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Added old version, to start playground integration

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Ozzie Gooen 2022-02-06 14:25:51 -05:00
parent 584159af42
commit 306f273a74
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16
packages/squiggle-old/.gitignore vendored Normal file
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.DS_Store
.merlin
.bsb.lock
npm-debug.log
/node_modules/
.cache
.cache/*
dist
lib/*
*.cache
build
yarn-error.log
*.bs.js
# Local Netlify folder
.netlify
.idea

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MIT License
Copyright (c) 2020 Foretold
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

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# Squiggle
This is an experiment DSL/language for making probabilistic estimates.
## DistPlus
We have a custom library called DistPlus to handle distributions with additional metadata. This helps handle mixed distributions (continuous + discrete), a cache for a cdf, possible unit types (specific times are supported), and limited domains.
## Running
Currently it only has a few very simple models.
```
yarn
yarn run start
yarn run parcel
```
## Expected future setup
![setup](https://raw.githubusercontent.com/foretold-app/widedomain/master/Screen%20Shot%202020-06-30%20at%208.27.32%20AM.png)

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packages/squiggle-old/__tests__/Bandwidth__Test.re Normal file
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open Jest;
open Expect;
describe("Bandwidth", () => {
test("nrd0()", () => {
let data = [|1., 4., 3., 2.|];
expect(Bandwidth.nrd0(data)) |> toEqual(0.7625801874014622);
});
test("nrd()", () => {
let data = [|1., 4., 3., 2.|];
expect(Bandwidth.nrd(data)) |> toEqual(0.8981499984950554);
});
});

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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("DistTypes", () => {
describe("Domain", () => {
let makeComplete = (yPoint, expectation) =>
makeTest(
"With input: " ++ Js.Float.toString(yPoint),
DistTypes.Domain.yPointToSubYPoint(Complete, yPoint),
expectation,
);
let makeSingle =
(
direction: [ | `left | `right],
excludingProbabilityMass,
yPoint,
expectation,
) =>
makeTest(
"Excluding: "
++ Js.Float.toString(excludingProbabilityMass)
++ " and yPoint: "
++ Js.Float.toString(yPoint),
DistTypes.Domain.yPointToSubYPoint(
direction == `left
? LeftLimited({xPoint: 3.0, excludingProbabilityMass})
: RightLimited({xPoint: 3.0, excludingProbabilityMass}),
yPoint,
),
expectation,
);
let makeDouble = (domain, yPoint, expectation) =>
makeTest(
"Excluding: limits",
DistTypes.Domain.yPointToSubYPoint(domain, yPoint),
expectation,
);
describe("With Complete Domain", () => {
makeComplete(0.0, Some(0.0));
makeComplete(0.6, Some(0.6));
makeComplete(1.0, Some(1.0));
});
describe("With Left Limit", () => {
makeSingle(`left, 0.5, 1.0, Some(1.0));
makeSingle(`left, 0.5, 0.75, Some(0.5));
makeSingle(`left, 0.8, 0.9, Some(0.5));
makeSingle(`left, 0.5, 0.4, None);
makeSingle(`left, 0.5, 0.5, Some(0.0));
});
describe("With Right Limit", () => {
makeSingle(`right, 0.5, 1.0, None);
makeSingle(`right, 0.5, 0.25, Some(0.5));
makeSingle(`right, 0.8, 0.5, None);
makeSingle(`right, 0.2, 0.2, Some(0.25));
makeSingle(`right, 0.5, 0.5, Some(1.0));
makeSingle(`right, 0.5, 0.0, Some(0.0));
makeSingle(`right, 0.5, 0.5, Some(1.0));
});
describe("With Left and Right Limit", () => {
makeDouble(
LeftAndRightLimited(
{excludingProbabilityMass: 0.25, xPoint: 3.0},
{excludingProbabilityMass: 0.25, xPoint: 10.0},
),
0.5,
Some(0.5),
);
makeDouble(
LeftAndRightLimited(
{excludingProbabilityMass: 0.1, xPoint: 3.0},
{excludingProbabilityMass: 0.1, xPoint: 10.0},
),
0.2,
Some(0.125),
);
makeDouble(
LeftAndRightLimited(
{excludingProbabilityMass: 0.1, xPoint: 3.0},
{excludingProbabilityMass: 0.1, xPoint: 10.0},
),
0.1,
Some(0.0),
);
makeDouble(
LeftAndRightLimited(
{excludingProbabilityMass: 0.1, xPoint: 3.0},
{excludingProbabilityMass: 0.1, xPoint: 10.0},
),
0.05,
None,
);
});
})
});

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open Jest;
open Expect;
let shape: DistTypes.xyShape = {xs: [|1., 4., 8.|], ys: [|8., 9., 2.|]};
// let makeTest = (~only=false, str, item1, item2) =>
// only
// ? Only.test(str, () =>
// expect(item1) |> toEqual(item2)
// )
// : test(str, () =>
// expect(item1) |> toEqual(item2)
// );
// let makeTestCloseEquality = (~only=false, str, item1, item2, ~digits) =>
// only
// ? Only.test(str, () =>
// expect(item1) |> toBeSoCloseTo(item2, ~digits)
// )
// : test(str, () =>
// expect(item1) |> toBeSoCloseTo(item2, ~digits)
// );
// describe("Shape", () => {
// describe("Continuous", () => {
// open Continuous;
// let continuous = make(`Linear, shape, None);
// makeTest("minX", T.minX(continuous), 1.0);
// makeTest("maxX", T.maxX(continuous), 8.0);
// makeTest(
// "mapY",
// T.mapY(r => r *. 2.0, continuous) |> getShape |> (r => r.ys),
// [|16., 18.0, 4.0|],
// );
// describe("xToY", () => {
// describe("when Linear", () => {
// makeTest(
// "at 4.0",
// T.xToY(4., continuous),
// {continuous: 9.0, discrete: 0.0},
// );
// // Note: This below is weird to me, I'm not sure if it's what we want really.
// makeTest(
// "at 0.0",
// T.xToY(0., continuous),
// {continuous: 8.0, discrete: 0.0},
// );
// makeTest(
// "at 5.0",
// T.xToY(5., continuous),
// {continuous: 7.25, discrete: 0.0},
// );
// makeTest(
// "at 10.0",
// T.xToY(10., continuous),
// {continuous: 2.0, discrete: 0.0},
// );
// });
// describe("when Stepwise", () => {
// let continuous = make(`Stepwise, shape, None);
// makeTest(
// "at 4.0",
// T.xToY(4., continuous),
// {continuous: 9.0, discrete: 0.0},
// );
// makeTest(
// "at 0.0",
// T.xToY(0., continuous),
// {continuous: 0.0, discrete: 0.0},
// );
// makeTest(
// "at 5.0",
// T.xToY(5., continuous),
// {continuous: 9.0, discrete: 0.0},
// );
// makeTest(
// "at 10.0",
// T.xToY(10., continuous),
// {continuous: 2.0, discrete: 0.0},
// );
// });
// });
// makeTest(
// "integral",
// T.Integral.get(~cache=None, continuous) |> getShape,
// {xs: [|1.0, 4.0, 8.0|], ys: [|0.0, 25.5, 47.5|]},
// );
// makeTest(
// "toLinear",
// {
// let continuous =
// make(`Stepwise, {xs: [|1., 4., 8.|], ys: [|0.1, 5., 1.0|]}, None);
// continuous |> toLinear |> E.O.fmap(getShape);
// },
// Some({
// xs: [|1.00007, 1.00007, 4.0, 4.00007, 8.0, 8.00007|],
// ys: [|0.0, 0.1, 0.1, 5.0, 5.0, 1.0|],
// }),
// );
// makeTest(
// "toLinear",
// {
// let continuous = make(`Stepwise, {xs: [|0.0|], ys: [|0.3|]}, None);
// continuous |> toLinear |> E.O.fmap(getShape);
// },
// Some({xs: [|0.0|], ys: [|0.3|]}),
// );
// makeTest(
// "integralXToY",
// T.Integral.xToY(~cache=None, 0.0, continuous),
// 0.0,
// );
// makeTest(
// "integralXToY",
// T.Integral.xToY(~cache=None, 2.0, continuous),
// 8.5,
// );
// makeTest(
// "integralXToY",
// T.Integral.xToY(~cache=None, 100.0, continuous),
// 47.5,
// );
// makeTest(
// "integralEndY",
// continuous
// |> T.normalize //scaleToIntegralSum(~intendedSum=1.0)
// |> T.Integral.sum(~cache=None),
// 1.0,
// );
// });
// describe("Discrete", () => {
// open Discrete;
// let shape: DistTypes.xyShape = {
// xs: [|1., 4., 8.|],
// ys: [|0.3, 0.5, 0.2|],
// };
// let discrete = make(shape, None);
// makeTest("minX", T.minX(discrete), 1.0);
// makeTest("maxX", T.maxX(discrete), 8.0);
// makeTest(
// "mapY",
// T.mapY(r => r *. 2.0, discrete) |> (r => getShape(r).ys),
// [|0.6, 1.0, 0.4|],
// );
// makeTest(
// "xToY at 4.0",
// T.xToY(4., discrete),
// {discrete: 0.5, continuous: 0.0},
// );
// makeTest(
// "xToY at 0.0",
// T.xToY(0., discrete),
// {discrete: 0.0, continuous: 0.0},
// );
// makeTest(
// "xToY at 5.0",
// T.xToY(5., discrete),
// {discrete: 0.0, continuous: 0.0},
// );
// makeTest(
// "scaleBy",
// scaleBy(~scale=4.0, discrete),
// make({xs: [|1., 4., 8.|], ys: [|1.2, 2.0, 0.8|]}, None),
// );
// makeTest(
// "normalize, then scale by 4.0",
// discrete
// |> T.normalize
// |> scaleBy(~scale=4.0),
// make({xs: [|1., 4., 8.|], ys: [|1.2, 2.0, 0.8|]}, None),
// );
// makeTest(
// "scaleToIntegralSum: back and forth",
// discrete
// |> T.normalize
// |> scaleBy(~scale=4.0)
// |> T.normalize,
// discrete,
// );
// makeTest(
// "integral",
// T.Integral.get(~cache=None, discrete),
// Continuous.make(
// `Stepwise,
// {xs: [|1., 4., 8.|], ys: [|0.3, 0.8, 1.0|]},
// None
// ),
// );
// makeTest(
// "integral with 1 element",
// T.Integral.get(~cache=None, Discrete.make({xs: [|0.0|], ys: [|1.0|]}, None)),
// Continuous.make(`Stepwise, {xs: [|0.0|], ys: [|1.0|]}, None),
// );
// makeTest(
// "integralXToY",
// T.Integral.xToY(~cache=None, 6.0, discrete),
// 0.9,
// );
// makeTest("integralEndY", T.Integral.sum(~cache=None, discrete), 1.0);
// makeTest("mean", T.mean(discrete), 3.9);
// makeTestCloseEquality(
// "variance",
// T.variance(discrete),
// 5.89,
// ~digits=7,
// );
// });
// describe("Mixed", () => {
// open Distributions.Mixed;
// let discreteShape: DistTypes.xyShape = {
// xs: [|1., 4., 8.|],
// ys: [|0.3, 0.5, 0.2|],
// };
// let discrete = Discrete.make(discreteShape, None);
// let continuous =
// Continuous.make(
// `Linear,
// {xs: [|3., 7., 14.|], ys: [|0.058, 0.082, 0.124|]},
// None
// )
// |> Continuous.T.normalize; //scaleToIntegralSum(~intendedSum=1.0);
// let mixed = Mixed.make(
// ~continuous,
// ~discrete,
// );
// makeTest("minX", T.minX(mixed), 1.0);
// makeTest("maxX", T.maxX(mixed), 14.0);
// makeTest(
// "mapY",
// T.mapY(r => r *. 2.0, mixed),
// Mixed.make(
// ~continuous=
// Continuous.make(
// `Linear,
// {
// xs: [|3., 7., 14.|],
// ys: [|
// 0.11588411588411589,
// 0.16383616383616384,
// 0.24775224775224775,
// |],
// },
// None
// ),
// ~discrete=Discrete.make({xs: [|1., 4., 8.|], ys: [|0.6, 1.0, 0.4|]}, None)
// ),
// );
// makeTest(
// "xToY at 4.0",
// T.xToY(4., mixed),
// {discrete: 0.25, continuous: 0.03196803196803197},
// );
// makeTest(
// "xToY at 0.0",
// T.xToY(0., mixed),
// {discrete: 0.0, continuous: 0.028971028971028972},
// );
// makeTest(
// "xToY at 5.0",
// T.xToY(7., mixed),
// {discrete: 0.0, continuous: 0.04095904095904096},
// );
// makeTest("integralEndY", T.Integral.sum(~cache=None, mixed), 1.0);
// makeTest(
// "scaleBy",
// Mixed.scaleBy(~scale=2.0, mixed),
// Mixed.make(
// ~continuous=
// Continuous.make(
// `Linear,
// {
// xs: [|3., 7., 14.|],
// ys: [|
// 0.11588411588411589,
// 0.16383616383616384,
// 0.24775224775224775,
// |],
// },
// None
// ),
// ~discrete=Discrete.make({xs: [|1., 4., 8.|], ys: [|0.6, 1.0, 0.4|]}, None),
// ),
// );
// makeTest(
// "integral",
// T.Integral.get(~cache=None, mixed),
// Continuous.make(
// `Linear,
// {
// xs: [|1.00007, 1.00007, 3., 4., 4.00007, 7., 8., 8.00007, 14.|],
// ys: [|
// 0.0,
// 0.0,
// 0.15,
// 0.18496503496503497,
// 0.4349674825174825,
// 0.5398601398601399,
// 0.5913086913086913,
// 0.6913122927072927,
// 1.0,
// |],
// },
// None,
// ),
// );
// });
// describe("Distplus", () => {
// open DistPlus;
// let discreteShape: DistTypes.xyShape = {
// xs: [|1., 4., 8.|],
// ys: [|0.3, 0.5, 0.2|],
// };
// let discrete = Discrete.make(discreteShape, None);
// let continuous =
// Continuous.make(
// `Linear,
// {xs: [|3., 7., 14.|], ys: [|0.058, 0.082, 0.124|]},
// None
// )
// |> Continuous.T.normalize; //scaleToIntegralSum(~intendedSum=1.0);
// let mixed =
// Mixed.make(
// ~continuous,
// ~discrete,
// );
// let distPlus =
// DistPlus.make(
// ~shape=Mixed(mixed),
// ~squiggleString=None,
// (),
// );
// makeTest("minX", T.minX(distPlus), 1.0);
// makeTest("maxX", T.maxX(distPlus), 14.0);
// makeTest(
// "xToY at 4.0",
// T.xToY(4., distPlus),
// {discrete: 0.25, continuous: 0.03196803196803197},
// );
// makeTest(
// "xToY at 0.0",
// T.xToY(0., distPlus),
// {discrete: 0.0, continuous: 0.028971028971028972},
// );
// makeTest(
// "xToY at 5.0",
// T.xToY(7., distPlus),
// {discrete: 0.0, continuous: 0.04095904095904096},
// );
// makeTest("integralEndY", T.Integral.sum(~cache=None, distPlus), 1.0);
// makeTest(
// "integral",
// T.Integral.get(~cache=None, distPlus) |> T.toContinuous,
// Some(
// Continuous.make(
// `Linear,
// {
// xs: [|1.00007, 1.00007, 3., 4., 4.00007, 7., 8., 8.00007, 14.|],
// ys: [|
// 0.0,
// 0.0,
// 0.15,
// 0.18496503496503497,
// 0.4349674825174825,
// 0.5398601398601399,
// 0.5913086913086913,
// 0.6913122927072927,
// 1.0,
// |],
// },
// None,
// ),
// ),
// );
// });
// describe("Shape", () => {
// let mean = 10.0;
// let stdev = 4.0;
// let variance = stdev ** 2.0;
// let numSamples = 10000;
// open Distributions.Shape;
// let normal: SymbolicTypes.symbolicDist = `Normal({mean, stdev});
// let normalShape = ExpressionTree.toShape(numSamples, `SymbolicDist(normal));
// let lognormal = SymbolicDist.Lognormal.fromMeanAndStdev(mean, stdev);
// let lognormalShape = ExpressionTree.toShape(numSamples, `SymbolicDist(lognormal));
// makeTestCloseEquality(
// "Mean of a normal",
// T.mean(normalShape),
// mean,
// ~digits=2,
// );
// makeTestCloseEquality(
// "Variance of a normal",
// T.variance(normalShape),
// variance,
// ~digits=1,
// );
// makeTestCloseEquality(
// "Mean of a lognormal",
// T.mean(lognormalShape),
// mean,
// ~digits=2,
// );
// makeTestCloseEquality(
// "Variance of a lognormal",
// T.variance(lognormalShape),
// variance,
// ~digits=0,
// );
// });
// });

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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 evalParams: ExpressionTypes.ExpressionTree.evaluationParams = {
samplingInputs: {
sampleCount: 1000,
outputXYPoints: 10000,
kernelWidth: None,
shapeLength: 1000,
},
environment:
[|
("K", `SymbolicDist(`Float(1000.0))),
("M", `SymbolicDist(`Float(1000000.0))),
("B", `SymbolicDist(`Float(1000000000.0))),
("T", `SymbolicDist(`Float(1000000000000.0))),
|]
->Belt.Map.String.fromArray,
evaluateNode: ExpressionTreeEvaluator.toLeaf,
};
let shape1: DistTypes.xyShape = {xs: [|1., 4., 8.|], ys: [|0.2, 0.4, 0.8|]};
describe("XYShapes", () => {
describe("logScorePoint", () => {
makeTest(
"When identical",
{
let foo =
HardcodedFunctions.(
makeRenderedDistFloat("scaleMultiply", (dist, float) =>
verticalScaling(`Multiply, dist, float)
)
);
TypeSystem.Function.T.run(
evalParams,
[|
`SymbolicDist(`Float(100.0)),
`SymbolicDist(`Float(1.0)),
|],
foo,
);
},
Error("Sad"),
)
})
});

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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("min", Lodash.min([|1, 3, 4|]), 1);
makeTest("max", Lodash.max([|1, 3, 4|]), 4);
makeTest("uniq", Lodash.uniq([|1, 3, 4, 4|]), [|1, 3, 4|]);
makeTest(
"countBy",
Lodash.countBy([|1, 3, 4, 4|], r => r),
Js.Dict.fromArray([|("1", 1), ("3", 1), ("4", 2)|]),
);
})
});

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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",
SamplesToShape.Internals.T.splitContinuousAndDiscrete([|1.432, 1.33455, 2.0|]),
([|1.432, 1.33455, 2.0|], E.FloatFloatMap.empty()),
);
makeTest(
"split",
SamplesToShape.Internals.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) =
SamplesToShape.Internals.T.splitContinuousAndDiscrete(makeDuplicatedArray(10));
let toArr = discrete |> E.FloatFloatMap.toArray;
makeTest("splitMedium", toArr |> Belt.Array.length, 10);
let (c, discrete) =
SamplesToShape.Internals.T.splitContinuousAndDiscrete(makeDuplicatedArray(500));
let toArr = discrete |> E.FloatFloatMap.toArray;
makeTest("splitMedium", toArr |> Belt.Array.length, 500);
})
});

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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),
);
});
// describe("transverse", () => {
// makeTest(
// "When very different",
// XYShape.Transversal._transverse(
// (aCurrent, aLast) => aCurrent +. aLast,
// [|1.0, 2.0, 3.0, 4.0|],
// ),
// [|1.0, 3.0, 6.0, 10.0|],
// )
// });
describe("integrateWithTriangles", () => {
makeTest(
"integrates correctly",
XYShape.Range.integrateWithTriangles(shape1),
Some({
xs: [|1., 4., 8.|],
ys: [|0.0, 0.9000000000000001, 3.3000000000000007|],
}),
)
});
});

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{
"name": "probExample",
"reason": {
"react-jsx": 3
},
"sources": [
{
"dir": "src",
"subdirs": true
},
{
"dir": "showcase",
"type": "dev",
"subdirs": true
},
{
"dir": "__tests__",
"type": "dev",
"subdirs": true
}
],
"bsc-flags": [
"-bs-super-errors",
"-bs-no-version-header",
"-bs-g"
],
"package-specs": [
{
"module": "commonjs",
"in-source": true
}
],
"suffix": ".bs.js",
"namespace": true,
"bs-dependencies": [
"@glennsl/bs-jest",
"@glennsl/bs-json",
"@rescriptbr/reform",
"@rescript/react",
"bs-css",
"bs-css-dom",
"rationale",
"bs-moment",
"reschema"
],
"refmt": 3,
"warnings": {
"number": "+A-42-48-9-30-4-102"
},
"ppx-flags": [
"lenses-ppx/ppx"
]
}

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# Squiggle
Squiggle is a DSL for making probabilistic estimations. It is meant
to be a programming analogue of the [Guesstimate](https://www.getguesstimate.com/)
application.
There are several use cases for a language that represent uncertainty. Some include
writing cost effectiveness analysis, as well as doing accurate forecasting.
Squiggle is written in [Rescript](https://rescript-lang.org/) and is presented
as a website.
If you wish to try squiggle out, you can visit our [main page](https://squiggle-language.com/).
## Syntax
We use the [Math.js expression language](https://mathjs.org/index.html) for Squiggle.
So any expression that's available on Math.js is supported on Squiggle.
To represent uncertainty, we use a custom DSL called [DistML](https://docs.google.com/document/d/1xlEC8KjchP4PL-KdSxfBJr0UZ9nVMSAlz-rjAQEinyA/edit#).
## Contributing
To contribute to this project, we recommend visiting our [Contributing Guide](contributing.md).

