Attached inputs to editor

src/components/DistBuilder3.re

@@ -37,7 +37,14 @@ module DemoDist = {
     let parsed1 = MathJsParser.fromString(guesstimatorString);
     let shape =
       switch (parsed1) {
-      | Ok(r) => Some(ExpressionTree.toShape(10000, r))
+      | Ok(r) =>
+        Some(
+          ExpressionTree.toShape(
+            10000,
+            {sampleCount: 10000, outputXYPoints: 10000, kernelWidth: None},
+            r,
+          ),
+        )
       | _ => None
       };
 

src/components/Drawer.re

@@ -161,7 +161,6 @@ module Convert = {
   let canvasShapeToContinuousShape =
       (~canvasShape: Types.canvasShape, ~canvasElement: Dom.element)
       : Types.continuousShape => {
-      
     let xs = canvasShape.xValues;
     let hs = canvasShape.hs;
     let rectangle: Types.rectangle =
@@ -170,8 +169,8 @@ module Convert = {
     let paddingFactorY = CanvasContext.paddingFactorX(rectangle.height);
     let windowScrollY: float = [%raw "window.scrollY"];
 
-    let y0Line = bottom+.windowScrollY-.paddingFactorY;
+    let y0Line = bottom +. windowScrollY -. paddingFactorY;
-    let ys = E.A.fmap( h => y0Line -. h, hs);
+    let ys = E.A.fmap(h => y0Line -. h, hs);
 
     let xyShape: Types.xyShape = {xs, ys};
     let continuousShape: Types.continuousShape = {
@@ -389,7 +388,12 @@ module Draw = {
     let numSamples = 3000;
 
     let normal: SymbolicTypes.symbolicDist = `Normal({mean, stdev});
-    let normalShape = ExpressionTree.toShape(numSamples, `SymbolicDist(normal));
+    let normalShape =
+      ExpressionTree.toShape(
+        numSamples,
+        {sampleCount: 10000, outputXYPoints: 10000, kernelWidth: None},
+        `SymbolicDist(normal),
+      );
     let xyShape: Types.xyShape =
       switch (normalShape) {
       | Mixed(_) => {xs: [||], ys: [||]}
@@ -668,10 +672,7 @@ module State = {
         Convert.canvasShapeToContinuousShape(~canvasShape, ~canvasElement);
 
       /* create a cdf from a pdf */
-      let _pdf =
+      let _pdf = Continuous.T.normalize(pdf);
-        Continuous.T.normalize(
-          pdf,
-        );
 
       let cdf = Continuous.T.integral(~cache=None, _pdf);
       let xs = [||];

src/distPlus/expressionTree/ExpressionTree.re

@@ -1,9 +1,13 @@
 open ExpressionTypes.ExpressionTree;
 
-let toShape = (sampleCount: int, node: node) => {
+let toShape = (intendedShapeLength: int, samplingInputs, node: node) => {
   let renderResult =
     `Render(`Normalize(node))
-    |> ExpressionTreeEvaluator.toLeaf({sampleCount: sampleCount, evaluateNode: ExpressionTreeEvaluator.toLeaf});
+    |> ExpressionTreeEvaluator.toLeaf({
+         samplingInputs,
+         intendedShapeLength,
+         evaluateNode: ExpressionTreeEvaluator.toLeaf,
+       });
 
   switch (renderResult) {
   | Ok(`RenderedDist(rs)) =>

src/distPlus/expressionTree/ExpressionTreeEvaluator.re

@@ -4,8 +4,6 @@ open ExpressionTypes.ExpressionTree;
 type t = node;
 type tResult = node => result(node, string);
 
