Minor cleanup

__tests__/Guesstimator__Test.re

@@ -1,21 +0,0 @@
-open Jest;
-open Expect;
-
-let makeTest = (~only=false, str, item1, item2) =>
-  only
-    ? Only.test(str, () =>
-        expect(item1) |> toEqual(item2)
-      )
-    : test(str, () =>
-        expect(item1) |> toEqual(item2)
-      ) /* })*/;
-
-// These fail because of issues with Jest, Babel, and Bucklescript
-// describe("XYShapes", () => {
-//   describe("logScorePoint", () => {
-//     makeTest(
-//       "When identical",
-//       Some(Guesstimator.stringToMixedShape(~string="5 to 20")),
-//       None,
-//     )
-//   })

__tests__/Lodash__test.re

@@ -10,63 +10,6 @@ let makeTest = (~only=false, str, item1, item2) =>
         expect(item1) |> toEqual(item2)
       );
 
-module FloatFloatMap = {
-  module Id =
-    Belt.Id.MakeComparable({
-      type t = float;
-      let cmp: (float, float) => int = Pervasives.compare;
-    });
-
-  type t = Belt.MutableMap.t(Id.t, float, Id.identity);
-
-  let fromArray = (ar: array((float, float))) =>
-    Belt.MutableMap.fromArray(ar, ~id=(module Id));
-  let toArray = (t: t) => Belt.MutableMap.toArray(t);
-  let empty = () => Belt.MutableMap.make(~id=(module Id));
-  let increment = (el, t: t) =>
-    Belt.MutableMap.update(
-      t,
-      el,
-      fun
-      | Some(n) => Some(n +. 1.0)
-      | None => Some(1.0),
-    );
-
-  let get = (el, t: t) => Belt.MutableMap.get(t, el);
-  let fmap = (fn, t: t) => Belt.MutableMap.map(t, fn);
-};
-
-let split = (sortedArray: array(float)) => {
-  let continuous = [||];
-  let discrete = 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
-        ? FloatFloatMap.increment(element, discrete)
-        : {
-          let _ = Js.Array.push(element, continuous);
-          ();
-        };
-      ();
-    },
-  );
-
-  (continuous, discrete);
-};
-
 describe("Lodash", () => {
   describe("Lodash", () => {
     makeTest("min", Lodash.min([|1, 3, 4|]), 1);
@@ -77,31 +20,5 @@ describe("Lodash", () => {
       Lodash.countBy([|1, 3, 4, 4|], r => r),
       Js.Dict.fromArray([|("1", 1), ("3", 1), ("4", 2)|]),
     );
-    makeTest(
-      "split",
-      split([|1.432, 1.33455, 2.0|]),
-      ([|1.432, 1.33455, 2.0|], FloatFloatMap.empty()),
-    );
-    makeTest(
-      "split",
-      split([|1.432, 1.33455, 2.0, 2.0, 2.0, 2.0|])
-      |> (((c, disc)) => (c, disc |> FloatFloatMap.toArray)),
-      ([|1.432, 1.33455|], [|(2.0, 4.0)|]),
-    );
-
-    let makeDuplicatedArray = count => {
-      let arr = Belt.Array.range(1, count) |> E.A.fmap(float_of_int);
-      let sorted = arr |> Belt.SortArray.stableSortBy(_, compare);
-      E.A.concatMany([|sorted, sorted, sorted, sorted|])
-      |> Belt.SortArray.stableSortBy(_, compare);
-    };
-
-    let (_, discrete) = split(makeDuplicatedArray(10));
-    let toArr = discrete |> FloatFloatMap.toArray;
-    makeTest("splitMedium", toArr |> Belt.Array.length, 10);
-
-    let (c, discrete) = split(makeDuplicatedArray(500));
-    let toArr = discrete |> FloatFloatMap.toArray;
-    makeTest("splitMedium", toArr |> Belt.Array.length, 500);
   })
 });

