Merge pull request #147 from QURIresearch/issue-100

Combining GenericDistribution library with Reducer library
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Ozzie Gooen 2022-04-04 11:18:18 -04:00 committed by GitHub
commit cbd4ad3a79
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15 changed files with 373 additions and 38 deletions

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@ -0,0 +1,125 @@
open Jest
let testSkip: (bool, string, unit => assertion) => unit = (skip: bool) =>
if skip {
Skip.test
} else {
test
}
let testEval = (~skip=false, str, result) =>
testSkip(skip)(str, () => Reducer_TestHelpers.expectEvalToBe(str, result))
let testParse = (~skip=false, str, result) =>
testSkip(skip)(str, () => Reducer_TestHelpers.expectParseToBe(str, result))
describe("eval on distribution functions", () => {
describe("normal distribution", () => {
testEval("normal(5,2)", "Ok(Normal(5,2))")
})
describe("lognormal distribution", () => {
testEval("lognormal(5,2)", "Ok(Lognormal(5,2))")
})
describe("unaryMinus", () => {
testEval("mean(-normal(5,2))", "Ok(-5.002887370380851)")
})
describe("to", () => {
testEval("5 to 2", "Error(TODO: Low value must be less than high value.)")
testEval("to(2,5)", "Ok(Lognormal(1.1512925464970227,0.278507821238345))")
testEval("to(-2,2)", "Ok(Normal(0,1.215913388057542))")
})
describe("mean", () => {
testEval("mean(normal(5,2))", "Ok(5)")
testEval("mean(lognormal(1,2))", "Ok(20.085536923187668)")
})
describe("normalize", () => {
testEval("normalize(normal(5,2))", "Ok(Normal(5,2))")
})
describe("toPointSet", () => {
testEval("toPointSet(normal(5,2))", "Ok(Point Set Distribution)")
})
describe("toSampleSet", () => {
testEval("toSampleSet(normal(5,2), 100)", "Ok(Sample Set Distribution)")
})
describe("add", () => {
testEval("add(normal(5,2), normal(10,2))", "Ok(Normal(15,2.8284271247461903))")
testEval("add(normal(5,2), lognormal(10,2))", "Ok(Sample Set Distribution)")
testEval("add(normal(5,2), 3)", "Ok(Point Set Distribution)")
testEval("add(3, normal(5,2))", "Ok(Point Set Distribution)")
testEval("3+normal(5,2)", "Ok(Point Set Distribution)")
testEval("normal(5,2)+3", "Ok(Point Set Distribution)")
})
describe("truncate", () => {
testEval("truncateLeft(normal(5,2), 3)", "Ok(Point Set Distribution)")
testEval("truncateRight(normal(5,2), 3)", "Ok(Point Set Distribution)")
testEval("truncate(normal(5,2), 3, 8)", "Ok(Point Set Distribution)")
})
describe("exp", () => {
testEval("exp(normal(5,2))", "Ok(Point Set Distribution)")
})
describe("pow", () => {
testEval("pow(3, uniform(5,8))", "Ok(Point Set Distribution)")
testEval("pow(uniform(5,8), 3)", "Ok(Point Set Distribution)")
testEval("pow(uniform(5,8), uniform(9, 10))", "Ok(Sample Set Distribution)")
})
describe("log", () => {
testEval("log(2, uniform(5,8))", "Ok(Point Set Distribution)")
testEval("log(normal(5,2), 3)", "Ok(Point Set Distribution)")
testEval("log(normal(5,2), normal(10,1))", "Ok(Sample Set Distribution)")
testEval("log(uniform(5,8))", "Ok(Point Set Distribution)")
testEval("log10(uniform(5,8))", "Ok(Point Set Distribution)")
})
describe("dotLog", () => {
testEval("dotLog(normal(5,2), 3)", "Ok(Point Set Distribution)")
testEval("dotLog(normal(5,2), 3)", "Ok(Point Set Distribution)")
testEval("dotLog(normal(5,2), normal(10,1))", "Ok(Point Set Distribution)")
})
describe("dotAdd", () => {
testEval("dotAdd(normal(5,2), lognormal(10,2))", "Ok(Point Set Distribution)")
testEval("dotAdd(normal(5,2), 3)", "Ok(Point Set Distribution)")
})
describe("equality", () => {
testEval(~skip=true, "normal(5,2) == normal(5,2)", "Ok(true)")
})
describe("mixture", () => {
testEval(
~skip=true,
"mx(normal(5,2), normal(10,1), normal(15, 1))",
"Ok(Point Set Distribution)",
)
testEval(
~skip=true,
"mixture(normal(5,2), normal(10,1), [.2,, .4])",
"Ok(Point Set Distribution)",
)
})
})
describe("parse on distribution functions", () => {
describe("power", () => {
testParse("normal(5,2) ^ normal(5,1)", "Ok((:pow (:normal 5 2) (:normal 5 1)))")
testParse("3 ^ normal(5,1)", "Ok((:pow 3 (:normal 5 1)))")
testParse("normal(5,2) ^ 3", "Ok((:pow (:normal 5 2) 3))")
})
describe("pointwise arithmetic expressions", () => {
testParse(~skip=true, "normal(5,2) .+ normal(5,1)", "Ok((:dotAdd (:normal 5 2) (:normal 5 1)))")
testParse(~skip=true, "normal(5,2) .- normal(5,1)", "Ok((:dotSubtract (:normal 5 2) (:normal 5 1)))")
testParse("normal(5,2) .* normal(5,1)", "Ok((:dotMultiply (:normal 5 2) (:normal 5 1)))")
testParse("normal(5,2) ./ normal(5,1)", "Ok((:dotDivide (:normal 5 2) (:normal 5 1)))")
testParse("normal(5,2) .^ normal(5,1)", "Ok((:dotPow (:normal 5 2) (:normal 5 1)))")
})
describe("equality", () => {
testParse("5 == normal(5,2)", "Ok((:equal 5 (:normal 5 2)))")
})
describe("pointwise adding two normals", () => {
testParse(~skip=true, "normal(5,2) .+ normal(5,1)", "Ok((:dotAdd (:normal 5 2) (:normal 5 1)))")
})
describe("exponential of one distribution", () => {
testParse(~skip=true, "exp(normal(5,2)", "Ok((:pow (:normal 5 2) 3))")
})
})