-type renderParams = {sampleCount: int};
-
 /* Given two random variables A and B, this returns the distribution
    of a new variable that is the result of the operation on A and B.
    For instance, normal(0, 1) + normal(1, 1) -> normal(1, 2).
@@ -51,15 +49,23 @@ module AlgebraicCombination = {
     |> E.R.bind(
          _,
          ((a, b)) => {
-           let samples = tryCombination(evaluationParams.sampleCount, algebraicOp, a, b);
+           let samples =
+             tryCombination(
+               evaluationParams.samplingInputs.sampleCount,
+               algebraicOp,
+               a,
+               b,
+             );
            let shape =
              samples
              |> E.O.fmap(
                   Samples.T.fromSamples(
                     ~samplingInputs={
-                      sampleCount: Some(evaluationParams.sampleCount),
+                      sampleCount:
-                      outputXYPoints: None,
+                        Some(evaluationParams.samplingInputs.sampleCount),
-                      kernelWidth: None,
+                      outputXYPoints:
+                        Some(evaluationParams.samplingInputs.outputXYPoints),
+                      kernelWidth: evaluationParams.samplingInputs.kernelWidth,
                     },
                   ),
                 )
@@ -235,7 +241,7 @@ module Render = {
     | `SymbolicDist(d) =>
       Ok(
         `RenderedDist(
-          SymbolicDist.T.toShape(evaluationParams.sampleCount, d),
+          SymbolicDist.T.toShape(evaluationParams.intendedShapeLength, d),
         ),
       )
     | `RenderedDist(_) as t => Ok(t) // already a rendered shape, we're done here

src/distPlus/expressionTree/ExpressionTypes.re

@@ -16,8 +16,15 @@ module ExpressionTree = {
     | `FloatFromDist(distToFloatOperation, node)
   ];
 
-  type evaluationParams = {
+  type samplingInputs = {
     sampleCount: int,
+    outputXYPoints: int,
+    kernelWidth: option(float),
+  };
+
+  type evaluationParams = {
+    samplingInputs,
+    intendedShapeLength: int,
     evaluateNode: (evaluationParams, node) => Belt.Result.t(node, string),
   };
 
@@ -28,18 +35,22 @@ module ExpressionTree = {
     evaluateNode(evaluationParams, `Render(r));
 
   let evaluateAndRetry = (evaluationParams, fn, node) =>
-    node |> evaluationParams.evaluateNode(evaluationParams) |> E.R.bind(_, fn(evaluationParams));
+    node
+    |> evaluationParams.evaluateNode(evaluationParams)
+    |> E.R.bind(_, fn(evaluationParams));
 
-  let renderable = fun
+  let renderable =
+    fun
     | `SymbolicDist(_) => true
     | `RenderedDist(_) => true
     | _ => false;
 
-  let mapRenderable = (renderedFn, symFn, item: node) => switch(item) {
+  let mapRenderable = (renderedFn, symFn, item: node) =>
+    switch (item) {
     | `SymbolicDist(s) => Some(symFn(s))
     | `RenderedDist(r) => Some(renderedFn(r))
     | _ => None
-  }
+    };
 };
 
 type simplificationResult = [

src/distPlus/renderers/ShapeRenderer.re

@@ -14,14 +14,24 @@ let formatString = str => {
   str |> formatMessyArray;
 };
 
-let runSymbolic = (guesstimatorString, length) => {
+let runSymbolic = (inputs: RenderTypes.ShapeRenderer.Combined.inputs) => {
-  let str = formatString(guesstimatorString);
+  let str = formatString(inputs.guesstimatorString);
   let graph = MathJsParser.fromString(str);
   graph
   |> E.R.fmap(g =>
        RenderTypes.ShapeRenderer.Symbolic.make(
          g,
-         ExpressionTree.toShape(length, 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,
+         ),
        )
      );
 };
@@ -29,8 +39,7 @@ let runSymbolic = (guesstimatorString, length) => {
 let run =
     (inputs: RenderTypes.ShapeRenderer.Combined.inputs)
     : RenderTypes.ShapeRenderer.Combined.outputs => {
-  let symbolic =
+  let symbolic = runSymbolic(inputs);
-    runSymbolic(inputs.guesstimatorString, inputs.symbolicInputs.length);
   let sampling =
     switch (symbolic) {
     | Ok(_) => None