__tests__/Samples__test.re

@@ -0,0 +1,51 @@
+open Jest;
+open Expect;
+
+let makeTest = (~only=false, str, item1, item2) =>
+  only
+    ? Only.test(str, () =>
+        expect(item1) |> toEqual(item2)
+      )
+    : test(str, () =>
+        expect(item1) |> toEqual(item2)
+      );
+
+describe("Lodash", () => {
+  describe("Lodash", () => {
+    makeTest(
+      "split",
+      Samples.T.splitContinuousAndDiscrete([|1.432, 1.33455, 2.0|]),
+      ([|1.432, 1.33455, 2.0|], E.FloatFloatMap.empty()),
+    );
+    makeTest(
+      "split",
+      Samples.T.splitContinuousAndDiscrete([|
+        1.432,
+        1.33455,
+        2.0,
+        2.0,
+        2.0,
+        2.0,
+      |])
+      |> (((c, disc)) => (c, disc |> E.FloatFloatMap.toArray)),
+      ([|1.432, 1.33455|], [|(2.0, 4.0)|]),
+    );
+
+    let makeDuplicatedArray = count => {
+      let arr = Belt.Array.range(1, count) |> E.A.fmap(float_of_int);
+      let sorted = arr |> Belt.SortArray.stableSortBy(_, compare);
+      E.A.concatMany([|sorted, sorted, sorted, sorted|])
+      |> Belt.SortArray.stableSortBy(_, compare);
+    };
+
+    let (_, discrete) =
+      Samples.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));
+    let toArr = discrete |> E.FloatFloatMap.toArray;
+    makeTest("splitMedium", toArr |> Belt.Array.length, 500);
+  })
+});

package.json

@@ -26,7 +26,6 @@
   "author": "",
   "license": "MIT",
   "dependencies": {
-    "@foretold/cdf": "1.0.15",
     "@foretold/components": "0.0.3",
     "@foretold/guesstimator": "1.0.10",
     "@glennsl/bs-jest": "^0.5.0",

src/Samples.re

@@ -0,0 +1,112 @@
+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 "./utility/KdeLibrary.js"]
+  external samplesToContinuousPdf: (array(float), int, int) => distJs =
+    "samplesToContinuousPdf";
+};
+
+module KDE = {
+  let normalSampling = (samples, outputXYPoints, kernelWidth) => {
+    samples
+    |> JS.samplesToContinuousPdf(_, outputXYPoints, kernelWidth)
+    |> JS.jsToDist;
+  };
+
+  let inGroups = (samples, outputXYPoints, kernelWidth, ~cuttoff=0.9, ()) => {
+    let partitionAt =
+      samples
+      |> E.A.length
+      |> float_of_int
+      |> (e => e *. cuttoff)
+      |> int_of_float;
+    let part1XYPoints =
+      outputXYPoints |> float_of_int |> (e => e *. cuttoff) |> int_of_float;
+    let part2XYPoints = outputXYPoints - part1XYPoints |> Js.Math.max_int(30);
+    let part1Data =
+      samples |> Belt.Array.slice(_, ~offset=0, ~len=partitionAt);
+    let part2DataLength = (samples |> E.A.length) - partitionAt;
+    let part2Data =
+      samples
+      |> Belt.Array.slice(
+           _,
+           ~offset=(-1) * part2DataLength,
+           ~len=part2DataLength,
+         );
+    let part1 =
+      part1Data
+      |> JS.samplesToContinuousPdf(_, part1XYPoints, kernelWidth)
+      |> JS.jsToDist;
+    let part2 =
+      part2Data
+      |> JS.samplesToContinuousPdf(_, part2XYPoints, 3)
+      |> JS.jsToDist;
+    let opp = 1.0 -. cuttoff;
+    part1;
+  };
+};
+
+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);
+  };
+
+  // todo: Figure out some way of doing this without having to integrate so many times.
+  let toShape = (~samples: t, ~outputXYPoints=3000, ~kernelWidth=10, ()) => {
+    Array.fast_sort(compare, samples);
+    let (continuousPart, discretePart) = E.A.Floats.split(samples);
+    let length = samples |> E.A.length;
+    let lengthFloat = float_of_int(length);
+    let discrete: DistTypes.xyShape =
+      discretePart
+      |> E.FloatFloatMap.fmap(r => r /. lengthFloat)
+      |> E.FloatFloatMap.toArray
+      |> XYShape.T.fromZippedArray;
+    let pdf: DistTypes.xyShape =
+      continuousPart |> E.A.length > 20
+        ? {
+          samples |> KDE.normalSampling(_, outputXYPoints, kernelWidth);
+        }
+        : {xs: [||], ys: [||]};
+    let continuous = pdf |> Distributions.Continuous.fromShape;
+    let shape = MixedShapeBuilder.buildSimple(~continuous, ~discrete);
+    shape;
+  };
+};

src/distributions/DistPlusIngredients.re

@@ -8,6 +8,13 @@ let make =
   unit,
 };
 