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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>Squiggle Documentation</title>
<meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1" />
<meta name="description" content="Description">
<meta name="viewport" content="width=device-width, initial-scale=1.0, minimum-scale=1.0">
<link rel="stylesheet" href="//cdn.jsdelivr.net/npm/docsify@4/lib/themes/vue.css">
</head>
<body>
<div id="app"></div>
<script>
window.$docsify = {
name: 'Squiggle',
repo: 'foretold-app/squiggle',
loadSidebar: true
}
</script>
<!-- Docsify v4 -->
<script src="//cdn.jsdelivr.net/npm/docsify@4"></script>
<!-- CDN files for docsify-katex -->
<script src="//cdn.jsdelivr.net/npm/docsify-katex@latest/dist/docsify-katex.js"></script>
<!-- or <script src="//cdn.jsdelivr.net/gh/upupming/docsify-katex@latest/dist/docsify-katex.js"></script> -->
<link rel="stylesheet" href="//cdn.jsdelivr.net/npm/katex@latest/dist/katex.min.css"/>
</body>
</html>

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{
"devDependencies": {
"docsify-cli": "^4.4.3"
}
}

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[[redirects]]
from = "/*"
to = "/index.html"
status = 200

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{
"name": "estiband",
"version": "0.1.0",
"homepage": "https://foretold-app.github.io/estiband/",
"scripts": {
"build": "rescript build",
"build:style": "tailwind build src/styles/index.css -o src/styles/tailwind.css",
"start": "rescript build -w",
"clean": "rescript clean",
"parcel": "parcel ./src/index.html",
"parcel-build": "parcel build ./src/index.html --no-source-maps --no-autoinstall",
"showcase": "PORT=12345 parcel showcase/index.html",
"server": "moduleserve ./ --port 8000",
"predeploy": "parcel build ./src/index.html --no-source-maps --no-autoinstall",
"deploy": "gh-pages -d dist",
"test": "jest",
"test:ci": "yarn jest",
"watch:test": "jest --watchAll",
"watch:s": "yarn jest -- Converter_test --watch"
},
"keywords": [
"BuckleScript",
"ReasonReact",
"reason-react"
],
"author": "",
"license": "MIT",
"dependencies": {
"@glennsl/bs-json": "^5.0.2",
"@rescript/react": "^0.10.3",
"@rescriptbr/reform": "^11.0.1",
"ace-builds": "^1.4.12",
"antd": "^4.18.5",
"autoprefixer": "9.8.8",
"babel-plugin-transform-es2015-modules-commonjs": "^6.26.2",
"binary-search-tree": "0.2.6",
"bs-ant-design-alt": "2.0.0-alpha.33",
"bs-css": "^15.1.0",
"bs-css-dom": "^3.1.0",
"bs-moment": "0.6.0",
"bs-reform": "^10.0.3",
"bsb-js": "1.1.7",
"d3": "7.3.0",
"gh-pages": "2.2.0",
"jest": "^25.5.1",
"jstat": "1.9.2",
"lenses-ppx": "5.1.0",
"less": "3.10.3",
"lodash": "4.17.15",
"mathjs": "5.10.3",
"moduleserve": "0.9.1",
"moment": "2.24.0",
"pdfast": "^0.2.0",
"postcss-cli": "7.1.0",
"rationale": "0.2.0",
"react": "^16.10.0",
"react-ace": "^9.2.0",
"react-dom": "^0.13.0 || ^0.14.0 || ^15.0.1 || ^16.0.0",
"react-use": "^17.3.2",
"react-vega": "^7.4.4",
"reason-react": ">=0.7.0",
"reschema": "^2.2.0",
"rescript": "^9.1.4",
"tailwindcss": "1.2.0",
"vega": "*",
"vega-embed": "6.6.0",
"vega-lite": "*"
},
"devDependencies": {
"@glennsl/bs-jest": "^0.5.1",
"bs-platform": "9.0.2",
"docsify": "^4.12.2",
"parcel-bundler": "1.12.4",
"parcel-plugin-bundle-visualiser": "^1.2.0",
"parcel-plugin-less-js-enabled": "1.0.2"
},
"alias": {
"react": "./node_modules/react",
"react-dom": "./node_modules/react-dom"
}
}

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//postcss.config.js
const tailwindcss = require('tailwindcss');
module.exports = {
plugins: [
tailwindcss('./tailwind.js'),
require('autoprefixer'),
],
};

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{ pkgs ? import <nixpkgs> {} }:
pkgs.mkShell {
name = "squiggle";
buildInputs = with pkgs; [ yarn yarn2nix nodePackages.npm ];
}

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let entries = [];

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type compEntry = {
mutable id: string,
title: string,
render: unit => React.element,
container: containerType,
}
and folderEntry = {
mutable id: string,
title: string,
children: list(navEntry),
}
and navEntry =
| CompEntry(compEntry)
| FolderEntry(folderEntry)
and containerType =
| FullWidth
| Sidebar;
let entry = (~title, ~render): navEntry => {
CompEntry({id: "", title, render, container: FullWidth});
};
// Maybe different api, this avoids breaking changes
let sidebar = (~title, ~render): navEntry => {
CompEntry({id: "", title, render, container: Sidebar});
};
let folder = (~title, ~children): navEntry => {
FolderEntry({id: "", title, children});
};

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open EntryTypes
module HS = Belt.HashMap.String
let entriesByPath: HS.t<navEntry> = HS.make(~hintSize=100)
/* Creates unique id's per scope based on title */
let buildIds = entries => {
let genId = (title, path) => {
let noSpaces = Js.String.replaceByRe(%re("/\\s+/g"), "-", title)
if !HS.has(entriesByPath, path ++ ("/" ++ noSpaces)) {
noSpaces
} else {
let rec loop = num => {
let testId = noSpaces ++ ("-" ++ string_of_int(num))
if !HS.has(entriesByPath, path ++ ("/" ++ testId)) {
testId
} else {
loop(num + 1)
}
}
loop(2)
}
}
let rec processFolder = (f: folderEntry, curPath) => {
f.id = curPath ++ ("/" ++ genId(f.title, curPath))
HS.set(entriesByPath, f.id, FolderEntry(f))
f.children |> E.L.iter(x =>
switch x {
| CompEntry(c) => processEntry(c, f.id)
| FolderEntry(f) => processFolder(f, f.id)
}
)
}
and processEntry = (c: compEntry, curPath) => {
c.id = curPath ++ ("/" ++ genId(c.title, curPath))
HS.set(entriesByPath, c.id, CompEntry(c))
}
entries |> E.L.iter(x =>
switch x {
| CompEntry(c) => processEntry(c, "")
| FolderEntry(f) => processFolder(f, "")
}
)
}
let entries = Entries.entries
buildIds(entries)
module Styles = {
open CssJs
let pageContainer = style(. [ display(#flex), height(#vh(100.)) ])
let leftNav = style(. [ padding(#em(2.)),
flexBasis(#px(200)),
flexShrink(0.),
backgroundColor(#hex("eaeff3")),
boxShadows([ Shadow.box(~x=px(-1), ~blur=px(1), ~inset=true, rgba(0, 0, 0, #percent(0.1))) ]),
])
let folderNav = style(. [ selector(.
">h4",
[ cursor(#pointer), margin2(~v=#em(0.3), ~h=#zero), hover([ color(#hex("7089ad")) ]) ],
),
])
let folderChildren = style(. [ paddingLeft(#px(7)) ])
let compNav = style(. [ cursor(#pointer),
paddingBottom(#px(3)),
hover([ color(#hex("7089ad")) ]),
])
let compContainer = style(. [ padding(#em(2.)), flexGrow(1.) ])
// Approximate sidebar container for entry
let sidebarContainer = style(. [ maxWidth(#px(430)) ])
let folderChildContainer = style(. [ marginBottom(#em(2.)) ])
}
let baseUrl = "/showcase/index.html"
module Index = {
type state = {route: RescriptReactRouter.url}
type action =
| ItemClick(string)
| ChangeRoute(RescriptReactRouter.url)
let changeId = (id: string) => {
let _ = RescriptReactRouter.push(baseUrl ++ ("#" ++ id))
}
let buildNav = _ => {
let rec buildFolder = (f: folderEntry) =>
<div key=f.id style=Styles.folderNav>
<h4 onClick={_e => changeId(f.id)}> {f.title->React.string} </h4>
<div style=Styles.folderChildren>
{(f.children
|> E.L.fmap(e =>
switch e {
| FolderEntry(folder) => buildFolder(folder)
| CompEntry(entry) => buildEntry(entry)
}
)
|> E.L.toArray)->React.array}
</div>
</div>
and buildEntry = (e: compEntry) =>
<div key=e.id style=Styles.compNav onClick={_e => changeId(e.id)}>
{e.title->React.string}
</div>
(entries
|> E.L.fmap(e =>
switch e {
| FolderEntry(folder) => buildFolder(folder)
| CompEntry(entry) => buildEntry(entry)
}
)
|> E.L.toArray)->React.array
}
let renderEntry = e =>
switch e.container {
| FullWidth => e.render()
| Sidebar => <div style=Styles.sidebarContainer> {e.render()} </div>
}
@react.component
let make = () => {
let (route, setRoute) = React.useState(() => {
let url: RescriptReactRouter.url = {path: list{}, hash: "", search: ""}
url
})
React.useState(() => {
let _ = RescriptReactRouter.watchUrl(url => setRoute(_ => url))
}) |> ignore
<div style=Styles.pageContainer>
<div style=Styles.leftNav> {buildNav(setRoute)} </div>
<div style=Styles.compContainer>
{if route.hash == "" {
React.null
} else {
switch HS.get(entriesByPath, route.hash) {
| Some(navEntry) =>
switch navEntry {
| CompEntry(c) => renderEntry(c)
| FolderEntry(f) =>
/* Rendering immediate children */
(f.children
|> E.L.fmap(child =>
switch child {
| CompEntry(c) =>
<div style=Styles.folderChildContainer key=c.id> {renderEntry(c)} </div>
| _ => React.null
}
)
|> E.L.toArray)->React.array
}
| None => <div> {"Component not found"->React.string} </div>
}
}}
</div>
</div>
}
}

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switch(ReactDOM.querySelector("main")){
| Some(root) => ReactDOM.render(<div> <Lib.Index /> </div>, root)
| None => () // do nothing
}
RescriptReactRouter.push("")

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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta http-equiv="X-UA-Compatible" content="ie=edge">
<link href="https://fonts.googleapis.com/css?family=Lato:300,400,700,900" rel="stylesheet">
<link href="https://fonts.googleapis.com/css?family=Lato:300,400,700,900" rel="stylesheet">
<link href="../src/styles/index.css" rel="stylesheet">
<style>
body {
margin: 0;
}
</style>
<title>Showcase</title>
</head>
<body>
<div id="main"></div>
<script src=" ./ShowcaseIndex.bs.js "></script>
</body>
</html>

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module Input = Antd_Input
module Grid = Antd_Grid
module Form = Antd_Form
module Card = Antd_Card
module Button = Antd_Button
module IconName = Antd_IconName

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@deriving(abstract)
type props
type makeType = props => React.element
@obj external makeProps:
(
~disabled: bool=?,
~ghost: bool=?,
~href: string=?,
~htmlType: @string [#button | #submit | #submit]=?,
~icon: 'a=?,
~shape: @string [#circle | #round]=?,
~size: @string [#small | #large]=?,
~target: string=?,
~loading: bool=?,
~_type: @string
[
| #primary
| #default
| #dashed
| #danger
| #link
| #ghost
]=?,
~onClick: ReactEvent.Mouse.t => unit=?,
~block: bool=?,
~children: React.element=?,
~className: string=?,
~id: string=?,
~testId: string=?,
unit
) =>
props =
""
@module("antd")
external make : makeType = "Button"

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@deriving(abstract)
type props
type makeType = props => React.element
@obj external makeProps: (
~actions: array<React.element>=?,
~activeTabKey: string=?,
~headStyle: ReactDOMStyle.t=?,
~bodyStyle: ReactDOMStyle.t=?,
~style: ReactDOMStyle.t=?,
~bordered: bool=?,
~cover: React.element=?,
~defaultActiveTabKey: string=?,
~extra: React.element=?,
~hoverable: bool=?,
~loading: bool=?,
~tabList: array<{
"key": string,
"tab": React.element,
}>
=?,
~size: @string [ #default | #small]=?,
~title: 'a=?,
~_type: string=?,
~onTabChange: string => unit=?,
~children: React.element=?,
unit // This unit is a quirk of the type system. Apparently it must exist to have optional arguments in a type
) => props = ""
@module("antd")
external make : makeType = "Card"

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@deriving(abstract)
type props
type makeType = props => React.element
@obj
external makeProps:
(
~onSubmit: ReactEvent.Form.t => unit=?,
~hideRequiredMark: bool=?,
~id: string=?,
~className: string=?,
~style: ReactDOMStyle.t=?,
~colon: bool=?,
~validateStatus: string=?,
~extra: string=?,
~required: bool=?,
~label: string=?,
~help: string=?,
~hasFeedback: bool=?,
~children:React.element=?,
unit
) =>
props =
""
@module("antd")
external make : makeType = "Form"
module Item = {
type props
type makeType = props => React.element
@obj
external makeProps:
(
~colon:string=?,
~validateStatus:string=?,
~extra:string=?,
~className:string=?,
~required:bool=?,
~style:ReactDOMStyle.t=?,
~label:string=?,
~id:string=?,
~help:string=?,
~hasFeedback:bool=?,
~children:React.element=?,
unit
) => props = ""
@module("antd")
external make : makeType = "Form.Item"
}

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module Row = {
type props
@obj
external makeProps:
(
~className: string=?,
~_type: string=?,
~align: string=?,
~justify: string=?,
~gutter: 'a=?,
~style: ReactDOMStyle.t=?,
~prefixCls: string=?,
~children: React.element=?,
unit
) =>
props =
"";
type makeType = props => React.element
@module("antd")
external make : makeType = "Row"
}
module Col = {
type props
@obj
external makeProps:
(
~className: string=?,
~span: int=?,
~order: int=?,
~offset: int=?,
~push: int=?,
~pull: int=?,
~xs: 'a=?,
~sm: 'b=?,
~md: 'c=?,
~lg: 'd=?,
~xl: 'e=?,
~xxl: 'f=?,
~prefixCls: string=?,
~style: ReactDOMStyle.t=?,
~children: React.element=?,
unit
) =>
props =
"";
type makeType = props => React.element
@module("antd")
external make : makeType = "Col"
}

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type t = string
let toString = t => t
let fromString = t => t
let compare = (t1, t2) => t1 == t2
let stepBackward = "step-backward"
let stepForward = "step-forward"
let fastBackward = "fast-backward"
let fastForward = "fast-forward"
let shrink = "shrink"
let arrowsAlt = "arrows-alt"
let down = "down"
let up = "up"
let left = "left"
let right = "right"
let caretUp = "caret-up"
let caretDown = "caret-down"
let caretLeft = "caret-left"
let caretRight = "caret-right"
let upCircle = "up-circle"
let downCircle = "down-circle"
let leftCircle = "left-circle"
let rightCircle = "right-circle"
let upCircleO = "up-circle-o"
let downCircleO = "down-circle-o"
let rightCircleO = "right-circle-o"
let leftCircleO = "left-circle-o"
let doubleRight = "double-right"
let doubleLeft = "double-left"
let verticleLeft = "verticle-left"
let verticleRight = "verticle-right"
let forward = "forward"
let backward = "backward"
let rollback = "rollback"
let enter = "enter"
let retweet = "retweet"
let swap = "swap"
let swapLeft = "swap-left"
let swapRight = "swap-right"
let arrowUp = "arrow-up"
let arrowDown = "arrow-down"
let arrowLeft = "arrow-left"
let arrowRight = "arrow-right"
let playCircle = "play-circle"
let playCircleO = "play-circle-o"
let upSquare = "up-square"
let downSquare = "down-square"
let leftSquare = "left-square"
let rightSquare = "right-square"
let upSquareO = "up-square-o"
let downSquareO = "down-square-o"
let leftSquareO = "left-square-o"
let rightSquareO = "right-square-o"
let login = "login"
let logout = "logout"
let menuFold = "menu-fold"
let menuUnfold = "menu-unfold"
let question = "question"
let questionCircleO = "question-circle-o"
let questionCircle = "question-circle"
let plus = "plus"
let plusCircleO = "plus-circle-o"
let plusCircle = "plus-circle"
let pause = "pause"
let pauseCircleO = "pause-circle-o"
let pauseCircle = "pause-circle"
let minus = "minus"
let minusCircleO = "minus-circle-o"
let minusCircle = "minus-circle"
let plusSquare = "plus-square"
let plusSquareO = "plus-square-o"
let minusSquare = "minus-square"
let minusSquareO = "minus-square-o"
let info = "info"
let infoCircleO = "info-circle-o"
let infoCircle = "info-circle"
let exclamation = "exclamation"
let exclamationCircleO = "exclamation-circle-o"
let exclamationCircle = "exclamation-circle"
let close = "close"
let closeCircle = "close-circle"
let closeCircleO = "close-circle-o"
let closeSquare = "close-square"
let closeSquareO = "close-square-o"
let check = "check"
let checkCircle = "check-circle"
let checkCircleO = "check-circle-o"
let checkSquare = "check-square"
let checkSquareO = "check-square-o"
let clockCircleO = "clock-circle-o"
let clockCircle = "clock-circle"
let warning = "warning"
let lock = "lock"
let unlock = "unlock"
let areaChart = "area-chart"
let pieChart = "pie-chart"
let barChart = "bar-chart"
let dotChart = "dot-chart"
let bars = "bars"
let book = "book"
let calendar = "calendar"
let cloud = "cloud"
let cloudDownload = "cloud-download"
let code = "code"
let codeO = "code-o"
let copy = "copy"
let creditCard = "credit-card"
let delete = "delete"
let desktop = "desktop"
let download = "download"
let edit = "edit"
let ellipsis = "ellipsis"
let file = "file"
let fileText = "file-text"
let fileUnknown = "file-unknown"
let filePdf = "file-pdf"
let fileWord = "file-word"
let fileExcel = "file-excel"
let fileJpg = "file-jpg"
let filePpt = "file-ppt"
let fileMarkdown = "file-markdown"
let fileAdd = "file-add"
let folder = "folder"
let folderOpen = "folder-open"
let folderAdd = "folder-add"
let hdd = "hdd"
let frown = "frown"
let frownO = "frown-o"
let meh = "meh"
let mehO = "meh-o"
let smile = "smile"
let smileO = "smile-o"
let inbox = "inbox"
let laptop = "laptop"
let appstoreO = "appstore-o"
let appstore = "appstore"
let lineChart = "line-chart"
let link = "link"
let mail = "mail"
let mobile = "mobile"
let notification = "notification"
let paperClip = "paper-clip"
let picture = "picture"
let poweroff = "poweroff"
let reload = "reload"
let search = "search"
let setting = "setting"
let shareAlt = "share-alt"
let shoppingCart = "shopping-cart"
let tablet = "tablet"
let tag = "tag"
let tagO = "tag-o"
let tags = "tags"
let tagsO = "tags-o"
let toTop = "to-top"
let upload = "upload"
let user = "user"
let videoCamera = "video-camera"
let home = "home"
let loading = "loading"
let loading3Quarters = "loading-3-quarters"
let cloudUploadO = "cloud-upload-o"
let cloudDownloadO = "cloud-download-o"
let cloudUpload = "cloud-upload"
let cloudO = "cloud-o"
let starO = "star-o"
let star = "star"
let heartO = "heart-o"
let heart = "heart"
let environment = "environment"
let environmentO = "environment-o"
let eye = "eye"
let eyeO = "eye-o"
let camera = "camera"
let cameraO = "camera-o"
let save = "save"
let team = "team"
let solution = "solution"
let phone = "phone"
let filter = "filter"
let exception_ = "exception"
let \"export" = "export"
let customerService = "customer-service"
let qrcode = "qrcode"
let scan = "scan"
let like = "like"
let likeO = "like-o"
let dislike = "dislike"
let dislikeO = "dislike-o"
let message = "message"
let payCircle = "pay-circle"
let payCircleO = "pay-circle-o"
let calculator = "calculator"
let pushpin = "pushpin"
let pushpinO = "pushpin-o"
let bulb = "bulb"
let select = "select"
let switcher = "switcher"
let rocket = "rocket"
let bell = "bell"
let disconnect = "disconnect"
let database = "database"
let compass = "compass"
let barcode = "barcode"
let hourglass = "hourglass"
let key = "key"
let flag = "flag"
let layout = "layout"
let printer = "printer"
let sound = "sound"
let usb = "usb"
let skin = "skin"
let tool = "tool"
let sync = "sync"
let wifi = "wifi"
let car = "car"
let schedule = "schedule"
let userAdd = "user-add"
let userDelete = "user-delete"
let usergroupAdd = "usergroup-add"
let usergroupDelete = "usergroup-delete"
let man = "man"
let woman = "woman"
let shop = "shop"
let gift = "gift"
let idcard = "idcard"
let medicineBox = "medicine-box"
let redEnvelope = "red-envelope"
let coffee = "coffee"
let copyright = "copyright"
let trademark = "trademark"
let safety = "safety"
let wallet = "wallet"
let bank = "bank"
let trophy = "trophy"
let contacts = "contacts"
let global = "global"
let shake = "shake"
let api = "api"
let fork = "fork"
let dashboard = "dashboard"
let form = "form"
let table = "table"
let profile = "profile"
let android = "android"
let androidO = "android-o"
let apple = "apple"
let appleO = "apple-o"
let windows = "windows"
let windowsO = "windows-o"
let ie = "ie"
let chrome = "chrome"
let github = "github"
let aliwangwang = "aliwangwang"
let aliwangwangO = "aliwangwang-o"
let dingding = "dingding"
let dingdingO = "dingding-o"
let weiboSquare = "weibo-square"
let weiboCircle = "weibo-circle"
let taobaoCircle = "taobao-circle"
let html5 = "html5"
let weibo = "weibo"
let twitter = "twitter"
let wechat = "wechat"
let youtube = "youtube"
let alipayCircle = "alipay-circle"
let taobao = "taobao"
let skype = "skype"
let qq = "qq"
let mediumWorkmark = "medium-workmark"
let gitlab = "gitlab"
let medium = "medium"
let linkedin = "linkedin"
let googlePlus = "google-plus"
let dropbox = "dropbox"
let facebook = "facebook"
let codepen = "codepen"
let amazon = "amazon"
let google = "google"
let codepenCircle = "codepen-circle"
let alipay = "alipay"
let antDesign = "ant-design"
let aliyun = "aliyun"
let zhihu = "zhihu"
let slack = "slack"
let slackSquare = "slack-square"
let behance = "behance"
let behanceSquare = "behance-square"
let dribbble = "dribbble"
let dribbbleSquare = "dribbble-square"
let instagram = "instagram"
let yuque = "yuque"