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@ -41,7 +41,7 @@
},
"refmt": 3,
"warnings": {
"number": "+A-42-48-9-30-4-102"
"number": "+A-42-48-9-30-4-102-20-27-41"
},
"ppx-flags": []
}

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@ -228,7 +228,7 @@ let pointwiseCombinationFloat = (
): result<t, error> => {
let m = switch arithmeticOperation {
| #Add | #Subtract => Error(GenericDist_Types.DistributionVerticalShiftIsInvalid)
| (#Multiply | #Divide | #Exponentiate | #Log) as arithmeticOperation =>
| (#Multiply | #Divide | #Exponentiate | #Logarithm) as arithmeticOperation =>
toPointSetFn(t)->E.R2.fmap(t => {
//TODO: Move to PointSet codebase
let fn = (secondary, main) => Operation.Scale.toFn(arithmeticOperation, main, secondary)

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@ -48,12 +48,24 @@ module OutputLocal = {
| _ => None
}
let toFloatR = (t: t): result<float, error> =>
switch t {
| Float(r) => Ok(r)
| e => Error(toErrorOrUnreachable(e))
}
let toString = (t: t) =>
switch t {
| String(d) => Some(d)
| _ => None
}
let toStringR = (t: t): result<string, error> =>
switch t {
| String(r) => Ok(r)
| e => Error(toErrorOrUnreachable(e))
}
//This is used to catch errors in other switch statements.
let fromResult = (r: result<t, error>): outputType =>
switch r {