+let applyTruncation = (truncateTo, distPlus) =>
+  switch (truncateTo, distPlus) {
+  | (Some(t), Some(d)) => Some(d |> Distributions.DistPlus.T.truncate(t))
+  | (None, Some(d)) => Some(d)
+  | _ => None
+  };
+
 let toDistPlus =
     (
       ~sampleCount=2000,
@@ -17,18 +24,9 @@ let toDistPlus =
       t: distPlusIngredients,
     )
     : option(distPlus) => {
-  let shape =
+  let samples =
-    Guesstimator.toMixed(
+    Guesstimator.stringToSamples(t.guesstimatorString, sampleCount);
-      ~string=t.guesstimatorString,
+  let shape = Samples.T.toShape(~samples, ~outputXYPoints, ~kernelWidth, ());
-      ~sampleCount,
-      ~outputXYPoints,
-      ~kernelWidth,
-      (),
-    );
-  // TODO:
-  // Truncate before resizing.
-  // Faster sort
-  let distPlus =
   shape
   |> E.O.fmap(
        Distributions.DistPlus.make(
@@ -39,12 +37,6 @@ let toDistPlus =
          (),
        ),
      )
-    |> E.O.fmap(
+  |> E.O.fmap(Distributions.DistPlus.T.scaleToIntegralSum(~intendedSum=1.0))
-         Distributions.DistPlus.T.scaleToIntegralSum(~intendedSum=1.0),
+  |> applyTruncation(truncateTo);
-       );
-  switch (truncateTo, distPlus) {
-  | (Some(t), Some(d)) => Some(d |> Distributions.DistPlus.T.truncate(t))
-  | (None, Some(d)) => Some(d)
-  | _ => None
-  };
 };