21
packages/squiggle-old/src/Antd/Antd_Input.res Normal file
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@deriving(abstract)
type props
type makeType = props => React.element
@obj external makeProps: (
@as("type")
~htmlType: string=?,
~name: string=?,
~value: string=?,
~defaultValue: string=?,
~onChange: ReactEvent.Form.t => unit=?,
~onPressEnter: ReactEvent.Keyboard.t => unit=?,
~onBlur: ReactEvent.Focus.t => unit=?,
~className: string=?,
~style: ReactDOMStyle.t=?,
~placeholder: string=?,
unit // This unit is a quirk of the type system. Apparently it must exist to have optional arguments in a type
) => props = ""
@module("antd")
external make : makeType = "Input"

78
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type route =
| DistBuilder
| Home
| NotFound
let routeToPath = route =>
switch route {
| DistBuilder => "/dist-builder"
| Home => "/"
| _ => "/"
}
module Menu = {
module Styles = {
open CssJs
let menu = style(. [ position(#relative),
marginTop(em(0.25)),
marginBottom(em(0.25)),
selector(.
"a",
[ borderRadius(em(0.25)),
display(#inlineBlock),
backgroundColor(#hex("eee")),
padding(em(1.)),
cursor(#pointer),
],
),
selector(. "a:hover", [ backgroundColor(#hex("bfcad4")) ]),
selector(. "a:hover", [ backgroundColor(#hex("bfcad4")) ]),
selector(.
"a:not(:firstChild):not(:lastChild)",
[ marginRight(em(0.25)), marginLeft(em(0.25)) ],
),
])
}
module Item = {
@react.component
let make = (~href, ~children) =>
<a
href
onClick={e => {
e->ReactEvent.Synthetic.preventDefault
RescriptReactRouter.push(href)
}}>
children
</a>
}
@react.component
let make = () =>
<div style=Styles.menu>
<Item href={routeToPath(Home)} key="home"> {"Home" |> R.ste} </Item>
<Item href={routeToPath(DistBuilder)} key="dist-builder"> {"Dist Builder" |> R.ste} </Item>
</div>
}
let fixedLength = r => <div className="w-full max-w-screen-xl mx-auto px-6"> r </div>
@react.component
let make = () => {
let url = RescriptReactRouter.useUrl()
let routing = switch url.path {
| list{"dist-builder"} => DistBuilder
| list{} => Home
| _ => NotFound
}
<>
<Menu />
{switch routing {
| DistBuilder => <DistBuilder />
| Home => <Home />
| _ => fixedLength("Page is not found" |> R.ste)
}}
</>
}

44
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let reasonReactBlue = "#48a9dc";
// The {j|...|j} feature is just string interpolation, from
// bucklescript.github.io/docs/en/interop-cheatsheet#string-unicode-interpolation
// This allows us to conveniently write CSS, together with variables, by
// constructing a string
let style = {j|
body {
background-color: rgb(224, 226, 229);
display: flex;
flex-direction: column;
align-items: center;
}
button {
background-color: white;
color: $reasonReactBlue;
box-shadow: 0 0 0 1px $reasonReactBlue;
border: none;
padding: 8px;
font-size: 16px;
}
button:active {
background-color: $reasonReactBlue;
color: white;
}
.container {
margin: 12px 0px;
box-shadow: 0px 4px 16px rgb(200, 200, 200);
width: 720px;
border-radius: 12px;
font-family: sans-serif;
}
.containerTitle {
background-color: rgb(242, 243, 245);
border-radius: 12px 12px 0px 0px;
padding: 12px;
font-weight: bold;
}
.containerContent {
background-color: white;
padding: 16px;
border-radius: 0px 0px 12px 12px;
}
|j};

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let normal = (mean: float, std: float) =>
Js.Float.(
{
let nMean = toPrecisionWithPrecision(mean, ~digits=4);
let nStd = toPrecisionWithPrecision(std, ~digits=2);
{j|normal($(nMean), $(nStd))|j};
}
);
let logNormal = (mean: float, std: float) => {
Js.Float.(
{
let nMean = toPrecisionWithPrecision(mean, ~digits=4);
let nStd = toPrecisionWithPrecision(std, ~digits=2);
{j|lognormal({mean: $(nMean), stdev: $(nStd)})|j};
}
);
};
let divide = (str1: string, str2: string) => {j|$(str1)/$(str2)|j};
let min = (str1: string, str2: string) => {j|min($(str1),$(str2))|j};

5
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%raw(`import('./styles/index.css')`)
switch ReactDOM.querySelector("#app") {
| Some(root) => ReactDOM.render(<App />, root)
| None => ()
}

8
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let ste = React.string
let showIf = (cond, comp) => cond ? comp : React.null
module O = {
let defaultNull = E.O.default(React.null)
let fmapOrNull = (fn, el) => el |> E.O.fmap(fn) |> E.O.default(React.null)
let flatten = E.O.default(React.null)
}

36
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import React from "react";
import AceEditor from "react-ace";
import "ace-builds/src-noconflict/mode-golang";
import "ace-builds/src-noconflict/theme-github";
import "ace-builds/src-noconflict/ext-language_tools";
import "ace-builds/src-noconflict/keybinding-vim";
function onChange(newValue) {
console.log("change", newValue);
}
export function CodeEditor(props) {
return (
<AceEditor
value={props.value}
mode="golang"
height="400px"
width="100%"
theme="github"
showGutter={false}
highlightActiveLine={false}
showPrintMargin={false}
onChange={props.onChange}
name="UNIQUE_ID_OF_DIV"
editorProps={{
$blockScrolling: true,
}}
setOptions={{
enableBasicAutocompletion: false,
enableLiveAutocompletion: true,
enableSnippets: true,
}}
/>
);
}

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type props
@obj external makeProps : (~value:string=?, ~onChange: string => unit, ~children: React.element=?, unit) => props = ""
@module("./CodeEditor.js")
external make: props => React.element = "CodeEditor"

271
packages/squiggle-old/src/components/DistBuilder.res Normal file
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open ReForm
open Antd.Grid
module FormConfig = %lenses(
type state = {
squiggleString: string,
sampleCount: string,
outputXYPoints: string,
downsampleTo: string,
kernelWidth: string,
diagramStart: string,
diagramStop: string,
diagramCount: string,
}
)
type options = {
sampleCount: int,
outputXYPoints: int,
downsampleTo: option<int>,
kernelWidth: option<float>,
diagramStart: float,
diagramStop: float,
diagramCount: int,
}
module Form = ReForm.Make(FormConfig)
module FieldText = {
@react.component
let make = (~field, ~label) => <>
<Form.Field
field
render={({handleChange, error, value, validate}) =>{
Js.Console.log(CodeEditor.make);
(<CodeEditor value onChange={r => handleChange(r)} />)
}
}
/>
</>
}
module FieldString = {
@react.component
let make = (~field, ~label) =>
<Form.Field
field
render={({handleChange, error, value, validate}) =>
<Antd.Form.Item label={label}>
<Antd.Input
value onChange={ReForm.Helpers.handleChange(handleChange)} onBlur={_ => validate()}
/>
</Antd.Form.Item>}
/>
}
module FieldFloat = {
@react.component
let make = (~field, ~label, ~className=CssJs.style(. [])) =>
<Form.Field
field
render={({handleChange, error, value, validate}) =>
<Antd.Input
value
onChange={ReForm.Helpers.handleChange(handleChange)}
onBlur={_ => validate()}
style={className}
/>
}
/>
}
module Styles = {
open CssJs
let rows = style(. [ selector(. ">.antCol:firstChild", [ paddingLeft(em(0.25)), paddingRight(em(0.125)) ]),
selector(. ">.antCol:lastChild", [ paddingLeft(em(0.125)), paddingRight(em(0.25)) ]),
selector(.
">.antCol:not(:firstChild):not(:lastChild)",
[ paddingLeft(em(0.125)), paddingRight(em(0.125)) ],
),
])
let parent = style(. [ selector(. ".antInputNumber", [ width(#percent(100.)) ]),
selector(. ".anticon", [ verticalAlign(#zero) ]),
])
let form = style(. [ backgroundColor(hex("eee")), padding(em(1.)) ])
let dist = style(. [ padding(em(1.)) ])
let spacer = style(. [ marginTop(em(1.)) ])
let groupA = style(. [ selector(. ".antInputNumberInput", [ backgroundColor(hex("fff7db")) ]),
])
let groupB = style(. [ selector(. ".antInputNumberInput", [ backgroundColor(hex("eaf4ff")) ]),
])
}
module DemoDist = {
@react.component
let make = (~squiggleString: string, ~options) =>
<Antd.Card title={"Distribution"}>
<div>
{switch options {
| Some(options) =>
let inputs1 = ProgramEvaluator.Inputs.make(
~samplingInputs={
sampleCount: Some(options.sampleCount),
outputXYPoints: Some(options.outputXYPoints),
kernelWidth: options.kernelWidth,
shapeLength: Some(options.downsampleTo |> E.O.default(1000)),
},
~squiggleString,
~environment=[
("K", #SymbolicDist(#Float(1000.0))),
("M", #SymbolicDist(#Float(1000000.0))),
("B", #SymbolicDist(#Float(1000000000.0))),
("T", #SymbolicDist(#Float(1000000000000.0))),
]->Belt.Map.String.fromArray,
(),
)
let distributionList = ProgramEvaluator.evaluateProgram(inputs1)
let renderExpression = response1 =>
switch response1 {
| #DistPlus(distPlus1) => <DistPlusPlot distPlus={DistPlus.T.normalize(distPlus1)} />
| #Float(f) => <NumberShower number=f precision=3 />
| #Function((f, a), env) =>
// Problem: When it gets the function, it doesn't save state about previous commands
let foo: ProgramEvaluator.Inputs.inputs = {
squiggleString: squiggleString,
samplingInputs: inputs1.samplingInputs,
environment: env,
}
let results =
E.A.Floats.range(options.diagramStart, options.diagramStop, options.diagramCount)
|> E.A.fmap(r =>
ProgramEvaluator.evaluateFunction(
foo,
(f, a),
[#SymbolicDist(#Float(r))],
) |> E.R.bind(_, a =>
switch a {
| #DistPlus(d) => Ok((r, DistPlus.T.normalize(d)))
| n =>
Js.log2("Error here", n)
Error("wrong type")
}
)
)
|> E.A.R.firstErrorOrOpen
switch results {
| Ok(dists) => <PercentilesChart dists />
| Error(r) => r |> R.ste
}
}
// Render the list of distributions given by the
switch distributionList {
| Ok(xs) =>
let childrenElements = List.map(renderExpression, xs)
Js.Console.log(childrenElements)
<ul>
{Belt.List.toArray(Belt.List.mapWithIndex(childrenElements, (i, child) => <li key={Belt.Int.toString(i)}>child</li>))->React.array}
</ul>
| Error(r) => r |> R.ste
}
| _ => "Nothing to show. Try to change the distribution description." |> R.ste
}}
</div>
</Antd.Card>
}
@react.component
let make = () => {
let (reloader, setReloader) = React.useState(() => 1)
let reform = Form.use(
~validationStrategy=OnDemand,
~schema=Form.Validation.Schema([]),
~onSubmit=({state}) => None,
~initialState={
//squiggleString: "mm(normal(-10, 2), uniform(18, 25), lognormal({mean: 10, stdev: 8}), triangular(31,40,50))",
squiggleString: "mm(normal(5,2), normal(10,2))",
sampleCount: "1000",
outputXYPoints: "1000",
downsampleTo: "",
kernelWidth: "",
diagramStart: "0",
diagramStop: "10",
diagramCount: "20",
},
(),
)
let onSubmit = e => {
e->ReactEvent.Synthetic.preventDefault
reform.submit()
}
let squiggleString = reform.state.values.squiggleString
let sampleCount = reform.state.values.sampleCount |> Js.Float.fromString
let outputXYPoints = reform.state.values.outputXYPoints |> Js.Float.fromString
let downsampleTo = reform.state.values.downsampleTo |> Js.Float.fromString
let kernelWidth = reform.state.values.kernelWidth |> Js.Float.fromString
let diagramStart = reform.state.values.diagramStart |> Js.Float.fromString
let diagramStop = reform.state.values.diagramStop |> Js.Float.fromString
let diagramCount = reform.state.values.diagramCount |> Js.Float.fromString
let options = switch (sampleCount, outputXYPoints, downsampleTo) {
| (_, _, _)
if !Js.Float.isNaN(sampleCount) &&
(!Js.Float.isNaN(outputXYPoints) &&
(!Js.Float.isNaN(downsampleTo) && (sampleCount > 10. && outputXYPoints > 10.))) =>
Some({
sampleCount: sampleCount |> int_of_float,
outputXYPoints: outputXYPoints |> int_of_float,
downsampleTo: int_of_float(downsampleTo) > 0 ? Some(int_of_float(downsampleTo)) : None,
kernelWidth: kernelWidth == 0.0 ? None : Some(kernelWidth),
diagramStart: diagramStart,
diagramStop: diagramStop,
diagramCount: diagramCount |> int_of_float,
})
| _ => None
}
let demoDist = React.useMemo1(
() => <DemoDist squiggleString options />,
[
reform.state.values.squiggleString,
reform.state.values.sampleCount,
reform.state.values.outputXYPoints,
reform.state.values.downsampleTo,
reform.state.values.kernelWidth,
reform.state.values.diagramStart,
reform.state.values.diagramStop,
reform.state.values.diagramCount,
reloader |> string_of_int,
],
)
let onReload = _ => setReloader(_ => reloader + 1)
<div className="grid grid-cols-2 gap-4">
<div>
<Antd.Card
title={"Distribution Form" |> R.ste}
extra={<Antd.Button icon=Antd.IconName.reload shape=#circle onClick=onReload />}>
<Form.Provider value=reform>
<Antd.Form onSubmit>
<Row _type="flex" style=Styles.rows>
<Col span=24> <FieldText field=FormConfig.SquiggleString label="Program" /> </Col>
</Row>
<Row _type="flex" style=Styles.rows>
<Col span=12> <FieldFloat field=FormConfig.SampleCount label="Sample Count" /> </Col>
<Col span=12>
<FieldFloat field=FormConfig.OutputXYPoints label="Output XY-points" />
</Col>
<Col span=12>
<FieldFloat field=FormConfig.DownsampleTo label="Downsample To" />
</Col>
<Col span=12> <FieldFloat field=FormConfig.KernelWidth label="Kernel Width" /> </Col>
<Col span=12>
<FieldFloat field=FormConfig.DiagramStart label="Diagram Start" />
</Col>
<Col span=12> <FieldFloat field=FormConfig.DiagramStop label="Diagram Stop" /> </Col>
<Col span=12>
<FieldFloat field=FormConfig.DiagramCount label="Diagram Count" />
</Col>
</Row>
</Antd.Form>
</Form.Provider>
</Antd.Card>
</div>
<div> demoDist </div>
</div>
}

