Basic mixed discrete-continuous distributions

src/lib/Prop.re

@@ -61,13 +61,10 @@ module Value = {
       let newDistribution =
         GenericDistribution.renderIfNeeded(~sampleCount=1000, r);
       switch (newDistribution) {
-      | Some({generationSource: Shape(Mixed({continuous: n}))}) =>
+      | Some({generationSource: Shape(Mixed({continuous: n, discrete: d}))}) =>
         <div>
           <Chart height=100 data={n |> Shape.Continuous.toJs} />
-          <Chart
-            height=100
-            data={n |> Shape.Continuous.toCdf |> Shape.Continuous.toJs}
-          />
+          {Shape.Discrete.render(d)}
         </div>
       | None => "Something went wrong" |> ReasonReact.string
       | _ => <div />

src/lib/Shape.re

@@ -45,6 +45,18 @@ module Discrete = {
       |> Belt.Array.unzip;
     fromArrays(xs, ys);
   };
+
+  let render = (t: t) =>
+    Belt.Array.zip(t.xs, t.ys)
+    |> E.A.fmap(((x, y)) =>
+         <div>
+           {E.Float.toFixed(x)
+            ++ "---"
+            ++ E.Float.with3DigitsPrecision(y *. 100.)
+            |> ReasonReact.string}
+         </div>
+       )
+    |> ReasonReact.array;
 };
 
 module Mixed = {

src/models/GlobalCatastrophe.re

@@ -1,8 +1,10 @@
+// ~generationSource=GuesstimatorString(FloatCdf.logNormal(20., 3.)),
 module Model = {
   let make = (currentDateTime: MomentRe.Moment.t) => {
     let genericDistribution =
       GenericDistribution.make(
-        ~generationSource=GuesstimatorString(FloatCdf.logNormal(20., 3.)),
+        ~generationSource=
+          GuesstimatorString("mm(floor(10 to 15), 20 to 30, [.5,.5])"),
         ~probabilityType=Cdf,
         ~domain=RightLimited({xPoint: 200., excludingProbabilityMass: 0.3}),
         ~unit=Time({zero: currentDateTime, unit: `years}),

src/utility/GuesstimatorLibrary.js

@@ -37,15 +37,21 @@ const ratioSize = samples => {
 const toPdf = (values, sampleCount, min, max) => {
   let duplicateSamples = _(values).groupBy().pickBy(x => x.length > 1).keys().value();
   let totalLength = _.size(values);
-  let frequencies = duplicateSamples.map(s => ({value: parseFloat(s), percentage: totalLength/_(values).filter(x => x ==s).size()}));
+  let frequencies = duplicateSamples.map(s => ({value: parseFloat(s), percentage: _(values).filter(x => x ==s).size()/totalLength}));
   let continuousSamples = _.difference(values, frequencies.map(f => f.value));
-  const samples = new Samples(continuousSamples);
 
-  const ratioSize$ = ratioSize(samples);
-  const width = ratioSize$ === 'SMALL' ? 20 : 1;
+  let discrete = {xs: frequencies.map(f => f.value), ys: frequencies.map(f => f.percentage)};
+  let continuous = {ys: [], xs: []};
+  if (continuousSamples.length > 1){
+    const samples = new Samples(continuousSamples);
 
-  const cdf = samples.toCdf({ size: sampleCount, width, min, max });
-  return {continuous:{ys:cdf.ys, xs:cdf.xs}, discrete: {xs: frequencies.map(f => f.value), ys: frequencies.map(f => f.percentage)}};
+    const ratioSize$ = ratioSize(samples);
+    const width = ratioSize$ === 'SMALL' ? 20 : 1;
+
+    const cdf = samples.toCdf({ size: sampleCount, width, min, max });
+    continuous = cdf;
+  }
+  return {continuous, discrete};
 };
 
 let run = (text, sampleCount, inputs=[], min=false, max=false) => {
@@ -63,10 +69,14 @@ let run = (text, sampleCount, inputs=[], min=false, max=false) => {
     const values = _.filter(value.values, _.isFinite);
 
     let update;
+    let blankResponse = {
+      continuous: {ys: [], xs: []},
+      discrete: {ys: [], xs: []}
+    };
     if (values.length === 0) {
-      update = {xs: [], ys: []};
+      update = blankResponse;
     } else if (values.length === 1) {
-      update = {xs: [], ys: []};
+      update = blankResponse;
     } else {
       update = toPdf(values, sampleCount, min, max);
     }