src/utility/CdfLibrary.js

@@ -1,170 +0,0 @@
-const {
-  Cdf,
-  Pdf,
-  ContinuousDistribution,
-  ContinuousDistributionCombination,
-  scoringFunctions,
-} = require("@foretold/cdf/lib");
-const _ = require("lodash");
-
-/**
- *
- * @param xs
- * @param ys
- * @returns {{ys: *, xs: *}}
- */
-function cdfToPdf({ xs, ys }) {
-  let cdf = new Cdf(xs, ys);
-  let pdf = cdf.toPdf();
-  return { xs: pdf.xs, ys: pdf.ys };
-}
-
-/**
- *
- * @param xs
- * @param ys
- * @returns {{ys: *, xs: *}}
- */
-function pdfToCdf({ xs, ys }) {
-  let cdf = new Pdf(xs, ys);
-  let pdf = cdf.toCdf();
-  return { xs: pdf.xs, ys: pdf.ys };
-}
-
-/**
- *
- * @param sampleCount
- * @param vars
- * @returns {{ys: *, xs: *}}
- */
-function mean(sampleCount, vars) {
-  let cdfs = vars.map(r => new Cdf(r.xs, r.ys));
-  let comb = new ContinuousDistributionCombination(cdfs);
-  let newCdf = comb.combineYsWithMean(sampleCount);
-
-  return { xs: newCdf.xs, ys: newCdf.ys };
-}
-
-/**
- *
- * @param sampleCount
- * @param predictionCdf
- * @param resolutionCdf
- */
-function scoreNonMarketCdfCdf(sampleCount, predictionCdf, resolutionCdf, resolutionUniformAdditionWeight = 0) {
-  let toCdf = (r) => (new Cdf(r.xs, r.ys));
-  let prediction = toCdf(predictionCdf);
-  if (_.isFinite(resolutionUniformAdditionWeight)) {
-    prediction = prediction.combineWithUniformOfCdf(
-      {
-        cdf: toCdf(resolutionCdf),
-        uniformWeight: resolutionUniformAdditionWeight,
-        sampleCount
-      }
-    );
-  }
-
-  return scoringFunctions.distributionInputDistributionOutputMarketless({
-    predictionCdf: prediction,
-    resultCdf: toCdf(resolutionCdf),
-    sampleCount,
-  });
-}
-
-/**
- *
- * @param sampleCount
- * @param cdf
- */
-function differentialEntropy(sampleCount, cdf) {
-  let toCdf = (r) => (new Cdf(r.xs, r.ys));
-
-  return scoringFunctions.differentialEntropy({
-    cdf: toCdf(cdf),
-    sampleCount: sampleCount
-  });
-}
-
-/**
- *
- * @param x
- * @param xs
- * @param ys
- * @returns {number}
- */
-function findY(x, { xs, ys }) {
-  let cdf = new Cdf(xs, ys);
-  return cdf.findY(x);
-}
-
-/**
- *
- * @param x
- * @param xs
- * @param ys
- * @returns {number[]}
- */
-function convertToNewLength(n, { xs, ys }) {
-  let dist = new ContinuousDistribution(xs, ys);
-  return dist.convertToNewLength(n);
-}
-
-/**
- *
- * @param y
- * @param xs
- * @param ys
- * @returns {number}
- */
-function findX(y, { xs, ys }) {
-  let cdf = new Cdf(xs, ys);
-  return cdf.findX(y);
-}
-
-/**
- *
- * @param xs
- * @param ys
- * @returns {number[]}
- */
-function integral({ xs, ys }) {
-  if (_.includes(ys, NaN)) {
-    return NaN;
-  } else if (_.includes(ys, Infinity) && _.includes(ys, -Infinity)) {
-    return NaN;
-  } else if (_.includes(ys, Infinity)) {
-    return Infinity;
-  } else if (_.includes(ys, -Infinity)) {
-    return -Infinity;
-  }
-
-  let integral = 0;
-  for (let i = 1; i < ys.length; i++) {
-    let thisY = ys[i];
-    let lastY = ys[i - 1];
-    let thisX = xs[i];
-    let lastX = xs[i - 1];
-
-    if (
-      _.isFinite(thisY) && _.isFinite(lastY) &&
-      _.isFinite(thisX) && _.isFinite(lastX)
-    ) {
-      let sectionInterval = ((thisY + lastY) / 2) * (thisX - lastX);
-      integral = integral + sectionInterval;
-    }
-
-  }
-  return integral;
-}
-
-module.exports = {
-  cdfToPdf,
-  pdfToCdf,
-  findY,
-  findX,
-  convertToNewLength,
-  mean,
-  scoreNonMarketCdfCdf,
-  differentialEntropy,
-  integral,
-};

src/utility/CdfLibrary.re

@@ -1,56 +0,0 @@
-module JS = {
-  [@bs.deriving abstract]
-  type distJs = {
-    xs: array(float),
-    ys: array(float),
-  };
-
-  let distToJs = (d: DistTypes.xyShape) => distJs(~xs=d.xs, ~ys=d.ys);
-
-  let jsToDist = (d: distJs): DistTypes.xyShape => {
-    xs: xsGet(d),
-    ys: ysGet(d),
-  };
-
-  let doAsDist = (f, d: DistTypes.xyShape) => d |> distToJs |> f |> jsToDist;
-
-  [@bs.module "./CdfLibrary.js"]
-  external cdfToPdf: distJs => distJs = "cdfToPdf";
-
-  [@bs.module "./CdfLibrary.js"]
-  external pdfToCdf: distJs => distJs = "pdfToCdf";
-
-  [@bs.module "./CdfLibrary.js"]
-  external findY: (float, distJs) => float = "findY";
-
-  [@bs.module "./CdfLibrary.js"]
-  external findX: (float, distJs) => float = "findX";
-
-  [@bs.module "./CdfLibrary.js"]
-  external integral: distJs => float = "integral";
-
-  [@bs.module "./CdfLibrary.js"]
-  external differentialEntropy: (int, distJs) => distJs =
-    "differentialEntropy";
-
-  [@bs.module "./CdfLibrary.js"]
-  external convertToNewLength: (int, distJs) => distJs = "convertToNewLength";
-};
-
-module Distribution = {
-  let convertToNewLength = (int, {xs, _} as dist: DistTypes.xyShape) =>
-    switch (E.A.length(xs)) {
-    | 0
-    | 1 => dist
-    | _ => dist |> JS.doAsDist(JS.convertToNewLength(int))
-    };
-  let toPdf = dist => dist |> JS.doAsDist(JS.cdfToPdf);
-  let toCdf = dist => dist |> JS.doAsDist(JS.pdfToCdf);
-  let findX = (y, dist) => dist |> JS.distToJs |> JS.findX(y);
-  let findY = (x, dist) => dist |> JS.distToJs |> JS.findY(x);
-  let integral = dist => dist |> JS.distToJs |> JS.integral;
-  let differentialEntropy = (maxCalculationLength, dist) =>
-    dist
-    |> JS.doAsDist(JS.differentialEntropy(maxCalculationLength))
-    |> integral;
-};

