Added native logScoring and related functionality to XYShape

__tests__/XYShape__Test.re

@@ -0,0 +1,43 @@
+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)
+      );
+
+let shape1: DistTypes.xyShape = {xs: [|1., 4., 8.|], ys: [|0.2, 0.4, 0.8|]};
+
+let shape2: DistTypes.xyShape = {
+  xs: [|1., 5., 10.|],
+  ys: [|0.2, 0.5, 0.8|],
+};
+
+let shape3: DistTypes.xyShape = {
+  xs: [|1., 20., 50.|],
+  ys: [|0.2, 0.5, 0.8|],
+};
+
+describe("XYShapes", () => {
+  describe("logScorePoint", () => {
+    makeTest(
+      "When identical",
+      XYShape.logScorePoint(30, shape1, shape1),
+      Some(0.0),
+    );
+    makeTest(
+      "When similar",
+      XYShape.logScorePoint(30, shape1, shape2),
+      Some(1.658971191043856),
+    );
+    makeTest(
+      "When very different",
+      XYShape.logScorePoint(30, shape1, shape3),
+      Some(210.3721280423322),
+    );
+  })
+});

src/components/charts/DistributionPlot/DistributionPlot.re

@@ -134,12 +134,12 @@ let make =
       ?xScale
       ?yScale
       ?timeScale
-      discrete={discrete |> E.O.fmap(XYShape.toJs)}
+      discrete={discrete |> E.O.fmap(XYShape.T.toJs)}
       height
       marginBottom=50
       marginTop=0
       onHover
-      continuous={continuous |> E.O.fmap(XYShape.toJs)}
+      continuous={continuous |> E.O.fmap(XYShape.T.toJs)}
       showDistributionLines
       showDistributionYAxis
       showVerticalLine

src/distributions/Distributions.re

@@ -82,7 +82,7 @@ module Continuous = {
     interpolation,
   };
   let lastY = (t: t) =>
-    t |> xyShape |> XYShape.unsafeLast |> (((_, y)) => y);
+    t |> xyShape |> XYShape.T.unsafeLast |> (((_, y)) => y);
   let oShapeMap =
       (fn, {xyShape, interpolation}: t): option(DistTypes.continuousShape) =>
     fn(xyShape) |> E.O.fmap(make(_, interpolation));
@@ -105,22 +105,22 @@ module Continuous = {
     Dist({
       type t = DistTypes.continuousShape;
       type integral = DistTypes.continuousShape;
-      let minX = shapeFn(XYShape.minX);
-      let maxX = shapeFn(XYShape.maxX);
+      let minX = shapeFn(XYShape.T.minX);
+      let maxX = shapeFn(XYShape.T.maxX);
       let toDiscreteProbabilityMass = _ => 0.0;
       let pointwiseFmap = (fn, t: t) =>
-        t |> xyShape |> XYShape.pointwiseMap(fn) |> fromShape;
+        t |> xyShape |> XYShape.T.pointwiseMap(fn) |> fromShape;
       let toShape = (t: t): DistTypes.shape => Continuous(t);
       let xToY = (f, {interpolation, xyShape}: t) =>
         switch (interpolation) {
         | `Stepwise =>
           xyShape
-          |> XYShape.XtoY.stepwiseIncremental(f)
+          |> XYShape.T.XtoY.stepwiseIncremental(f)
           |> E.O.default(0.0)
           |> DistTypes.MixedPoint.makeContinuous
         | `Linear =>
           xyShape
-          |> XYShape.XtoY.linear(f)
+          |> XYShape.T.XtoY.linear(f)
           |> DistTypes.MixedPoint.makeContinuous
         };
 
