Merge pull request #68 from foretold-app/variable-test

Adds simple variables and functions

__tests__/Samples__test.re

@@ -14,12 +14,12 @@ describe("Lodash", () => {
   describe("Lodash", () => {
     makeTest(
       "split",
-      Samples.T.splitContinuousAndDiscrete([|1.432, 1.33455, 2.0|]),
+      SamplesToShape.Internals.T.splitContinuousAndDiscrete([|1.432, 1.33455, 2.0|]),
       ([|1.432, 1.33455, 2.0|], E.FloatFloatMap.empty()),
     );
     makeTest(
       "split",
-      Samples.T.splitContinuousAndDiscrete([|
+      SamplesToShape.Internals.T.splitContinuousAndDiscrete([|
         1.432,
         1.33455,
         2.0,
@@ -39,12 +39,12 @@ describe("Lodash", () => {
     };
 
     let (_, discrete) =
-      Samples.T.splitContinuousAndDiscrete(makeDuplicatedArray(10));
+      SamplesToShape.Internals.T.splitContinuousAndDiscrete(makeDuplicatedArray(10));
     let toArr = discrete |> E.FloatFloatMap.toArray;
     makeTest("splitMedium", toArr |> Belt.Array.length, 10);
 
     let (c, discrete) =
-      Samples.T.splitContinuousAndDiscrete(makeDuplicatedArray(500));
+      SamplesToShape.Internals.T.splitContinuousAndDiscrete(makeDuplicatedArray(500));
     let toArr = discrete |> E.FloatFloatMap.toArray;
     makeTest("splitMedium", toArr |> Belt.Array.length, 500);
   })

showcase/entries/Continuous2.re

@@ -6,18 +6,18 @@
 // uniform(0,1) > 0.3 ? lognormal(6.652, -0.41): 0
 
 let timeDist ={
-  let ingredients = RenderTypes.DistPlusRenderer.Ingredients.make(
+  let ingredients = DistPlusRenderer.Inputs.Ingredients.make(
     ~guesstimatorString="(floor(10 to 15))",
     ~domain=RightLimited({xPoint: 50.0, excludingProbabilityMass: 0.3}),
     ~unit=
       DistTypes.TimeDistribution({zero: MomentRe.momentNow(), unit: `years}),
     ());
-  let inputs = RenderTypes.DistPlusRenderer.make(~distPlusIngredients=ingredients,())
+  let inputs = DistPlusRenderer.Inputs.make(~distPlusIngredients=ingredients,())
   inputs |> DistPlusRenderer.run
 }
 
 let setup = dist =>
-  RenderTypes.DistPlusRenderer.make(~distPlusIngredients=dist,())
+  DistPlusRenderer.Inputs.make(~distPlusIngredients=dist,())
   |> DistPlusRenderer.run
   |> E.R.fmap(distPlus => <DistPlusPlot distPlus />)
   |> E.R.toOption
@@ -28,7 +28,7 @@ let simpleExample = (name, guesstimatorString) =>
     <h3 className="text-gray-600 text-lg font-bold">
       {name |> ReasonReact.string}
     </h3>
-    {setup(RenderTypes.DistPlusRenderer.Ingredients.make(~guesstimatorString, ()))}
+    {setup(DistPlusRenderer.Inputs.Ingredients.make(~guesstimatorString, ()))}
   </>;
 
 let timeExample = (name, guesstimatorString) =>
@@ -37,7 +37,7 @@ let timeExample = (name, guesstimatorString) =>
       {name |> ReasonReact.string}
     </h3>
     {setup(
-       RenderTypes.DistPlusRenderer.Ingredients.make(
+       DistPlusRenderer.Inputs.Ingredients.make(
          ~guesstimatorString,
          ~unit=TimeDistribution({zero: MomentRe.momentNow(), unit: `years}),
          (),

showcase/entries/ExpressionTreeExamples.re

@@ -1,5 +1,5 @@
 let setup = dist =>
-  RenderTypes.DistPlusRenderer.make(~distPlusIngredients=dist, ())
+  DistPlusRenderer.Inputs.make(~distPlusIngredients=dist, ())
   |> DistPlusRenderer.run
   |> E.R.fmap(distPlus => <DistPlusPlot distPlus />)
   |> E.R.toOption
@@ -10,7 +10,7 @@ let simpleExample = (guesstimatorString, ~problem="", ()) =>
     <p> {guesstimatorString |> ReasonReact.string} </p>
     <p> {problem |> (e => "problem: " ++ e) |> ReasonReact.string} </p>
     {setup(
-       RenderTypes.DistPlusRenderer.Ingredients.make(~guesstimatorString, ()),
+       DistPlusRenderer.Inputs.Ingredients.make(~guesstimatorString, ()),
      )}
   </>;
 

src/components/DistBuilder.re

@@ -33,6 +33,23 @@ module Form = ReForm.Make(FormConfig);
 
 let schema = Form.Validation.Schema([||]);
 
+module FieldText = {
+  [@react.component]
+  let make = (~field, ~label) => {
+    <Form.Field
+      field
+      render={({handleChange, error, value, validate}) =>
+        <Antd.Form.Item label={label |> R.ste}>
+          <Antd.Input.TextArea
+            value
+            onChange={BsReform.Helpers.handleChange(handleChange)}
+            onBlur={_ => validate()}
+          />
+        </Antd.Form.Item>
+      }
+    />;
+  };
+};
 module FieldString = {
   [@react.component]
   let make = (~field, ~label) => {
@@ -111,13 +128,6 @@ module Styles = {
     ]);
 };
 
-type inputs = {
-  samplingInputs: RenderTypes.ShapeRenderer.Sampling.inputs,
-  guesstimatorString: string,
-  length: int,
-  shouldDownsampleSampledDistribution: int,
-};
-
 module DemoDist = {
   [@react.component]
   let make = (~guesstimatorString, ~domain, ~unit, ~options) => {
@@ -127,30 +137,34 @@ module DemoDist = {
         {switch (domain, unit, options) {
          | (Some(domain), Some(unit), Some(options)) =>
            let distPlusIngredients =
-             RenderTypes.DistPlusRenderer.Ingredients.make(
+             DistPlusRenderer.Inputs.Ingredients.make(
                ~guesstimatorString,
                ~domain,
                ~unit,
                (),
              );
-           let inputs =
+           let inputs1 =
-             RenderTypes.DistPlusRenderer.make(
+             DistPlusRenderer.Inputs.make(
                ~samplingInputs={
                  sampleCount: Some(options.sampleCount),
                  outputXYPoints: Some(options.outputXYPoints),
                  kernelWidth: options.kernelWidth,
+                 shapeLength: Some(options.downsampleTo |> E.O.default(1000))
                },
                ~distPlusIngredients,
-               ~shouldDownsample=options.downsampleTo |> E.O.isSome,
+               ~environment=
-               ~recommendedLength=options.downsampleTo |> E.O.default(1000),
+                 [|("p", `SymbolicDist(`Float(1.0)))|]
+                 ->Belt.Map.String.fromArray,
                (),
              );
-           let response = DistPlusRenderer.run(inputs);
+
-           switch (response) {
+           let response1 = DistPlusRenderer.run(inputs1);
-           | Ok(distPlus) =>
+           switch (response1) {
-             let normalizedDistPlus = DistPlus.T.normalize(distPlus);
+           | (Ok(distPlus1)) =>
-             <DistPlusPlot distPlus=normalizedDistPlus />;
+             <>
-           | Error(r) => r |> R.ste
+               <DistPlusPlot distPlus={DistPlus.T.normalize(distPlus1)} />
+             </>
+           | (Error(r)) => r |> R.ste
            };
          | _ =>
            "Nothing to show. Try to change the distribution description."
@@ -314,7 +328,7 @@ let make = () => {
         <Antd.Form onSubmit>
           <Row _type=`flex className=Styles.rows>
             <Col span=24>
-              <FieldString
+              <FieldText
                 field=FormConfig.GuesstimatorString
                 label="Guesstimator String"
               />

src/components/Drawer.re

@@ -392,8 +392,8 @@ module Draw = {
     let normal: SymbolicTypes.symbolicDist = `Normal({mean, stdev});
     let normalShape =
       ExpressionTree.toShape(
-        numSamples,
+        {sampleCount: 10000, outputXYPoints: 10000, kernelWidth: None, shapeLength:numSamples},
-        {sampleCount: 10000, outputXYPoints: 10000, kernelWidth: None},
+        ExpressionTypes.ExpressionTree.Environment.empty,
         `SymbolicDist(normal),
       ) |> E.R.toExn;
     let xyShape: Types.xyShape =

src/components/charts/DistPlusPlotReducer.re

@@ -106,7 +106,6 @@ let init = {
   showParams: false,
   showPercentiles: true,
   distributions: [
-    {yLog: false, xLog: false, isCumulative: false, height: 4},
+    {yLog: false, xLog: false, isCumulative: false, height: 1},
-    {yLog: false, xLog: false, isCumulative: true, height: 1},
   ],
 };

src/distPlus/distribution/AlgebraicShapeCombination.re

@@ -27,15 +27,15 @@ let toDiscretePointMassesFromTriangulars =
   let xsProdN1: array(float) = Belt.Array.makeUninitializedUnsafe(n - 1);
   let xsProdN2: array(float) = Belt.Array.makeUninitializedUnsafe(n - 2);
   for (i in 0 to n - 1) {
-     Belt.Array.set(xsSq, i, xs[i] *. xs[i]) |> ignore;
+    Belt.Array.set(xsSq, i, xs[i] *. xs[i]) |> ignore;
     ();
   };
   for (i in 0 to n - 2) {
-     Belt.Array.set(xsProdN1, i, xs[i] *. xs[i + 1]) |> ignore;
+    Belt.Array.set(xsProdN1, i, xs[i] *. xs[i + 1]) |> ignore;
     ();
   };
   for (i in 0 to n - 3) {
-     Belt.Array.set(xsProdN2, i, xs[i] *. xs[i + 2]) |> ignore;
+    Belt.Array.set(xsProdN2, i, xs[i] *. xs[i + 2]) |> ignore;
     ();
   };
   // means and variances
@@ -45,11 +45,8 @@ let toDiscretePointMassesFromTriangulars =
 
   if (inverse) {
     for (i in 1 to n - 2) {
-      Belt.Array.set(
+      Belt.Array.set(masses, i - 1, (xs[i + 1] -. xs[i - 1]) *. ys[i] /. 2.)
-        masses,
+      |> ignore;
-        i - 1,
-        (xs[i + 1] -. xs[i - 1]) *. ys[i] /. 2.,
-      ) |> ignore;
 