src/utility/E.re

@@ -1,5 +1,31 @@
 open Rationale.Function.Infix;
 
+module FloatFloatMap = {
+  module Id =
+    Belt.Id.MakeComparable({
+      type t = float;
+      let cmp: (float, float) => int = Pervasives.compare;
+    });
+
+  type t = Belt.MutableMap.t(Id.t, float, Id.identity);
+
+  let fromArray = (ar: array((float, float))) =>
+    Belt.MutableMap.fromArray(ar, ~id=(module Id));
+  let toArray = (t: t) => Belt.MutableMap.toArray(t);
+  let empty = () => Belt.MutableMap.make(~id=(module Id));
+  let increment = (el, t: t) =>
+    Belt.MutableMap.update(
+      t,
+      el,
+      fun
+      | Some(n) => Some(n +. 1.0)
+      | None => Some(1.0),
+    );
+
+  let get = (el, t: t) => Belt.MutableMap.get(t, el);
+  let fmap = (fn, t: t) => Belt.MutableMap.map(t, fn);
+};
+
 /* Utils */
 module U = {
   let isEqual = (a, b) => a == b;
@@ -298,6 +324,39 @@ module A = {
       };
     };
   };
+
+  module Floats = {
+    let split = (sortedArray: array(float)) => {
+      let continuous = [||];
+      let discrete = 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
+            ? FloatFloatMap.increment(element, discrete)
+            : {
+              let _ = Js.Array.push(element, continuous);
+              ();
+            };
+          ();
+        },
+      );
+
+      (continuous, discrete);
+    };
+  };
 };
 
 module JsArray = {

src/utility/Guesstimator.re

@@ -1,4 +1,3 @@
-module Internals = {
 [@bs.deriving abstract]
 type discrete = {
   xs: array(float),
@@ -10,177 +9,5 @@ module Internals = {
   ys: ysGet(d),
 };
 