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@ -26,7 +26,9 @@ module Output: {
let toDist: t => option<GenericDist_Types.genericDist>
let toDistR: t => result<GenericDist_Types.genericDist, GenericDist_Types.error>
let toFloat: t => option<float>
let toFloatR: t => result<float, GenericDist_Types.error>
let toString: t => option<string>
let toStringR: t => result<string, GenericDist_Types.error>
let toError: t => option<GenericDist_Types.error>
let fmap: (~env: env, t, GenericDist_Types.Operation.singleParamaterFunction) => t
}

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@ -20,7 +20,7 @@ module Operation = {
| #Subtract
| #Divide
| #Exponentiate
| #Log
| #Logarithm
]
let arithmeticToFn = (arithmetic: arithmeticOperation) =>
@ -30,7 +30,7 @@ module Operation = {
| #Subtract => \"-."
| #Exponentiate => \"**"
| #Divide => \"/."
| #Log => (a, b) => log(a) /. log(b)
| #Logarithm => (a, b) => log(a) /. log(b)
}
type toFloat = [

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@ -12,6 +12,7 @@ type rec expressionValue =
| EvSymbol(string)
| EvArray(array<expressionValue>)
| EvRecord(Js.Dict.t<expressionValue>)
| EvDistribution(GenericDist_Types.genericDist)
type functionCall = (string, array<expressionValue>)
@ -35,6 +36,7 @@ let rec toString = aValue =>
->Js.String.concatMany("")
`{${pairs}}`
}
| EvDistribution(dist) => `${GenericDist.toString(dist)}`
}
let toStringWithType = aValue =>
@ -45,6 +47,7 @@ let toStringWithType = aValue =>
| EvSymbol(_) => `Symbol::${toString(aValue)}`
| EvArray(_) => `Array::${toString(aValue)}`
| EvRecord(_) => `Record::${toString(aValue)}`
| EvDistribution(_) => `Distribution::${toString(aValue)}`
}
let argsToString = (args: array<expressionValue>): string => {

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@ -13,13 +13,10 @@ module Sample = {
/*
Map external calls of Reducer
*/
let dispatch = (call: ExpressionValue.functionCall, chain): result<expressionValue, 'e> =>
switch call {
| ("add", [EvNumber(a), EvNumber(b)]) => Sample.customAdd(a, b)->EvNumber->Ok
| call => chain(call)
/*
ReducerInterface_GenericDistribution.dispatch(call) |> E.O.default(chain(call))
/*
If your dispatch is too big you can divide it into smaller dispatches and pass the call so that it gets called finally.
The final chain(call) invokes the builtin default functions of the interpreter.
@ -35,4 +32,3 @@ Remember from the users point of view, there are no different modules:
// "doSth( constructorType2 )"
doSth gets dispatched to the correct module because of the type signature. You get function and operator abstraction for free. You don't need to combine different implementations into one type. That would be duplicating the repsonsibility of the dispatcher.
*/
}