       // this only works when the whole triange is either on the left or on the right of zero
       let a = xs[i - 1];
@@ -70,9 +67,9 @@ let toDiscretePointMassesFromTriangulars =
         -. inverseMean
         ** 2.;
 
-       Belt.Array.set(means, i - 1, inverseMean) |> ignore;
+      Belt.Array.set(means, i - 1, inverseMean) |> ignore;
 
-       Belt.Array.set(variances, i - 1, inverseVar) |> ignore;
+      Belt.Array.set(variances, i - 1, inverseVar) |> ignore;
       ();
     };
 
@@ -80,14 +77,12 @@ let toDiscretePointMassesFromTriangulars =
   } else {
     for (i in 1 to n - 2) {
       // area of triangle = width * height / 2
-      Belt.Array.set(
+      Belt.Array.set(masses, i - 1, (xs[i + 1] -. xs[i - 1]) *. ys[i] /. 2.)
-        masses,
+      |> ignore;
-        i - 1,
-        (xs[i + 1] -. xs[i - 1]) *. ys[i] /. 2.,
-      ) |> ignore;
 
       // means of triangle = (a + b + c) / 3
-      Belt.Array.set(means, i - 1, (xs[i - 1] +. xs[i] +. xs[i + 1]) /. 3.) |> ignore;
+      Belt.Array.set(means, i - 1, (xs[i - 1] +. xs[i] +. xs[i + 1]) /. 3.)
+      |> ignore;
 
       // variance of triangle = (a^2 + b^2 + c^2 - ab - ac - bc) / 18
       Belt.Array.set(
@@ -102,7 +97,8 @@ let toDiscretePointMassesFromTriangulars =
           -. xsProdN2[i - 1]
         )
         /. 18.,
-      ) |> ignore;
+      )
+      |> ignore;
       ();
     };
     {n: n - 2, masses, means, variances};
@@ -134,8 +130,10 @@ let combineShapesContinuousContinuous =
     | `Subtract => ((m1, m2) => m1 -. m2)
     | `Multiply => ((m1, m2) => m1 *. m2)
     | `Divide => ((m1, mInv2) => m1 *. mInv2)
+    | `Exponentiate => ((m1, mInv2) => m1 ** mInv2)
     }; // note: here, mInv2 = mean(1 / t2) ~= 1 / mean(t2)
 
+  // TODO: I don't know what the variances are for exponentatiation
   // converts the variances and means of the two inputs into the variance of the output
   let combineVariancesFn =
     switch (op) {
@@ -144,6 +142,8 @@ let combineShapesContinuousContinuous =
     | `Multiply => (
         (v1, v2, m1, m2) => v1 *. v2 +. v1 *. m2 ** 2. +. v2 *. m1 ** 2.
       )
+    | `Exponentiate =>
+      ((v1, v2, m1, m2) => v1 *. v2 +. v1 *. m2 ** 2. +. v2 *. m1 ** 2.);
     | `Divide => (
         (v1, vInv2, m1, mInv2) =>
           v1 *. vInv2 +. v1 *. mInv2 ** 2. +. vInv2 *. m1 ** 2.
@@ -225,9 +225,12 @@ let toDiscretePointMassesFromDiscrete =
 };
 
 let combineShapesContinuousDiscrete =
-    (op: ExpressionTypes.algebraicOperation, continuousShape: DistTypes.xyShape, discreteShape: DistTypes.xyShape)
+    (
+      op: ExpressionTypes.algebraicOperation,
+      continuousShape: DistTypes.xyShape,
+      discreteShape: DistTypes.xyShape,
+    )
     : DistTypes.xyShape => {
-
   let t1n = continuousShape |> XYShape.T.length;
   let t2n = discreteShape |> XYShape.T.length;
 
@@ -248,15 +251,19 @@ let combineShapesContinuousDiscrete =
         Belt.Array.set(
           dxyShape,
           i,
-          (fn(continuousShape.xs[i], discreteShape.xs[j]),
+          (
-          continuousShape.ys[i] *. discreteShape.ys[j]),
+            fn(continuousShape.xs[i], discreteShape.xs[j]),
-        ) |> ignore;
+            continuousShape.ys[i] *. discreteShape.ys[j],
+          ),
+        )
+        |> ignore;
         ();
       };
       Belt.Array.set(outXYShapes, j, dxyShape) |> ignore;
       ();
     }
   | `Multiply
+  | `Exponentiate
   | `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.
@@ -266,8 +273,12 @@ let combineShapesContinuousDiscrete =
         Belt.Array.set(
           dxyShape,
           i,
-          (fn(continuousShape.xs[i], discreteShape.xs[j]), continuousShape.ys[i] *. discreteShape.ys[j] /. discreteShape.xs[j]),
+          (
-        ) |> ignore;
+            fn(continuousShape.xs[i], discreteShape.xs[j]),
+            {continuousShape.ys[i] *. discreteShape.ys[j] /. discreteShape.xs[j]}
+          ),
+        )
+        |> ignore;
         ();
       };
       Belt.Array.set(outXYShapes, j, dxyShape) |> ignore;
@@ -278,7 +289,10 @@ let combineShapesContinuousDiscrete =
   outXYShapes
   |> E.A.fmap(XYShape.T.fromZippedArray)
   |> E.A.fold_left(
-      XYShape.PointwiseCombination.combine((+.),
+       XYShape.PointwiseCombination.combine(
-                                           XYShape.XtoY.continuousInterpolator(`Linear, `UseZero)),
+         (+.),
-      XYShape.T.empty);
+         XYShape.XtoY.continuousInterpolator(`Linear, `UseZero),
+       ),
+       XYShape.T.empty,
+     );
 };

src/distPlus/distribution/Continuous.re

@@ -37,6 +37,7 @@ let empty: DistTypes.continuousShape = {
 let stepwiseToLinear = (t: t): t =>
   make(~integralSumCache=t.integralSumCache, ~integralCache=t.integralCache, XYShape.Range.stepwiseToLinear(t.xyShape));
 
+// Note: This results in a distribution with as many points as the sum of those in t1 and t2.
 let combinePointwise =
     (
       ~integralSumCachesFn=(_, _) => None,

src/distPlus/distribution/Shape.re

@@ -216,6 +216,11 @@ let sample = (t: t): float => {
   bar;
 };
 
+let isFloat = (t:t) => switch(t){
+| Discrete({xyShape: {xs: [|_|], ys: [|1.0|]}}) => true
+| _ => false
+}
+
 let sampleNRendered = (n, dist) => {
   let integralCache = T.Integral.get(dist);
   let distWithUpdatedIntegralCache = T.updateIntegralCache(Some(integralCache), dist);

src/distPlus/expressionTree/ExpressionTree.re

@@ -1,13 +1,17 @@
 open ExpressionTypes.ExpressionTree;
 
-let toShape = (intendedShapeLength: int, samplingInputs, node: node) => {
+let toLeaf = (samplingInputs, environment, node: node) => {
+  node
+  |> ExpressionTreeEvaluator.toLeaf({
+       samplingInputs,
+       environment,
+       evaluateNode: ExpressionTreeEvaluator.toLeaf,
+     });
+};
+
+let toShape = (samplingInputs, environment, node: node) => {
   let renderResult =
-    `Render(`Normalize(node))
+    `Render(`Normalize(node)) |> toLeaf(samplingInputs, environment);
-    |> ExpressionTreeEvaluator.toLeaf({
-         samplingInputs,
-         intendedShapeLength,
-         evaluateNode: ExpressionTreeEvaluator.toLeaf,
-       });
 
   switch (renderResult) {
   | Ok(`RenderedDist(shape)) => Ok(shape)

src/distPlus/expressionTree/ExpressionTreeEvaluator.re

@@ -151,7 +151,7 @@ module PointwiseCombination = {
     };
   };
 
-  let pointwiseMultiply = (evaluationParams: evaluationParams, t1: t, t2: t) => {
+  let pointwiseCombine = (fn, evaluationParams: evaluationParams, t1: t, t2: t) => {
     // TODO: construct a function that we can easily sample from, to construct
     // a RenderedDist. Use the xMin and xMax of the rendered shapes to tell the sampling function where to look.
     // TODO: This should work for symbolic distributions too!
@@ -176,7 +176,8 @@ module PointwiseCombination = {
       ) => {
     switch (pointwiseOp) {
     | `Add => pointwiseAdd(evaluationParams, t1, t2)
-    | `Multiply => pointwiseMultiply(evaluationParams, t1, t2)
+    | `Multiply => pointwiseCombine(( *. ),evaluationParams, t1, t2)
+    | `Exponentiate => pointwiseCombine(( *. ),evaluationParams, t1, t2)
     };
   };
 };
@@ -259,14 +260,27 @@ module FloatFromDist = {
   };
 };
 
+// TODO: This forces things to be floats
+let callableFunction = (evaluationParams, name, args) => {
+  let b =
+    args
+    |> E.A.fmap(a =>
+         Render.render(evaluationParams, a)
+         |> E.R.bind(_, Render.toFloat)
+       )
+    |> E.A.R.firstErrorOrOpen;
+  b |> E.R.bind(_, Functions.fnn(evaluationParams, name));
+};
+
 module Render = {
   let rec operationToLeaf =
           (evaluationParams: evaluationParams, t: node): result(t, string) => {
     switch (t) {
+    | `Function(_) => Error("Cannot render a function")
     | `SymbolicDist(d) =>
       Ok(
         `RenderedDist(
-          SymbolicDist.T.toShape(evaluationParams.intendedShapeLength, d),
+          SymbolicDist.T.toShape(evaluationParams.samplingInputs.shapeLength, d),
         ),
       )
     | `RenderedDist(_) as t => Ok(t) // already a rendered shape, we're done here
@@ -275,6 +289,13 @@ module Render = {
   };
 };
 