@@ -161,14 +161,14 @@ module Discrete = {
       let integral = (~cache, t) =>
         switch (cache) {
         | Some(c) => c
-        | None => Continuous.make(XYShape.accumulateYs(t), `Stepwise)
+        | None => Continuous.make(XYShape.T.accumulateYs(t), `Stepwise)
         };
       let integralEndY = (~cache, t) =>
         t |> integral(~cache) |> Continuous.lastY;
-      let minX = XYShape.minX;
-      let maxX = XYShape.maxX;
+      let minX = XYShape.T.minX;
+      let maxX = XYShape.T.maxX;
       let toDiscreteProbabilityMass = t => 1.0;
-      let pointwiseFmap = XYShape.pointwiseMap;
+      let pointwiseFmap = XYShape.T.pointwiseMap;
       let toShape = (t: t): DistTypes.shape => Discrete(t);
       let toContinuous = _ => None;
       let toDiscrete = t => Some(t);
@@ -176,7 +176,7 @@ module Discrete = {
       let toScaledDiscrete = t => Some(t);
 
       let xToY = (f, t) => {
-        XYShape.XtoY.stepwiseIfAtX(f, t)
+        XYShape.T.XtoY.stepwiseIfAtX(f, t)
         |> E.O.default(0.0)
         |> DistTypes.MixedPoint.makeDiscrete;
       };
@@ -294,7 +294,7 @@ module Mixed = {
 
           let result =
             Continuous.make(
-              XYShape.Combine.combineLinear(
+              XYShape.T.Combine.combineLinear(
                 Continuous.getShape(cont), Continuous.getShape(dist), (a, b) =>
                 a +. b
               ),

src/distributions/MixedShapeBuilder.re

@@ -10,8 +10,11 @@ type assumptions = {
 
 let buildSimple = (~continuous, ~discrete): option(DistTypes.shape) => {
   let cLength =
-    continuous |> Distributions.Continuous.getShape |> XYShape.xs |> E.A.length;
-  let dLength = discrete |> XYShape.xs |> E.A.length;
+    continuous
+    |> Distributions.Continuous.getShape
+    |> XYShape.T.xs
+    |> E.A.length;
+  let dLength = discrete |> XYShape.T.xs |> E.A.length;
   switch (cLength, dLength) {
   | (0 | 1, 0) => None
   | (0 | 1, _) => Some(Discrete(discrete))

src/distributions/XYShape.re

@@ -1,6 +1,8 @@
 open DistTypes;
 
+module T = {
   type t = xyShape;
+  type ts = array(xyShape);
 
   let toJs = (t: t) => {
     {"xs": t.xs, "ys": t.ys};
@@ -115,7 +117,6 @@ let comparePoints = ((x1: float, y1: float), (x2: float, y2: float)) =>
 
   // todo: This is broken :(
   let combine = (t1: t, t2: t) => {
-  let totalLength = E.A.length(t1.xs) + E.A.length(t2.xs);
     let array = Belt.Array.concat(zip(t1), zip(t2));
     Array.sort(comparePoints, array);
     array |> Belt.Array.unzip |> fromArray;
@@ -144,7 +145,8 @@ let ySum = yFold((a, b) => a +. b);
   let _transverse = fn =>
     Belt.Array.reduce(_, [||], (items, (x, y)) =>
       switch (E.A.last(items)) {
-    | Some((_, yLast)) => Belt.Array.concat(items, [|(x, fn(y, yLast))|])
+      | Some((_, yLast)) =>
+        Belt.Array.concat(items, [|(x, fn(y, yLast))|])
       | None => [|(x, y)|]
       }
     );
@@ -164,6 +166,7 @@ let subtractYs = _transverseShape((aCurrent, aLast) => aCurrent -. aLast);
 
   let findY = CdfLibrary.Distribution.findY;
   let findX = CdfLibrary.Distribution.findX;
+};
 