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@ -0,0 +1,185 @@
module ExpressionValue = ReducerInterface_ExpressionValue
type expressionValue = ReducerInterface_ExpressionValue.expressionValue
let runGenericOperation = GenericDist_GenericOperation.run(
~env={
sampleCount: 1000,
xyPointLength: 1000,
},
)
module Helpers = {
let arithmeticMap = r =>
switch r {
| "add" => #Add
| "dotAdd" => #Add
| "subtract" => #Subtract
| "dotSubtract" => #Subtract
| "divide" => #Divide
| "log" => #Logarithm
| "dotDivide" => #Divide
| "pow" => #Exponentiate
| "dotPow" => #Exponentiate
| "multiply" => #Multiply
| "dotMultiply" => #Multiply
| "dotLog" => #Logarithm
| _ => #Multiply
}
let catchAndConvertTwoArgsToDists = (args: array<expressionValue>): option<(
GenericDist_Types.genericDist,
GenericDist_Types.genericDist,
)> => {
switch args {
| [EvDistribution(a), EvDistribution(b)] => Some((a, b))
| [EvNumber(a), EvDistribution(b)] => Some((GenericDist.fromFloat(a), b))
| [EvDistribution(a), EvNumber(b)] => Some((a, GenericDist.fromFloat(b)))
| _ => None
}
}
let toFloatFn = (
fnCall: GenericDist_Types.Operation.toFloat,
dist: GenericDist_Types.genericDist,
) => {
FromDist(GenericDist_Types.Operation.ToFloat(fnCall), dist)->runGenericOperation->Some
}
let toDistFn = (fnCall: GenericDist_Types.Operation.toDist, dist) => {
FromDist(GenericDist_Types.Operation.ToDist(fnCall), dist)->runGenericOperation->Some
}
let twoDiststoDistFn = (direction, arithmetic, dist1, dist2) => {
FromDist(
GenericDist_Types.Operation.ToDistCombination(
direction,
arithmeticMap(arithmetic),
#Dist(dist2),
),
dist1,
)->runGenericOperation
}
}
module SymbolicConstructors = {
let oneFloat = name =>
switch name {
| "exponential" => Ok(SymbolicDist.Exponential.make)
| _ => Error("Unreachable state")
}
let twoFloat = name =>
switch name {
| "normal" => Ok(SymbolicDist.Normal.make)
| "uniform" => Ok(SymbolicDist.Uniform.make)
| "beta" => Ok(SymbolicDist.Beta.make)
| "lognormal" => Ok(SymbolicDist.Lognormal.make)
| "to" => Ok(SymbolicDist.From90thPercentile.make)
| _ => Error("Unreachable state")
}
let threeFloat = name =>
switch name {
| "triangular" => Ok(SymbolicDist.Triangular.make)
| _ => Error("Unreachable state")
}
let symbolicResultToOutput = (
symbolicResult: result<SymbolicDistTypes.symbolicDist, string>,
): option<GenericDist_GenericOperation.outputType> =>
switch symbolicResult {
| Ok(r) => Some(Dist(Symbolic(r)))
| Error(r) => Some(GenDistError(Other(r)))
}
}
module Math = {
let e = 2.718281828459
}
let dispatchToGenericOutput = (call: ExpressionValue.functionCall): option<
GenericDist_GenericOperation.outputType,
> => {
let (fnName, args) = call
switch (fnName, args) {
| ("exponential" as fnName, [EvNumber(f1)]) =>
SymbolicConstructors.oneFloat(fnName)
->E.R.bind(r => r(f1))
->SymbolicConstructors.symbolicResultToOutput
| (
("normal" | "uniform" | "beta" | "lognormal" | "to") as fnName,
[EvNumber(f1), EvNumber(f2)],
) =>
SymbolicConstructors.twoFloat(fnName)
->E.R.bind(r => r(f1, f2))
->SymbolicConstructors.symbolicResultToOutput
| ("triangular" as fnName, [EvNumber(f1), EvNumber(f2), EvNumber(f3)]) =>
