Implemented step function transformation

showcase/entries/Continuous.re

@@ -2,7 +2,7 @@
 let timeDist =
   GenericDistribution.make(
     ~generationSource=
-      GuesstimatorString("mm(floor(normal(30,3)), normal(39,1), [.5,.5])"),
+      GuesstimatorString("mm(floor(normal(30,2)), normal(39,1), [.5,.5])"),
     ~probabilityType=Pdf,
     ~domain=Complete,
     ~unit=TimeDistribution({zero: MomentRe.momentNow(), unit: `days}),

src/components/charts/ComplexPowerChart.re

@@ -23,6 +23,37 @@ module ComplexPowerChart = {
   };
 };
 
+let bar: DistributionTypes.xyShape = {
+  ys: [|0.5, 0.8, 0.4, 1.0, 2.0|],
+  xs: [|0.0, 1., 2., 5., 8.|],
+};
+
+module IntegralChart = {
+  [@react.component]
+  let make = (~complexPower: DistributionTypes.complexPower, ~onHover) => {
+    open DistFunctor.ComplexPower;
+    let integral =
+      DistFunctor.ComplexPower.T.Integral.get(~cache=None, complexPower);
+    let continuous =
+      integral
+      |> T.toContinuous
+      |> E.O.fmap(DistFunctor.Continuous.toLinear)
+      |> E.O.fmap(DistFunctor.Continuous.getShape);
+    let minX = T.minX(integral);
+    let maxX = T.maxX(integral);
+    let timeScale =
+      complexPower.unit |> DistributionTypes.DistributionUnit.toJson;
+    <CdfChart__Plain
+      minX
+      maxX
+      ?continuous
+      color={`hex("333")}
+      timeScale
+      onHover
+    />;
+  };
+};
+
 [@react.component]
 let make = (~complexPower: DistributionTypes.complexPower) => {
   let (x, setX) = React.useState(() => 0.);
@@ -31,8 +62,14 @@ let make = (~complexPower: DistributionTypes.complexPower) => {
       () => {<ComplexPowerChart complexPower onHover={r => {setX(_ => r)}} />},
       [|complexPower|],
     );
+  let chart2 =
+    React.useMemo1(
+      () => {<IntegralChart complexPower onHover={r => {setX(_ => r)}} />},
+      [|complexPower|],
+    );
   <div>
     chart
+    chart2
     <table className="table-auto">
       <thead>
         <tr>

src/core/DistFunctor.re

@@ -77,18 +77,28 @@ module Continuous = {
       : option(DistributionTypes.continuousShape) =>
     fn(xyShape) |> E.O.fmap(xyShape => make(xyShape, interpolation));
 
+  let toLinear = (t: t): t =>
+    switch (t) {
+    | {interpolation: `Stepwise, xyShape} => {
+        interpolation: `Linear,
+        xyShape: xyShape |> XYShape.Range.stepsToContinuous |> E.O.toExt(""),
+      }
+    | {interpolation: `Linear, _} => t
+    };
+
   module T =
     Dist({
       type t = DistributionTypes.continuousShape;
       type integral = DistributionTypes.continuousShape;
       let shapeFn = (fn, t: t) => t |> xyShape |> fn;
+      // TODO: Obviously fix this, it's terrible
       let integral = (~cache, t) =>
         cache
         |> E.O.default(
              t
              |> xyShape
              |> XYShape.Range.integrateWithTriangles
-             |> E.O.toExt("")
+             |> E.O.toExt("Error1")
              |> fromShape,
            );
       //   This seems wrong, we really want the ending bit, I'd assume
@@ -118,7 +128,16 @@ module Discrete = {
       type integral = DistributionTypes.continuousShape;
       let integral = (~cache, t) =>
         cache
-        |> E.O.default(t |> XYShape.accumulateYs |> Continuous.fromShape);
+        |> E.O.default(
+             {
+               Continuous.make(
+                 XYShape.accumulateYs(t)
+                 |> XYShape.Range.stepsToContinuous
+                 |> E.O.toExt("ERROR"),
+                 `Stepwise,
+               );
+             },
+           );
       let integralSum = (~cache, t) => t |> XYShape.ySum;
       let minX = XYShape.minX;
       let maxX = XYShape.maxX;
@@ -197,26 +216,42 @@ module Mixed = {
         DistributionTypes.MixedPoint.add(c, d);
       };
 
-      let toScaledContinuous =
+      let scaleContinuous =
-          ({continuous, discreteProbabilityMassFraction}: t) =>
+          ({discreteProbabilityMassFraction}: t, continuous) =>
-        Some(
+        continuous
-          continuous
+        |> Continuous.T.scaleBy(~scale=1.0 -. discreteProbabilityMassFraction);
-          |> Continuous.T.scaleBy(
-               ~scale=1.0 -. discreteProbabilityMassFraction,
-             ),
-        );
 
-      let toScaledDiscrete = ({discrete, discreteProbabilityMassFraction}: t) =>
+      let scaleDiscrete = ({discreteProbabilityMassFraction}: t, disrete) =>
-        Some(
+        disrete |> Discrete.T.scaleBy(~scale=discreteProbabilityMassFraction);
-          discrete
+
-          |> Discrete.T.scaleBy(~scale=discreteProbabilityMassFraction),
+      let toScaledContinuous = ({continuous} as t: t) =>
-        );
+        Some(scaleContinuous(t, continuous));
+
+      let toScaledDiscrete = ({discrete} as t: t) =>
+        Some(scaleDiscrete(t, discrete));
 