+let run = (node, fnNode) => {
+  switch (fnNode) {
+  | `Function(r) => Ok(r(node))
+  | _ => Error("Not a function")
+  };
+};
+
 /* This function recursively goes through the nodes of the parse tree,
    replacing each Operation node and its subtree with a Data node.
    Whenever possible, the replacement produces a new Symbolic Data node,
@@ -314,5 +335,9 @@ let toLeaf =
     FloatFromDist.operationToLeaf(evaluationParams, distToFloatOp, t)
   | `Normalize(t) => Normalize.operationToLeaf(evaluationParams, t)
   | `Render(t) => Render.operationToLeaf(evaluationParams, t)
+  | `Function(t) => Ok(`Function(t))
+  | `Symbol(r) => ExpressionTypes.ExpressionTree.Environment.get(evaluationParams.environment, r) |> E.O.toResult("Undeclared variable " ++ r)
+  | `FunctionCall(name, args) =>
+    callableFunction(evaluationParams, name, args)
   };
 };

src/distPlus/expressionTree/ExpressionTypes.re

@@ -1,5 +1,5 @@
-type algebraicOperation = [ | `Add | `Multiply | `Subtract | `Divide];
+type algebraicOperation = [ | `Add | `Multiply | `Subtract | `Divide | `Exponentiate];
-type pointwiseOperation = [ | `Add | `Multiply];
+type pointwiseOperation = [ | `Add | `Multiply | `Exponentiate];
 type scaleOperation = [ | `Multiply | `Exponentiate | `Log];
 type distToFloatOperation = [
   | `Pdf(float)
@@ -20,17 +20,37 @@ module ExpressionTree = {
     | `Truncate(option(float), option(float), node)
     | `Normalize(node)
     | `FloatFromDist(distToFloatOperation, node)
+    | `Function(array(string), node)
+    | `FunctionCall(string, array(node))
+    | `Symbol(string)
   ];
 
   type samplingInputs = {
     sampleCount: int,
     outputXYPoints: int,
     kernelWidth: option(float),
+    shapeLength: int
   };
 
+  type environment = Belt.Map.String.t(node);
+
+  module Environment = {
+    type t = environment
+    module MS = Belt.Map.String;
+    let fromArray = MS.fromArray
+    let empty:t = [||]->fromArray;
+    let mergeKeepSecond = (a:t,b:t) => MS.merge(a,b, (_,a,b) =>switch(a,b){
+      | (_, Some(b)) => Some(b)
+      | (Some(a), _) => Some(a)
+      | _ => None
+    })
+    let update = (t,str, fn) => MS.update(t, str, fn)
+    let get = (t:t,str) => MS.get(t, str)
+  }
+
   type evaluationParams = {
     samplingInputs,
-    intendedShapeLength: int,
+    environment,
     evaluateNode: (evaluationParams, node) => Belt.Result.t(node, string),
   };
 
@@ -71,8 +91,20 @@ module ExpressionTree = {
       | `RenderedDist(r) => Some(r)
       | _ => None
       };
-  };
 
+    let _toFloat = (t: DistTypes.shape) =>
+      switch (t) {
+      | Discrete({xyShape: {xs: [|x|], ys: [|1.0|]}}) =>
+        Some(`SymbolicDist(`Float(x)))
+      | _ => None
+      };
+
+    let toFloat = (item: node): result(node, string) =>
+      item
+      |> getShape
+      |> E.O.bind(_, _toFloat)
+      |> E.O.toResult("Not valid shape");
+  };
 };
 
 type simplificationResult = [
@@ -80,3 +112,8 @@ type simplificationResult = [
   | `Error(string)
   | `NoSolution
 ];
+
+module Program = {
+  type statement = [ | `Assignment(string, ExpressionTree.node) | `Expression(ExpressionTree.node)];
+  type program = array(statement);
+}

src/distPlus/expressionTree/Functions.re

@@ -0,0 +1,122 @@
+type node = ExpressionTypes.ExpressionTree.node;
+
+let toOkSym = r => Ok(`SymbolicDist(r));
+
+let twoFloats = (fn, n1: node, n2: node): result(node, string) =>
+  switch (n1, n2) {
+  | (`SymbolicDist(`Float(a)), `SymbolicDist(`Float(b))) => fn(a, b)
+  | _ => Error("Variables have wrong type")
+  };
+
+let threeFloats = (fn, n1: node, n2: node, n3: node): result(node, string) =>
+  switch (n1, n2, n3) {
+  | (
+      `SymbolicDist(`Float(a)),
+      `SymbolicDist(`Float(b)),
+      `SymbolicDist(`Float(c)),
+    ) =>
+    fn(a, b, c)
+  | _ => Error("Variables have wrong type")
+  };
+
+let twoFloatsToOkSym = fn => twoFloats((f1, f2) => fn(f1, f2) |> toOkSym);
+
+let threeFloats = fn => threeFloats((f1, f2, f3) => fn(f1, f2, f3));
+
+let apply2 = (fn, args): result(node, string) =>
+  switch (args) {
+  | [|a, b|] => fn(a, b)
+  | _ => Error("Needs 2 args")
+  };
+
+let apply3 = (fn, args: array(node)): result(node, string) =>
+  switch (args) {
+  | [|a, b, c|] => fn(a, b, c)
+  | _ => Error("Needs 3 args")
+  };
+
+let to_: array(node) => result(node, string) =
+  fun
+  | [|`SymbolicDist(`Float(low)), `SymbolicDist(`Float(high))|]
+      when low <= 0.0 && low < high => {
+      Ok(`SymbolicDist(SymbolicDist.Normal.from90PercentCI(low, high)));
+    }
+  | [|`SymbolicDist(`Float(low)), `SymbolicDist(`Float(high))|]
+      when low < high => {
+      Ok(`SymbolicDist(SymbolicDist.Lognormal.from90PercentCI(low, high)));
+    }
+  | [|`SymbolicDist(`Float(_)), `SymbolicDist(_)|] =>
+    Error("Low value must be less than high value.")
+  | _ => Error("Requires 2 variables");
+
+let processCustomFn =
+    (
+      evaluationParams: ExpressionTypes.ExpressionTree.evaluationParams,
+      args: array(node),
+      argNames: array(string),
+      fnResult: node,
+    ) =>
+  if (E.A.length(args) == E.A.length(argNames)) {
+    let newEnvironment =
+      Belt.Array.zip(argNames, args)
+      |> ExpressionTypes.ExpressionTree.Environment.fromArray;
+    let newEvaluationParams: ExpressionTypes.ExpressionTree.evaluationParams = {
+      samplingInputs: evaluationParams.samplingInputs,
+      environment:
+        ExpressionTypes.ExpressionTree.Environment.mergeKeepSecond(
+          evaluationParams.environment,
+          newEnvironment,
+        ),
+      evaluateNode: evaluationParams.evaluateNode,
+    };
+    evaluationParams.evaluateNode(newEvaluationParams, fnResult);
+  } else {
+    Error("Failure");
+  };
+
+let fnn =
+    (
+      evaluationParams: ExpressionTypes.ExpressionTree.evaluationParams,
+      name,
+      args: array(node),
+    ) =>
+  switch (
+    name,
+    ExpressionTypes.ExpressionTree.Environment.get(
+      evaluationParams.environment,
+      name,
+    ),
+  ) {
+  | (_, Some(`Function(argNames, tt))) =>
+    processCustomFn(evaluationParams, args, argNames, tt)
+  | ("normal", _) =>
+    apply2(twoFloatsToOkSym(SymbolicDist.Normal.make), args)
+  | ("uniform", _) =>
+    apply2(twoFloatsToOkSym(SymbolicDist.Uniform.make), args)
+  | ("beta", _) => apply2(twoFloatsToOkSym(SymbolicDist.Beta.make), args)
+  | ("cauchy", _) =>
+    apply2(twoFloatsToOkSym(SymbolicDist.Cauchy.make), args)
+  | ("lognormal", _) =>
+    apply2(twoFloatsToOkSym(SymbolicDist.Lognormal.make), args)
+  | ("lognormalFromMeanAndStdDev", _) =>
+    apply2(twoFloatsToOkSym(SymbolicDist.Lognormal.fromMeanAndStdev), args)
+  | ("exponential", _) =>
+    switch (args) {
+    | [|`SymbolicDist(`Float(a))|] =>
+      Ok(`SymbolicDist(SymbolicDist.Exponential.make(a)))
+    | _ => Error("Needs 3 valid arguments")
+    }
+  | ("triangular", _) =>
+    switch (args) {
+    | [|
+        `SymbolicDist(`Float(a)),
+        `SymbolicDist(`Float(b)),
+        `SymbolicDist(`Float(c)),
+      |] =>
+      SymbolicDist.Triangular.make(a, b, c)
+      |> E.R.fmap(r => `SymbolicDist(r))
+    | _ => Error("Needs 3 valid arguments")
+    }
+  | ("to", _) => to_(args)
+  | _ => Error("Function not found")
+  };

src/distPlus/expressionTree/MathJsParser.re

@@ -4,10 +4,18 @@ module MathJsonToMathJsAdt = {
     | Value(float)
     | Fn(fn)
     | Array(array(arg))
+    | Blocks(array(arg))
     | Object(Js.Dict.t(arg))
+    | Assignment(arg, arg)
+    | FunctionAssignment(fnAssignment)
   and fn = {
     name: string,
     args: array(arg),
+  }
+  and fnAssignment = {
+    name: string,
+    args: array(string),
+    expression: arg,
   };
 
   let rec run = (j: Js.Json.t) =>
@@ -40,6 +48,25 @@ module MathJsonToMathJsAdt = {
         let items = field("items", array(run), j);
         Some(Array(items |> E.A.O.concatSomes));
       | "SymbolNode" => Some(Symbol(field("name", string, j)))
+      | "AssignmentNode" =>
+        let object_ = j |> field("object", run);
+        let value_ = j |> field("value", run);
+        switch (object_, value_) {
+        | (Some(o), Some(v)) => Some(Assignment(o, v))
+        | _ => None
+        };
+      | "BlockNode" =>
+        let block = r => r |> field("node", run);
+        let args = j |> field("blocks", array(block)) |> E.A.O.concatSomes;
+        Some(Blocks(args));
+      | "FunctionAssignmentNode" =>
+        let name = j |> field("name", string);
+        let args = j |> field("params", array(field("name", string)));
+        let expression = j |> field("expr", run);
+        expression
+        |> E.O.fmap(expression =>
+             FunctionAssignment({name, args, expression})
+           );
       | n =>
         Js.log3("Couldn't parse mathjs node", j, n);
         None;
@@ -50,29 +77,37 @@ module MathJsonToMathJsAdt = {
 module MathAdtToDistDst = {
   open MathJsonToMathJsAdt;
 
