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Added native logScoring and related functionality to XYShape

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This commit is contained in:
Ozzie Gooen 2020-03-14 21:18:34 +00:00
parent f887af22ea
commit a99415e5bc
7 changed files with 258 additions and 173 deletions
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0
__tests__/Foo/DistTypes__Test.re → __tests__/DistTypes__Test.re
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0
__tests__/Foo/Foo__Test.re → __tests__/Distributions__Test.re
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43
__tests__/XYShape__Test.re Normal file
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@ -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),
);
})
});

4
src/components/charts/DistributionPlot/DistributionPlot.re
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@ -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

24
src/distributions/Distributions.re
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@ -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
),

7
src/distributions/MixedShapeBuilder.re
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@ -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))

145
src/distributions/XYShape.re
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@ -1,36 +1,38 @@
open DistTypes;
type t = xyShape;
module T = {
type t = xyShape;
type ts = array(xyShape);
let toJs = (t: t) => {
let toJs = (t: t) => {
{"xs": t.xs, "ys": t.ys};
};
let xs = (t: t) => t.xs;
let minX = (t: t) => t |> xs |> E.A.first;
let maxX = (t: t) => t |> xs |> E.A.last;
let xTotalRange = (t: t) =>
};
let xs = (t: t) => t.xs;
let minX = (t: t) => t |> xs |> E.A.first;
let maxX = (t: t) => t |> xs |> E.A.last;
let xTotalRange = (t: t) =>
switch (minX(t), maxX(t)) {
| (Some(min), Some(max)) => Some(max -. min)
| _ => None
};
let first = ({xs, ys}: t) =>
let first = ({xs, ys}: t) =>
switch (xs |> E.A.first, ys |> E.A.first) {
| (Some(x), Some(y)) => Some((x, y))
| _ => None
};
let last = ({xs, ys}: t) =>
let last = ({xs, ys}: t) =>
switch (xs |> E.A.last, ys |> E.A.last) {
| (Some(x), Some(y)) => Some((x, y))
| _ => None
};
let unsafeFirst = (t: t) => first(t) |> E.O.toExn("Unsafe operation");
let unsafeLast = (t: t) => last(t) |> E.O.toExn("Unsafe operation");
let unsafeFirst = (t: t) => first(t) |> E.O.toExn("Unsafe operation");
let unsafeLast = (t: t) => last(t) |> E.O.toExn("Unsafe operation");
let zip = ({xs, ys}: t) => Belt.Array.zip(xs, ys);
let getBy = (t: t, fn) => t |> zip |> Belt.Array.getBy(_, fn);
let zip = ({xs, ys}: t) => Belt.Array.zip(xs, ys);
let getBy = (t: t, fn) => t |> zip |> Belt.Array.getBy(_, fn);
let firstPairAtOrBeforeValue = (xValue, t: t) => {
let firstPairAtOrBeforeValue = (xValue, t: t) => {
let zipped = zip(t);
let firstIndex =
zipped |> Belt.Array.getIndexBy(_, ((x, y)) => x > xValue);
@ -41,9 +43,9 @@ let firstPairAtOrBeforeValue = (xValue, t: t) => {
| Some(n) => Some(n - 1)
};
previousIndex |> Belt.Option.flatMap(_, Belt.Array.get(zipped));
};
};
module XtoY = {
module XtoY = {
let stepwiseIncremental = (f, t: t) =>
firstPairAtOrBeforeValue(f, t) |> E.O.fmap(((_, y)) => y);
@ -53,14 +55,14 @@ module XtoY = {
// TODO: When Roman's PR comes in, fix this bit. This depends on interpolation, obviously.
let linear = (f, t: t) => t |> CdfLibrary.Distribution.findY(f);
};
};
let pointwiseMap = (fn, t: t): t => {xs: t.xs, ys: t.ys |> E.A.fmap(fn)};
let xMap = (fn, t: t): t => {xs: E.A.fmap(fn, t.xs), ys: t.ys};
let fromArray = ((xs, ys)): t => {xs, ys};
let fromArrays = (xs, ys): t => {xs, ys};
let pointwiseMap = (fn, t: t): t => {xs: t.xs, ys: t.ys |> E.A.fmap(fn)};
let xMap = (fn, t: t): t => {xs: E.A.fmap(fn, t.xs), ys: t.ys};
let fromArray = ((xs, ys)): t => {xs, ys};
let fromArrays = (xs, ys): t => {xs, ys};
module Combine = {
module Combine = {
let combineLinear = (t1: t, t2: t, fn: (float, float) => float) => {
let allXs = Belt.Array.concat(xs(t1), xs(t2));
allXs |> Array.sort(compare);
@ -101,27 +103,26 @@ module Combine = {
});
fromArrays(allXs, allYs);
};
};
};
// todo: maybe not needed?
// let comparePoint = (a: float, b: float) => a > b ? 1 : (-1);
// todo: maybe not needed?
// let comparePoint = (a: float, b: float) => a > b ? 1 : (-1);
let comparePoints = ((x1: float, y1: float), (x2: float, y2: float)) =>
let comparePoints = ((x1: float, y1: float), (x2: float, y2: float)) =>
switch (x1 == x2, y1 == y2) {
| (false, _) => compare(x1, x2)
| (true, false) => compare(y1, y2)
| (true, true) => (-1)
};
// todo: This is broken :(
let combine = (t1: t, t2: t) => {
let totalLength = E.A.length(t1.xs) + E.A.length(t2.xs);
// todo: This is broken :(
let combine = (t1: t, t2: t) => {
let array = Belt.Array.concat(zip(t1), zip(t2));
Array.sort(comparePoints, array);
array |> Belt.Array.unzip |> fromArray;
};
};
let intersperce = (t1: t, t2: t) => {
let intersperce = (t1: t, t2: t) => {
let items: ref(array((float, float))) = ref([||]);
let t1 = zip(t1);
let t2 = zip(t2);
@ -133,37 +134,39 @@ let intersperce = (t1: t, t2: t) => {
}
});
items^ |> Belt.Array.unzip |> fromArray;
};
};
let yFold = (fn, t: t) => {
let yFold = (fn, t: t) => {
E.A.fold_left(fn, 0., t.ys);
};
};
let ySum = yFold((a, b) => a +. b);
let ySum = yFold((a, b) => a +. b);
let _transverse = fn =>
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)|]
}
);
let _transverseShape = (fn, p: t) => {
let _transverseShape = (fn, p: t) => {
Belt.Array.zip(p.xs, p.ys)
|> _transverse(fn)
|> Belt.Array.unzip
|> fromArray;
};
};
let filter = (fn, t: t) =>
let filter = (fn, t: t) =>
t |> zip |> E.A.filter(fn) |> Belt.Array.unzip |> fromArray;
let accumulateYs = _transverseShape((aCurrent, aLast) => aCurrent +. aLast);
let subtractYs = _transverseShape((aCurrent, aLast) => aCurrent -. aLast);
let accumulateYs = _transverseShape((aCurrent, aLast) => aCurrent +. aLast);
let subtractYs = _transverseShape((aCurrent, aLast) => aCurrent -. aLast);
let findY = CdfLibrary.Distribution.findY;
let findX = CdfLibrary.Distribution.findX;
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);