SymbolicConstructors.threeFloat(fnName)
->E.R.bind(r => r(f1, f2, f3))
->SymbolicConstructors.symbolicResultToOutput
| ("sample", [EvDistribution(dist)]) => Helpers.toFloatFn(#Sample, dist)
| ("mean", [EvDistribution(dist)]) => Helpers.toFloatFn(#Mean, dist)
| ("exp", [EvDistribution(a)]) =>
// https://mathjs.org/docs/reference/functions/exp.html
Helpers.twoDiststoDistFn(Algebraic, "pow", GenericDist.fromFloat(Math.e), a)->Some
| ("normalize", [EvDistribution(dist)]) => Helpers.toDistFn(Normalize, dist)
| ("toPointSet", [EvDistribution(dist)]) => Helpers.toDistFn(ToPointSet, dist)
| ("cdf", [EvDistribution(dist), EvNumber(float)]) => Helpers.toFloatFn(#Cdf(float), dist)
| ("pdf", [EvDistribution(dist), EvNumber(float)]) => Helpers.toFloatFn(#Pdf(float), dist)
| ("inv", [EvDistribution(dist), EvNumber(float)]) => Helpers.toFloatFn(#Inv(float), dist)
| ("toSampleSet", [EvDistribution(dist), EvNumber(float)]) =>
Helpers.toDistFn(ToSampleSet(Belt.Int.fromFloat(float)), dist)
| ("truncateLeft", [EvDistribution(dist), EvNumber(float)]) =>
Helpers.toDistFn(Truncate(Some(float), None), dist)
| ("truncateRight", [EvDistribution(dist), EvNumber(float)]) =>
Helpers.toDistFn(Truncate(None, Some(float)), dist)
| ("truncate", [EvDistribution(dist), EvNumber(float1), EvNumber(float2)]) =>
Helpers.toDistFn(Truncate(Some(float1), Some(float2)), dist)
| ("log", [EvDistribution(a)]) =>
Helpers.twoDiststoDistFn(Algebraic, "log", a, GenericDist.fromFloat(Math.e))->Some
| ("log10", [EvDistribution(a)]) =>
Helpers.twoDiststoDistFn(Algebraic, "log", a, GenericDist.fromFloat(10.0))->Some
| ("unaryMinus", [EvDistribution(a)]) =>
Helpers.twoDiststoDistFn(Algebraic, "multiply", a, GenericDist.fromFloat(-1.0))->Some
| (("add" | "multiply" | "subtract" | "divide" | "pow" | "log") as arithmetic, [a, b] as args) =>
Helpers.catchAndConvertTwoArgsToDists(args)->E.O2.fmap(((fst, snd)) =>
Helpers.twoDiststoDistFn(Algebraic, arithmetic, fst, snd)
)
| (
("dotAdd"
| "dotMultiply"
| "dotSubtract"
| "dotDivide"
| "dotPow"
| "dotLog") as arithmetic,
[a, b] as args,
) =>
Helpers.catchAndConvertTwoArgsToDists(args)->E.O2.fmap(((fst, snd)) =>
Helpers.twoDiststoDistFn(Pointwise, arithmetic, fst, snd)
)
| ("dotLog", [EvDistribution(a)]) =>
Helpers.twoDiststoDistFn(Pointwise, "dotLog", a, GenericDist.fromFloat(Math.e))->Some
| ("dotExp", [EvDistribution(a)]) =>
Helpers.twoDiststoDistFn(Pointwise, "dotPow", GenericDist.fromFloat(Math.e), a)->Some
| _ => None
}
}
let genericOutputToReducerValue = (o: GenericDist_GenericOperation.outputType): result<
expressionValue,
Reducer_ErrorValue.errorValue,
> =>
switch o {
| Dist(d) => Ok(ReducerInterface_ExpressionValue.EvDistribution(d))
| Float(d) => Ok(EvNumber(d))
| String(d) => Ok(EvString(d))
| GenDistError(NotYetImplemented) => Error(RETodo("Function not yet implemented"))
| GenDistError(Unreachable) => Error(RETodo("Unreachable"))
| GenDistError(DistributionVerticalShiftIsInvalid) =>
Error(RETodo("Distribution Vertical Shift is Invalid"))
| GenDistError(Other(s)) => Error(RETodo(s))
}
let dispatch = call => {
dispatchToGenericOutput(call)->E.O2.fmap(genericOutputToReducerValue)
}