+  let handleSymbol = sym => {
+    Ok(`Symbol(sym));
+  };
+
   module MathAdtCleaner = {
     let transformWithSymbol = (f: float, s: string) =>
       switch (s) {
       | "K"
-      | "k" => f *. 1000.
+      | "k" => Some(f *. 1000.)
       | "M"
-      | "m" => f *. 1000000.
+      | "m" => Some(f *. 1000000.)
       | "B"
-      | "b" => f *. 1000000000.
+      | "b" => Some(f *. 1000000000.)
       | "T"
-      | "t" => f *. 1000000000000.
+      | "t" => Some(f *. 1000000000000.)
-      | _ => f
+      | _ => None
       };
-
     let rec run =
       fun
-      | Fn({name: "multiply", args: [|Value(f), Symbol(s)|]}) =>
+      | Fn({name: "multiply", args: [|Value(f), Symbol(s)|]}) as doNothing =>
-        Value(transformWithSymbol(f, s))
+        transformWithSymbol(f, s)
+        |> E.O.fmap(r => Value(r))
+        |> E.O.default(doNothing)
       | Fn({name: "unaryMinus", args: [|Value(f)|]}) => Value((-1.0) *. f)
       | Fn({name, args}) => Fn({name, args: args |> E.A.fmap(run)})
       | Array(args) => Array(args |> E.A.fmap(run))
       | Symbol(s) => Symbol(s)
       | Value(v) => Value(v)
+      | Blocks(args) => Blocks(args |> E.A.fmap(run))
+      | Assignment(a, b) => Assignment(a, run(b))
+      | FunctionAssignment(a) => FunctionAssignment(a)
       | Object(v) =>
         Object(
           v
@@ -82,83 +117,31 @@ module MathAdtToDistDst = {
         );
   };
 
-  let normal:
+  let lognormal = (args, parseArgs, nodeParser) =>
-    array(arg) => result(ExpressionTypes.ExpressionTree.node, string) =
+    switch (args) {
-    fun
+    | [|Object(o)|] =>
-    | [|Value(mean), Value(stdev)|] =>
+      let g = s =>
-      Ok(`SymbolicDist(`Normal({mean, stdev})))
+        Js.Dict.get(o, s)
-    | _ => Error("Wrong number of variables in normal distribution");
+        |> E.O.toResult("Variable was empty")
-
+        |> E.R.bind(_, nodeParser);
-  let lognormal:
+      switch (g("mean"), g("stdev"), g("mu"), g("sigma")) {
-    array(arg) => result(ExpressionTypes.ExpressionTree.node, string) =
+      | (Ok(mean), Ok(stdev), _, _) =>
-    fun
-    | [|Value(mu), Value(sigma)|] =>
-      Ok(`SymbolicDist(`Lognormal({mu, sigma})))
-    | [|Object(o)|] => {
-        let g = Js.Dict.get(o);
-        switch (g("mean"), g("stdev"), g("mu"), g("sigma")) {
-        | (Some(Value(mean)), Some(Value(stdev)), _, _) =>
-          Ok(
-            `SymbolicDist(
-              SymbolicDist.Lognormal.fromMeanAndStdev(mean, stdev),
-            ),
-          )
-        | (_, _, Some(Value(mu)), Some(Value(sigma))) =>
-          Ok(`SymbolicDist(`Lognormal({mu, sigma})))
-        | _ => Error("Lognormal distribution would need mean and stdev")
-        };
-      }
-    | _ => Error("Wrong number of variables in lognormal distribution");
-
-  let to_: array(arg) => result(ExpressionTypes.ExpressionTree.node, string) =
-    fun
-    | [|Value(low), Value(high)|] when low <= 0.0 && low < high => {
-        Ok(`SymbolicDist(SymbolicDist.Normal.from90PercentCI(low, high)));
-      }
-    | [|Value(low), Value(high)|] when low < high => {
         Ok(
-          `SymbolicDist(SymbolicDist.Lognormal.from90PercentCI(low, high)),
+          `FunctionCall(("lognormalFromMeanAndStdDev", [|mean, stdev|])),
-        );
+        )
-      }
+      | (_, _, Ok(mu), Ok(sigma)) =>
-    | [|Value(_), Value(_)|] =>
+        Ok(`FunctionCall(("lognormal", [|mu, sigma|])))
-      Error("Low value must be less than high value.")
+      | _ =>
-    | _ => Error("Wrong number of variables in lognormal distribution");
+        Error(
-
+          "Lognormal distribution needs either mean and stdev or mu and sigma",
-  let uniform:
+        )
-    array(arg) => result(ExpressionTypes.ExpressionTree.node, string) =
+      };
-    fun
+    | _ =>
-    | [|Value(low), Value(high)|] =>
+      parseArgs()
-      Ok(`SymbolicDist(`Uniform({low, high})))
+      |> E.R.fmap((args: array(ExpressionTypes.ExpressionTree.node)) =>
-    | _ => Error("Wrong number of variables in lognormal distribution");
+           `FunctionCall(("lognormal", args))
-
+         )
-  let beta: array(arg) => result(ExpressionTypes.ExpressionTree.node, string) =
+    };
-    fun
-    | [|Value(alpha), Value(beta)|] =>
-      Ok(`SymbolicDist(`Beta({alpha, beta})))
-    | _ => Error("Wrong number of variables in lognormal distribution");
-
-  let exponential:
-    array(arg) => result(ExpressionTypes.ExpressionTree.node, string) =
-    fun
-    | [|Value(rate)|] => Ok(`SymbolicDist(`Exponential({rate: rate})))
-    | _ => Error("Wrong number of variables in Exponential distribution");
-
-  let cauchy:
-    array(arg) => result(ExpressionTypes.ExpressionTree.node, string) =
-    fun
-    | [|Value(local), Value(scale)|] =>
-      Ok(`SymbolicDist(`Cauchy({local, scale})))
-    | _ => Error("Wrong number of variables in cauchy distribution");
-
-  let triangular:
-    array(arg) => result(ExpressionTypes.ExpressionTree.node, string) =
-    fun
-    | [|Value(low), Value(medium), Value(high)|]
-        when low < medium && medium < high =>
-      Ok(`SymbolicDist(`Triangular({low, medium, high})))
-    | [|Value(_), Value(_), Value(_)|] =>
-      Error("Triangular values must be increasing order")
-    | _ => Error("Wrong number of variables in triangle distribution");
 
   let multiModal =
       (
@@ -166,15 +149,6 @@ module MathAdtToDistDst = {
         weights: option(array(float)),
       ) => {
     let weights = weights |> E.O.default([||]);
-
-    /*let dists:  =
-      args
-      |> E.A.fmap(
-           fun
-          | Ok(a) => a
-          | Error(e) => Error(e)
-          );*/
-
     let firstWithError = args |> Belt.Array.getBy(_, Belt.Result.isError);
     let withoutErrors = args |> E.A.fmap(E.R.toOption) |> E.A.O.concatSomes;
 
@@ -203,101 +177,75 @@ module MathAdtToDistDst = {
     };
   };
 