 // I'm really not sure this part is actually what we want at this point.
 module Range = {
@@ -171,7 +174,7 @@ module Range = {
   type zippedRange = ((float, float), (float, float));
 
   let floatSum = Belt.Array.reduce(_, 0., (a, b) => a +. b);
-  let toT = r => r |> Belt.Array.unzip |> fromArray;
+  let toT = r => r |> Belt.Array.unzip |> T.fromArray;
   let nextX = ((_, (nextX, _)): zippedRange) => nextX;
 
   let rangePointAssumingSteps =
@@ -197,21 +200,21 @@ module Range = {
   let integrateWithTriangles = z => {
     let rangeItems = mapYsBasedOnRanges(rangeAreaAssumingTriangles, z);
     (
-      switch (rangeItems, z |> first) {
+      switch (rangeItems, z |> T.first) {
       | (Some(r), Some((firstX, _))) =>
         Some(Belt.Array.concat([|(firstX, 0.0)|], r))
       | _ => None
       }
     )
     |> E.O.fmap(toT)
-    |> E.O.fmap(accumulateYs);
+    |> E.O.fmap(T.accumulateYs);
   };
 
   let derivative = mapYsBasedOnRanges(delta_y_over_delta_x);
 
   // TODO: It would be nicer if this the diff didn't change the first element, and also maybe if there were a more elegant way of doing this.
   let stepsToContinuous = t => {
-    let diff = xTotalRange(t) |> E.O.fmap(r => r *. 0.00001);
+    let diff = T.xTotalRange(t) |> E.O.fmap(r => r *. 0.00001);
     let items =
       switch (diff, E.A.toRanges(Belt.Array.zip(t.xs, t.ys))) {
       | (Some(diff), Ok(items)) =>
@@ -219,21 +222,57 @@ module Range = {
           items
           |> Belt.Array.map(_, rangePointAssumingSteps)
           |> Belt.Array.unzip
-          |> fromArray
-          |> intersperce(t |> xMap(e => e +. diff)),
+          |> T.fromArray
+          |> T.intersperce(t |> T.xMap(e => e +. diff)),
         )
       | _ => Some(t)
       };
-    let bar = items |> E.O.fmap(zip) |> E.O.bind(_, E.A.get(_, 0));
+    let bar = items |> E.O.fmap(T.zip) |> E.O.bind(_, E.A.get(_, 0));
     let items =
       switch (items, bar) {
       | (Some(items), Some((0.0, _))) => Some(items)
       | (Some(items), Some((firstX, _))) =>
-        let all = E.A.append([|(firstX, 0.0)|], items |> zip);
-        let foo = all |> Belt.Array.unzip |> fromArray;
+        let all = E.A.append([|(firstX, 0.0)|], items |> T.zip);
+        let foo = all |> Belt.Array.unzip |> T.fromArray;
         Some(foo);
       | _ => None
       };
     items;
   };
 };
+
+module Ts = {
+  type t = T.ts;
+  let minX = (t: t) =>
+    t |> E.A.fmap(T.minX) |> E.A.O.concatSomes |> Functions.min;
+  let maxX = (t: t) =>
+    t |> E.A.fmap(T.maxX) |> E.A.O.concatSomes |> Functions.max;
+
+  // TODO/Warning: This will break if the shapes are empty.
+  let equallyDividedXs = (t: t, newLength) => {
+    Functions.range(minX(t), maxX(t), newLength);
+  };
+};
+
+let combinePointwise = (fn, sampleCount, t1: xyShape, t2: xyShape) => {
+  let xs = Ts.equallyDividedXs([|t1, t2|], sampleCount);
+  let ys =
+    xs |> E.A.fmap(x => fn(T.XtoY.linear(x, t1), T.XtoY.linear(x, t2)));
+  T.fromArrays(xs, ys);
+};
+
+let logScoreDist =
+  combinePointwise((prediction, answer) =>
+    switch (answer) {
+    | 0. => 0.0
+    | answer =>
+      answer *. Js.Math.log2(Js.Math.abs_float(prediction /. answer))
+    }
+  );
+
+let logScorePoint = (sampleCount, t1, t2) =>
+  logScoreDist(sampleCount, t1, t2)
+  |> Range.integrateWithTriangles
+  |> E.O.fmap(T.accumulateYs)
+  |> E.O.bind(_, T.last)
+  |> E.O.fmap(((_, y)) => y);