Cleanup of Domain functions
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2e1287e746
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@ -1,8 +1,3 @@
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let data: DistributionTypes.xyShape = {
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xs: [|1., 10., 10., 200., 250., 292., 330.|],
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ys: [|0.0, 0.0, 0.1, 0.3, 0.5, 0.2, 0.1|],
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};
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// "mm(floor(uniform(30,35)), normal(50,20), [.25,.5])",
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let timeDist =
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GenericDistribution.make(
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@ -1,107 +1,12 @@
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module Mixed = {
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[@react.component]
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let make = (~data: DistributionTypes.mixedShape, ~unit) => {
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let (x, setX) = React.useState(() => 0.);
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let timeScale = unit |> DistributionTypes.DistributionUnit.toJson;
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let chart =
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React.useMemo1(
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() =>
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<CdfChart__Plain
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continuous={data.continuous}
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discrete={data.discrete}
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color={`hex("333")}
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timeScale
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onHover={r => setX(_ => r)}
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showDistributionYAxis=true
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/>,
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[|data|],
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);
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<div>
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chart
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<table className="table-auto">
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<thead>
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<tr>
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<th className="px-4 py-2"> {"X Point" |> ReasonReact.string} </th>
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<th className="px-4 py-2">
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{"Y Integral to Point" |> ReasonReact.string}
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</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<th className="px-4 py-2 border ">
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{x |> E.Float.toString |> ReasonReact.string}
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</th>
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<th className="px-4 py-2 border ">
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{Shape.Mixed.findYIntegral(x, data)
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|> E.O.fmap(E.Float.with2DigitsPrecision)
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|> E.O.default("")
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|> ReasonReact.string}
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</th>
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</tr>
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</tbody>
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</table>
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<div />
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{data.discrete
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|> Shape.Discrete.scaleYToTotal(data.discreteProbabilityMassFraction)
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|> Shape.Discrete.render}
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</div>;
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};
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};
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let discreteComponent = (p: DistributionTypes.pointsType) =>
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switch (p) {
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| Mixed(mixedShape) => Some(mixedShape.discrete)
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| Discrete(discreteShape) => Some(discreteShape)
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| Continuous(_) => None
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};
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let continuousComponent = (p: DistributionTypes.pointsType) =>
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switch (p) {
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| Mixed(mixedShape) => Some(mixedShape.continuous)
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| Discrete(_) => None
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| Continuous(c) => Some(c)
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};
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let discreteScaleFactor = (p: DistributionTypes.pointsType) =>
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switch (p) {
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| Mixed(mixedShape) => Some(mixedShape.discreteProbabilityMassFraction)
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| Discrete(_) => None
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| Continuous(_) => None
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};
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module Shapee = {
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[@react.component]
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let make = (~shape: DistributionTypes.pointsType, ~timeScale, ~onHover) => {
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let discreteScaleFactor = shape |> discreteScaleFactor;
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let continuous =
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continuousComponent(shape)
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|> E.O.bind(
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_,
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Shape.Continuous.scalePdf(
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~scaleTo=
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discreteScaleFactor
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|> E.O.fmap(r => 1. -. r)
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|> E.O.default(1.0),
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),
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);
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let discrete =
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discreteComponent(shape)
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|> E.O.fmap(
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Shape.Discrete.scaleYToTotal(
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discreteScaleFactor |> E.O.default(1.0),
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),
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);
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let minX = {
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Shape.Any.minX(shape);
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};
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let maxX = {
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Shape.Any.maxX(shape);
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};
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let discrete = Shape.Any.scaledDiscreteComponent(shape);
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let continuous = Shape.Any.scaledContinuousComponent(shape);
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<div>
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<CdfChart__Plain
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minX
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maxX
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minX={Shape.Any.minX(shape)}
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maxX={Shape.Any.maxX(shape)}
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?discrete
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?continuous
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color={`hex("333")}
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@ -1,5 +1,33 @@
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open DistributionTypes;
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module Domain = {
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let excludedProbabilityMass = (t: DistributionTypes.domain) => {
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switch (t) {
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| Complete => 1.0
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| LeftLimited({excludingProbabilityMass}) => excludingProbabilityMass
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| RightLimited({excludingProbabilityMass}) => excludingProbabilityMass
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| LeftAndRightLimited(
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{excludingProbabilityMass: l},
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{excludingProbabilityMass: r},
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) =>
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l +. r
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};
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};
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let initialProbabilityMass = (t: DistributionTypes.domain) => {
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switch (t) {
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| Complete
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| RightLimited(_) => 0.0
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| LeftLimited({excludingProbabilityMass}) => excludingProbabilityMass
