Simple mixed distribution
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@ -1,12 +1,17 @@
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type t = {
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distribution: Types.distribution,
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distribution: Types.ContinuousDistribution.t,
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domainMaxX: float,
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};
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let make = (~distribution, ~domainMaxX): t => {distribution, domainMaxX};
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let fromCdf = (cdf: Types.cdf, domainMaxX: float, probabilityAtMaxX: float) => {
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let distribution: Types.distribution = {
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let fromCdf =
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(
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cdf: Types.ContinuousDistribution.t,
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domainMaxX: float,
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probabilityAtMaxX: float,
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) => {
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let distribution: Types.ContinuousDistribution.t = {
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xs: cdf.xs,
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ys: cdf.ys |> E.A.fmap(r => r *. probabilityAtMaxX),
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};
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@ -66,7 +66,7 @@ type t = {
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let make =
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(
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~timeVector: timeVector,
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~distribution: Types.distribution,
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~distribution: Types.ContinuousDistribution.t,
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~probabilityAtMaxX: float,
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~maxX: [ | `time(MomentRe.Moment.t) | `x(float)],
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)
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@ -17,7 +17,7 @@ module Value = {
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| Conditional(conditional)
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| TimeLimitedDomainCdf(TimeLimitedDomainCdf.t)
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| TimeLimitedDomainCdfLazy(
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(string => Types.distribution) => TimeLimitedDomainCdf.t,
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(string => Types.ContinuousDistribution.t) => TimeLimitedDomainCdf.t,
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)
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| ConditionalArray(array(conditional))
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| FloatCdf(string);
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@ -59,23 +59,34 @@ module Value = {
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let timeLimited = r(CdfLibrary.Distribution.fromString(_, 1000));
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let cdf = timeLimited.limitedDomainCdf.distribution;
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<>
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<Chart height=100 data={cdf |> Types.toJs} />
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<Chart height=100 data={cdf |> Types.ContinuousDistribution.toJs} />
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<Chart
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height=100
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data={cdf |> CdfLibrary.Distribution.toPdf |> Types.toJs}
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data={
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cdf
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|> CdfLibrary.Distribution.toPdf
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|> Types.ContinuousDistribution.toJs
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}
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/>
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{FloatCdf.logNormal(50., 20.) |> ReasonReact.string}
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</>;
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| TimeLimitedDomainCdf(r) =>
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let cdf: Types.distribution = r.limitedDomainCdf.distribution;
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<> <Chart height=100 data={cdf |> Types.toJs} /> </>;
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let cdf: Types.ContinuousDistribution.t =
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r.limitedDomainCdf.distribution;
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<>
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<Chart height=100 data={cdf |> Types.ContinuousDistribution.toJs} />
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</>;
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| FloatCdf(r) =>
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let cdf: Types.distribution =
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let cdf: Types.ContinuousDistribution.t =
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CdfLibrary.Distribution.fromString(r, 2000);
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<>
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<Chart
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height=100
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data={cdf |> CdfLibrary.Distribution.toPdf |> Types.toJs}
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data={
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cdf
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|> CdfLibrary.Distribution.toPdf
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|> Types.ContinuousDistribution.toJs
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}
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/>
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{r |> ReasonReact.string}
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</>;
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@ -1,54 +1,66 @@
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type distribution = {
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xs: array(float),
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ys: array(float),
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};
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let toJs = (t: distribution) => {
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{"xs": t.xs, "ys": t.ys};
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};
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let toComponentsDist = (d: distribution): ForetoldComponents.Types.Dist.t => {
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xs: d.xs,
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ys: d.ys,
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};
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type pdf = distribution;
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type cdf = distribution;
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let foo = (b: pdf) => 3.9;
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let bar: cdf = {xs: [||], ys: [||]};
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let cc = foo(bar);
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module LimitedDomainCdf = {
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module ContinuousDistribution = {
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type t = {
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distribution,
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domainMaxX: float,
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xs: array(float),
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ys: array(float),
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};
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let fromCdf = (cdf: cdf, domainMaxX: float, probabilityAtMaxX: float) => {
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let distribution: distribution = {
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xs: cdf.xs,
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ys: cdf.ys |> E.A.fmap(r => r *. probabilityAtMaxX),
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};
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{distribution, domainMaxX};
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let toJs = (t: t) => {
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{"xs": t.xs, "ys": t.ys};
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};
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let toComponentsDist = (d: t): ForetoldComponents.Types.Dist.t => {
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xs: d.xs,
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ys: d.ys,
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};
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type pdf = t;
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type cdf = t;
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};
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module DiscreteDistribution = {
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type t = {
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xs: array(float),
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ys: array(float),
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};
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let fromArray = (xs, ys) => {xs, ys};
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let _lastElement = (a: array('a)) =>
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switch (Belt.Array.size(a)) {
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| 0 => None
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| n => Belt.Array.get(a, n)
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};
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let probabilityBeforeDomainMax = (t: t) => _lastElement(t.distribution.ys);
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let derivative = (p: t) => {
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let (xs, ys) =
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Belt.Array.zip(p.xs, p.ys)
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->Belt.Array.reduce([||], (items, (x, y)) =>
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switch (_lastElement(items)) {
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| Some((_, yLast)) => [|(x, y -. yLast)|]
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| None => [|(x, y)|]
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}
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)
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|> Belt.Array.unzip;
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fromArray(xs, ys);
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};
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let chanceByX = (t: t) => t.distribution;
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let integral = (p: t) => {
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let (xs, ys) =
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Belt.Array.zip(p.xs, p.ys)
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->Belt.Array.reduce([||], (items, (x, y)) =>
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switch (_lastElement(items)) {
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| Some((_, yLast)) => [|(x, y +. yLast)|]
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| None => [|(x, y)|]
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}
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)
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|> Belt.Array.unzip;
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fromArray(xs, ys);
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};
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};
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let domainMaxX = (t: t) => t.domainMaxX;
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// let probabilityDistribution = (t: t) =>
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// t.distribution |> CdfLibrary.Distribution.toPdf;
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// let probability = (t: t, xPoint: float) =>
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// CdfLibrary.Distribution.findY(xPoint, probabilityDistribution(t));
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// let cumulativeProbability = (t: t, xPoint: float) =>
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// CdfLibrary.Distribution.findY(xPoint, t.distribution);
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module MixedDistribution = {
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type distribution = {
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discrete: DiscreteDistribution.t,
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continuous: ContinuousDistribution.t,
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};
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};
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@ -5,14 +5,16 @@ module JS = {
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ys: array(float),
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};
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let distToJs = (d: Types.distribution) => distJs(~xs=d.xs, ~ys=d.ys);
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let distToJs = (d: Types.ContinuousDistribution.t) =>
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distJs(~xs=d.xs, ~ys=d.ys);
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let jsToDist = (d: distJs): Types.distribution => {
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let jsToDist = (d: distJs): Types.ContinuousDistribution.t => {
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xs: xsGet(d),
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ys: ysGet(d),
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};
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let doAsDist = (f, d: Types.distribution) => d |> distToJs |> f |> jsToDist;
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let doAsDist = (f, d: Types.ContinuousDistribution.t) =>
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d |> distToJs |> f |> jsToDist;
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[@bs.module "./CdfLibrary.js"]
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external cdfToPdf: distJs => distJs = "cdfToPdf";
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