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open DistPlusPlotReducer
let plotBlue = #hex("1860ad")
let showAsForm = (distPlus: DistTypes.distPlus) =>
<div> <Antd.Input value={distPlus.squiggleString |> E.O.default("")} /> </div>
let showFloat = (~precision=3, number) => <NumberShower number precision />
let table = (distPlus, x) =>
<div>
<table className="table-auto text-sm">
<thead>
<tr>
<td className="px-4 py-2 "> {"X Point" |> React.string} </td>
<td className="px-4 py-2"> {"Discrete Value" |> React.string} </td>
<td className="px-4 py-2"> {"Continuous Value" |> React.string} </td>
<td className="px-4 py-2"> {"Y Integral to Point" |> React.string} </td>
<td className="px-4 py-2"> {"Y Integral Total" |> React.string} </td>
</tr>
</thead>
<tbody>
<tr>
<td className="px-4 py-2 border"> {x |> E.Float.toString |> React.string} </td>
<td className="px-4 py-2 border ">
{distPlus
|> DistPlus.T.xToY(x)
|> DistTypes.MixedPoint.toDiscreteValue
|> Js.Float.toPrecisionWithPrecision(_, ~digits=7)
|> React.string}
</td>
<td className="px-4 py-2 border ">
{distPlus
|> DistPlus.T.xToY(x)
|> DistTypes.MixedPoint.toContinuousValue
|> Js.Float.toPrecisionWithPrecision(_, ~digits=7)
|> React.string}
</td>
<td className="px-4 py-2 border ">
{distPlus
|> DistPlus.T.Integral.xToY(x)
|> E.Float.with2DigitsPrecision
|> React.string}
</td>
<td className="px-4 py-2 border ">
{distPlus
|> DistPlus.T.Integral.sum
|> E.Float.with2DigitsPrecision
|> React.string}
</td>
</tr>
</tbody>
</table>
<table className="table-auto text-sm">
<thead>
<tr>
<td className="px-4 py-2"> {"Continuous Total" |> React.string} </td>
<td className="px-4 py-2"> {"Discrete Total" |> React.string} </td>
</tr>
</thead>
<tbody>
<tr>
<td className="px-4 py-2 border">
{distPlus
|> DistPlus.T.toContinuous
|> E.O.fmap(Continuous.T.Integral.sum)
|> E.O.fmap(E.Float.with2DigitsPrecision)
|> E.O.default("")
|> React.string}
</td>
<td className="px-4 py-2 border ">
{distPlus
|> DistPlus.T.toDiscrete
|> E.O.fmap(Discrete.T.Integral.sum)
|> E.O.fmap(E.Float.with2DigitsPrecision)
|> E.O.default("")
|> React.string}
</td>
</tr>
</tbody>
</table>
</div>
let percentiles = distPlus =>
<div>
<table className="table-auto text-sm">
<thead>
<tr>
<td className="px-4 py-2"> {"1" |> React.string} </td>
<td className="px-4 py-2"> {"5" |> React.string} </td>
<td className="px-4 py-2"> {"25" |> React.string} </td>
<td className="px-4 py-2"> {"50" |> React.string} </td>
<td className="px-4 py-2"> {"75" |> React.string} </td>
<td className="px-4 py-2"> {"95" |> React.string} </td>
<td className="px-4 py-2"> {"99" |> React.string} </td>
<td className="px-4 py-2"> {"99.999" |> React.string} </td>
</tr>
</thead>
<tbody>
<tr>
<td className="px-4 py-2 border">
{distPlus |> DistPlus.T.Integral.yToX(0.01) |> showFloat}
</td>
<td className="px-4 py-2 border">
{distPlus |> DistPlus.T.Integral.yToX(0.05) |> showFloat}
</td>
<td className="px-4 py-2 border">
{distPlus |> DistPlus.T.Integral.yToX(0.25) |> showFloat}
</td>
<td className="px-4 py-2 border">
{distPlus |> DistPlus.T.Integral.yToX(0.5) |> showFloat}
</td>
<td className="px-4 py-2 border">
{distPlus |> DistPlus.T.Integral.yToX(0.75) |> showFloat}
</td>
<td className="px-4 py-2 border">
{distPlus |> DistPlus.T.Integral.yToX(0.95) |> showFloat}
</td>
<td className="px-4 py-2 border">
{distPlus |> DistPlus.T.Integral.yToX(0.99) |> showFloat}
</td>
<td className="px-4 py-2 border">
{distPlus |> DistPlus.T.Integral.yToX(0.99999) |> showFloat}
</td>
</tr>
</tbody>
</table>
<table className="table-auto text-sm">
<thead>
<tr>
<td className="px-4 py-2"> {"mean" |> React.string} </td>
<td className="px-4 py-2"> {"standard deviation" |> React.string} </td>
<td className="px-4 py-2"> {"variance" |> React.string} </td>
</tr>
</thead>
<tbody>
<tr>
<td className="px-4 py-2 border"> {distPlus |> DistPlus.T.mean |> showFloat} </td>
<td className="px-4 py-2 border">
{distPlus |> DistPlus.T.variance |> (r => r ** 0.5) |> showFloat}
</td>
<td className="px-4 py-2 border"> {distPlus |> DistPlus.T.variance |> showFloat} </td>
</tr>
</tbody>
</table>
</div>
let adjustBoth = discreteProbabilityMassFraction => {
let yMaxDiscreteDomainFactor = discreteProbabilityMassFraction
let yMaxContinuousDomainFactor = 1.0 -. discreteProbabilityMassFraction
// use the bigger proportion, such that whichever is the bigger proportion, the yMax is 1.
let yMax = yMaxDiscreteDomainFactor > 0.5 ? yMaxDiscreteDomainFactor : yMaxContinuousDomainFactor
(yMax /. yMaxDiscreteDomainFactor, yMax /. yMaxContinuousDomainFactor)
}
module DistPlusChart = {
@react.component
let make = (~distPlus: DistTypes.distPlus, ~config: chartConfig, ~onHover) => {
open DistPlus
let discrete = distPlus |> T.toDiscrete |> E.O.fmap(Discrete.getShape)
let continuous = distPlus |> T.toContinuous |> E.O.fmap(Continuous.getShape)
// // We subtract a bit from the range to make sure that it fits. Maybe this should be done in d3 instead.
// let minX =
// switch (
// distPlus
// |> DistPlus.T.Integral.yToX(0.0001),
// range,
// ) {
// | (min, Some(range)) => Some(min -. range *. 0.001)
// | _ => None
// };
let minX = distPlus |> DistPlus.T.Integral.yToX(0.00001)
let maxX = distPlus |> DistPlus.T.Integral.yToX(0.99999)
let timeScale = distPlus.unit |> DistTypes.DistributionUnit.toJson
let discreteProbabilityMassFraction = distPlus |> DistPlus.T.toDiscreteProbabilityMassFraction
let (yMaxDiscreteDomainFactor, yMaxContinuousDomainFactor) = adjustBoth(
discreteProbabilityMassFraction,
)
<DistributionPlot
xScale={config.xLog ? "log" : "linear"}
yScale={config.yLog ? "log" : "linear"}
height={DistPlusPlotReducer.heightToPix(config.height)}
minX
maxX
yMaxDiscreteDomainFactor
yMaxContinuousDomainFactor
?discrete
?continuous
color=plotBlue
onHover
timeScale
/>
}
}
module IntegralChart = {
@react.component
let make = (~distPlus: DistTypes.distPlus, ~config: chartConfig, ~onHover) => {
let integral = distPlus.integralCache
let continuous = integral |> Continuous.toLinear |> E.O.fmap(Continuous.getShape)
let minX = distPlus |> DistPlus.T.Integral.yToX(0.00001)
let maxX = distPlus |> DistPlus.T.Integral.yToX(0.99999)
let timeScale = distPlus.unit |> DistTypes.DistributionUnit.toJson
<DistributionPlot
xScale={config.xLog ? "log" : "linear"}
yScale={config.yLog ? "log" : "linear"}
height={DistPlusPlotReducer.heightToPix(config.height)}
minX
maxX
?continuous
color=plotBlue
timeScale
onHover
/>
}
}
module Chart = {
@react.component
let make = (~distPlus: DistTypes.distPlus, ~config: chartConfig, ~onHover) => {
let chart = React.useMemo2(
() =>
config.isCumulative
? <IntegralChart distPlus config onHover />
: <DistPlusChart distPlus config onHover />,
(distPlus, config),
)
<div
style={
open CssJs
style(. [ minHeight(#px(DistPlusPlotReducer.heightToPix(config.height))) ])
}>
chart
</div>
}
}
let button = "bg-gray-300 hover:bg-gray-500 text-grey-darkest text-xs px-4 py-1"
@react.component
let make = (~distPlus: DistTypes.distPlus) => {
let (x, setX) = React.useState(() => 0.)
let (state, dispatch) = React.useReducer(DistPlusPlotReducer.reducer, DistPlusPlotReducer.init)
<div>
{state.distributions
|> E.L.fmapi((index, config) =>
<div className="flex" key={string_of_int(index)}>
<div className="w-4/5"> <Chart distPlus config onHover={r => setX(_ => r)} /> </div>
<div className="w-1/5">
<div className="opacity-50 hover:opacity-100">
<button className=button onClick={_ => dispatch(CHANGE_X_LOG(index))}>
{(config.xLog ? "x-log" : "x-linear") |> React.string}
</button>
<button className=button onClick={_ => dispatch(CHANGE_Y_LOG(index))}>
{(config.yLog ? "y-log" : "y-linear") |> React.string}
</button>
<button
className=button
onClick={_ => dispatch(CHANGE_IS_CUMULATIVE(index, !config.isCumulative))}>
{(config.isCumulative ? "cdf" : "pdf") |> React.string}
</button>
<button className=button onClick={_ => dispatch(HEIGHT_INCREMENT(index))}>
{"expand" |> React.string}
</button>
<button className=button onClick={_ => dispatch(HEIGHT_DECREMENT(index))}>
{"shrink" |> React.string}
</button>
{index != 0
? <button className=button onClick={_ => dispatch(REMOVE_DIST(index))}>
{"remove" |> React.string}
</button>
: React.null}
</div>
</div>
</div>
)
|> E.L.toArray
|> React.array}
<div className="inline-flex opacity-50 hover:opacity-100">
<button className=button onClick={_ => dispatch(CHANGE_SHOW_PERCENTILES)}>
{"Percentiles" |> React.string}
</button>
<button className=button onClick={_ => dispatch(CHANGE_SHOW_STATS)}>
{"Debug Stats" |> React.string}
</button>
<button className=button onClick={_ => dispatch(CHANGE_SHOW_PARAMS)}>
{"Params" |> React.string}
</button>
<button className=button onClick={_ => dispatch(ADD_DIST)}>
{"Add" |> React.string}
</button>
</div>
{state.showParams ? showAsForm(distPlus) : React.null}
{state.showStats ? table(distPlus, x) : React.null}
{state.showPercentiles ? percentiles(distPlus) : React.null}
</div>
}

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type chartConfig = {
xLog: bool,
yLog: bool,
isCumulative: bool,
height: int,
};
type state = {
showStats: bool,
showPercentiles: bool,
showParams: bool,
distributions: list(chartConfig),
};
type action =
| CHANGE_SHOW_STATS
| CHANGE_SHOW_PARAMS
| CHANGE_SHOW_PERCENTILES
| REMOVE_DIST(int)
| ADD_DIST
| CHANGE_X_LOG(int)
| CHANGE_Y_LOG(int)
| CHANGE_IS_CUMULATIVE(int, bool)
| HEIGHT_INCREMENT(int)
| HEIGHT_DECREMENT(int);
let changeHeight = (currentHeight, foo: [ | `increment | `decrement]) =>
switch (currentHeight, foo) {
| (1, `decrement) => 1
| (2, `decrement) => 1
| (3, `decrement) => 2
| (4, `decrement) => 3
| (5, `decrement) => 4
| (1, `increment) => 2
| (2, `increment) => 3
| (3, `increment) => 4
| (4, `increment) => 5
| (5, `increment) => 5
| _ => 1
};
let heightToPix =
fun
| 1 => 80
| 2 => 140
| 3 => 240
| 4 => 340
| 5 => 440
| _ => 140;
let distributionReducer = (index, state: list(chartConfig), action) => {
switch (action, E.L.get(state, index)) {
| (HEIGHT_INCREMENT(_), Some(dist)) =>
E.L.update(
{...dist, height: changeHeight(dist.height, `increment)},
index,
state,
)
| (HEIGHT_DECREMENT(_), Some(dist)) =>
E.L.update(
{...dist, height: changeHeight(dist.height, `decrement)},
index,
state,
)
| (CHANGE_IS_CUMULATIVE(_, isCumulative), Some(dist)) =>
E.L.update({...dist, isCumulative}, index, state)
| (CHANGE_X_LOG(_), Some(dist)) =>
E.L.update({...dist, xLog: !dist.xLog}, index, state)
| (CHANGE_Y_LOG(_), Some(dist)) =>
E.L.update({...dist, yLog: !dist.yLog}, index, state)
| (REMOVE_DIST(_), Some(_)) => E.L.remove(index, 1, state)
| (ADD_DIST, Some(_)) =>
E.L.append(
state,
[{yLog: false, xLog: false, isCumulative: false, height: 4}],
)
| _ => state
};
};
let reducer = (state: state, action: action) =>
switch (action) {
| CHANGE_X_LOG(i)
| CHANGE_Y_LOG(i)
| CHANGE_IS_CUMULATIVE(i, _)
| HEIGHT_DECREMENT(i)
| REMOVE_DIST(i)
| HEIGHT_INCREMENT(i) => {
...state,
distributions: distributionReducer(i, state.distributions, action),
}
| ADD_DIST => {
...state,
distributions: distributionReducer(0, state.distributions, action),
}
| CHANGE_SHOW_STATS => {...state, showStats: !state.showStats}
| CHANGE_SHOW_PARAMS => {...state, showParams: !state.showParams}
| CHANGE_SHOW_PERCENTILES => {
...state,
showPercentiles: !state.showPercentiles,
}
};
let init = {
showStats: false,
showParams: false,
showPercentiles: false,
distributions: [
{yLog: false, xLog: false, isCumulative: false, height: 4},
{yLog: false, xLog: false, isCumulative: true, height: 1},
],
};

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module RawPlot = {
type primaryDistribution = option<{"xs": array<float>, "ys": array<float>}>
type discrete = option<{"xs": array<float>, "ys": array<float>}>
type props
type makeType = props => React.element
@obj external makeProps: (
~height: int=?,
~marginBottom: int=?,
~marginTop: int=?,
~maxX: float=?,
~minX: float=?,
~yMaxContinuousDomainFactor: float=?,
~yMaxDiscreteDomainFactor: float=?,
~onHover: float => (),
~continuous: option<{"xs": array<float>, "ys": array<float>}>=?,
~discrete: option<{"xs": array<float>, "ys": array<float>}>=?,
~xScale: string=?,
~yScale: string=?,
~showDistributionLines: bool=?,
~showDistributionYAxis: bool=?,
~showVerticalLine: bool=?,
~timeScale:Js.Null.t<{"unit": string, "zero": MomentRe.Moment.t}>=?,
~verticalLine: int=?,
~children: array<React.element>=?,
unit // This unit is a quirk of the type system. Apparently it must exist to have optional arguments in a type
) => props = ""
@module("./distPlotReact.js")
external make : makeType = "default"
}
module Styles = {
open CssJs
let textOverlay = style(. [position(#absolute)])
let mainText = style(. [ fontSize(#em(1.1))])
let secondaryText = style(. [fontSize(#em(0.9))])
let graph = chartColor =>
style(. [
position(#relative),
selector(. ".xAxis", [fontSize(#px(9))]),
selector(. ".xAxis .domain", [ display(#none) ]),
selector(. ".xAxis .tick line", [ display(#none) ]),
selector(. ".xAxis .tick text", [ color(#hex("7a8998")) ]),
selector(. ".chart .areaPath", [ SVG.fill(chartColor) ]),
selector(. ".lollipopsLine", [ SVG.stroke(#hex("bfcad4")) ]),
selector(. ".lollipopsCircle", [ SVG.stroke(#hex("bfcad4")), SVG.fill(#hex("bfcad4")) ]),
selector(. ".lollipopsXAxis .domain", [ display(#none) ]),
selector(. ".lollipopsXAxis .tick line", [ display(#none) ]),
selector(. ".lollipopsXAxis .tick text", [ display(#none) ]),
selector(.
".lollipopsTooltip",
[ position(#absolute),
textAlign(#center),
padding(px(2)),
backgroundColor(hex("bfcad4")),
borderRadius(px(3)),
],
),
selector(.
".lollipopsCircleMouseover",
[ SVG.fill(hex("ffa500")), SVG.stroke(#hex("fff")) ],
),
selector(. ".lollipopsLineMouseover", [ SVG.stroke(#hex("ffa500")) ]),
])
}
@react.component
let make = (
~color=#hex("111"),
~discrete=?,
~height=200,
~maxX=?,
~minX=?,
~yMaxDiscreteDomainFactor=?,
~yMaxContinuousDomainFactor=?,
~onHover: float => unit=_ => (),
~continuous=?,
~xScale=?,
~yScale=?,
~showDistributionLines=false,
~showDistributionYAxis=false,
~showVerticalLine=false,
~timeScale=?,
) =>
<div style={Styles.graph(color)}>
<RawPlot
?maxX
?minX
?yMaxDiscreteDomainFactor
?yMaxContinuousDomainFactor
?xScale
?yScale
?timeScale
discrete={discrete |> E.O.fmap(XYShape.T.toJs)}
height
marginBottom=50
marginTop=0
onHover
continuous={continuous |> E.O.fmap(XYShape.T.toJs)}
showDistributionLines
showDistributionYAxis
showVerticalLine
/>
</div>

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import * as _ from "lodash";
import { createClassFromSpec } from "react-vega";
import spec from "./spec-percentiles";
const PercentilesChart = createClassFromSpec({
spec,
style: "width: 100%",
});
export { PercentilesChart };

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@module("./PercentilesChart.js")
external percentilesChart: React.element = "PercentilesChart"
module Internal = {
type props
type makeType = props => React.element
type dataType = { "facet": array<
{
"p1": float,
"p10": float,
"p20": float,
"p30": float,
"p40": float,
"p5": float,
"p50": float,
"p60": float,
"p70": float,
"p80": float,
"p90": float,
"p95": float,
"p99": float,
"x": float,
}>}
@obj external makeProps: (~data: dataType, ~signalListeners: list<string>,~children:React.element, unit) => props = ""
@module("./PercentilesChart.js")
external make : makeType = "PercentilesChart"
}
@react.component
@module("./PercentilesChart.js")
let make = (~dists: array<(float, DistTypes.distPlus)>, ~children=React.null) => {
let data = dists |> E.A.fmap(((x, r)) =>
{
"x": x,
"p1": r |> DistPlus.T.Integral.yToX(0.01),
"p5": r |> DistPlus.T.Integral.yToX(0.05),
"p10": r |> DistPlus.T.Integral.yToX(0.1),
"p20": r |> DistPlus.T.Integral.yToX(0.2),
"p30": r |> DistPlus.T.Integral.yToX(0.3),
"p40": r |> DistPlus.T.Integral.yToX(0.4),
"p50": r |> DistPlus.T.Integral.yToX(0.5),
"p60": r |> DistPlus.T.Integral.yToX(0.6),
"p70": r |> DistPlus.T.Integral.yToX(0.7),
"p80": r |> DistPlus.T.Integral.yToX(0.8),
"p90": r |> DistPlus.T.Integral.yToX(0.9),
"p95": r |> DistPlus.T.Integral.yToX(0.95),
"p99": r |> DistPlus.T.Integral.yToX(0.99),
}
)
Js.log3("Data", dists, data)
let da = {"facet": data}
<Internal data=da signalListeners=list{}>children</Internal>
}