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@ -0,0 +1,3 @@
let dispatch: ReducerInterface_ExpressionValue.functionCall => option<
result<ReducerInterface_ExpressionValue.expressionValue, Reducer_ErrorValue.errorValue>,
>

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@ -229,6 +229,6 @@ let all = [
),
makeRenderedDistFloat("scaleExp", (dist, float) => verticalScaling(#Exponentiate, dist, float)),
makeRenderedDistFloat("scaleMultiply", (dist, float) => verticalScaling(#Multiply, dist, float)),
makeRenderedDistFloat("scaleLog", (dist, float) => verticalScaling(#Log, dist, float)),
makeRenderedDistFloat("scaleLog", (dist, float) => verticalScaling(#Logarithm, dist, float)),
Multimodal._function,
]

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@ -115,7 +115,7 @@ let combineShapesContinuousContinuous = (
| #Multiply => (m1, m2) => m1 *. m2
| #Divide => (m1, mInv2) => m1 *. mInv2
| #Exponentiate => (m1, mInv2) => m1 ** mInv2
| #Log => (m1, m2) => log(m1) /. log(m2)
| #Logarithm => (m1, m2) => log(m1) /. log(m2)
} // note: here, mInv2 = mean(1 / t2) ~= 1 / mean(t2)
// TODO: I don't know what the variances are for exponentatiation
@ -233,7 +233,7 @@ let combineShapesContinuousDiscrete = (
}
| #Multiply
| #Exponentiate
| #Log
| #Logarithm
| #Divide =>
for j in 0 to t2n - 1 {
// creates a new continuous shape for each one of the discrete points, and collects them in outXYShapes.

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@ -2,7 +2,7 @@ open SymbolicDistTypes
module Normal = {
type t = normal
let make = (mean: float, stdev: float): result<symbolicDist,string> =>
let make = (mean: float, stdev: float): result<symbolicDist, string> =>
stdev > 0.0
? Ok(#Normal({mean: mean, stdev: stdev}))
: Error("Standard deviation of normal distribution must be larger than 0")
@ -48,11 +48,13 @@ module Normal = {
module Exponential = {
type t = exponential
let make = (rate: float): result<symbolicDist,string> =>
let make = (rate: float): result<symbolicDist, string> =>
rate > 0.0
? Ok(#Exponential({
rate: rate,
}))
? Ok(
#Exponential({
rate: rate,
}),
)
: Error("Exponential distributions mean must be larger than 0")
let pdf = (x, t: t) => Jstat.Exponential.pdf(x, t.rate)
let cdf = (x, t: t) => Jstat.Exponential.cdf(x, t.rate)
@ -89,7 +91,7 @@ module Triangular = {
module Beta = {
type t = beta
let make = (alpha, beta) =>
let make = (alpha, beta) =>
alpha > 0.0 && beta > 0.0
? Ok(#Beta({alpha: alpha, beta: beta}))
: Error("Beta distribution parameters must be positive")
@ -103,10 +105,10 @@ module Beta = {
module Lognormal = {
type t = lognormal
let make = (mu, sigma) =>
sigma > 0.0
? Ok(#Lognormal({mu: mu, sigma: sigma}))
: Error("Lognormal standard deviation must be larger than 0")
let make = (mu, sigma) =>
sigma > 0.0
? Ok(#Lognormal({mu: mu, sigma: sigma}))
: Error("Lognormal standard deviation must be larger than 0")
let pdf = (x, t: t) => Jstat.Lognormal.pdf(x, t.mu, t.sigma)
let cdf = (x, t: t) => Jstat.Lognormal.cdf(x, t.mu, t.sigma)
let inv = (p, t: t) => Jstat.Lognormal.inv(p, t.mu, t.sigma)
@ -127,8 +129,7 @@ module Lognormal = {
let mu = Js.Math.log(mean) -. 0.5 *. Js.Math.log(variance /. meanSquared +. 1.0)
let sigma = Js.Math.pow_float(~base=Js.Math.log(variance /. meanSquared +. 1.0), ~exp=0.5)
Ok(#Lognormal({mu: mu, sigma: sigma}))
}
else {
} else {
Error("Lognormal standard deviation must be larger than 0")
}
}
@ -154,9 +155,7 @@ module Lognormal = {
module Uniform = {
type t = uniform
let make = (low, high) =>
high > low
? Ok(#Uniform({low: low, high: high}))
: Error("High must be larger than low")
high > low ? Ok(#Uniform({low: low, high: high})) : Error("High must be larger than low")
let pdf = (x, t: t) => Jstat.Uniform.pdf(x, t.low, t.high)
let cdf = (x, t: t) => Jstat.Uniform.cdf(x, t.low, t.high)
@ -165,7 +164,7 @@ module Uniform = {
let mean = (t: t) => Ok(Jstat.Uniform.mean(t.low, t.high))
let toString = ({low, high}: t) => j`Uniform($low,$high)`
let truncate = (low, high, t: t): t => {
//todo: add check
//todo: add check
let newLow = max(E.O.default(neg_infinity, low), t.low)
let newHigh = min(E.O.default(infinity, high), t.high)
{low: newLow, high: newHigh}
@ -183,6 +182,15 @@ module Float = {
let toString = Js.Float.toString
}
module From90thPercentile = {
let make = (low, high) =>
switch (low, high) {
| (low, high) if low <= 0.0 && low < high => Ok(Normal.from90PercentCI(low, high))
| (low, high) if low < high => Ok(Lognormal.from90PercentCI(low, high))
| (_, _) => Error("Low value must be less than high value.")
}
}
module T = {
let minCdfValue = 0.0001
let maxCdfValue = 0.9999