       // TODO: Add these two directly, once interpolation is added.
-      let integral = (~cache, t) => {
+      let integral =
-        //   let cont = scaledContinuousComponent(t);
+          (
-        //   let discrete = scaledDiscreteComponent(t);
+            ~cache,
-        cache |> E.O.toExt("");
+            {continuous, discrete, discreteProbabilityMassFraction} as t: t,
+          ) => {
+        cache
+        |> E.O.default(
+             {
+               let cont =
+                 continuous
+                 |> Continuous.T.Integral.get(~cache=None)
+                 |> scaleContinuous(t);
+               let dist =
+                 discrete
+                 |> Discrete.T.Integral.get(~cache=None)
+                 |> Continuous.T.scaleBy(
+                      ~scale=discreteProbabilityMassFraction,
+                    );
+               dist;
+             },
+           );
       };
 
       let integralSum =
@@ -323,7 +358,7 @@ module Shape = {
         );
       let minX = (t: t) =>
         mapToAll(t, (Mixed.T.minX, Discrete.T.minX, Continuous.T.minX));
-      let integral = (~cache, t: t) =>
+      let integral = (~cache, t: t) => {
         mapToAll(
           t,
           (
@@ -332,6 +367,7 @@ module Shape = {
             Continuous.T.Integral.get(~cache),
           ),
         );
+      };
       let integralSum = (~cache, t: t) =>
         mapToAll(
           t,

src/core/DistributionTypes.re

@@ -14,6 +14,11 @@ type xyShape = {
   ys: array(float),
 };
 
+let foo = {xs: [|1., 2., 5.|], ys: [|1., 2., 3.|]};
+let answer = {xs: [|1., 2., 2., 5., 5.|], ys: [|1., 1., 2., 2., 3.|]};
+
+let toStepwise = (xyShape: xyShape) => {};
+
 type interpolationMethod = [ | `Stepwise | `Linear];
 
 type continuousShape = {

src/core/GenericDistribution.re

@@ -15,8 +15,7 @@ let make =
   unit,
 };
 
-let toComplexPower =
+let toComplexPower = (~sampleCount, t: genericDistribution) => {
-    (~sampleCount, t: genericDistribution): option(complexPower) => {
   let shape =
     switch (t.generationSource) {
     | GuesstimatorString(s) =>

src/core/XYShape.re

@@ -19,8 +19,24 @@ let zip = t => Belt.Array.zip(t.xs, t.ys);
 
 let fmap = (t: t, y): t => {xs: t.xs, ys: t.ys |> E.A.fmap(y)};
 
+let fromArray = ((xs, ys)): t => {xs, ys};
+let fromArrays = (xs, ys): t => {xs, ys};
 let pointwiseMap = (fn, t: t): t => {xs: t.xs, ys: t.ys |> E.A.fmap(fn)};
 
+let intersperce = (t1: t, t2: t) => {
+  let foo: ref(array((float, float))) = ref([||]);
+  let t1 = zip(t1);
+  let t2 = zip(t2);
+
+  Belt.Array.forEachWithIndex(t1, (i, item) => {
+    switch (Belt.Array.get(t2, i)) {
+    | Some(r) => foo := E.A.append(foo^, [|item, r|])
+    | None => foo := E.A.append(foo^, [|item|])
+    }
+  });
+  foo^ |> Belt.Array.unzip |> fromArray;
+};
+
 let scaleCdfTo = (~scaleTo=1., t: t) =>
   switch (_lastElement(t.ys)) {
   | Some(n) =>
@@ -35,9 +51,6 @@ let yFold = (fn, t: t) => {
 
 let ySum = yFold((a, b) => a +. b);
 
-let fromArray = ((xs, ys)): t => {xs, ys};
-let fromArrays = (xs, ys): t => {xs, ys};
-
 let _transverse = fn =>
   Belt.Array.reduce(_, [||], (items, (x, y)) =>
     switch (_lastElement(items)) {
@@ -68,6 +81,12 @@ module Range = {
   let rangeAreaAssumingSteps = (((lastX, lastY), (nextX, _)): zippedRange) =>
     (nextX -. lastX) *. lastY;
 
+  let rangePointAssumingSteps =
+      (((lastX, lastY), (nextX, nextY)): zippedRange) => (
+    nextX,
+    lastY,
+  );
+
   let rangeAreaAssumingTriangles =
       (((lastX, lastY), (nextX, nextY)): zippedRange) =>
     (nextX -. lastX) *. (lastY +. nextY) /. 2.;
@@ -93,6 +112,15 @@ module Range = {
     |> E.O.fmap(accumulateYs);
 
   let derivative = mapYsBasedOnRanges(delta_y_over_delta_x);
+
+  let stepsToContinuous = t =>
+    Belt.Array.zip(t.xs, t.ys)
+    |> E.A.toRanges
+    |> E.R.toOption
+    |> E.O.fmap(r => r |> Belt.Array.map(_, rangePointAssumingSteps))
+    |> E.O.fmap(Belt.Array.unzip)
+    |> E.O.fmap(fromArray)
+    |> E.O.fmap(intersperce(t));
 };
 
 let findY = CdfLibrary.Distribution.findY;