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const _ = require('lodash');
const d3 = require('d3');
const moment = require('moment');
require('./styles.css');
/**
* @param arr
* @returns {*}
*/
function exists(arr) {
return arr.find(num => _.isFinite(num));
}
export class DistPlotD3 {
constructor() {
this.attrs = {
svgWidth: 400,
svgHeight: 400,
marginTop: 5,
marginBottom: 5,
marginRight: 50,
marginLeft: 5,
container: null,
// X
minX: null,
maxX: null,
xScaleType: 'linear',
xScaleTimeOptions: null,
xScaleLogBase: 10,
// Y
minY: null,
maxY: null,
yScaleType: 'linear',
yScaleTimeOptions: null,
yScaleLogBase: 10,
xMinContinuousDomainFactor: 1,
xMaxContinuousDomainFactor: 1,
yMaxContinuousDomainFactor: 1,
yMaxDiscreteDomainFactor: 1,
showDistributionYAxis: false,
showDistributionLines: true,
areaColors: ['#E1E5EC', '#E1E5EC'],
verticalLine: 110,
showVerticalLine: true,
data: {
continuous: null,
discrete: null,
},
onHover: (e) => {
},
};
this.calc = {
chartLeftMargin: null,
chartTopMargin: null,
chartWidth: null,
chartHeight: null,
};
this.chart = null;
this.svg = null;
this._container = null;
this.formatDates = this.formatDates.bind(this);
}
/**
* @param {string} name
* @param value
* @returns {DistPlotD3}
*/
set(name, value) {
_.set(this.attrs, [name], value);
return this;
}
/**
* @param data
* @returns {DistPlotD3}
*/
data(data) {
const continuousXs = _.get(data, 'continuous.xs', []);
const continuousYs = _.get(data, 'continuous.ys', []);
const discreteXs = _.get(data, 'discrete.xs', []);
const discreteYs = _.get(data, 'discrete.ys', []);
this.attrs.data = data;
this.attrs.data.continuous = {
xs: continuousXs,
ys: continuousYs,
};
this.attrs.data.discrete = {
xs: discreteXs,
ys: discreteYs,
};
return this;
}
render() {
this._container = d3.select(this.attrs.container);
if (this._container.node() === null) {
throw new Error('Container for D3 is not defined.');
}
if (!['log', 'linear'].includes(this.attrs.xScaleType)) {
throw new Error('X-scale type should be either "log" or "linear".');
}
if (!['log', 'linear'].includes(this.attrs.yScaleType)) {
throw new Error('Y-scale type should be either "log" or "linear".');
}
// Log Scale.
if (this.attrs.xScaleType === 'log') {
this.logFilter('continuous', (x, y) => x > 0);
this.logFilter('discrete', (x, y) => x > 0);
}
if (this.attrs.yScaleType === 'log') {
this.logFilter('continuous', (x, y) => y > 0);
this.logFilter('discrete', (x, y) => y > 0);
}
if (
this.attrs.xScaleType === 'log'
&& this.attrs.minX !== null
&& this.attrs.minX < 0
) {
console.warn('minX should be positive.');
this.attrs.minX = undefined;
}
if (
this.attrs.yScaleType === 'log'
&& this.attrs.minY !== null
&& this.attrs.minY < 0
) {
console.warn('minY should be positive.');
this.attrs.minY = undefined;
}
// Fields.
const fields = [
'marginLeft', 'marginRight',
'marginTop', 'marginBottom',
'svgWidth', 'svgHeight',
'yMaxContinuousDomainFactor',
'yMaxDiscreteDomainFactor',
'xScaleLogBase', 'yScaleLogBase',
];
for (const field of fields) {
if (!_.isNumber(this.attrs[field])) {
throw new Error(`${field} should be a number.`);
}
}
// Sets the width from the DOM element.
const containerRect = this._container.node().getBoundingClientRect();
if (containerRect.width > 0) {
this.attrs.svgWidth = containerRect.width;
}
// Calculated properties.
this.calc.chartLeftMargin = this.attrs.marginLeft;
this.calc.chartTopMargin = this.attrs.marginTop;
this.calc.chartWidth = this.attrs.svgWidth
- this.attrs.marginRight
- this.attrs.marginLeft;
this.calc.chartHeight = this.attrs.svgHeight
- this.attrs.marginBottom
- this.attrs.marginTop;
// Add svg.
this.svg = this._container
.createObject({ tag: 'svg', selector: 'svg-chart-container' })
.attr('width', '100%')
.attr('height', this.attrs.svgHeight)
.attr('pointer-events', 'none');
// Add container 'g' (empty) element.
this.chart = this.svg
.createObject({ tag: 'g', selector: 'chart' })
.attr(
'transform',
`translate(${this.calc.chartLeftMargin}, ${this.calc.chartTopMargin})`,
);
try {
const common = this.getCommonThings();
if (this.hasDate('continuous')) {
this.addDistributionChart(common);
}
if (this.hasDate('discrete')) {
this.addLollipopsChart(common);
}
} catch (e) {
this._container.selectAll("*").remove();
throw e;
}
return this;
}
/**
* @returns {*}
*/
getCommonThings() {
// Boundaries.
const xMin = exists([
this.attrs.minX,
d3.min(this.attrs.data.continuous.xs),
d3.min(this.attrs.data.discrete.xs),
]);
const xMax = exists([
this.attrs.maxX,
d3.max(this.attrs.data.continuous.xs),
d3.max(this.attrs.data.discrete.xs),
]);
const yMin = exists([
this.attrs.minY,
d3.min(this.attrs.data.continuous.ys),
d3.min(this.attrs.data.discrete.ys),
]);
const yMax = exists([
this.attrs.maxY,
d3.max(this.attrs.data.continuous.ys),
d3.max(this.attrs.data.discrete.ys),
]);
// Errors.
if (!_.isFinite(xMin)) throw new Error('xMin is undefined');
if (!_.isFinite(xMax)) throw new Error('xMax is undefined');
if (!_.isFinite(yMin)) throw new Error('yMin is undefined');
if (!_.isFinite(yMax)) throw new Error('yMax is undefined');
// X-domains.
const xMinDomainFactor = _.get(this.attrs, 'xMinContinuousDomainFactor', 1);
const xMaxDomainFactor = _.get(this.attrs, 'xMaxContinuousDomainFactor', 1);
const yMinDomainFactor = _.get(this.attrs, 'yMinContinuousDomainFactor', 1);
const yMaxDomainFactor = _.get(this.attrs, 'yMaxContinuousDomainFactor', 1);
const xMinDomain = xMin * xMinDomainFactor;
const xMaxDomain = xMax * xMaxDomainFactor;
const yMinDomain = yMin * yMinDomainFactor;
const yMaxDomain = yMax * yMaxDomainFactor;
// X-scale.
const xScale = this.attrs.xScaleType === 'linear'
? d3.scaleLinear()
.domain([xMinDomain, xMaxDomain])
.range([0, this.calc.chartWidth])
: d3.scaleLog()
.base(this.attrs.xScaleLogBase)
.domain([xMinDomain, xMaxDomain])
.range([0, this.calc.chartWidth]);
// Y-scale.
const yScale = this.attrs.yScaleType === 'linear'
? d3.scaleLinear()
.domain([yMinDomain, yMaxDomain])
.range([this.calc.chartHeight, 0])
: d3.scaleLog()
.base(this.attrs.yScaleLogBase)
.domain([yMinDomain, yMaxDomain])
.range([this.calc.chartHeight, 0]);
return {
xMin, xMax,
xScale, yScale,
};
}
/**
* @param common
*/
addDistributionChart(common) {
const areaColorRange = d3.scaleOrdinal().range(this.attrs.areaColors);
const dataPoints = [this.getDataPoints('continuous')];
const { xMin, xMax, xScale, yScale } = common;
// X-axis.
let xAxis = null;
if (!!this.attrs.xScaleTimeOptions) {
// Calculates the projection on X-axis.
const zero = _.get(this.attrs, 'xScaleTimeOptions.zero', moment());
const unit = _.get(this.attrs, 'xScaleTimeOptions.unit', 'years');
const diff = Math.abs(xMax - xMin);
const left = zero.clone().add(xMin, unit);
const right = left.clone().add(diff, unit);
// X-time-scale.
const xScaleTime = d3.scaleTime()
.domain([left.toDate(), right.toDate()])
.nice()
.range([0, this.calc.chartWidth]);
xAxis = d3.axisBottom()
.scale(xScaleTime)
.ticks(this.getTimeTicksByStr(unit))
.tickFormat(this.formatDates);
} else {
xAxis = d3.axisBottom(xScale)
.ticks(3)
.tickFormat(d => {
if (Math.abs(d) < 1) {
return d3.format('.2')(d);
} else if (xMin > 1000 && xMax < 3000) {
// Condition which identifies years; 2019, 2020, 2021.
return d3.format('.0')(d);
} else {
const prefix = d3.formatPrefix('.0', d);
return prefix(d).replace('G', 'B');
}
});
}
// Y-axis.
const yAxis = d3.axisRight(yScale);
// Add axis.
this.chart
.createObject({ tag: 'g', selector: 'x-axis' })
.attr('transform', `translate(0, ${this.calc.chartHeight})`)
.call(xAxis);
if (this.attrs.showDistributionYAxis) {
this.chart
.createObject({ tag: 'g', selector: 'y-axis' })
.call(yAxis);
}
// Draw area.
const area = d3.area()
.x(d => xScale(d.x))
.y1(d => yScale(d.y))
.y0(this.calc.chartHeight);
this.chart
.createObjectsWithData({
tag: 'path',
selector: 'area-path',
data: dataPoints,
})
.attr('d', area)
.attr('fill', (d, i) => areaColorRange(i))
.attr('opacity', (d, i) => i === 0 ? 0.7 : 0.5);
// Draw line.
if (this.attrs.showDistributionLines) {
const line = d3.line()
.x(d => xScale(d.x))
.y(d => yScale(d.y));
this.chart
.createObjectsWithData({
tag: 'path',
selector: 'line-path',
data: dataPoints,
})
.attr('d', line)
.attr('id', (d, i) => 'line-' + (i + 1))
.attr('opacity', (d, i) => i === 0 ? 0.7 : 1)
.attr('fill', 'none');
}
if (this.attrs.showVerticalLine) {
this.chart
.createObject({ tag: 'line', selector: 'v-line' })
.attr('x1', xScale(this.attrs.verticalLine))
.attr('x2', xScale(this.attrs.verticalLine))
.attr('y1', 0)
.attr('y2', this.calc.chartHeight)
.attr('stroke-width', 1.5)
.attr('stroke-dasharray', '6 6')
.attr('stroke', 'steelblue');
}
const hoverLine = this.chart
.createObject({ tag: 'line', selector: 'hover-line' })
.attr('x1', 0)
.attr('x2', 0)
.attr('y1', 0)
.attr('y2', this.calc.chartHeight)
.attr('opacity', 0)
.attr('stroke-width', 1.5)
.attr('stroke-dasharray', '6 6')
.attr('stroke', '#22313F');
// Add drawing rectangle.
{
const context = this;
function mouseover() {
const mouse = d3.mouse(this);
hoverLine
.attr('opacity', 1)
.attr('x1', mouse[0])
.attr('x2', mouse[0]);
const xValue = xScale.invert(mouse[0]);
context.attrs.onHover(xValue);
}
function mouseout() {
hoverLine.attr('opacity', 0);
}
this.chart
.createObject({ tag: 'rect', selector: 'mouse-rect' })
.attr('width', this.calc.chartWidth)
.attr('height', this.calc.chartHeight)
.attr('fill', 'transparent')
.attr('pointer-events', 'all')
.on('mouseover', mouseover)
.on('mousemove', mouseover)
.on('mouseout', mouseout);
}
}
/**
* @param {object} common
* @param {object} common.xScale
* @param {object} common.yScale
*/
addLollipopsChart(common) {
const data = this.getDataPoints('discrete');
const yMin = 0.;
const yMax = d3.max(this.attrs.data.discrete.ys);
// X axis.
this.chart.append('g')
.attr('class', 'lollipops-x-axis')
.attr('transform', `translate(0, ${this.calc.chartHeight})`)
.call(d3.axisBottom(common.xScale));
// Y-domain.
const yMinDomainFactor = _.get(this.attrs, 'yMinDiscreteDomainFactor', 1);
const yMaxDomainFactor = _.get(this.attrs, 'yMaxDiscreteDomainFactor', 1);
const yMinDomain = yMin * yMinDomainFactor;
const yMaxDomain = yMax * yMaxDomainFactor;
// Y-scale.
const yScale = this.attrs.yScaleType === 'linear'
? d3.scaleLinear()
.domain([yMinDomain, yMaxDomain])
.range([this.calc.chartHeight, 0])
: d3.scaleLog()
.base(this.attrs.yScaleLogBase)
.domain([yMinDomain, yMaxDomain])
.range([this.calc.chartHeight, 0]);
//
const yTicks = Math.floor(this.calc.chartHeight / 20);
const yAxis = d3.axisLeft(yScale).ticks(yTicks);
// Adds 'g' for an y-axis.
this.chart.append('g')
.attr('class', 'lollipops-y-axis')
.attr('transform', `translate(${this.calc.chartWidth}, 0)`)
.call(yAxis);
const thi$ = this;
function showTooltip(d) {
thi$.chart.select('.lollipops-line-' + d.id)
.classed('lollipops-line-mouseover', true);
thi$.chart.select('.lollipops-circle-' + d.id)
.classed('lollipops-circle-mouseover', true)
.attr('r', 6);
tooltip.transition()
.style('opacity', .9);
tooltip.html(`x: ${d.x}, y: ${(d.y * 100).toFixed(1)}%`)
.style('left', (common.xScale(d.x) + 60) + 'px')
.style('top', yScale(d.y) + 'px');
}
function hideTooltip(d) {
thi$.chart.select('.lollipops-line-' + d.id)
.classed('lollipops-line-mouseover', false);
thi$.chart.select('.lollipops-circle-' + d.id)
.classed('lollipops-circle-mouseover', false)
.attr('r', 4);
tooltip.transition()
.style('opacity', 0);
}
// Lines.
this.chart.selectAll('lollipops-line')
.data(data)
.enter()
.append('line')
.attr('class', 'lollipops-line')
.attr('class', d => 'lollipops-line lollipops-line-' + d.id)
.attr('x1', d => common.xScale(d.x))
.attr('x2', d => common.xScale(d.x))
.attr('y1', d => yScale(d.y))
.attr('y2', yScale(yMin));
// Define the div for the tooltip
const tooltip = this._container.append('div')
.attr('class', 'lollipop-tooltip')
.style('opacity', 0);
// Circles.
this.chart.selectAll('lollipops-circle')
.data(data)
.enter()
.append('circle')
.attr('class', d => 'lollipops-circle lollipops-circle-' + d.id)
.attr('cx', d => common.xScale(d.x))
.attr('cy', d => yScale(d.y))
.attr('r', '4');
// Rectangles.
this.chart.selectAll('lollipops-rectangle')
.data(data)
.enter()
.append('rect')
.attr('width', 30)
.attr('height', d => this.calc.chartHeight - yScale(d.y) + 10)
.attr('x', d => common.xScale(d.x) - 15)
.attr('y', d => yScale(d.y) - 10)
.attr('opacity', 0)
.attr('pointer-events', 'all')
.on('mouseover', showTooltip)
.on('mouseout', hideTooltip)
;
}
/**
* @param ts
* @returns {string}
*/
formatDates(ts) {
return moment(ts).format('MMMM Do YYYY');
}
/**
* @param {string} unit
* @returns {*}
*/
getTimeTicksByStr(unit) {
switch (unit) {
case 'months':
return d3.timeMonth.every(4);
case 'quarters':
// It is temporary solution, but it works
// if the difference between edge dates is not
// much more than 10 units.
return d3.timeMonth.every(12);
case 'hours':
return d3.timeHour.every(10);
case 'days':
return d3.timeDay.every(7);
case 'seconds':
return d3.timeSecond.every(10);
case 'years':
return d3.timeYear.every(10);
case 'minutes':
return d3.timeMinute.every(10);
case 'weeks':
return d3.timeWeek.every(10);
case 'milliseconds':
return d3.timeMillisecond.every(10);
default:
return d3.timeYear.every(10);
}
}
/**
* @param {string} key
* @returns {{x: number[], y: number[]}}
*/
getDataPoints(key) {
const dt = [];
const emptyShape = { xs: [], ys: [] };
const data = _.get(this.attrs.data, key, emptyShape);
const len = data.xs.length;
for (let i = 0; i < len; i++) {
const x = data.xs[i];
const y = data.ys[i];
const id = i;
dt.push({ x, y, id });
}
return dt;
}
/**
* @param {string} key
* @param {function} pred
* @returns {{x: number[], y: number[]}}
*/
logFilter(key, pred) {
const xs = [];
const ys = [];
const emptyShape = { xs: [], ys: [] };
const data = _.get(this.attrs.data, key, emptyShape);
for (let i = 0, len = data.xs.length; i < len; i++) {
const x = data.xs[i];
const y = data.ys[i];
if (pred(x, y)) {
xs.push(x);
ys.push(y);
}
}
_.set(this.attrs.data, [key, 'xs'], xs);
_.set(this.attrs.data, [key, 'ys'], ys);
}
/**
* @param {string} key
* @returns {boolean}
*/
hasDate(key) {
const xs = _.get(this.attrs, ['data', key, 'xs']);
return !!_.size(xs);
}
}
/**
* @docs: https://github.com/d3/d3-selection
* @param {object} params
* @param {string} params.selector
* @param {string} params.tag
* @returns {*}
*/
d3.selection.prototype.createObject = function createObject(params) {
const selector = params.selector;
const tag = params.tag;
return this.insert(tag).attr('class', selector);
};
/**
* @docs: https://github.com/d3/d3-selection
* @param {object} params
* @param {string} params.selector
* @param {string} params.tag
* @param {*[]} params.data
* @returns {*}
*/
d3.selection.prototype.createObjectsWithData = function createObjectsWithData(params) {
const selector = params.selector;
const tag = params.tag;
const data = params.data;
return this.selectAll('.' + selector)
.data(data)
.enter()
.insert(tag)
.attr('class', selector);
};

81
packages/squiggle-old/src/components/charts/DistributionPlot/distPlotReact.js Normal file
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import React, { useEffect } from 'react';
import { useSize } from 'react-use';
import { DistPlotD3 } from './distPlotD3';
/**
* @param min
* @param max
* @returns {number}
*/
function getRandomInt(min, max) {
min = Math.ceil(min);
max = Math.floor(max);
return Math.floor(Math.random() * (max - min + 1)) + min;
}
/**
* @param props
* @returns {*}
* @constructor
*/
function DistPlotReact(props) {
const containerRef = React.createRef();
const key = "cdf-chart-react-" + getRandomInt(0, 1000);
const style = !!props.width ? { width: props.width + "px" } : {};
const [sized, { width }] = useSize(() => {
return React.createElement("div", {
key: "resizable-div",
});
}, {
width: props.width,
});
useEffect(() => {
try {
new DistPlotD3()
.set('svgWidth', width)
.set('svgHeight', props.height)
.set('maxX', props.maxX)
.set('minX', props.minX)
.set('onHover', props.onHover)
.set('marginBottom', props.marginBottom || 15)
.set('marginLeft', 30)
.set('marginRight', 30)
.set('marginTop', 5)
.set('showDistributionLines', props.showDistributionLines)
.set('showDistributionYAxis', props.showDistributionYAxis)
.set('verticalLine', props.verticalLine || 110)
.set('showVerticalLine', props.showVerticalLine)
.set('container', containerRef.current)
.set('xScaleType', props.xScale || 'linear')
.set('yScaleType', props.yScale || 'linear')
.set('xScaleTimeOptions', props.timeScale)
.set('yMaxContinuousDomainFactor', props.yMaxContinuousDomainFactor || 1)
.set('yMaxDiscreteDomainFactor', props.yMaxDiscreteDomainFactor || 1)
.data({
continuous: props.continuous,
discrete: props.discrete,
})
.render();
} catch (e) {
console.error("distPlotD3 Error: ", e)
}
});
return React.createElement("div", {
style: {
paddingLeft: "10px",
paddingRight: "10px",
},
}, [
sized,
React.createElement("div", {
key,
style,
ref: containerRef,
}),
]);
}
export default DistPlotReact;

208
packages/squiggle-old/src/components/charts/DistributionPlot/spec-percentiles.json Normal file
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{
"$schema": "https://vega.github.io/schema/vega/v5.json",
"width": 500,
"height": 400,
"padding": 5,
"data": [
{
"name": "facet",
"values": [],
"format": { "type": "json", "parse": { "timestamp": "date" } }
},
{
"name": "table",
"source": "facet",
"transform": [
{
"type": "aggregate",
"groupby": ["x"],
"ops": [
"mean",
"mean",
"mean",
"mean",
"mean",
"mean",
"mean",
"mean",
"mean",
"mean",
"mean",
"mean",
"mean"
],
"fields": [
"p1",
"p5",
"p10",
"p20",
"p30",
"p40",
"p50",
"p60",
"p70",
"p80",
"p90",
"p95",
"p99"
],
"as": [
"p1",
"p5",
"p10",
"p20",
"p30",
"p40",
"p50",
"p60",
"p70",
"p80",
"p90",
"p95",
"p99"
]
}
]
}
],
"scales": [
{
"name": "xscale",
"type": "linear",
"nice": true,
"domain": { "data": "facet", "field": "x" },
"range": "width"
},
{
"name": "yscale",
"type": "linear",
"range": "height",
"nice": true,
"zero": true,
"domain": { "data": "facet", "field": "p99" }
}
],
"axes": [
{
"orient": "bottom",
"scale": "xscale",
"grid": false,
"tickSize": 2,
"encode": {
"grid": { "enter": { "stroke": { "value": "#ccc" } } },
"ticks": { "enter": { "stroke": { "value": "#ccc" } } }
}
},
{
"orient": "left",
"scale": "yscale",
"grid": false,
"domain": false,
"tickSize": 2,
"encode": {
"grid": { "enter": { "stroke": { "value": "#ccc" } } },
"ticks": { "enter": { "stroke": { "value": "#ccc" } } }
}
}
],
"marks": [
{
"type": "area",
"from": { "data": "table" },
"encode": {
"enter": { "fill": { "value": "#4C78A8" } },
"update": {
"interpolate": { "value": "monotone" },
"x": { "scale": "xscale", "field": "x" },
"y": { "scale": "yscale", "field": "p1" },
"y2": { "scale": "yscale", "field": "p99" },
"opacity": { "value": 0.05 }
}
}
},
{
"type": "area",
"from": { "data": "table" },
"encode": {
"enter": { "fill": { "value": "#4C78A8" } },
"update": {
"interpolate": { "value": "monotone" },
"x": { "scale": "xscale", "field": "x" },
"y": { "scale": "yscale", "field": "p5" },
"y2": { "scale": "yscale", "field": "p95" },
"opacity": { "value": 0.1 }
}
}
},
{
"type": "area",
"from": { "data": "table" },
"encode": {
"enter": { "fill": { "value": "#4C78A8" } },
"update": {
"interpolate": { "value": "monotone" },
"x": { "scale": "xscale", "field": "x" },
"y": { "scale": "yscale", "field": "p10" },
"y2": { "scale": "yscale", "field": "p90" },
"opacity": { "value": 0.15 }
}
}
},
{
"type": "area",
"from": { "data": "table" },
"encode": {
"enter": { "fill": { "value": "#4C78A8" } },
"update": {
"interpolate": { "value": "monotone" },
"x": { "scale": "xscale", "field": "x" },
"y": { "scale": "yscale", "field": "p20" },
"y2": { "scale": "yscale", "field": "p80" },
"opacity": { "value": 0.2 }
}
}
},
{
"type": "area",
"from": { "data": "table" },
"encode": {
"enter": { "fill": { "value": "#4C78A8" } },
"update": {
"interpolate": { "value": "monotone" },
"x": { "scale": "xscale", "field": "x" },
"y": { "scale": "yscale", "field": "p30" },
"y2": { "scale": "yscale", "field": "p70" },
"opacity": { "value": 0.2 }
}
}
},
{
"type": "area",
"from": { "data": "table" },
"encode": {
"enter": { "fill": { "value": "#4C78A8" } },
"update": {
"interpolate": { "value": "monotone" },
"x": { "scale": "xscale", "field": "x" },
"y": { "scale": "yscale", "field": "p40" },
"y2": { "scale": "yscale", "field": "p60" },
"opacity": { "value": 0.2 }
}
}
},
{
"type": "line",
"from": { "data": "table" },
"encode": {
"update": {
"interpolate": { "value": "monotone" },
"stroke": { "value": "#4C78A8" },
"strokeWidth": { "value": 2 },
"opacity": { "value": 0.8 },
"x": { "scale": "xscale", "field": "x" },
"y": { "scale": "yscale", "field": "p50" }
}
}
}
]
}

10
packages/squiggle-old/src/components/charts/DistributionPlot/styles.css Normal file
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.lollipops-line-mouseover {
stroke-dasharray: 4;
animation: dash 2s linear infinite;
}
@keyframes dash {
to {
stroke-dashoffset: 1000;
}
}