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@ -100,6 +100,7 @@ module O = {
module O2 = {
let default = (a, b) => O.default(b, a)
let toExn = (a, b) => O.toExn(b, a)
let fmap = (a, b) => O.fmap(b, a)
}
/* Functions */

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@ -7,11 +7,11 @@ type algebraicOperation = [
| #Subtract
| #Divide
| #Exponentiate
| #Log
| #Logarithm
]
@genType
type pointwiseOperation = [#Add | #Multiply | #Exponentiate]
type scaleOperation = [#Multiply | #Exponentiate | #Log | #Divide]
type scaleOperation = [#Multiply | #Exponentiate | #Logarithm | #Divide]
type distToFloatOperation = [
| #Pdf(float)
| #Cdf(float)
@ -29,7 +29,7 @@ module Algebraic = {
| #Multiply => \"*."
| #Exponentiate => \"**"
| #Divide => \"/."
| #Log => (a, b) => log(a) /. log(b)
| #Logarithm => (a, b) => log(a) /. log(b)
}
let applyFn = (t, f1, f2) =>
@ -45,7 +45,7 @@ module Algebraic = {
| #Multiply => "*"
| #Exponentiate => "**"
| #Divide => "/"
| #Log => "log"
| #Logarithm => "log"
}
let format = (a, b, c) => b ++ (" " ++ (toString(a) ++ (" " ++ c)))
@ -84,7 +84,7 @@ module Scale = {
| #Multiply => \"*."
| #Divide => \"/."
| #Exponentiate => \"**"
| #Log => (a, b) => log(a) /. log(b)
| #Logarithm => (a, b) => log(a) /. log(b)
}
let format = (operation: t, value, scaleBy) =>
@ -92,7 +92,7 @@ module Scale = {
| #Multiply => j`verticalMultiply($value, $scaleBy) `
| #Divide => j`verticalDivide($value, $scaleBy) `
| #Exponentiate => j`verticalExponentiate($value, $scaleBy) `
| #Log => j`verticalLog($value, $scaleBy) `
| #Logarithm => j`verticalLog($value, $scaleBy) `
}
let toIntegralSumCacheFn = x =>
@ -100,7 +100,7 @@ module Scale = {
| #Multiply => (a, b) => Some(a *. b)
| #Divide => (a, b) => Some(a /. b)
| #Exponentiate => (_, _) => None
| #Log => (_, _) => None
| #Logarithm => (_, _) => None
}
let toIntegralCacheFn = x =>
@ -108,7 +108,7 @@ module Scale = {
| #Multiply => (_, _) => None // TODO: this could probably just be multiplied out (using Continuous.scaleBy)
| #Divide => (_, _) => None
| #Exponentiate => (_, _) => None
| #Log => (_, _) => None
| #Logarithm => (_, _) => None
}
}