-  // let arrayParser =
+          //  Error("Dotwise exponentiation needs two operands")
-  //     (args: array(arg))
-  //     : result(ExpressionTypes.ExpressionTree.node, string) => {
-  //   let samples =
-  //     args
-  //     |> E.A.fmap(
-  //          fun
-  //          | Value(n) => Some(n)
-  //          | _ => None,
-  //        )
-  //     |> E.A.O.concatSomes;
-  //   let outputs = Samples.T.fromSamples(samples);
-  //   let pdf =
-  //     outputs.shape |> E.O.bind(_, Shape.T.toContinuous);
-  //   let shape =
-  //     pdf
-  //     |> E.O.fmap(pdf => {
-  //          let _pdf = Continuous.T.normalize(pdf);
-  //          let cdf = Continuous.T.integral(~cache=None, _pdf);
-  //          SymbolicDist.ContinuousShape.make(_pdf, cdf);
-  //        });
-  //   switch (shape) {
-  //   | Some(s) => Ok(`SymbolicDist(`ContinuousShape(s)))
-  //   | None => Error("Rendering did not work")
-  //   };
-  // };
-
   let operationParser =
       (
         name: string,
-        args: array(result(ExpressionTypes.ExpressionTree.node, string)),
+        args: result(array(ExpressionTypes.ExpressionTree.node), string),
-      ) => {
+      ):result(ExpressionTypes.ExpressionTree.node,string) => {
     let toOkAlgebraic = r => Ok(`AlgebraicCombination(r));
     let toOkPointwise = r => Ok(`PointwiseCombination(r));
     let toOkTruncate = r => Ok(`Truncate(r));
     let toOkFloatFromDist = r => Ok(`FloatFromDist(r));
-    switch (name, args) {
+    args
-    | ("add", [|Ok(l), Ok(r)|]) => toOkAlgebraic((`Add, l, r))
+    |> E.R.bind(_, args => {
-    | ("add", _) => Error("Addition needs two operands")
+         switch (name, args) {
-    | ("subtract", [|Ok(l), Ok(r)|]) => toOkAlgebraic((`Subtract, l, r))
+         | ("add", [|l, r|]) => toOkAlgebraic((`Add, l, r))
-    | ("subtract", _) => Error("Subtraction needs two operands")
+         | ("add", _) => Error("Addition needs two operands")
-    | ("multiply", [|Ok(l), Ok(r)|]) => toOkAlgebraic((`Multiply, l, r))
+         | ("subtract", [|l, r|]) => toOkAlgebraic((`Subtract, l, r))
-    | ("multiply", _) => Error("Multiplication needs two operands")
+         | ("subtract", _) => Error("Subtraction needs two operands")
-    | ("dotMultiply", [|Ok(l), Ok(r)|]) => toOkPointwise((`Multiply, l, r))
+         | ("multiply", [|l, r|]) => toOkAlgebraic((`Multiply, l, r))
-    | ("dotMultiply", _) =>
+         | ("multiply", _) => Error("Multiplication needs two operands")
-      Error("Dotwise multiplication needs two operands")
+         | ("pow", [|l,r|]) => toOkAlgebraic((`Exponentiate, l, r))
-    | ("rightLogShift", [|Ok(l), Ok(r)|]) => toOkPointwise((`Add, l, r))
+         | ("pow", _) => Error("Exponentiation needs two operands")
-    | ("rightLogShift", _) => Error("Dotwise addition needs two operands")
+         | ("dotMultiply", [|l, r|]) => toOkPointwise((`Multiply, l, r))
-    | ("divide", [|Ok(l), Ok(r)|]) => toOkAlgebraic((`Divide, l, r))
+         | ("dotMultiply", _) =>
-    | ("divide", _) => Error("Division needs two operands")
+           Error("Dotwise multiplication needs two operands")
-    | ("pow", _) => Error("Exponentiation is not yet supported.")
+         | ("rightLogShift", [|l, r|]) => toOkPointwise((`Add, l, r))
-    | ("leftTruncate", [|Ok(d), Ok(`SymbolicDist(`Float(lc)))|]) =>
+         | ("rightLogShift", _) =>
-      toOkTruncate((Some(lc), None, d))
+           Error("Dotwise addition needs two operands")
-    | ("leftTruncate", _) =>
+         | ("divide", [|l, r|]) => toOkAlgebraic((`Divide, l, r))
-      Error("leftTruncate needs two arguments: the expression and the cutoff")
+         | ("divide", _) => Error("Division needs two operands")
-    | ("rightTruncate", [|Ok(d), Ok(`SymbolicDist(`Float(rc)))|]) =>
+         | ("leftTruncate", [|d, `SymbolicDist(`Float(lc))|]) =>
-      toOkTruncate((None, Some(rc), d))
+           toOkTruncate((Some(lc), None, d))
-    | ("rightTruncate", _) =>
+         | ("leftTruncate", _) =>
-      Error(
+           Error(
-        "rightTruncate needs two arguments: the expression and the cutoff",
+             "leftTruncate needs two arguments: the expression and the cutoff",
-      )
+           )
-    | (
+         | ("rightTruncate", [|d, `SymbolicDist(`Float(rc))|]) =>
-        "truncate",
+           toOkTruncate((None, Some(rc), d))
-        [|
+         | ("rightTruncate", _) =>
-          Ok(d),
+           Error(
-          Ok(`SymbolicDist(`Float(lc))),
+             "rightTruncate needs two arguments: the expression and the cutoff",
-          Ok(`SymbolicDist(`Float(rc))),
+           )
-        |],
+         | (
-      ) =>
+             "truncate",
-      toOkTruncate((Some(lc), Some(rc), d))
+             [|d, `SymbolicDist(`Float(lc)), `SymbolicDist(`Float(rc))|],
-    | ("truncate", _) =>
+           ) =>
-      Error("truncate needs three arguments: the expression and both cutoffs")
+           toOkTruncate((Some(lc), Some(rc), d))
-    | ("pdf", [|Ok(d), Ok(`SymbolicDist(`Float(v)))|]) =>
+         | ("truncate", _) =>
-      toOkFloatFromDist((`Pdf(v), d))
+           Error(
-    | ("cdf", [|Ok(d), Ok(`SymbolicDist(`Float(v)))|]) =>
+             "truncate needs three arguments: the expression and both cutoffs",
-      toOkFloatFromDist((`Cdf(v), d))
+           )
-    | ("inv", [|Ok(d), Ok(`SymbolicDist(`Float(v)))|]) =>
+         | ("pdf", [|d, `SymbolicDist(`Float(v))|]) =>
-      toOkFloatFromDist((`Inv(v), d))
+           toOkFloatFromDist((`Pdf(v), d))
-    | ("mean", [|Ok(d)|]) => toOkFloatFromDist((`Mean, d))
+         | ("cdf", [|d, `SymbolicDist(`Float(v))|]) =>
-    | ("sample", [|Ok(d)|]) => toOkFloatFromDist((`Sample, d))
+           toOkFloatFromDist((`Cdf(v), d))
-    | _ => Error("This type not currently supported")
+         | ("inv", [|d, `SymbolicDist(`Float(v))|]) =>
-    };
+           toOkFloatFromDist((`Inv(v), d))
+         | ("mean", [|d|]) => toOkFloatFromDist((`Mean, d))
+         | ("sample", [|d|]) => toOkFloatFromDist((`Sample, d))
+         | _ => Error("This type not currently supported")
+         }
+       });
   };
 
   let functionParser = (nodeParser, name, args) => {
-    let parseArgs = () => args |> E.A.fmap(nodeParser);
+    let parseArray = ags =>
+      ags |> E.A.fmap(nodeParser) |> E.A.R.firstErrorOrOpen;
+    let parseArgs = () => parseArray(args);
     switch (name) {
-    | "normal" => normal(args)
+    | "lognormal" => lognormal(args, parseArgs, nodeParser)
-    | "lognormal" => lognormal(args)
-    | "uniform" => uniform(args)
-    | "beta" => beta(args)
-    | "to" => to_(args)
-    | "exponential" => exponential(args)
-    | "cauchy" => cauchy(args)
-    | "triangular" => triangular(args)
     | "mm" =>
       let weights =
         args
@@ -338,27 +286,55 @@ module MathAdtToDistDst = {
     | "sample"
     | "cdf"
     | "pdf" => operationParser(name, parseArgs())
-    | n => Error(n ++ "(...) is not currently supported")
+    | name =>
+      parseArgs()
+      |> E.R.fmap((args: array(ExpressionTypes.ExpressionTree.node)) =>
+           `FunctionCall((name, args))
+         )
     };
   };
 
-  let rec nodeParser =
+  let rec nodeParser:
+    MathJsonToMathJsAdt.arg =>
+    result(ExpressionTypes.ExpressionTree.node, string) =
     fun
     | Value(f) => Ok(`SymbolicDist(`Float(f)))
+    | Symbol(sym) => Ok(`Symbol(sym))
     | Fn({name, args}) => functionParser(nodeParser, name, args)
     | _ => {
-        Error("This type not currently supported");
+        Error("This type not currently supported")
       };
 
-  let topLevel =
+  // | FunctionAssignment({name, args, expression}) => {
-    fun
+  //   let evaluatedExpression = run(expression);
-    | Value(_) as r => nodeParser(r)
+  //   `Function(_ => Ok(evaluatedExpression));
-    | Fn(_) as r => nodeParser(r)
+  // }
+  let rec topLevel = (r): result(ExpressionTypes.Program.program, string) =>
+    switch (r) {
+    | FunctionAssignment({name, args, expression}) =>
+      switch (nodeParser(expression)) {
+      | Ok(r) => Ok([|`Assignment((name, `Function((args, r))))|])
+      | Error(r) => Error(r)
+      }
+    | Value(_) as r => nodeParser(r) |> E.R.fmap(r => [|`Expression(r)|])
+    | Fn(_) as r => nodeParser(r) |> E.R.fmap(r => [|`Expression(r)|])
     | Array(_) => Error("Array not valid as top level")
-    | Symbol(_) => Error("Symbol not valid as top level")
+    | Symbol(s) => handleSymbol(s) |> E.R.fmap(r => [|`Expression(r)|])
-    | Object(_) => Error("Object not valid as top level");
+    | Object(_) => Error("Object not valid as top level")
+    | Assignment(name, value) =>
+      switch (name) {
+      | Symbol(symbol) =>
+        nodeParser(value) |> E.R.fmap(r => [|`Assignment((symbol, r))|])
+      | _ => Error("Symbol not a string")
+      }
+    | Blocks(blocks) =>
+      blocks
+      |> E.A.fmap(b => topLevel(b))
+      |> E.A.R.firstErrorOrOpen
+      |> E.R.fmap(E.A.concatMany)
+    };
 
-  let run = (r): result(ExpressionTypes.ExpressionTree.node, string) =>
+  let run = (r): result(ExpressionTypes.Program.program, string) =>
     r |> MathAdtCleaner.run |> topLevel;
 };
 
@@ -369,7 +345,7 @@ module MathAdtToDistDst = {
    */
 let pointwiseToRightLogShift = Js.String.replaceByRe([%re "/\.\+/g"], ">>>");
 
-let fromString = str => {
+let fromString2 = str => {
   /* We feed the user-typed string into Mathjs.parseMath,
        which returns a JSON with (hopefully) a single-element array.
        This array element is the top-level node of a nested-object tree
@@ -390,3 +366,7 @@ let fromString = str => {
   let value = E.R.bind(mathJsParse, MathAdtToDistDst.run);
   value;
 };
+
+let fromString = str => {
+  fromString2(str);
+};

src/distPlus/expressionTree/Operation.re

@@ -7,6 +7,7 @@ module Algebraic = {
     | `Add => (+.)
     | `Subtract => (-.)
     | `Multiply => ( *. )
+    | `Exponentiate => ( ** )
     | `Divide => (/.);
 
   let applyFn = (t, f1, f2) => {
@@ -21,6 +22,7 @@ module Algebraic = {
     | `Add => "+"
     | `Subtract => "-"
     | `Multiply => "*"
+    | `Exponentiate => ( "**" )
     | `Divide => "/";
 
   let format = (a, b, c) => b ++ " " ++ toString(a) ++ " " ++ c;

src/distPlus/expressionTree/Program.re

@@ -0,0 +1,5 @@
+type t = ExpressionTypes.Program.program;
+
+let last = (r:t) => E.A.last(r) |> E.O.toResult("No rendered lines");
+// let run = (p:program) => p |> E.A.last |> E.O.fmap(r => 
+// )

src/distPlus/expressionTree/SamplingDistribution.re

@@ -60,17 +60,11 @@ let combineShapesUsingSampling =
          let shape =
            samples
            |> E.O.fmap(
-                Samples.T.fromSamples(
+                SamplesToShape.fromSamples(
-                  ~samplingInputs={
+                  ~samplingInputs=evaluationParams.samplingInputs,
-                    sampleCount:
-                      Some(evaluationParams.samplingInputs.sampleCount),
-                    outputXYPoints:
-                      Some(evaluationParams.samplingInputs.outputXYPoints),
-                    kernelWidth: evaluationParams.samplingInputs.kernelWidth,
-                  },
                 ),
               )
-           |> E.O.bind(_, (r) => r.shape)
+           |> E.O.bind(_, r => r.shape)
            |> E.O.toResult("No response");
          shape |> E.R.fmap(r => `Normalize(`RenderedDist(r)));
        },