31
packages/squiggle-old/src/components/charts/NumberShower.res Normal file
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module JS = {
@deriving(abstract)
type numberPresentation = {
value: string,
power: option<float>,
symbol: option<string>,
}
@module("./numberShower.js")
external numberShow: (float, int) => numberPresentation = "numberShow"
}
let sup = {
open CssJs
style(. [ fontSize(#em(0.6)), verticalAlign(#super) ])
}
@react.component
let make = (~number, ~precision) => {
let numberWithPresentation = JS.numberShow(number, precision)
<span>
{JS.valueGet(numberWithPresentation) |> React.string}
{JS.symbolGet(numberWithPresentation) |> E.O.React.fmapOrNull(React.string)}
{JS.powerGet(numberWithPresentation) |> E.O.React.fmapOrNull(e =>
<span>
{j`\\u00b710` |> React.string}
<span style=sup> {e |> E.Float.toString |> React.string} </span>
</span>
)}
</span>
}

65
packages/squiggle-old/src/components/charts/numberShower.js Normal file
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// 105 -> 3
const orderOfMagnitudeNum = (n) => {
return Math.pow(10, n);
};
// 105 -> 3
const orderOfMagnitude = (n) => {
return Math.floor(Math.log(n) / Math.LN10 + 0.000000001);
};
function withXSigFigs(number, sigFigs) {
const withPrecision = number.toPrecision(sigFigs);
const formatted = Number(withPrecision);
return `${formatted}`;
}
class NumberShower {
constructor(number, precision = 2) {
this.number = number;
this.precision = precision;
}
convert() {
const number = Math.abs(this.number);
const response = this.evaluate(number);
if (this.number < 0) {
response.value = '-' + response.value;
}
return response
}
metricSystem(number, order) {
const newNumber = number / orderOfMagnitudeNum(order);
const precision = this.precision;
return `${withXSigFigs(newNumber, precision)}`;
}
evaluate(number) {
if (number === 0) {
return { value: this.metricSystem(0, 0) }
}
const order = orderOfMagnitude(number);
if (order < -2) {
return { value: this.metricSystem(number, order), power: order };
} else if (order < 4) {
return { value: this.metricSystem(number, 0) };
} else if (order < 6) {
return { value: this.metricSystem(number, 3), symbol: 'K' };
} else if (order < 9) {
return { value: this.metricSystem(number, 6), symbol: 'M' };
} else if (order < 12) {
return { value: this.metricSystem(number, 9), symbol: 'B' };
} else if (order < 15) {
return { value: this.metricSystem(number, 12), symbol: 'T' };
} else {
return { value: this.metricSystem(number, order), power: order };
}
}
}
export function numberShow(number, precision = 2) {
const ns = new NumberShower(number, precision);
return ns.convert();
}

171
packages/squiggle-old/src/distPlus/ProgramEvaluator.res Normal file
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// TODO: This setup is more confusing than it should be, there's more work to do in cleanup here.
module Inputs = {
module SamplingInputs = {
type t = {
sampleCount: option<int>,
outputXYPoints: option<int>,
kernelWidth: option<float>,
shapeLength: option<int>,
}
}
let defaultRecommendedLength = 100
let defaultShouldDownsample = true
type inputs = {
squiggleString: string,
samplingInputs: SamplingInputs.t,
environment: ExpressionTypes.ExpressionTree.environment,
}
let empty: SamplingInputs.t = {
sampleCount: None,
outputXYPoints: None,
kernelWidth: None,
shapeLength: None,
}
let make = (
~samplingInputs=empty,
~squiggleString,
~environment=ExpressionTypes.ExpressionTree.Environment.empty,
(),
): inputs => {
samplingInputs: samplingInputs,
squiggleString: squiggleString,
environment: environment,
}
}
type \"export" = [
| #DistPlus(ProbExample.DistPlus.t)
| #Float(float)
| #Function(
(array<string>, ProbExample.ExpressionTypes.ExpressionTree.node),
ProbExample.ExpressionTypes.ExpressionTree.environment,
)
]
module Internals = {
let addVariable = (
{samplingInputs, squiggleString, environment}: Inputs.inputs,
str,
node,
): Inputs.inputs => {
samplingInputs: samplingInputs,
squiggleString: squiggleString,
environment: ExpressionTypes.ExpressionTree.Environment.update(environment, str, _ => Some(
node,
)),
}
type outputs = {
graph: ExpressionTypes.ExpressionTree.node,
shape: DistTypes.shape,
}
let makeOutputs = (graph, shape): outputs => {graph: graph, shape: shape}
let makeInputs = (inputs: Inputs.inputs): ExpressionTypes.ExpressionTree.samplingInputs => {
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),
}
let runNode = (inputs, node) =>
ExpressionTree.toLeaf(makeInputs(inputs), inputs.environment, node)
let runProgram = (inputs: Inputs.inputs, p: ExpressionTypes.Program.program) => {
let ins = ref(inputs)
p
|> E.A.fmap(x =>
switch x {
| #Assignment(name, node) =>
ins := addVariable(ins.contents, name, node)
None
| #Expression(node) =>
Some(runNode(ins.contents, node) |> E.R.fmap(r => (ins.contents.environment, r)))
}
)
|> E.A.O.concatSomes
|> E.A.R.firstErrorOrOpen
}
let inputsToLeaf = (inputs: Inputs.inputs) =>
MathJsParser.fromString(inputs.squiggleString)
|> E.R.bind(_, g => runProgram(inputs, g))
let outputToDistPlus = (inputs: Inputs.inputs, shape: DistTypes.shape) =>
DistPlus.make(~shape, ~squiggleString=Some(inputs.squiggleString), ())
}
let renderIfNeeded = (inputs: Inputs.inputs, node: ExpressionTypes.ExpressionTree.node): result<
ExpressionTypes.ExpressionTree.node,
string,
> =>
node |> (
x =>
switch x {
| #Normalize(_) as n
| #SymbolicDist(_) as n =>
#Render(n)
|> Internals.runNode(inputs)
|> (
x =>
switch x {
| Ok(#RenderedDist(_)) as r => r
| Error(r) => Error(r)
| _ => Error("Didn't render, but intended to")
}
)
| n => Ok(n)
}
)
// TODO: Consider using ExpressionTypes.ExpressionTree.getFloat or similar in this function
let coersionToExportedTypes = (
inputs,
env: ProbExample.ExpressionTypes.ExpressionTree.environment,
node: ExpressionTypes.ExpressionTree.node,
): result<\"export", string> =>
node
|> renderIfNeeded(inputs)
|> E.R.bind(_, x =>
switch x {
| #RenderedDist(Discrete({xyShape: {xs: [x], ys: [1.0]}})) => Ok(#Float(x))
| #SymbolicDist(#Float(x)) => Ok(#Float(x))
| #RenderedDist(n) => Ok(#DistPlus(Internals.outputToDistPlus(inputs, n)))
| #Function(n) => Ok(#Function(n, env))
| n => Error("Didn't output a rendered distribution. Format:" ++ ExpressionTree.toString(n))
}
)
let rec mapM = (f, xs) =>
switch xs {
| list{} => Ok(list{})
| list{x, ...rest} =>
switch f(x) {
| Error(err) => Error(err)
| Ok(val) =>
switch mapM(f, rest) {
| Error(err) => Error(err)
| Ok(restList) => Ok(list{val, ...restList})
}
}
}
let evaluateProgram = (inputs: Inputs.inputs) =>
inputs |> Internals.inputsToLeaf |> E.R.bind(_, xs => mapM(((a, b)) => coersionToExportedTypes(inputs, a, b), (Array.to_list(xs))))
let evaluateFunction = (
inputs: Inputs.inputs,
fn: (array<string>, ExpressionTypes.ExpressionTree.node),
fnInputs,
) => {
let output = ExpressionTree.runFunction(
Internals.makeInputs(inputs),
inputs.environment,
fnInputs,
fn,
)
output |> E.R.bind(_, coersionToExportedTypes(inputs, inputs.environment))
}

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type pointMassesWithMoments = {
n: int,
masses: array(float),
means: array(float),
variances: array(float),
};
/* This function takes a continuous distribution and efficiently approximates it as
point masses that have variances associated with them.
We estimate the means and variances from overlapping triangular distributions which we imagine are making up the
XYShape.
We can then use the algebra of random variables to "convolve" the point masses and their variances,
and finally reconstruct a new distribution from them, e.g. using a Fast Gauss Transform or Raykar et al. (2007). */
let toDiscretePointMassesFromTriangulars =
(~inverse=false, s: XYShape.T.t): pointMassesWithMoments => {
// TODO: what if there is only one point in the distribution?
let n = s |> XYShape.T.length;
// first, double up the leftmost and rightmost points:
let {xs, ys}: XYShape.T.t = s;
Js.Array.unshift(xs[0], xs) |> ignore;
Js.Array.unshift(ys[0], ys) |> ignore;
Js.Array.push(xs[n - 1], xs) |> ignore;
Js.Array.push(ys[n - 1], ys) |> ignore;
let n = E.A.length(xs);
// squares and neighbourly products of the xs
let xsSq: array(float) = Belt.Array.makeUninitializedUnsafe(n);
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;
();
};
for (i in 0 to n - 2) {
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;
();
};
// means and variances
let masses: array(float) = Belt.Array.makeUninitializedUnsafe(n - 2); // doesn't include the fake first and last points
let means: array(float) = Belt.Array.makeUninitializedUnsafe(n - 2);
let variances: array(float) = Belt.Array.makeUninitializedUnsafe(n - 2);
if (inverse) {
for (i in 1 to n - 2) {
Belt.Array.set(masses, 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];
let c = xs[i];
let b = xs[i + 1];
// These are the moments of the reciprocal of a triangular distribution, as symbolically integrated by Mathematica.
// They're probably pretty close to invMean ~ 1/mean = 3/(a+b+c) and invVar. But I haven't worked out
// the worst case error, so for now let's use these monster equations
let inverseMean =
2.
*. (a *. log(a /. c) /. (a -. c) +. b *. log(c /. b) /. (b -. c))
/. (a -. b);
let inverseVar =
2.
*. (log(c /. a) /. (a -. c) +. b *. log(b /. c) /. (b -. c))
/. (a -. b)
-. inverseMean
** 2.;
Belt.Array.set(means, i - 1, inverseMean) |> ignore;
Belt.Array.set(variances, i - 1, inverseVar) |> ignore;
();
};
{n: n - 2, masses, means, variances};
} else {
for (i in 1 to n - 2) {
// area of triangle = width * height / 2
Belt.Array.set(masses, 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;
// variance of triangle = (a^2 + b^2 + c^2 - ab - ac - bc) / 18
Belt.Array.set(
variances,
i - 1,
(
xsSq[i - 1]
+. xsSq[i]
+. xsSq[i + 1]
-. xsProdN1[i - 1]
-. xsProdN1[i]
-. xsProdN2[i - 1]
)
/. 18.,
)
|> ignore;
();
};
{n: n - 2, masses, means, variances};
};
};
let combineShapesContinuousContinuous =
(
op: ExpressionTypes.algebraicOperation,
s1: DistTypes.xyShape,
s2: DistTypes.xyShape,
)
: DistTypes.xyShape => {
let t1n = s1 |> XYShape.T.length;
let t2n = s2 |> XYShape.T.length;
// if we add the two distributions, we should probably use normal filters.
// if we multiply the two distributions, we should probably use lognormal filters.
let t1m = toDiscretePointMassesFromTriangulars(s1);
let t2m =
switch (op) {
| `Divide => toDiscretePointMassesFromTriangulars(~inverse=true, s2)
| _ => toDiscretePointMassesFromTriangulars(~inverse=false, s2)
};
let combineMeansFn =
switch (op) {
| `Add => ((m1, m2) => m1 +. m2)
| `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) {
| `Add => ((v1, v2, _, _) => v1 +. v2)
| `Subtract => ((v1, v2, _, _) => v1 +. v2)
| `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.
)
};
// TODO: If operating on two positive-domain distributions, we should take that into account
let outputMinX: ref(float) = ref(infinity);
let outputMaxX: ref(float) = ref(neg_infinity);
let masses: array(float) =
Belt.Array.makeUninitializedUnsafe(t1m.n * t2m.n);
let means: array(float) =
Belt.Array.makeUninitializedUnsafe(t1m.n * t2m.n);
let variances: array(float) =
Belt.Array.makeUninitializedUnsafe(t1m.n * t2m.n);
// then convolve the two sets of pointMassesWithMoments
for (i in 0 to t1m.n - 1) {
for (j in 0 to t2m.n - 1) {
let k = i * t2m.n + j;
Belt.Array.set(masses, k, t1m.masses[i] *. t2m.masses[j]) |> ignore;
let mean = combineMeansFn(t1m.means[i], t2m.means[j]);
let variance =
combineVariancesFn(
t1m.variances[i],
t2m.variances[j],
t1m.means[i],
t2m.means[j],
);
Belt.Array.set(means, k, mean) |> ignore;
Belt.Array.set(variances, k, variance) |> ignore;
// update bounds
let minX = mean -. 2. *. sqrt(variance) *. 1.644854;
let maxX = mean +. 2. *. sqrt(variance) *. 1.644854;
if (minX < outputMinX^) {
outputMinX := minX;
};
if (maxX > outputMaxX^) {
outputMaxX := maxX;
};
};
};
// we now want to create a set of target points. For now, let's just evenly distribute 200 points between
// between the outputMinX and outputMaxX
let nOut = 300;
let outputXs: array(float) =
E.A.Floats.range(outputMinX^, outputMaxX^, nOut);
let outputYs: array(float) = Belt.Array.make(nOut, 0.0);
// now, for each of the outputYs, accumulate from a Gaussian kernel over each input point.
for (j in 0 to E.A.length(masses) - 1) {
// go through all of the result points
if (variances[j] > 0. && masses[j] > 0.) {
for (i in 0 to E.A.length(outputXs) - 1) {
// go through all of the target points
let dx = outputXs[i] -. means[j];
let contribution =
masses[j]
*. exp(-. (dx ** 2.) /. (2. *. variances[j]))
/. sqrt(2. *. 3.14159276 *. variances[j]);
Belt.Array.set(outputYs, i, outputYs[i] +. contribution) |> ignore;
};
};
};
{xs: outputXs, ys: outputYs};
};
let toDiscretePointMassesFromDiscrete =
(s: DistTypes.xyShape): pointMassesWithMoments => {
let {xs, ys}: XYShape.T.t = s;
let n = E.A.length(xs);
let masses: array(float) = Belt.Array.makeBy(n, i => ys[i]);
let means: array(float) = Belt.Array.makeBy(n, i => xs[i]);
let variances: array(float) = Belt.Array.makeBy(n, i => 0.0);
{n, masses, means, variances};
};
let combineShapesContinuousDiscrete =
(
op: ExpressionTypes.algebraicOperation,
continuousShape: DistTypes.xyShape,
discreteShape: DistTypes.xyShape,
)
: DistTypes.xyShape => {
let t1n = continuousShape |> XYShape.T.length;
let t2n = discreteShape |> XYShape.T.length;
// each x pair is added/subtracted
let fn = Operation.Algebraic.toFn(op);
let outXYShapes: array(array((float, float))) =
Belt.Array.makeUninitializedUnsafe(t2n);
switch (op) {
| `Add
| `Subtract =>
for (j in 0 to t2n - 1) {
// creates a new continuous shape for each one of the discrete points, and collects them in outXYShapes.
let dxyShape: array((float, float)) =
Belt.Array.makeUninitializedUnsafe(t1n);
for (i in 0 to t1n - 1) {
Belt.Array.set(
dxyShape,
i,
(
fn(continuousShape.xs[i], discreteShape.xs[j]),
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.
let dxyShape: array((float, float)) =
Belt.Array.makeUninitializedUnsafe(t1n);
for (i in 0 to t1n - 1) {
Belt.Array.set(
dxyShape,
i,
(
fn(continuousShape.xs[i], discreteShape.xs[j]),
{continuousShape.ys[i] *. discreteShape.ys[j] /. discreteShape.xs[j]}
),
)
|> ignore;
();
};
Belt.Array.set(outXYShapes, j, dxyShape) |> ignore;
();
}
};
outXYShapes
|> E.A.fmap(XYShape.T.fromZippedArray)
|> E.A.fold_left(
XYShape.PointwiseCombination.combine(
(+.),
XYShape.XtoY.continuousInterpolator(`Linear, `UseZero),
),
XYShape.T.empty,
);
};

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open Distributions;
type t = DistTypes.continuousShape;
let getShape = (t: t) => t.xyShape;
let interpolation = (t: t) => t.interpolation;
let make =
(
~interpolation=`Linear,
~integralSumCache=None,
~integralCache=None,
xyShape,
)
: t => {
xyShape,
interpolation,
integralSumCache,
integralCache,
};
let shapeMap =
(fn, {xyShape, interpolation, integralSumCache, integralCache}: t): t => {
xyShape: fn(xyShape),
interpolation,
integralSumCache,
integralCache,
};
let lastY = (t: t) => t |> getShape |> XYShape.T.lastY;
let oShapeMap =
(fn, {xyShape, interpolation, integralSumCache, integralCache}: t)
: option(DistTypes.continuousShape) =>
fn(xyShape)
|> E.O.fmap(make(~interpolation, ~integralSumCache, ~integralCache));
let emptyIntegral: DistTypes.continuousShape = {
xyShape: {
xs: [|neg_infinity|],
ys: [|0.0|],
},
interpolation: `Linear,
integralSumCache: Some(0.0),
integralCache: None,
};
let empty: DistTypes.continuousShape = {
xyShape: XYShape.T.empty,
interpolation: `Linear,
integralSumCache: Some(0.0),
integralCache: Some(emptyIntegral),
};
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,
~integralCachesFn: (t, t) => option(t)=(_, _) => None,
~distributionType: DistTypes.distributionType=`PDF,
fn: (float, float) => float,
t1: DistTypes.continuousShape,
t2: DistTypes.continuousShape,
)
: DistTypes.continuousShape => {
// If we're adding the distributions, and we know the total of each, then we
// can just sum them up. Otherwise, all bets are off.
let combinedIntegralSum =
Common.combineIntegralSums(
integralSumCachesFn,
t1.integralSumCache,
t2.integralSumCache,
);
// TODO: does it ever make sense to pointwise combine the integrals here?
// It could be done for pointwise additions, but is that ever needed?
// If combining stepwise and linear, we must convert the stepwise to linear first,
// i.e. add a point at the bottom of each step
let (t1, t2) =
switch (t1.interpolation, t2.interpolation) {
| (`Linear, `Linear) => (t1, t2)
| (`Stepwise, `Stepwise) => (t1, t2)
| (`Linear, `Stepwise) => (t1, stepwiseToLinear(t2))
| (`Stepwise, `Linear) => (stepwiseToLinear(t1), t2)
};
let extrapolation =
switch (distributionType) {
| `PDF => `UseZero
| `CDF => `UseOutermostPoints
};
let interpolator =
XYShape.XtoY.continuousInterpolator(t1.interpolation, extrapolation);
make(
~integralSumCache=combinedIntegralSum,
XYShape.PointwiseCombination.combine(
fn,
interpolator,
t1.xyShape,
t2.xyShape,
),
);
};
let toLinear = (t: t): option(t) => {
switch (t) {
| {interpolation: `Stepwise, xyShape, integralSumCache, integralCache} =>
xyShape
|> XYShape.Range.stepsToContinuous
|> E.O.fmap(make(~integralSumCache, ~integralCache))
| {interpolation: `Linear} => Some(t)
};
};
let shapeFn = (fn, t: t) => t |> getShape |> fn;
let updateIntegralSumCache = (integralSumCache, t: t): t => {
...t,
integralSumCache,
};
let updateIntegralCache = (integralCache, t: t): t => {...t, integralCache};
let reduce =
(
~integralSumCachesFn: (float, float) => option(float)=(_, _) => None,
~integralCachesFn: (t, t) => option(t)=(_, _) => None,
fn,
continuousShapes,
) =>
continuousShapes
|> E.A.fold_left(
combinePointwise(~integralSumCachesFn, ~integralCachesFn, fn),
empty,
);
let mapY =
(~integralSumCacheFn=_ => None, ~integralCacheFn=_ => None, ~fn, t: t) => {
make(
~interpolation=t.interpolation,
~integralSumCache=t.integralSumCache |> E.O.bind(_, integralSumCacheFn),
~integralCache=t.integralCache |> E.O.bind(_, integralCacheFn),
t |> getShape |> XYShape.T.mapY(fn),
);
};
let rec scaleBy = (~scale=1.0, t: t): t => {
let scaledIntegralSumCache =
E.O.bind(t.integralSumCache, v => Some(scale *. v));
let scaledIntegralCache =
E.O.bind(t.integralCache, v => Some(scaleBy(~scale, v)));
t
|> mapY(~fn=(r: float) => r *. scale)
|> updateIntegralSumCache(scaledIntegralSumCache)
|> updateIntegralCache(scaledIntegralCache);
};
module T =
Dist({
type t = DistTypes.continuousShape;
type integral = DistTypes.continuousShape;
let minX = shapeFn(XYShape.T.minX);
let maxX = shapeFn(XYShape.T.maxX);
let mapY = mapY;
let updateIntegralCache = updateIntegralCache;
let toDiscreteProbabilityMassFraction = _ => 0.0;
let toShape = (t: t): DistTypes.shape => Continuous(t);
let xToY = (f, {interpolation, xyShape}: t) => {
(
switch (interpolation) {
| `Stepwise =>
xyShape |> XYShape.XtoY.stepwiseIncremental(f) |> E.O.default(0.0)
| `Linear => xyShape |> XYShape.XtoY.linear(f)
}
)
|> DistTypes.MixedPoint.makeContinuous;
};
let truncate =
(leftCutoff: option(float), rightCutoff: option(float), t: t) => {
let lc = E.O.default(neg_infinity, leftCutoff);
let rc = E.O.default(infinity, rightCutoff);
let truncatedZippedPairs =
t
|> getShape
|> XYShape.T.zip
|> XYShape.Zipped.filterByX(x => x >= lc && x <= rc);
let leftNewPoint =
leftCutoff
|> E.O.dimap(lc => [|(lc -. epsilon_float, 0.)|], _ => [||]);
let rightNewPoint =
rightCutoff
|> E.O.dimap(rc => [|(rc +. epsilon_float, 0.)|], _ => [||]);
let truncatedZippedPairsWithNewPoints =
E.A.concatMany([|leftNewPoint, truncatedZippedPairs, rightNewPoint|]);
let truncatedShape =
XYShape.T.fromZippedArray(truncatedZippedPairsWithNewPoints);
make(truncatedShape);
};
// TODO: This should work with stepwise plots.
let integral = t =>
switch (getShape(t) |> XYShape.T.isEmpty, t.integralCache) {
| (true, _) => emptyIntegral
| (false, Some(cache)) => cache
| (false, None) =>
t
|> getShape
|> XYShape.Range.integrateWithTriangles
|> E.O.toExt("This should not have happened")
|> make
};
let downsample = (length, t): t =>
t
|> shapeMap(
XYShape.XsConversion.proportionByProbabilityMass(
length,
integral(t).xyShape,
),
);
let integralEndY = (t: t) =>
t.integralSumCache |> E.O.default(t |> integral |> lastY);
let integralXtoY = (f, t: t) =>
t |> integral |> shapeFn(XYShape.XtoY.linear(f));
let integralYtoX = (f, t: t) =>
t |> integral |> shapeFn(XYShape.YtoX.linear(f));
let toContinuous = t => Some(t);
let toDiscrete = _ => None;
let normalize = (t: t): t => {
t
|> updateIntegralCache(Some(integral(t)))
|> scaleBy(~scale=1. /. integralEndY(t))
|> updateIntegralSumCache(Some(1.0));
};
let mean = (t: t) => {
let indefiniteIntegralStepwise = (p, h1) => h1 *. p ** 2.0 /. 2.0;
let indefiniteIntegralLinear = (p, a, b) =>
a *. p ** 2.0 /. 2.0 +. b *. p ** 3.0 /. 3.0;
XYShape.Analysis.integrateContinuousShape(
~indefiniteIntegralStepwise,
~indefiniteIntegralLinear,
t,
);
};
let variance = (t: t): float =>
XYShape.Analysis.getVarianceDangerously(
t,
mean,
XYShape.Analysis.getMeanOfSquaresContinuousShape,
);
});
/* This simply creates multiple copies of the continuous distribution, scaled and shifted according to
each discrete data point, and then adds them all together. */
let combineAlgebraicallyWithDiscrete =
(
op: ExpressionTypes.algebraicOperation,
t1: t,
t2: DistTypes.discreteShape,
) => {
let t1s = t1 |> getShape;
let t2s = t2.xyShape; // TODO would like to use Discrete.getShape here, but current file structure doesn't allow for that
if (XYShape.T.isEmpty(t1s) || XYShape.T.isEmpty(t2s)) {
empty;
} else {
let continuousAsLinear =
switch (t1.interpolation) {
| `Linear => t1
| `Stepwise => stepwiseToLinear(t1)
};
let combinedShape =
AlgebraicShapeCombination.combineShapesContinuousDiscrete(
op,
continuousAsLinear |> getShape,
t2s,
);
let combinedIntegralSum =
switch (op) {
| `Multiply
| `Divide =>
Common.combineIntegralSums(
(a, b) => Some(a *. b),
t1.integralSumCache,
t2.integralSumCache,
)
| _ => None
};
// TODO: It could make sense to automatically transform the integrals here (shift or scale)
make(
~interpolation=t1.interpolation,
~integralSumCache=combinedIntegralSum,
combinedShape,
);
};
};
let combineAlgebraically =
(op: ExpressionTypes.algebraicOperation, t1: t, t2: t) => {
let s1 = t1 |> getShape;
let s2 = t2 |> getShape;
let t1n = s1 |> XYShape.T.length;
let t2n = s2 |> XYShape.T.length;
if (t1n == 0 || t2n == 0) {
empty;
} else {
let combinedShape =
AlgebraicShapeCombination.combineShapesContinuousContinuous(op, s1, s2);
let combinedIntegralSum =
Common.combineIntegralSums(
(a, b) => Some(a *. b),
t1.integralSumCache,
t2.integralSumCache,
);
// return a new Continuous distribution
make(~integralSumCache=combinedIntegralSum, combinedShape);
};
};