-  [@bs.deriving abstract]
-  type combined = {
-    continuous: CdfLibrary.JS.distJs,
-    discrete,
-  };
-
-  // todo: Force to be fewer samples
-  let toContinous = (r: combined) =>
-    continuousGet(r)
-    |> CdfLibrary.JS.jsToDist
-    |> Distributions.Continuous.fromShape;
-
-  let toDiscrete = (r: combined): DistTypes.xyShape =>
-    discreteGet(r) |> jsToDistDiscrete;
-
-  [@bs.module "./GuesstimatorLibrary.js"]
-  external toCombinedFormat: (string, int, int, int) => combined = "run";
-
 [@bs.module "./GuesstimatorLibrary.js"]
 external stringToSamples: (string, int) => array(float) = "stringToSamples";
-
-  [@bs.module "./GuesstimatorLibrary.js"]
-  external samplesToContinuousPdf:
-    (array(float), int, int) => CdfLibrary.JS.distJs =
-    "samplesToContinuousPdf";
-};
-
-module KDE = {
-  let normalSampling = (samples, outputXYPoints, kernelWidth) => {
-    samples
-    |> Internals.samplesToContinuousPdf(_, outputXYPoints, kernelWidth)
-    |> CdfLibrary.JS.jsToDist;
-  };
-
-  let inGroups = (samples, outputXYPoints, kernelWidth, ~cuttoff=0.9, ()) => {
-    let partitionAt =
-      samples
-      |> E.A.length
-      |> float_of_int
-      |> (e => e *. cuttoff)
-      |> int_of_float;
-    let part1XYPoints =
-      outputXYPoints |> float_of_int |> (e => e *. cuttoff) |> int_of_float;
-    let part2XYPoints = outputXYPoints - part1XYPoints |> Js.Math.max_int(30);
-    let part1Data =
-      samples |> Belt.Array.slice(_, ~offset=0, ~len=partitionAt);
-    let part2DataLength = (samples |> E.A.length) - partitionAt;
-    let part2Data =
-      samples
-      |> Belt.Array.slice(
-           _,
-           ~offset=(-1) * part2DataLength,
-           ~len=part2DataLength,
-         );
-    let part1 =
-      part1Data
-      |> Internals.samplesToContinuousPdf(_, part1XYPoints, kernelWidth)
-      |> CdfLibrary.JS.jsToDist;
-    let part2 =
-      part2Data
-      |> Internals.samplesToContinuousPdf(_, part2XYPoints, 3)
-      |> CdfLibrary.JS.jsToDist;
-    let opp = 1.0 -. cuttoff;
-    // let result =
-    //   XYShape.T.Combine.combineLinear(
-    //     part1,
-    //     part2,
-    //     (a, b) => {
-    //       let aa = a *. cuttoff;
-    //       let bb = b *. opp;
-    //       aa +. bb;
-    //     },
-    //   );
-    // Js.log2("HI", result);
-    // result;
-    part1;
-  };
-};
-
-module FloatFloatMap = {
-  module Id =
-    Belt.Id.MakeComparable({
-      type t = float;
-      let cmp: (float, float) => int = Pervasives.compare;
-    });
-
-  type t = Belt.MutableMap.t(Id.t, float, Id.identity);
-
-  let fromArray = (ar: array((float, float))) =>
-    Belt.MutableMap.fromArray(ar, ~id=(module Id));
-  let toArray = (t: t) => Belt.MutableMap.toArray(t);
-  let empty = () => Belt.MutableMap.make(~id=(module Id));
-  let increment = (el, t: t) =>
-    Belt.MutableMap.update(
-      t,
-      el,
-      fun
-      | Some(n) => Some(n +. 1.0)
-      | None => Some(1.0),
-    );
-
-  let get = (el, t: t) => Belt.MutableMap.get(t, el);
-  let fmap = (fn, t: t) => Belt.MutableMap.map(t, fn);
-};
-
-// todo: Figure out some way of doing this without creating a new array.
-let split = (sortedArray: array(float)) => {
-  let continuous = [||];
-  let discrete = 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
-        ? FloatFloatMap.increment(element, discrete)
-        : {
-          let _ = Js.Array.push(element, continuous);
-          ();
-        };
-      ();
-    },
-  );
-
-  (continuous, discrete);
-};
-
-let toMixed =
-    (
-      ~string,
-      ~sampleCount=3000,
-      ~outputXYPoints=3000,
-      ~kernelWidth=10,
-      ~cuttoff=0.995,
-      (),
-    ) => {
-  let start = Js.Date.now();
-  let timeMessage = message => Js.log2(message, Js.Date.now() -. start);
-  timeMessage("Starting");
-  let samples = Internals.stringToSamples(string, sampleCount);
-  timeMessage("Finished sampling");
-
-  let length = samples |> E.A.length;
-  Array.fast_sort(compare, samples);
-  let (continuousPart, disc) = split(samples);
-  let lengthFloat = float_of_int(length);
-  let discrete: DistTypes.xyShape =
-    disc
-    |> FloatFloatMap.fmap(r => r /. lengthFloat)
-    |> FloatFloatMap.toArray
-    |> XYShape.T.fromZippedArray;
-  let pdf: DistTypes.xyShape =
-    continuousPart |> E.A.length > 20
-      ? {
-        // samples |> KDE.inGroups(_, outputXYPoints, kernelWidth, ~cuttoff, ());
-        samples |> KDE.normalSampling(_, outputXYPoints, kernelWidth);
-      }
-      : {xs: [||], ys: [||]};
-  timeMessage("Finished pdf");
-  let continuous = pdf |> Distributions.Continuous.fromShape;
-  let shape = MixedShapeBuilder.buildSimple(~continuous, ~discrete);
-  timeMessage("Finished shape");
-  shape;
-};