src/distPlus/renderers/DistPlusRenderer.re

@@ -1,23 +1,147 @@
-let run = (inputs: RenderTypes.DistPlusRenderer.inputs) => {
+// TODO: This setup is more confusing than it should be, there's more work to do in cleanup here.
-  let toDist = shape =>
+module Inputs = {
+  module SamplingInputs = {
+    type t = {
+      sampleCount: option(int),
+      outputXYPoints: option(int),
+      kernelWidth: option(float),
+      shapeLength: option(int),
+    };
+  };
+  let defaultRecommendedLength = 10000;
+  let defaultShouldDownsample = true;
+
+  type ingredients = {
+    guesstimatorString: string,
+    domain: DistTypes.domain,
+    unit: DistTypes.distributionUnit,
+  };
+  module Ingredients = {
+    type t = ingredients;
+    let make =
+        (
+          ~guesstimatorString,
+          ~domain=DistTypes.Complete,
+          ~unit=DistTypes.UnspecifiedDistribution,
+          (),
+        )
+        : t => {
+      guesstimatorString,
+      domain,
+      unit,
+    };
+  };
+
+  type inputs = {
+    distPlusIngredients: ingredients,
+    samplingInputs: SamplingInputs.t,
+    environment: ExpressionTypes.ExpressionTree.environment
+  };
+
+  let empty: SamplingInputs.t = {
+    sampleCount: None,
+    outputXYPoints: None,
+    kernelWidth: None,
+    shapeLength: None,
+  };
+
+  let make =
+      (
+        ~samplingInputs=empty,
+        ~distPlusIngredients,
+        ~environment=ExpressionTypes.ExpressionTree.Environment.empty,
+        (),
+      )
+      : inputs => {
+    distPlusIngredients,
+    samplingInputs,
+    environment,
+  };
+};
+
+module Internals = {
+  type inputs = {
+    samplingInputs: Inputs.SamplingInputs.t,
+    guesstimatorString: string,
+    environment: ExpressionTypes.ExpressionTree.environment,
+  };
+
+  let addVariable =
+      (
+        {samplingInputs, guesstimatorString, environment}: inputs,
+        str,
+        node,
+      )
+      : inputs => {
+    samplingInputs,
+    guesstimatorString,
+    environment:
+    ExpressionTypes.ExpressionTree.Environment.update(environment, str, _ => Some(node))
+  };
+
+  let distPlusRenderInputsToInputs = (inputs: Inputs.inputs): inputs => {
+    {
+      samplingInputs: inputs.samplingInputs,
+      guesstimatorString: inputs.distPlusIngredients.guesstimatorString,
+      environment: inputs.environment,
+    };
+  };
+
+  type outputs = {
+    graph: ExpressionTypes.ExpressionTree.node,
+    shape: DistTypes.shape,
+  };
+  let makeOutputs = (graph, shape): outputs => {graph, shape};
+
+  let runNode = (inputs, node) => {
+    ExpressionTree.toShape(
+      {
+        sampleCount: inputs.samplingInputs.sampleCount |> E.O.default(10000),
+        outputXYPoints:
+          inputs.samplingInputs.outputXYPoints |> E.O.default(10000),
+        kernelWidth: inputs.samplingInputs.kernelWidth,
+        shapeLength: inputs.samplingInputs.shapeLength |> E.O.default(10000),
+      },
+      inputs.environment,
+      node,
+    );
+  };
+
+  let runProgram = (inputs: inputs, p: ExpressionTypes.Program.program) => {
+    let ins = ref(inputs);
+    p
+    |> E.A.fmap(statement =>
+         switch (statement) {
+         | `Assignment(name, node) =>
+           ins := addVariable(ins^, name, node);
+           None;
+         | `Expression(node) => Some(runNode(ins^, node))
+         }
+       )
+    |> E.A.O.concatSomes
+    |> E.A.R.firstErrorOrOpen;
+  };
+
+  let inputsToShape = (inputs: inputs) => {
+    MathJsParser.fromString(inputs.guesstimatorString)
+    |> E.R.bind(_, g => runProgram(inputs, g))
+    |> E.R.bind(_, r => E.A.last(r) |> E.O.toResult("No rendered lines") |> E.R.fmap(Shape.T.normalize));
+  };
+
+  let outputToDistPlus = (inputs: Inputs.inputs, shape: DistTypes.shape) => {
     DistPlus.make(
       ~shape,
       ~domain=inputs.distPlusIngredients.domain,
       ~unit=inputs.distPlusIngredients.unit,
       ~guesstimatorString=Some(inputs.distPlusIngredients.guesstimatorString),
       (),
-    )
+    );
-    |> DistPlus.T.normalize;
+  };
-  let output =
+};
-    ShapeRenderer.run({
+
-      samplingInputs: inputs.samplingInputs,
+let run = (inputs: Inputs.inputs) => {
-      guesstimatorString: inputs.distPlusIngredients.guesstimatorString,
+  inputs
-      symbolicInputs: {
+  |> Internals.distPlusRenderInputsToInputs
-        length: inputs.recommendedLength,
+  |> Internals.inputsToShape
-      },
+  |> E.R.fmap(Internals.outputToDistPlus(inputs));
-    });
-  output
-  |> E.R.fmap((o: RenderTypes.ShapeRenderer.Symbolic.outputs) =>
-       toDist(o.shape)
-     );
 };

src/distPlus/renderers/RenderTypes.re

@@ -1,127 +0,0 @@
-module ShapeRenderer = {
-  module Sampling = {
-    type inputs = {
-      sampleCount: option(int),
-      outputXYPoints: option(int),
-      kernelWidth: option(float),
-    };
-    type samplingStats = {
-      sampleCount: int,
-      outputXYPoints: int,
-      bandwidthXSuggested: float,
-      bandwidthUnitSuggested: float,
-      bandwidthXImplemented: float,
-      bandwidthUnitImplemented: float,
-    };
-    type outputs = {
-      continuousParseParams: option(samplingStats),
-      shape: option(DistTypes.shape),
-    };
-    module Inputs = {
-      let defaultSampleCount = 5000;
-      let defaultOutputXYPoints = 10000;
-      let empty = {
-        sampleCount: None,
-        outputXYPoints: None,
-        kernelWidth: None,
-      };
-
-      type fInputs = {
-        sampleCount: int,
-        outputXYPoints: int,
-        kernelWidth: option(float),
-      };
-      let toF = (i: inputs): fInputs => {
-        sampleCount: i.sampleCount |> E.O.default(defaultSampleCount),
-        outputXYPoints:
-          i.outputXYPoints |> E.O.default(defaultOutputXYPoints),
-        kernelWidth: i.kernelWidth,
-      };
-    };
-  };
-
-  module Symbolic = {
-    type inputs = {length: int};
-    type outputs = {
-      graph: ExpressionTypes.ExpressionTree.node,
-      shape: DistTypes.shape,
-    };
-    let make = (graph, shape) => {graph, shape};
-  };
-
-  module Combined = {
-    type inputs = {
-      samplingInputs: Sampling.inputs,
-      symbolicInputs: Symbolic.inputs,
-      guesstimatorString: string,
-    };
-    type outputs = {
-      symbolic: option(Belt.Result.t(Symbolic.outputs, string)),
-      sampling: option(Sampling.outputs),
-    };
-    let methodUsed = ({symbolic, sampling}:outputs) => switch(symbolic, sampling){
-      | (Some(Ok(_)), _) => `Symbolic
-      | (_, Some({shape: Some(_)})) => `Sampling
-      | _ => `None
-    }
-    let getShape = (r: outputs) =>
-      switch (r.symbolic, r.sampling) {
-      | (Some(Ok({shape})), _) => Some(shape)
-      | (_, Some({shape})) => shape
-      | _ => None
-      };
-  };
-};
-
-module DistPlusRenderer = {
-  let defaultRecommendedLength = 10000;
-  let defaultShouldDownsample = true;
-  type ingredients = {
-    guesstimatorString: string,
-    domain: DistTypes.domain,
-    unit: DistTypes.distributionUnit,
-  };
-  type inputs = {
-    distPlusIngredients: ingredients,
-    samplingInputs: ShapeRenderer.Sampling.inputs,
-    recommendedLength: int,
-    shouldDownsample: bool,
-  };
-  module Ingredients = {
-    let make =
-        (
-          ~guesstimatorString,
-          ~domain=DistTypes.Complete,
-          ~unit=DistTypes.UnspecifiedDistribution,
-          (),
-        )
-        : ingredients => {
-      guesstimatorString,
-      domain,
-      unit,
-    };
-  };
-  let make =
-      (
-        ~samplingInputs=ShapeRenderer.Sampling.Inputs.empty,
-        ~recommendedLength=defaultRecommendedLength,
-        ~shouldDownsample=defaultShouldDownsample,
-        ~distPlusIngredients,
-        (),
-      )
-      : inputs => {
-    distPlusIngredients,
-    samplingInputs,
-    recommendedLength,
-    shouldDownsample,
-  };
-  type outputs = {
-    shapeRenderOutputs: ShapeRenderer.Combined.outputs,
-    distPlus: option(DistTypes.distPlus)
-  }
-  module Outputs = {
-    let distplus = (t:outputs) => t.distPlus
-    let shapeRenderOutputs = (t:outputs) => t.shapeRenderOutputs
-    let make = (shapeRenderOutputs, distPlus) => {shapeRenderOutputs, distPlus};
-  }
-};

src/distPlus/renderers/ShapeRenderer.re

@@ -1,39 +0,0 @@
-// This transforms an array intersperced with spaces or newlines with a normally formatted one.
-// "3 4 5 3 2 1 " -> "[3,4,5,3,2,1]""
-let formatMessyArray = str => {
-  let split = Js.String.splitByRe([%re "/\\n|\\r|\\s/"], str);
-  if (E.A.length(split) > 20) {
-    let inner = split |> Js.Array.joinWith(",");
-    {j|[$inner]|j};
-  } else {
-    str;
-  };
-};
-
-let formatString = str => {
-  str |> formatMessyArray;
-};
-
-let runSymbolic = (inputs: RenderTypes.ShapeRenderer.Combined.inputs) => {
-  let str = formatString(inputs.guesstimatorString);
-  let graph = MathJsParser.fromString(str);
-  graph
-  |> E.R.bind(_, g =>
-       ExpressionTree.toShape(
-         inputs.symbolicInputs.length,
-         {
-           sampleCount:
-             inputs.samplingInputs.sampleCount |> E.O.default(10000),
-           outputXYPoints:
-             inputs.samplingInputs.outputXYPoints |> E.O.default(10000),
-           kernelWidth: inputs.samplingInputs.kernelWidth,
-         },
-         g,
-       )
-       |> E.R.fmap(RenderTypes.ShapeRenderer.Symbolic.make(g))
-     );
-};
-
-let run = (inputs: RenderTypes.ShapeRenderer.Combined.inputs) => {
-  runSymbolic(inputs);
-};