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open Distributions;
type t = DistTypes.discreteShape;
let make = (~integralSumCache=None, ~integralCache=None, xyShape): t => {xyShape, integralSumCache, integralCache};
let shapeMap = (fn, {xyShape, integralSumCache, integralCache}: t): t => {
xyShape: fn(xyShape),
integralSumCache,
integralCache
};
let getShape = (t: t) => t.xyShape;
let oShapeMap = (fn, {xyShape, integralSumCache, integralCache}: t): option(t) =>
fn(xyShape) |> E.O.fmap(make(~integralSumCache, ~integralCache));
let emptyIntegral: DistTypes.continuousShape = {
xyShape: {xs: [|neg_infinity|], ys: [|0.0|]},
interpolation: `Stepwise,
integralSumCache: Some(0.0),
integralCache: None,
};
let empty: DistTypes.discreteShape = {
xyShape: XYShape.T.empty,
integralSumCache: Some(0.0),
integralCache: Some(emptyIntegral),
};
let shapeFn = (fn, t: t) => t |> getShape |> fn;
let lastY = (t: t) => t |> getShape |> XYShape.T.lastY;
let combinePointwise =
(
~integralSumCachesFn = (_, _) => None,
~integralCachesFn: (DistTypes.continuousShape, DistTypes.continuousShape) => option(DistTypes.continuousShape) = (_, _) => None,
fn,
t1: DistTypes.discreteShape,
t2: DistTypes.discreteShape,
)
: DistTypes.discreteShape => {
let combinedIntegralSum =
Common.combineIntegralSums(
integralSumCachesFn,
t1.integralSumCache,
t2.integralSumCache,
);
// TODO: does it ever make sense to pointwise combine the integrals here?
// It could be done for pointwise additions, but is that ever needed?
make(
~integralSumCache=combinedIntegralSum,
XYShape.PointwiseCombination.combine(
(+.),
XYShape.XtoY.discreteInterpolator,
t1.xyShape,
t2.xyShape,
),
);
};
let reduce =
(~integralSumCachesFn=(_, _) => None,
~integralCachesFn=(_, _) => None,
fn, discreteShapes)
: DistTypes.discreteShape =>
discreteShapes
|> E.A.fold_left(combinePointwise(~integralSumCachesFn, ~integralCachesFn, fn), empty);
let updateIntegralSumCache = (integralSumCache, t: t): t => {
...t,
integralSumCache,
};
let updateIntegralCache = (integralCache, t: t): t => {
...t,
integralCache,
};
/* This multiples all of the data points together and creates a new discrete distribution from the results.
Data points at the same xs get added together. It may be a good idea to downsample t1 and t2 before and/or the result after. */
let combineAlgebraically =
(op: ExpressionTypes.algebraicOperation, t1: t, t2: t): t => {
let t1s = t1 |> getShape;
let t2s = t2 |> getShape;
let t1n = t1s |> XYShape.T.length;
let t2n = t2s |> XYShape.T.length;
let combinedIntegralSum =
Common.combineIntegralSums(
(s1, s2) => Some(s1 *. s2),
t1.integralSumCache,
t2.integralSumCache,
);
let fn = Operation.Algebraic.toFn(op);
let xToYMap = E.FloatFloatMap.empty();
for (i in 0 to t1n - 1) {
for (j in 0 to t2n - 1) {
let x = fn(t1s.xs[i], t2s.xs[j]);
let cv = xToYMap |> E.FloatFloatMap.get(x) |> E.O.default(0.);
let my = t1s.ys[i] *. t2s.ys[j];
let _ = Belt.MutableMap.set(xToYMap, x, cv +. my);
();
};
};
let rxys = xToYMap |> E.FloatFloatMap.toArray |> XYShape.Zipped.sortByX;
let combinedShape = XYShape.T.fromZippedArray(rxys);
make(~integralSumCache=combinedIntegralSum, combinedShape);
};
let mapY = (~integralSumCacheFn=_ => None,
~integralCacheFn=_ => None,
~fn, t: t) => {
make(
~integralSumCache=t.integralSumCache |> E.O.bind(_, integralSumCacheFn),
~integralCache=t.integralCache |> E.O.bind(_, integralCacheFn),
t |> getShape |> XYShape.T.mapY(fn),
);
};
let scaleBy = (~scale=1.0, t: t): t => {
let scaledIntegralSumCache = t.integralSumCache |> E.O.fmap((*.)(scale));
let scaledIntegralCache = t.integralCache |> E.O.fmap(Continuous.scaleBy(~scale));
t
|> mapY(~fn=(r: float) => r *. scale)
|> updateIntegralSumCache(scaledIntegralSumCache)
|> updateIntegralCache(scaledIntegralCache)
};
module T =
Dist({
type t = DistTypes.discreteShape;
type integral = DistTypes.continuousShape;
let integral = (t) =>
switch (getShape(t) |> XYShape.T.isEmpty, t.integralCache) {
| (true, _) => emptyIntegral
| (false, Some(c)) => c
| (false, None) => {
let ts = getShape(t);
// The first xy of this integral should always be the zero, to ensure nice plotting
let firstX = ts |> XYShape.T.minX;
let prependedZeroPoint: XYShape.T.t = {xs: [|firstX -. epsilon_float|], ys: [|0.|]};
let integralShape =
ts
|> XYShape.T.concat(prependedZeroPoint)
|> XYShape.T.accumulateYs((+.));
Continuous.make(~interpolation=`Stepwise, integralShape);
}
};
let integralEndY = (t: t) =>
t.integralSumCache
|> E.O.default(t |> integral |> Continuous.lastY);
let minX = shapeFn(XYShape.T.minX);
let maxX = shapeFn(XYShape.T.maxX);
let toDiscreteProbabilityMassFraction = _ => 1.0;
let mapY = mapY;
let updateIntegralCache = updateIntegralCache;
let toShape = (t: t): DistTypes.shape => Discrete(t);
let toContinuous = _ => None;
let toDiscrete = t => Some(t);
let normalize = (t: t): t => {
t
|> scaleBy(~scale=1. /. integralEndY(t))
|> updateIntegralSumCache(Some(1.0));
};
let downsample = (i, t: t): t => {
// It's not clear how to downsample a set of discrete points in a meaningful way.
// The best we can do is to clip off the smallest values.
let currentLength = t |> getShape |> XYShape.T.length;
if (i < currentLength && i >= 1 && currentLength > 1) {
t
|> getShape
|> XYShape.T.zip
|> XYShape.Zipped.sortByY
|> Belt.Array.reverse
|> Belt.Array.slice(_, ~offset=0, ~len=i)
|> XYShape.Zipped.sortByX
|> XYShape.T.fromZippedArray
|> make;
} else {
t;
};
};
let truncate =
(leftCutoff: option(float), rightCutoff: option(float), t: t): t => {
t
|> getShape
|> XYShape.T.zip
|> XYShape.Zipped.filterByX(x =>
x >= E.O.default(neg_infinity, leftCutoff)
&& x <= E.O.default(infinity, rightCutoff)
)
|> XYShape.T.fromZippedArray
|> make;
};
let xToY = (f, t) =>
t
|> getShape
|> XYShape.XtoY.stepwiseIfAtX(f)
|> E.O.default(0.0)
|> DistTypes.MixedPoint.makeDiscrete;
let integralXtoY = (f, t) =>
t |> integral |> Continuous.getShape |> XYShape.XtoY.linear(f);
let integralYtoX = (f, t) =>
t |> integral |> Continuous.getShape |> XYShape.YtoX.linear(f);
let mean = (t: t): float => {
let s = getShape(t);
E.A.reducei(s.xs, 0.0, (acc, x, i) => acc +. x *. s.ys[i]);
};
let variance = (t: t): float => {
let getMeanOfSquares = t =>
t |> shapeMap(XYShape.Analysis.squareXYShape) |> mean;
XYShape.Analysis.getVarianceDangerously(t, mean, getMeanOfSquares);
};
});

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open DistTypes;
type t = DistTypes.distPlus;
let shapeIntegral = shape => Shape.T.Integral.get(shape);
let make =
(
~shape,
~squiggleString,
~domain=Complete,
~unit=UnspecifiedDistribution,
(),
)
: t => {
let integral = shapeIntegral(shape);
{shape, domain, integralCache: integral, unit, squiggleString};
};
let update =
(
~shape=?,
~integralCache=?,
~domain=?,
~unit=?,
~squiggleString=?,
t: t,
) => {
shape: E.O.default(t.shape, shape),
integralCache: E.O.default(t.integralCache, integralCache),
domain: E.O.default(t.domain, domain),
unit: E.O.default(t.unit, unit),
squiggleString: E.O.default(t.squiggleString, squiggleString),
};
let updateShape = (shape, t) => {
let integralCache = shapeIntegral(shape);
update(~shape, ~integralCache, t);
};
let domainIncludedProbabilityMass = (t: t) =>
Domain.includedProbabilityMass(t.domain);
let domainIncludedProbabilityMassAdjustment = (t: t, f) =>
f *. Domain.includedProbabilityMass(t.domain);
let toShape = ({shape, _}: t) => shape;
let shapeFn = (fn, {shape}: t) => fn(shape);
module T =
Distributions.Dist({
type t = DistTypes.distPlus;
type integral = DistTypes.distPlus;
let toShape = toShape;
let toContinuous = shapeFn(Shape.T.toContinuous);
let toDiscrete = shapeFn(Shape.T.toDiscrete);
let normalize = (t: t): t => {
let normalizedShape = t |> toShape |> Shape.T.normalize;
t |> updateShape(normalizedShape);
};
let truncate = (leftCutoff, rightCutoff, t: t): t => {
let truncatedShape =
t
|> toShape
|> Shape.T.truncate(leftCutoff, rightCutoff);
t |> updateShape(truncatedShape);
};
let xToY = (f, t: t) =>
t
|> toShape
|> Shape.T.xToY(f)
|> MixedPoint.fmap(domainIncludedProbabilityMassAdjustment(t));
let minX = shapeFn(Shape.T.minX);
let maxX = shapeFn(Shape.T.maxX);
let toDiscreteProbabilityMassFraction =
shapeFn(Shape.T.toDiscreteProbabilityMassFraction);
// This bit is kind of awkward, could probably use rethinking.
let integral = (t: t) =>
updateShape(Continuous(t.integralCache), t);
let updateIntegralCache = (integralCache: option(DistTypes.continuousShape), t) =>
update(~integralCache=E.O.default(t.integralCache, integralCache), t);
let downsample = (i, t): t =>
updateShape(t |> toShape |> Shape.T.downsample(i), t);
// todo: adjust for limit, maybe?
let mapY =
(
~integralSumCacheFn=previousIntegralSum => None,
~integralCacheFn=previousIntegralCache => None,
~fn,
{shape, _} as t: t,
)
: t =>
Shape.T.mapY(~integralSumCacheFn, ~fn, shape)
|> updateShape(_, t);
// get the total of everything
let integralEndY = (t: t) => {
Shape.T.Integral.sum(
toShape(t),
);
};
// TODO: Fix this below, obviously. Adjust for limits
let integralXtoY = (f, t: t) => {
Shape.T.Integral.xToY(
f,
toShape(t),
)
|> domainIncludedProbabilityMassAdjustment(t);
};
// TODO: This part is broken when there is a limit, if this is supposed to be taken into account.
let integralYtoX = (f, t: t) => {
Shape.T.Integral.yToX(f, toShape(t));
};
let mean = (t: t) => {
Shape.T.mean(t.shape);
};
let variance = (t: t) => Shape.T.variance(t.shape);
});

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open DistTypes;
type t = DistTypes.distPlus;
let unitToJson = ({unit}: t) => unit |> DistTypes.DistributionUnit.toJson;
let timeVector = ({unit}: t) =>
switch (unit) {
| TimeDistribution(timeVector) => Some(timeVector)
| UnspecifiedDistribution => None
};
let timeInVectorToX = (f: TimeTypes.timeInVector, t: t) => {
let timeVector = t |> timeVector;
timeVector |> E.O.fmap(TimeTypes.RelativeTimePoint.toXValue(_, f));
};
let xToY = (f: TimeTypes.timeInVector, t: t) => {
timeInVectorToX(f, t) |> E.O.fmap(DistPlus.T.xToY(_, t));
};
module Integral = {
include DistPlus.T.Integral;
let xToY = (f: TimeTypes.timeInVector, t: t) => {
timeInVectorToX(f, t)
|> E.O.fmap(x => DistPlus.T.Integral.xToY(x, t));
};
};

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type domainLimit = {
xPoint: float,
excludingProbabilityMass: float,
};
type domain =
| Complete
| LeftLimited(domainLimit)
| RightLimited(domainLimit)
| LeftAndRightLimited(domainLimit, domainLimit);
type distributionType = [
| `PDF
| `CDF
];
type xyShape = {
xs: array(float),
ys: array(float),
};
type interpolationStrategy = [
| `Stepwise
| `Linear
];
type extrapolationStrategy = [
| `UseZero
| `UseOutermostPoints
];
type interpolator = (xyShape, int, float) => float;
type continuousShape = {
xyShape,
interpolation: interpolationStrategy,
integralSumCache: option(float),
integralCache: option(continuousShape),
};
type discreteShape = {
xyShape,
integralSumCache: option(float),
integralCache: option(continuousShape),
};
type mixedShape = {
continuous: continuousShape,
discrete: discreteShape,
integralSumCache: option(float),
integralCache: option(continuousShape),
};
type shapeMonad('a, 'b, 'c) =
| Mixed('a)
| Discrete('b)
| Continuous('c);
type shape = shapeMonad(mixedShape, discreteShape, continuousShape);
module ShapeMonad = {
let fmap =
(t: shapeMonad('a, 'b, 'c), (fn1, fn2, fn3)): shapeMonad('d, 'e, 'f) =>
switch (t) {
| Mixed(m) => Mixed(fn1(m))
| Discrete(m) => Discrete(fn2(m))
| Continuous(m) => Continuous(fn3(m))
};
};
type generationSource =
| SquiggleString(string)
| Shape(shape);
type distributionUnit =
| UnspecifiedDistribution
| TimeDistribution(TimeTypes.timeVector);
type distPlus = {
shape,
domain,
integralCache: continuousShape,
unit: distributionUnit,
squiggleString: option(string),
};
module DistributionUnit = {
let toJson = (distributionUnit: distributionUnit) =>
switch (distributionUnit) {
| TimeDistribution({zero, unit}) =>
Js.Null.fromOption(
Some({"zero": zero, "unit": unit |> TimeTypes.TimeUnit.toString}),
)
| _ => Js.Null.fromOption(None)
};
};
module Domain = {
let excludedProbabilityMass = (t: domain) => {
switch (t) {
| Complete => 0.0
| LeftLimited({excludingProbabilityMass}) => excludingProbabilityMass
| RightLimited({excludingProbabilityMass}) => excludingProbabilityMass
| LeftAndRightLimited(
{excludingProbabilityMass: l},
{excludingProbabilityMass: r},
) =>
l +. r
};
};
let includedProbabilityMass = (t: domain) =>
1.0 -. excludedProbabilityMass(t);
let initialProbabilityMass = (t: domain) => {
switch (t) {
| Complete
| RightLimited(_) => 0.0
| LeftLimited({excludingProbabilityMass}) => excludingProbabilityMass
| LeftAndRightLimited({excludingProbabilityMass}, _) => excludingProbabilityMass
};
};
let normalizeProbabilityMass = (t: domain) => {
1. /. excludedProbabilityMass(t);
};
let yPointToSubYPoint = (t: domain, yPoint) => {
switch (t) {
| Complete => Some(yPoint)
| LeftLimited({excludingProbabilityMass})
when yPoint < excludingProbabilityMass =>
None
| LeftLimited({excludingProbabilityMass})
when yPoint >= excludingProbabilityMass =>
Some(
(yPoint -. excludingProbabilityMass) /. includedProbabilityMass(t),
)
| RightLimited({excludingProbabilityMass})
when yPoint > 1. -. excludingProbabilityMass =>
None
| RightLimited({excludingProbabilityMass})
when yPoint <= 1. -. excludingProbabilityMass =>
Some(yPoint /. includedProbabilityMass(t))
| LeftAndRightLimited({excludingProbabilityMass: l}, _) when yPoint < l =>
None
| LeftAndRightLimited(_, {excludingProbabilityMass: r})
when yPoint > 1.0 -. r =>
None
| LeftAndRightLimited({excludingProbabilityMass: l}, _) =>
Some((yPoint -. l) /. includedProbabilityMass(t))
| _ => None
};
};
};
type mixedPoint = {
continuous: float,
discrete: float,
};
module MixedPoint = {
type t = mixedPoint;
let toContinuousValue = (t: t) => t.continuous;
let toDiscreteValue = (t: t) => t.discrete;
let makeContinuous = (continuous: float): t => {continuous, discrete: 0.0};
let makeDiscrete = (discrete: float): t => {continuous: 0.0, discrete};
let fmap = (fn: float => float, t: t) => {
continuous: fn(t.continuous),
discrete: fn(t.discrete),
};
let combine2 = (fn, c: t, d: t): t => {
continuous: fn(c.continuous, d.continuous),
discrete: fn(c.discrete, d.discrete),
};
let add = combine2((a, b) => a +. b);
};