src/utility/GuesstimatorLibrary.js

@@ -1,89 +1,5 @@
-const {
-  Samples,
-} = require("@foretold/cdf/lib/samples");
 const _ = require("lodash");
 const { Guesstimator } = require('@foretold/guesstimator/src');
-const pdfast = require('pdfast');
-
-/**
- * @param values
- * @param outputResolutionCount
- * @param min
- * @param max
- * @returns {{discrete: {ys: *, xs: *}, continuous: {ys: [], xs: []}}}
- */
-const toPdf = (values, outputResolutionCount, width, 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: _(values).filter(x => x == s).size() / totalLength
-  }));
-  let continuousSamples = _.difference(values, frequencies.map(f => f.value));
-
-  let discrete = {
-    xs: frequencies.map(f => f.value),
-    ys: frequencies.map(f => f.percentage)
-  };
-  let continuous = { ys: [], xs: [] };
-
-  if (continuousSamples.length > 20) {
-    // let c = continuousSamples.map( r => (Math.log2(r)) * 1000);
-    let c = continuousSamples;
-    const samples = new Samples(c);
-
-    
-    const pdf = samples.toPdf({ size: outputResolutionCount, width, min, max });
-    // continuous = {xs: pdf.xs.map(r => Math.pow(2,r/1000)), ys: pdf.ys};
-    continuous = pdf;
-  }
-
-  return { continuous, discrete };
-};
-
-/**
- * @param text
- * @param sampleCount
- * @param outputResolutionCount
- * @param inputs
- * @param min
- * @param max
- * @returns {{discrete: {ys: *, xs: *}, continuous: {ys: *[], xs: *[]}}}
- */
-const run = (
-  text,
-  sampleCount,
-  outputResolutionCount,
-  width,
-  inputs = [],
-  min = false,
-  max = false,
-) => {
-  const [_error, item] = Guesstimator.parse({ text: "=" + text });
-  const { parsedInput } = item;
-
-  const guesstimator = new Guesstimator({ parsedInput });
-  const value = guesstimator.sample(
-    sampleCount,
-    inputs,
-  );
-
-  const values = _.filter(value.values, _.isFinite);
-
-  let update;
-  let blankResponse = {
-    continuous: { ys: [], xs: [] },
-    discrete: { ys: [], xs: [] }
-  };
-  if (values.length === 0) {
-    update = blankResponse;
-  } else if (values.length === 1) {
-    update = blankResponse;
-  } else {
-    update = toPdf(values, outputResolutionCount, width, min, max);
-  }
-  return update;
-};
 
 const stringToSamples = (
   text,
@@ -104,23 +20,6 @@ const stringToSamples = (
   }
 };
 
-
-const samplesToContinuousPdf = (
-  samples,
-  size,
-  width,
-  min = false,
-  max = false,
-) => {
-  let _samples = _.filter(samples, _.isFinite);
-  if (_.isFinite(min)) { _samples = _.filter(_samples, r => r > min) };
-  if (_.isFinite(max)) { _samples = _.filter(_samples, r => r < max) };
-  let pdf = pdfast.create(_samples, { size, width });
-  return {xs: pdf.map(r => r.x), ys: pdf.map(r => r.y)};
-};
-
 module.exports = {
-  run,
   stringToSamples,
-  samplesToContinuousPdf
 };

src/utility/KdeLibrary.js

@@ -0,0 +1,21 @@
+const pdfast = require('pdfast');
+const _ = require("lodash");
+
+const samplesToContinuousPdf = (
+  samples,
+  size,
+  width,
+  min = false,
+  max = false,
+) => {
+  let _samples = _.filter(samples, _.isFinite);
+  if (_.isFinite(min)) { _samples = _.filter(_samples, r => r > min) };
+  if (_.isFinite(max)) { _samples = _.filter(_samples, r => r < max) };
+  let pdf = pdfast.create(_samples, { size, width });
+  return {xs: pdf.map(r => r.x), ys: pdf.map(r => r.y)};
+};
+
+
+module.exports = {
+  samplesToContinuousPdf,
+};