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| LeftAndRightLimited({excludingProbabilityMass}, _) => excludingProbabilityMass
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};
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};
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let normalizeProbabilityMass = (t: DistributionTypes.domain) => {
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1. /. excludedProbabilityMass(t);
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};
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};
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let make =
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(
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~generationSource,
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@ -92,35 +120,9 @@ let normalize = (t: genericDistribution): option(genericDistribution) => {
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};
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};
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let excludedProbabilityMass = (t: DistributionTypes.domain) => {
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switch (t) {
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| Complete => 1.0
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| LeftLimited({excludingProbabilityMass}) => excludingProbabilityMass
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| RightLimited({excludingProbabilityMass}) => excludingProbabilityMass
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| LeftAndRightLimited(
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{excludingProbabilityMass: l},
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{excludingProbabilityMass: r},
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) =>
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l +. r
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};
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};
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let initialProbabilityMass = (t: DistributionTypes.domain) => {
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switch (t) {
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| Complete
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| RightLimited(_) => 0.0
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| LeftLimited({excludingProbabilityMass}) => excludingProbabilityMass
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| LeftAndRightLimited({excludingProbabilityMass}, _) => excludingProbabilityMass
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};
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};
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let normalizeProbabilityMass = (t: DistributionTypes.domain) => {
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1. /. excludedProbabilityMass(t);
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};
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let yIntegral = (t: DistributionTypes.genericDistribution, x) => {
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let addInitialMass = n => n +. initialProbabilityMass(t.domain);
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let normalize = n => n *. normalizeProbabilityMass(t.domain);
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let addInitialMass = n => n +. Domain.initialProbabilityMass(t.domain);
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let normalize = n => n *. Domain.normalizeProbabilityMass(t.domain);
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switch (t) {
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| {generationSource: Shape(shape)} =>
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Shape.Any.yIntegral(shape, x)
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@ -130,16 +132,16 @@ let yIntegral = (t: DistributionTypes.genericDistribution, x) => {
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};
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};
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// TODO: This obviously needs to be fleshed out a lot.
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let integrate = (t: DistributionTypes.genericDistribution) => {
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switch (t) {
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| {probabilityType: Pdf, generationSource: Shape(shape), domain, unit} =>
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Some({
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generationSource: Shape(shape),
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probabilityType: Cdf,
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probabilityType: Pdf,
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domain,
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unit,
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})
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| {probabilityType: Cdf, generationSource, domain, unit} => None
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| _ => None
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};
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};
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@ -283,11 +283,39 @@ module Any = {
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| Continuous(continuous) =>
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Continuous.toCdf(continuous) |> E.O.fmap(e => Continuous(e))
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};
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};
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module DomainMixed = {
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type t = {
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mixedShape,
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domain,
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let discreteComponent = (t: t) =>
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switch (t) {
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| Mixed({discrete}) => Some(discrete)
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| Discrete(d) => Some(d)
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| Continuous(_) => None
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};
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let continuousComponent = (t: t) =>
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switch (t) {
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| Mixed({continuous}) => Some(continuous)
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| Continuous(c) => Some(c)
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| Discrete(_) => None
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};
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let scaledContinuousComponent = (t: t): option(continuousShape) => {
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switch (t) {
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| Mixed({continuous, discreteProbabilityMassFraction}) =>
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Continuous.scalePdf(
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~scaleTo=1.0 -. discreteProbabilityMassFraction,
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continuous,
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)
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| Discrete(_) => None
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| Continuous(c) => Some(c)
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};
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};
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let scaledDiscreteComponent = (t: t): option(discreteShape) => {
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switch (t) {
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| Mixed({discrete, discreteProbabilityMassFraction}) =>
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Some(Discrete.scaleYToTotal(discreteProbabilityMassFraction, discrete))
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| Discrete(d) => Some(d)
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| Continuous(_) => None
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};
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};
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};
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@ -19,7 +19,7 @@ let propValue = (t: Prop.Value.t) => {
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| ConditionalArray(r) => "Array" |> ReasonReact.string
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| GenericDistribution(r) =>
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let newDistribution =
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GenericDistribution.renderIfNeeded(~sampleCount=1000, r);
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GenericDistribution.renderIfNeeded(~sampleCount=2000, r);
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switch (newDistribution) {
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| Some(distribution) =>
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<div>
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@ -1,4 +1,4 @@
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let guesstimatorString = GuesstimatorDist.logNormal(20., 3.);
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let guesstimatorString = "mm(10 to 30, floor(20 to 25), [.5,.5])";
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module Model = {
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let make = (currentDateTime: MomentRe.Moment.t) => {
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@ -46,7 +46,7 @@ const toPdf = (values, sampleCount, min, max) => {
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const samples = new Samples(continuousSamples);
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const ratioSize$ = ratioSize(samples);
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const width = ratioSize$ === 'SMALL' ? 20 : 1;
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const width = ratioSize$ === 'SMALL' ? 100 : 1;
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const pdf = samples.toPdf({ size: sampleCount, width, min, max });
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continuous = pdf;
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