src/distPlus/renderers/samplesRenderer/Samples.re

@@ -1,185 +0,0 @@
-module Types = {
-  let defaultSampleCount = 5000;
-  let defaultOutputXYPoints = 10000;
-
-  type inputs = {
-    sampleCount: option(int),
-    outputXYPoints: option(int),
-    kernelWidth: option(float),
-  };
-
-  type samplingStats = {
-    sampleCount: int,
-    outputXYPoints: int,
-    bandwidthXSuggested: float,
-    bandwidthUnitSuggested: float,
-    bandwidthXImplemented: float,
-    bandwidthUnitImplemented: float,
-  };
-
-  type outputs = {
-    continuousParseParams: option(samplingStats),
-    shape: option(DistTypes.shape),
-  };
-
-  let empty = {sampleCount: None, outputXYPoints: None, kernelWidth: None};
-
-  type fInputs = {
-    sampleCount: int,
-    outputXYPoints: int,
-    kernelWidth: option(float),
-  };
-
-  let toF = (i: inputs): fInputs => {
-    sampleCount: i.sampleCount |> E.O.default(defaultSampleCount),
-    outputXYPoints: i.outputXYPoints |> E.O.default(defaultOutputXYPoints),
-    kernelWidth: i.kernelWidth,
-  };
-};
-
-module JS = {
-  [@bs.deriving abstract]
-  type distJs = {
-    xs: array(float),
-    ys: array(float),
-  };
-
-  let jsToDist = (d: distJs): DistTypes.xyShape => {
-    xs: xsGet(d),
-    ys: ysGet(d),
-  };
-
-  [@bs.module "./KdeLibrary.js"]
-  external samplesToContinuousPdf: (array(float), int, int) => distJs =
-    "samplesToContinuousPdf";
-};
-
-module KDE = {
-  let normalSampling = (samples, outputXYPoints, kernelWidth) => {
-    samples
-    |> JS.samplesToContinuousPdf(_, outputXYPoints, kernelWidth)
-    |> JS.jsToDist;
-  };
-};
-
-module T = {
-  type t = array(float);
-
-  let splitContinuousAndDiscrete = (sortedArray: t) => {
-    let continuous = [||];
-    let discrete = E.FloatFloatMap.empty();
-    Belt.Array.forEachWithIndex(
-      sortedArray,
-      (index, element) => {
-        let maxIndex = (sortedArray |> Array.length) - 1;
-        let possiblySimilarElements =
-          (
-            switch (index) {
-            | 0 => [|index + 1|]
-            | n when n == maxIndex => [|index - 1|]
-            | _ => [|index - 1, index + 1|]
-            }
-          )
-          |> Belt.Array.map(_, r => sortedArray[r]);
-        let hasSimilarElement =
-          Belt.Array.some(possiblySimilarElements, r => r == element);
-        hasSimilarElement
-          ? E.FloatFloatMap.increment(element, discrete)
-          : {
-            let _ = Js.Array.push(element, continuous);
-            ();
-          };
-        ();
-      },
-    );
-    (continuous, discrete);
-  };
-
-  let xWidthToUnitWidth = (samples, outputXYPoints, xWidth) => {
-    let xyPointRange = E.A.Sorted.range(samples) |> E.O.default(0.0);
-    let xyPointWidth = xyPointRange /. float_of_int(outputXYPoints);
-    xWidth /. xyPointWidth;
-  };
-
-  let formatUnitWidth = w => Jstat.max([|w, 1.0|]) |> int_of_float;
-
-  let suggestedUnitWidth = (samples, outputXYPoints) => {
-    let suggestedXWidth = Bandwidth.nrd0(samples);
-    xWidthToUnitWidth(samples, outputXYPoints, suggestedXWidth);
-  };
-
-  let kde = (~samples, ~outputXYPoints, width) => {
-    KDE.normalSampling(samples, outputXYPoints, width);
-  };
-
-  let toShape =
-      (
-        ~samples: t,
-        ~samplingInputs: Types.fInputs,
-        (),
-      ) => {
-    Array.fast_sort(compare, samples);
-    let (continuousPart, discretePart) = E.A.Sorted.Floats.split(samples);
-    let length = samples |> E.A.length |> float_of_int;
-    let discrete: DistTypes.discreteShape =
-      discretePart
-      |> E.FloatFloatMap.fmap(r => r /. length)
-      |> E.FloatFloatMap.toArray
-      |> XYShape.T.fromZippedArray
-      |> Discrete.make;
-
-    let pdf =
-      continuousPart |> E.A.length > 5
-        ? {
-          let _suggestedXWidth = Bandwidth.nrd0(continuousPart);
-          // todo: This does some recalculating from the last step.
-          let _suggestedUnitWidth =
-            suggestedUnitWidth(continuousPart, samplingInputs.outputXYPoints);
-          let usedWidth =
-            samplingInputs.kernelWidth |> E.O.default(_suggestedXWidth);
-          let usedUnitWidth =
-            xWidthToUnitWidth(
-              samples,
-              samplingInputs.outputXYPoints,
-              usedWidth,
-            );
-          let foo: Types.samplingStats = {
-            sampleCount: samplingInputs.sampleCount,
-            outputXYPoints: samplingInputs.outputXYPoints,
-            bandwidthXSuggested: _suggestedXWidth,
-            bandwidthUnitSuggested: _suggestedUnitWidth,
-            bandwidthXImplemented: usedWidth,
-            bandwidthUnitImplemented: usedUnitWidth,
-          };
-          continuousPart
-          |> kde(
-               ~samples=_,
-               ~outputXYPoints=samplingInputs.outputXYPoints,
-               formatUnitWidth(usedUnitWidth),
-             )
-          |> Continuous.make
-          |> (r => Some((r, foo)));
-        }
-        : None;
-    let shape =
-      MixedShapeBuilder.buildSimple(
-        ~continuous=pdf |> E.O.fmap(fst),
-        ~discrete=Some(discrete),
-      );
-    let samplesParse: Types.outputs = {
-      continuousParseParams: pdf |> E.O.fmap(snd),
-      shape,
-    };
-    samplesParse;
-  };
-
-  let fromSamples =
-      (
-        ~samplingInputs=Types.empty,
-        samples,
-      ) => {
-    let samplingInputs =
-      Types.toF(samplingInputs);
-    toShape(~samples, ~samplingInputs, ());
-  };
-};

src/distPlus/renderers/samplesRenderer/SamplesToShape.re

@@ -0,0 +1,164 @@
+module Internals = {
+  module Types = {
+    type samplingStats = {
+      sampleCount: int,
+      outputXYPoints: int,
+      bandwidthXSuggested: float,
+      bandwidthUnitSuggested: float,
+      bandwidthXImplemented: float,
+      bandwidthUnitImplemented: float,
+    };
+
+    type outputs = {
+      continuousParseParams: option(samplingStats),
+      shape: option(DistTypes.shape),
+    };
+  };
+
+  module JS = {
+    [@bs.deriving abstract]
+    type distJs = {
+      xs: array(float),
+      ys: array(float),
+    };
+
+    let jsToDist = (d: distJs): DistTypes.xyShape => {
+      xs: xsGet(d),
+      ys: ysGet(d),
+    };
+
+    [@bs.module "./KdeLibrary.js"]
+    external samplesToContinuousPdf: (array(float), int, int) => distJs =
+      "samplesToContinuousPdf";
+  };
+
+  module KDE = {
+    let normalSampling = (samples, outputXYPoints, kernelWidth) => {
+      samples
+      |> JS.samplesToContinuousPdf(_, outputXYPoints, kernelWidth)
+      |> JS.jsToDist;
+    };
+  };
+
+  module T = {
+    type t = array(float);
+
+    let splitContinuousAndDiscrete = (sortedArray: t) => {
+      let continuous = [||];
+      let discrete = E.FloatFloatMap.empty();
+      Belt.Array.forEachWithIndex(
+        sortedArray,
+        (index, element) => {
+          let maxIndex = (sortedArray |> Array.length) - 1;
+          let possiblySimilarElements =
+            (
+              switch (index) {
+              | 0 => [|index + 1|]
+              | n when n == maxIndex => [|index - 1|]
+              | _ => [|index - 1, index + 1|]
+              }
+            )
+            |> Belt.Array.map(_, r => sortedArray[r]);
+          let hasSimilarElement =
+            Belt.Array.some(possiblySimilarElements, r => r == element);
+          hasSimilarElement
+            ? E.FloatFloatMap.increment(element, discrete)
+            : {
+              let _ = Js.Array.push(element, continuous);
+              ();
+            };
+          ();
+        },
+      );
+      (continuous, discrete);
+    };
+
+    let xWidthToUnitWidth = (samples, outputXYPoints, xWidth) => {
+      let xyPointRange = E.A.Sorted.range(samples) |> E.O.default(0.0);
+      let xyPointWidth = xyPointRange /. float_of_int(outputXYPoints);
+      xWidth /. xyPointWidth;
+    };
+
+    let formatUnitWidth = w => Jstat.max([|w, 1.0|]) |> int_of_float;
+
+    let suggestedUnitWidth = (samples, outputXYPoints) => {
+      let suggestedXWidth = Bandwidth.nrd0(samples);
+      xWidthToUnitWidth(samples, outputXYPoints, suggestedXWidth);
+    };
+
+    let kde = (~samples, ~outputXYPoints, width) => {
+      KDE.normalSampling(samples, outputXYPoints, width);
+    };
+  };
+};
+
+let toShape =
+    (
+      ~samples: Internals.T.t,
+      ~samplingInputs: ExpressionTypes.ExpressionTree.samplingInputs,
+      (),
+    ) => {
+  Array.fast_sort(compare, samples);
+  let (continuousPart, discretePart) = E.A.Sorted.Floats.split(samples);
+  let length = samples |> E.A.length |> float_of_int;
+  let discrete: DistTypes.discreteShape =
+    discretePart
+    |> E.FloatFloatMap.fmap(r => r /. length)
+    |> E.FloatFloatMap.toArray
+    |> XYShape.T.fromZippedArray
+    |> Discrete.make;
+
+  let pdf =
+    continuousPart |> E.A.length > 5
+      ? {
+        let _suggestedXWidth = Bandwidth.nrd0(continuousPart);
+        // todo: This does some recalculating from the last step.
+        let _suggestedUnitWidth =
+          Internals.T.suggestedUnitWidth(
+            continuousPart,
+            samplingInputs.outputXYPoints,
+          );
+        let usedWidth =
+          samplingInputs.kernelWidth |> E.O.default(_suggestedXWidth);
+        let usedUnitWidth =
+          Internals.T.xWidthToUnitWidth(
+            samples,
+            samplingInputs.outputXYPoints,
+            usedWidth,
+          );
+        let samplingStats: Internals.Types.samplingStats = {
+          sampleCount: samplingInputs.sampleCount,
+          outputXYPoints: samplingInputs.outputXYPoints,
+          bandwidthXSuggested: _suggestedXWidth,
+          bandwidthUnitSuggested: _suggestedUnitWidth,
+          bandwidthXImplemented: usedWidth,
+          bandwidthUnitImplemented: usedUnitWidth,
+        };
+        continuousPart
+        |> Internals.T.kde(
+             ~samples=_,
+             ~outputXYPoints=samplingInputs.outputXYPoints,
+             Internals.T.formatUnitWidth(usedUnitWidth),
+           )
+        |> Continuous.make
+        |> (r => Some((r, samplingStats)));
+      }
+      : None;
+
+  let shape =
+    MixedShapeBuilder.buildSimple(
+      ~continuous=pdf |> E.O.fmap(fst),
+      ~discrete=Some(discrete),
+    );
+
+  let samplesParse: Internals.Types.outputs = {
+    continuousParseParams: pdf |> E.O.fmap(snd),
+    shape,
+  };
+
+  samplesParse;
+};
+
+let fromSamples = (~samplingInputs, samples) => {
+  toShape(~samples, ~samplingInputs, ());
+};

