(d) => Ok(EvNumber(d))
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| String(d) => Ok(EvString(d))
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| GenDistError(NotYetImplemented) => Error(RETodo("Function not yet implemented"))
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| GenDistError(Unreachable) => Error(RETodo("Unreachable"))
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| GenDistError(DistributionVerticalShiftIsInvalid) =>
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Error(RETodo("Distribution Vertical Shift is Invalid"))
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| GenDistError(Other(s)) => Error(RETodo(s))
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}
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let dispatch = call => {
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dispatchToGenericOutput(call)->E.O2.fmap(genericOutputToReducerValue)
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}
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@ -229,6 +229,6 @@ let all = [
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),
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makeRenderedDistFloat("scaleExp", (dist, float) => verticalScaling(#Exponentiate, dist, float)),
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makeRenderedDistFloat("scaleMultiply", (dist, float) => verticalScaling(#Multiply, dist, float)),
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makeRenderedDistFloat("scaleLog", (dist, float) => verticalScaling(#Log, dist, float)),
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makeRenderedDistFloat("scaleLog", (dist, float) => verticalScaling(#Logarithm, dist, float)),
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Multimodal._function,
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]
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@ -115,7 +115,7 @@ let combineShapesContinuousContinuous = (
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| #Multiply => (m1, m2) => m1 *. m2
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| #Divide => (m1, mInv2) => m1 *. mInv2
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| #Exponentiate => (m1, mInv2) => m1 ** mInv2
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| #Log => (m1, m2) => log(m1) /. log(m2)
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| #Logarithm => (m1, m2) => log(m1) /. log(m2)
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} // note: here, mInv2 = mean(1 / t2) ~= 1 / mean(t2)
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// TODO: I don't know what the variances are for exponentatiation
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@ -233,7 +233,7 @@ let combineShapesContinuousDiscrete = (
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}
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| #Multiply
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| #Exponentiate
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| #Log
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| #Logarithm
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| #Divide =>
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for j in 0 to t2n - 1 {
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// creates a new continuous shape for each one of the discrete points, and collects them in outXYShapes.
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@ -50,9 +50,11 @@ module Exponential = {
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type t = exponential
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let make = (rate: float): result<symbolicDist, string> =>
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rate > 0.0
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? Ok(#Exponential({
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? Ok(
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#Exponential({
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rate: rate,
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}))
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}),
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)
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: Error("Exponential distributions mean must be larger than 0")
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let pdf = (x, t: t) => Jstat.Exponential.pdf(x, t.rate)
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let cdf = (x, t: t) => Jstat.Exponential.cdf(x, t.rate)
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@ -127,8 +129,7 @@ module Lognormal = {
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let mu = Js.Math.log(mean) -. 0.5 *. Js.Math.log(variance /. meanSquared +. 1.0)
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let sigma = Js.Math.pow_float(~base=Js.Math.log(variance /. meanSquared +. 1.0), ~exp=0.5)
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Ok(#Lognormal({mu: mu, sigma: sigma}))
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}
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else {
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} else {
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Error("Lognormal standard deviation must be larger than 0")
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}
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}
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@ -154,9 +155,7 @@ module Lognormal = {
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module Uniform = {
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type t = uniform
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let make = (low, high) =>
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high > low
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? Ok(#Uniform({low: low, high: high}))
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: Error("High must be larger than low")
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high > low ? Ok(#Uniform({low: low, high: high})) : Error("High must be larger than low")
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let pdf = (x, t: t) => Jstat.Uniform.pdf(x, t.low, t.high)
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let cdf = (x, t: t) => Jstat.Uniform.cdf(x, t.low, t.high)
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@ -183,6 +182,15 @@ module Float = {
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let toString = Js.Float.toString
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}
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module From90thPercentile = {
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let make = (low, high) =>
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switch (low, high) {
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| (low, high) if low <= 0.0 && low < high => Ok(Normal.from90PercentCI(low, high))
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| (low, high) if low < high => Ok(Lognormal.from90PercentCI(low, high))
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| (_, _) => Error("Low value must be less than high value.")
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}
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}
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module T = {
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let minCdfValue = 0.0001
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let maxCdfValue = 0.9999
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@ -7,11 +7,11 @@ type algebraicOperation = [
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| #Subtract
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| #Divide
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| #Exponentiate
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| #Log
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| #Logarithm
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]
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@genType
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type pointwiseOperation = [#Add | #Multiply | #Exponentiate]
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type scaleOperation = [#Multiply | #Exponentiate | #Log | #Divide]
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type scaleOperation = [#Multiply | #Exponentiate | #Logarithm | #Divide]
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type distToFloatOperation = [
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| #Pdf(float)
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| #Cdf(float)
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@ -29,7 +29,7 @@ module Algebraic = {
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| #Multiply => \"*."
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| #Exponentiate => \"**"
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| #Divide => \"/."
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| #Log => (a, b) => log(a) /. log(b)
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| #Logarithm => (a, b) => log(a) /. log(b)
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}
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let applyFn = (t, f1, f2) =>
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@ -45,7 +45,7 @@ module Algebraic = {
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| #Multiply => "*"
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| #Exponentiate => "**"
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| #Divide => "/"
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| #Log => "log"
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| #Logarithm => "log"
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}
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let format = (a, b, c) => b ++ (" " ++ (toString(a) ++ (" " ++ c)))
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@ -84,7 +84,7 @@ module Scale = {
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| #Multiply => \"*."
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| #Divide => \"/."
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| #Exponentiate => \"**"
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| #Log => (a, b) => log(a) /. log(b)
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| #Logarithm => (a, b) => log(a) /. log(b)
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}
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let format = (operation: t, value, scaleBy) =>
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@ -92,7 +92,7 @@ module Scale = {
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| #Multiply => j`verticalMultiply($value, $scaleBy) `
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| #Divide => j`verticalDivide($value, $scaleBy) `
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| #Exponentiate => j`verticalExponentiate($value, $scaleBy) `
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| #Log => j`verticalLog($value, $scaleBy) `
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| #Logarithm => j`verticalLog($value, $scaleBy) `
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}
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let toIntegralSumCacheFn = x =>
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@ -100,7 +100,7 @@ module Scale = {
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| #Multiply => (a, b) => Some(a *. b)
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| #Divide => (a, b) => Some(a /. b)
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| #Exponentiate => (_, _) => None
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| #Log => (_, _) => None
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| #Logarithm => (_, _) => None
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}
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let toIntegralCacheFn = x =>
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@ -108,7 +108,7 @@ module Scale = {
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| #Multiply => (_, _) => None // TODO: this could probably just be multiplied out (using Continuous.scaleBy)
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| #Divide => (_, _) => None
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| #Exponentiate => (_, _) => None
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| #Log => (_, _) => None
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| #Logarithm => (_, _) => None
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}
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}
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