src/distPlus/symbolic/SymbolicDist.re

@@ -2,6 +2,12 @@ open SymbolicTypes;
 
 module Exponential = {
   type t = exponential;
+  let make = (rate:float): symbolicDist =>
+    `Exponential(
+      {
+        rate:rate
+      },
+    );
   let pdf = (x, t: t) => Jstat.exponential##pdf(x, t.rate);
   let cdf = (x, t: t) => Jstat.exponential##cdf(x, t.rate);
   let inv = (p, t: t) => Jstat.exponential##inv(p, t.rate);
@@ -12,6 +18,7 @@ module Exponential = {
 
 module Cauchy = {
   type t = cauchy;
+  let make = (local, scale): symbolicDist => `Cauchy({local, scale});
   let pdf = (x, t: t) => Jstat.cauchy##pdf(x, t.local, t.scale);
   let cdf = (x, t: t) => Jstat.cauchy##cdf(x, t.local, t.scale);
   let inv = (p, t: t) => Jstat.cauchy##inv(p, t.local, t.scale);
@@ -22,6 +29,10 @@ module Cauchy = {
 
 module Triangular = {
   type t = triangular;
+  let make = (low, medium, high): result(symbolicDist, string) =>
+    low < medium && medium < high
+      ? Ok(`Triangular({low, medium, high}))
+      : Error("Triangular values must be increasing order");
   let pdf = (x, t: t) => Jstat.triangular##pdf(x, t.low, t.high, t.medium);
   let cdf = (x, t: t) => Jstat.triangular##cdf(x, t.low, t.high, t.medium);
   let inv = (p, t: t) => Jstat.triangular##inv(p, t.low, t.high, t.medium);
@@ -32,6 +43,7 @@ module Triangular = {
 
 module Normal = {
   type t = normal;
+  let make = (mean, stdev): symbolicDist => `Normal({mean, stdev});
   let pdf = (x, t: t) => Jstat.normal##pdf(x, t.mean, t.stdev);
   let cdf = (x, t: t) => Jstat.normal##cdf(x, t.mean, t.stdev);
 
@@ -75,6 +87,7 @@ module Normal = {
 
 module Beta = {
   type t = beta;
+  let make = (alpha, beta) => `Beta({alpha, beta});
   let pdf = (x, t: t) => Jstat.beta##pdf(x, t.alpha, t.beta);
   let cdf = (x, t: t) => Jstat.beta##cdf(x, t.alpha, t.beta);
   let inv = (p, t: t) => Jstat.beta##inv(p, t.alpha, t.beta);
@@ -85,6 +98,7 @@ module Beta = {
 
 module Lognormal = {
   type t = lognormal;
+  let make = (mu, sigma) => `Lognormal({mu, sigma});
   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);
@@ -131,6 +145,7 @@ module Lognormal = {
 
 module Uniform = {
   type t = uniform;
+  let make = (low, high) => `Uniform({low, high});
   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);
   let inv = (p, t: t) => Jstat.uniform##inv(p, t.low, t.high);
@@ -146,6 +161,7 @@ module Uniform = {
 
 module Float = {
   type t = float;
+  let make = t => `Float(t);
   let pdf = (x, t: t) => x == t ? 1.0 : 0.0;
   let cdf = (x, t: t) => x >= t ? 1.0 : 0.0;
   let inv = (p, t: t) => p < t ? 0.0 : 1.0;
@@ -317,13 +333,14 @@ module T = {
     switch (d) {
     | `Float(v) =>
       Discrete(
-        Discrete.make(~integralSumCache=Some(1.0), {xs: [|v|], ys: [|1.0|]}),
+        Discrete.make(
+          ~integralSumCache=Some(1.0),
+          {xs: [|v|], ys: [|1.0|]},
+        ),
       )
     | _ =>
       let xs = interpolateXs(~xSelection=`ByWeight, d, sampleCount);
       let ys = xs |> E.A.fmap(x => pdf(x, d));
-      Continuous(
+      Continuous(Continuous.make(~integralSumCache=Some(1.0), {xs, ys}));
-        Continuous.make(~integralSumCache=Some(1.0), {xs, ys}),
-      );
     };
 };

src/interface/FormBuilder.re

@@ -17,12 +17,10 @@ let propValue = (t: Prop.Value.t) => {
   switch (t) {
   | SelectSingle(r) => r |> ReasonReact.string
   | ConditionalArray(r) => "Array" |> ReasonReact.string
-  | DistPlusIngredients((r: RenderTypes.DistPlusRenderer.ingredients)) =>
+  | DistPlusIngredients((r: DistPlusRenderer.Inputs.ingredients)) =>
     let newDistribution =
-      RenderTypes.DistPlusRenderer.make(
+      DistPlusRenderer.Inputs.make(
         ~distPlusIngredients=r,
-        ~recommendedLength=10000,
-        ~shouldDownsample=true,
         (),
       )
       |> DistPlusRenderer.run;

src/interface/Prop.re

@@ -9,7 +9,7 @@ module Value = {
     | DateTime(MomentRe.Moment.t)
     | FloatPoint(float)
     | Probability(float)
-    | DistPlusIngredients(RenderTypes.DistPlusRenderer.ingredients)
+    | DistPlusIngredients(DistPlusRenderer.Inputs.ingredients)
     | ConditionalArray(array(conditional))
     | FloatCdf(string);
 
@@ -85,7 +85,7 @@ module ValueCluster = {
         [ | `combination(range(MomentRe.Moment.t)) | `item(string)],
       )
     | Probability([ | `item(string)])
-    | DistPlusIngredients([ | `item(RenderTypes.DistPlusRenderer.ingredients)])
+    | DistPlusIngredients([ | `item(DistPlusRenderer.Inputs.ingredients)])
     | ConditionalArray([ | `item(array(conditional))])
     | FloatCdf([ | `item(string)]);
 };

src/models/EAFunds.re

@@ -110,7 +110,7 @@ module Model = {
   // TODO: Fixe number that integral is calculated for
   let getGlobalCatastropheChance = dateTime => {
     GlobalCatastrophe.makeI(MomentRe.momentNow())
-    |> RenderTypes.DistPlusRenderer.make(~distPlusIngredients=_, ())
+    |> DistPlusRenderer.Inputs.make(~distPlusIngredients=_, ())
     |> DistPlusRenderer.run
     |> E.R.bind(_, r =>
          r
@@ -157,7 +157,7 @@ module Model = {
         };
 
       let distPlusIngredients =
-        RenderTypes.DistPlusRenderer.Ingredients.make(
+        DistPlusRenderer.Inputs.Ingredients.make(
           ~guesstimatorString=str,
           ~domain=Complete,
           ~unit=UnspecifiedDistribution,
@@ -167,7 +167,7 @@ module Model = {
 
     | CHANCE_OF_EXISTENCE =>
       Prop.Value.DistPlusIngredients(
-        RenderTypes.DistPlusRenderer.Ingredients.make(
+        DistPlusRenderer.Inputs.Ingredients.make(
           ~guesstimatorString=
             GuesstimatorDist.min(
               GlobalCatastrophe.guesstimatorString,

src/models/GlobalCatastrophe.re

@@ -1,7 +1,7 @@
 let guesstimatorString = "uniform(1, 100)";
 
 let makeI = (currentDateTime: MomentRe.Moment.t) => {
-  RenderTypes.DistPlusRenderer.Ingredients.make(
+  DistPlusRenderer.Inputs.Ingredients.make(
     ~guesstimatorString,
     ~unit=TimeDistribution({zero: currentDateTime, unit: `years}),
     ~domain=RightLimited({xPoint: 300.0, excludingProbabilityMass: 0.3}),

src/models/Human.re

@@ -2,7 +2,7 @@ let guesstimatorString = age =>
   GuesstimatorDist.normal(72.0 -. age, 5.0 -. age *. 0.01);
 
 let makeI = (age: float) => {
-  RenderTypes.DistPlusRenderer.Ingredients.make(
+  DistPlusRenderer.Inputs.Ingredients.make(
     ~guesstimatorString=guesstimatorString(age),
     ~unit=TimeDistribution({zero: MomentRe.momentNow(), unit: `years}),
     ~domain=RightLimited({xPoint: 300.0, excludingProbabilityMass: 0.3}),