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module type dist = {
type t;
type integral;
let minX: t => float;
let maxX: t => float;
let mapY:
(~integralSumCacheFn: float => option(float)=?, ~integralCacheFn: DistTypes.continuousShape => option(DistTypes.continuousShape)=?, ~fn: float => float, t) => t;
let xToY: (float, t) => DistTypes.mixedPoint;
let toShape: t => DistTypes.shape;
let toContinuous: t => option(DistTypes.continuousShape);
let toDiscrete: t => option(DistTypes.discreteShape);
let normalize: t => t;
let toDiscreteProbabilityMassFraction: t => float;
let downsample: (int, t) => t;
let truncate: (option(float), option(float), t) => t;
let updateIntegralCache: (option(DistTypes.continuousShape), t) => t;
let integral: (t) => integral;
let integralEndY: (t) => float;
let integralXtoY: (float, t) => float;
let integralYtoX: (float, t) => float;
let mean: t => float;
let variance: t => float;
};
module Dist = (T: dist) => {
type t = T.t;
type integral = T.integral;
let minX = T.minX;
let maxX = T.maxX;
let integral = T.integral;
let xTotalRange = (t: t) => maxX(t) -. minX(t);
let mapY = T.mapY;
let xToY = T.xToY;
let downsample = T.downsample;
let toShape = T.toShape;
let toDiscreteProbabilityMassFraction = T.toDiscreteProbabilityMassFraction;
let toContinuous = T.toContinuous;
let toDiscrete = T.toDiscrete;
let normalize = T.normalize;
let truncate = T.truncate;
let mean = T.mean;
let variance = T.variance;
let updateIntegralCache = T.updateIntegralCache;
module Integral = {
type t = T.integral;
let get = T.integral;
let xToY = T.integralXtoY;
let yToX = T.integralYtoX;
let sum = T.integralEndY;
};
};
module Common = {
let combineIntegralSums =
(
combineFn: (float, float) => option(float),
t1IntegralSumCache: option(float),
t2IntegralSumCache: option(float),
) => {
switch (t1IntegralSumCache, t2IntegralSumCache) {
| (None, _)
| (_, None) => None
| (Some(s1), Some(s2)) => combineFn(s1, s2)
};
};
let combineIntegrals =
(
combineFn: (DistTypes.continuousShape, DistTypes.continuousShape) => option(DistTypes.continuousShape),
t1IntegralCache: option(DistTypes.continuousShape),
t2IntegralCache: option(DistTypes.continuousShape),
) => {
switch (t1IntegralCache, t2IntegralCache) {
| (None, _)
| (_, None) => None
| (Some(s1), Some(s2)) => combineFn(s1, s2)
};
};
};

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open Distributions;
type t = DistTypes.mixedShape;
let make = (~integralSumCache=None, ~integralCache=None, ~continuous, ~discrete): t => {continuous, discrete, integralSumCache, integralCache};
let totalLength = (t: t): int => {
let continuousLength =
t.continuous |> Continuous.getShape |> XYShape.T.length;
let discreteLength = t.discrete |> Discrete.getShape |> XYShape.T.length;
continuousLength + discreteLength;
};
let scaleBy = (~scale=1.0, t: t): t => {
let scaledDiscrete = Discrete.scaleBy(~scale, t.discrete);
let scaledContinuous = Continuous.scaleBy(~scale, t.continuous);
let scaledIntegralCache = E.O.bind(t.integralCache, v => Some(Continuous.scaleBy(~scale, v)));
let scaledIntegralSumCache = E.O.bind(t.integralSumCache, s => Some(s *. scale));
make(~discrete=scaledDiscrete, ~continuous=scaledContinuous, ~integralSumCache=scaledIntegralSumCache, ~integralCache=scaledIntegralCache);
};
let toContinuous = ({continuous}: t) => Some(continuous);
let toDiscrete = ({discrete}: t) => Some(discrete);
let updateIntegralCache = (integralCache, t: t): t => {
...t,
integralCache,
};
module T =
Dist({
type t = DistTypes.mixedShape;
type integral = DistTypes.continuousShape;
let minX = ({continuous, discrete}: t) => {
min(Continuous.T.minX(continuous), Discrete.T.minX(discrete));
};
let maxX = ({continuous, discrete}: t) =>
max(Continuous.T.maxX(continuous), Discrete.T.maxX(discrete));
let toShape = (t: t): DistTypes.shape => Mixed(t);
let updateIntegralCache = updateIntegralCache;
let toContinuous = toContinuous;
let toDiscrete = toDiscrete;
let truncate =
(
leftCutoff: option(float),
rightCutoff: option(float),
{discrete, continuous}: t,
) => {
let truncatedContinuous =
Continuous.T.truncate(leftCutoff, rightCutoff, continuous);
let truncatedDiscrete =
Discrete.T.truncate(leftCutoff, rightCutoff, discrete);
make(~integralSumCache=None, ~integralCache=None, ~discrete=truncatedDiscrete, ~continuous=truncatedContinuous);
};
let normalize = (t: t): t => {
let continuousIntegral = Continuous.T.Integral.get(t.continuous);
let discreteIntegral = Discrete.T.Integral.get(t.discrete);
let continuous = t.continuous |> Continuous.updateIntegralCache(Some(continuousIntegral));
let discrete = t.discrete |> Discrete.updateIntegralCache(Some(discreteIntegral));
let continuousIntegralSum =
Continuous.T.Integral.sum(continuous);
let discreteIntegralSum =
Discrete.T.Integral.sum(discrete);
let totalIntegralSum = continuousIntegralSum +. discreteIntegralSum;
let newContinuousSum = continuousIntegralSum /. totalIntegralSum;
let newDiscreteSum = discreteIntegralSum /. totalIntegralSum;
let normalizedContinuous =
continuous
|> Continuous.scaleBy(~scale=newContinuousSum /. continuousIntegralSum)
|> Continuous.updateIntegralSumCache(Some(newContinuousSum));
let normalizedDiscrete =
discrete
|> Discrete.scaleBy(~scale=newDiscreteSum /. discreteIntegralSum)
|> Discrete.updateIntegralSumCache(Some(newDiscreteSum));
make(~integralSumCache=Some(1.0), ~integralCache=None, ~continuous=normalizedContinuous, ~discrete=normalizedDiscrete);
};
let xToY = (x, t: t) => {
// This evaluates the mixedShape at x, interpolating if necessary.
// Note that we normalize entire mixedShape first.
let {continuous, discrete}: t = normalize(t);
let c = Continuous.T.xToY(x, continuous);
let d = Discrete.T.xToY(x, discrete);
DistTypes.MixedPoint.add(c, d); // "add" here just combines the two values into a single MixedPoint.
};
let toDiscreteProbabilityMassFraction = ({discrete, continuous}: t) => {
let discreteIntegralSum =
Discrete.T.Integral.sum(discrete);
let continuousIntegralSum =
Continuous.T.Integral.sum(continuous);
let totalIntegralSum = discreteIntegralSum +. continuousIntegralSum;
discreteIntegralSum /. totalIntegralSum;
};
let downsample = (count, t: t): t => {
// We will need to distribute the new xs fairly between the discrete and continuous shapes.
// The easiest way to do this is to simply go by the previous probability masses.
let discreteIntegralSum =
Discrete.T.Integral.sum(t.discrete);
let continuousIntegralSum =
Continuous.T.Integral.sum(t.continuous);
let totalIntegralSum = discreteIntegralSum +. continuousIntegralSum;
// TODO: figure out what to do when the totalIntegralSum is zero.
let downsampledDiscrete =
Discrete.T.downsample(
int_of_float(
float_of_int(count) *. (discreteIntegralSum /. totalIntegralSum),
),
t.discrete,
);
let downsampledContinuous =
Continuous.T.downsample(
int_of_float(
float_of_int(count) *. (continuousIntegralSum /. totalIntegralSum),
),
t.continuous,
);
{...t, discrete: downsampledDiscrete, continuous: downsampledContinuous};
};
let integral = (t: t) => {
switch (t.integralCache) {
| Some(cache) => cache
| None =>
// note: if the underlying shapes aren't normalized, then these integrals won't be either -- but that's the way it should be.
let continuousIntegral = Continuous.T.Integral.get(t.continuous);
let discreteIntegral = Continuous.stepwiseToLinear(Discrete.T.Integral.get(t.discrete));
Continuous.make(
XYShape.PointwiseCombination.combine(
(+.),
XYShape.XtoY.continuousInterpolator(`Linear, `UseOutermostPoints),
Continuous.getShape(continuousIntegral),
Continuous.getShape(discreteIntegral),
),
);
};
};
let integralEndY = (t: t) => {
t |> integral |> Continuous.lastY;
};
let integralXtoY = (f, t) => {
t |> integral |> Continuous.getShape |> XYShape.XtoY.linear(f);
};
let integralYtoX = (f, t) => {
t |> integral |> Continuous.getShape |> XYShape.YtoX.linear(f);
};
// This pipes all ys (continuous and discrete) through fn.
// If mapY is a linear operation, we might be able to update the integralSumCaches as well;
// if not, they'll be set to None.
let mapY =
(
~integralSumCacheFn=previousIntegralSum => None,
~integralCacheFn=previousIntegral => None,
~fn,
t: t,
)
: t => {
let yMappedDiscrete: DistTypes.discreteShape =
t.discrete
|> Discrete.T.mapY(~fn)
|> Discrete.updateIntegralSumCache(E.O.bind(t.discrete.integralSumCache, integralSumCacheFn))
|> Discrete.updateIntegralCache(E.O.bind(t.discrete.integralCache, integralCacheFn));
let yMappedContinuous: DistTypes.continuousShape =
t.continuous
|> Continuous.T.mapY(~fn)
|> Continuous.updateIntegralSumCache(E.O.bind(t.continuous.integralSumCache, integralSumCacheFn))
|> Continuous.updateIntegralCache(E.O.bind(t.continuous.integralCache, integralCacheFn));
{
discrete: yMappedDiscrete,
continuous: yMappedContinuous,
integralSumCache: E.O.bind(t.integralSumCache, integralSumCacheFn),
integralCache: E.O.bind(t.integralCache, integralCacheFn),
};
};
let mean = ({discrete, continuous}: t): float => {
let discreteMean = Discrete.T.mean(discrete);
let continuousMean = Continuous.T.mean(continuous);
// the combined mean is the weighted sum of the two:
let discreteIntegralSum = Discrete.T.Integral.sum(discrete);
let continuousIntegralSum = Continuous.T.Integral.sum(continuous);
let totalIntegralSum = discreteIntegralSum +. continuousIntegralSum;
(
discreteMean
*. discreteIntegralSum
+. continuousMean
*. continuousIntegralSum
)
/. totalIntegralSum;
};
let variance = ({discrete, continuous} as t: t): float => {
// the combined mean is the weighted sum of the two:
let discreteIntegralSum = Discrete.T.Integral.sum(discrete);
let continuousIntegralSum = Continuous.T.Integral.sum(continuous);
let totalIntegralSum = discreteIntegralSum +. continuousIntegralSum;
let getMeanOfSquares = ({discrete, continuous}: t) => {
let discreteMean =
discrete
|> Discrete.shapeMap(XYShape.Analysis.squareXYShape)
|> Discrete.T.mean;
let continuousMean =
continuous |> XYShape.Analysis.getMeanOfSquaresContinuousShape;
(
discreteMean
*. discreteIntegralSum
+. continuousMean
*. continuousIntegralSum
)
/. totalIntegralSum;
};
switch (discreteIntegralSum /. totalIntegralSum) {
| 1.0 => Discrete.T.variance(discrete)
| 0.0 => Continuous.T.variance(continuous)
| _ =>
XYShape.Analysis.getVarianceDangerously(t, mean, getMeanOfSquares)
};
};
});
let combineAlgebraically =
(op: ExpressionTypes.algebraicOperation, t1: t, t2: t)
: t => {
// Discrete convolution can cause a huge increase in the number of samples,
// so we'll first downsample.
// An alternative (to be explored in the future) may be to first perform the full convolution and then to downsample the result;
// to use non-uniform fast Fourier transforms (for addition only), add web workers or gpu.js, etc. ...
// we have to figure out where to downsample, and how to effectively
//let downsampleIfTooLarge = (t: t) => {
// let sqtl = sqrt(float_of_int(totalLength(t)));
// sqtl > 10 ? T.downsample(int_of_float(sqtl), t) : t;
//};
let t1d = t1;
let t2d = t2;
// continuous (*) continuous => continuous, but also
// discrete (*) continuous => continuous (and vice versa). We have to take care of all combos and then combine them:
let ccConvResult =
Continuous.combineAlgebraically(
op,
t1.continuous,
t2.continuous,
);
let dcConvResult =
Continuous.combineAlgebraicallyWithDiscrete(
op,
t2.continuous,
t1.discrete,
);
let cdConvResult =
Continuous.combineAlgebraicallyWithDiscrete(
op,
t1.continuous,
t2.discrete,
);
let continuousConvResult =
Continuous.reduce((+.), [|ccConvResult, dcConvResult, cdConvResult|]);
// ... finally, discrete (*) discrete => discrete, obviously:
let discreteConvResult =
Discrete.combineAlgebraically(op, t1.discrete, t2.discrete);
let combinedIntegralSum =
Common.combineIntegralSums(
(a, b) => Some(a *. b),
t1.integralSumCache,
t2.integralSumCache,
);
{discrete: discreteConvResult, continuous: continuousConvResult, integralSumCache: combinedIntegralSum, integralCache: None};
};
let combinePointwise = (~integralSumCachesFn = (_, _) => None, ~integralCachesFn = (_, _) => None, fn, t1: t, t2: t): t => {
let reducedDiscrete =
[|t1, t2|]
|> E.A.fmap(toDiscrete)
|> E.A.O.concatSomes
|> Discrete.reduce(~integralSumCachesFn, ~integralCachesFn, fn);
let reducedContinuous =
[|t1, t2|]
|> E.A.fmap(toContinuous)
|> E.A.O.concatSomes
|> Continuous.reduce(~integralSumCachesFn, ~integralCachesFn, fn);
let combinedIntegralSum =
Common.combineIntegralSums(
integralSumCachesFn,
t1.integralSumCache,
t2.integralSumCache,
);
let combinedIntegral =
Common.combineIntegrals(
integralCachesFn,
t1.integralCache,
t2.integralCache,
);
make(~integralSumCache=combinedIntegralSum, ~integralCache=combinedIntegral, ~discrete=reducedDiscrete, ~continuous=reducedContinuous);
};

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type assumption =
| ADDS_TO_1
| ADDS_TO_CORRECT_PROBABILITY;
type assumptions = {
continuous: assumption,
discrete: assumption,
discreteProbabilityMass: option(float),
};
let buildSimple = (~continuous: option(DistTypes.continuousShape), ~discrete: option(DistTypes.discreteShape)): option(DistTypes.shape) => {
let continuous = continuous |> E.O.default(Continuous.make(~integralSumCache=Some(0.0), {xs: [||], ys: [||]}));
let discrete = discrete |> E.O.default(Discrete.make(~integralSumCache=Some(0.0), {xs: [||], ys: [||]}));
let cLength =
continuous
|> Continuous.getShape
|> XYShape.T.xs
|> E.A.length;
let dLength = discrete |> Discrete.getShape |> XYShape.T.xs |> E.A.length;
switch (cLength, dLength) {
| (0 | 1, 0) => None
| (0 | 1, _) => Some(Discrete(discrete))
| (_, 0) => Some(Continuous(continuous))
| (_, _) =>
let mixedDist =
Mixed.make(
~integralSumCache=None,
~integralCache=None,
~continuous,
~discrete,
);
Some(Mixed(mixedDist));
};
};

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open Distributions;
type t = DistTypes.shape;
let mapToAll = ((fn1, fn2, fn3), t: t) =>
switch (t) {
| Mixed(m) => fn1(m)
| Discrete(m) => fn2(m)
| Continuous(m) => fn3(m)
};
let fmap = ((fn1, fn2, fn3), t: t): t =>
switch (t) {
| Mixed(m) => Mixed(fn1(m))
| Discrete(m) => Discrete(fn2(m))
| Continuous(m) => Continuous(fn3(m))
};
let toMixed =
mapToAll((
m => m,
d => Mixed.make(~integralSumCache=d.integralSumCache, ~integralCache=d.integralCache, ~discrete=d, ~continuous=Continuous.empty),
c => Mixed.make(~integralSumCache=c.integralSumCache, ~integralCache=c.integralCache, ~discrete=Discrete.empty, ~continuous=c),
));
let combineAlgebraically =
(op: ExpressionTypes.algebraicOperation, t1: t, t2: t): t => {
switch (t1, t2) {
| (Continuous(m1), Continuous(m2)) =>
Continuous.combineAlgebraically(op, m1, m2) |> Continuous.T.toShape;
| (Continuous(m1), Discrete(m2))
| (Discrete(m2), Continuous(m1)) =>
Continuous.combineAlgebraicallyWithDiscrete(op, m1, m2) |> Continuous.T.toShape
| (Discrete(m1), Discrete(m2)) =>
Discrete.combineAlgebraically(op, m1, m2) |> Discrete.T.toShape
| (m1, m2) =>
Mixed.combineAlgebraically(
op,
toMixed(m1),
toMixed(m2),
)
|> Mixed.T.toShape
};
};
let combinePointwise =
(~integralSumCachesFn: (float, float) => option(float) = (_, _) => None,
~integralCachesFn: (DistTypes.continuousShape, DistTypes.continuousShape) => option(DistTypes.continuousShape) = (_, _) => None,
fn,
t1: t,
t2: t) =>
switch (t1, t2) {
| (Continuous(m1), Continuous(m2)) =>
DistTypes.Continuous(
Continuous.combinePointwise(~integralSumCachesFn, ~integralCachesFn, fn, m1, m2),
)
| (Discrete(m1), Discrete(m2)) =>
DistTypes.Discrete(
Discrete.combinePointwise(~integralSumCachesFn, ~integralCachesFn, fn, m1, m2),
)
| (m1, m2) =>
DistTypes.Mixed(
Mixed.combinePointwise(
~integralSumCachesFn,
~integralCachesFn,
fn,
toMixed(m1),
toMixed(m2),
),
)
};
module T =
Dist({
type t = DistTypes.shape;
type integral = DistTypes.continuousShape;
let xToY = (f: float) =>
mapToAll((
Mixed.T.xToY(f),
Discrete.T.xToY(f),
Continuous.T.xToY(f),
));
let toShape = (t: t) => t;
let toContinuous = t => None;
let toDiscrete = t => None;
let downsample = (i, t) =>
fmap(
(
Mixed.T.downsample(i),
Discrete.T.downsample(i),
Continuous.T.downsample(i),
),
t,
);
let truncate = (leftCutoff, rightCutoff, t): t =>
fmap(
(
Mixed.T.truncate(leftCutoff, rightCutoff),
Discrete.T.truncate(leftCutoff, rightCutoff),
Continuous.T.truncate(leftCutoff, rightCutoff),
),
t,
);
let toDiscreteProbabilityMassFraction = t => 0.0;
let normalize =
fmap((
Mixed.T.normalize,
Discrete.T.normalize,
Continuous.T.normalize
));
let updateIntegralCache = (integralCache, t: t): t =>
fmap((
Mixed.T.updateIntegralCache(integralCache),
Discrete.T.updateIntegralCache(integralCache),
Continuous.T.updateIntegralCache(integralCache),
), t);
let toContinuous =
mapToAll((
Mixed.T.toContinuous,
Discrete.T.toContinuous,
Continuous.T.toContinuous,
));
let toDiscrete =
mapToAll((
Mixed.T.toDiscrete,
Discrete.T.toDiscrete,
Continuous.T.toDiscrete,
));
let toDiscreteProbabilityMassFraction =
mapToAll((
Mixed.T.toDiscreteProbabilityMassFraction,
Discrete.T.toDiscreteProbabilityMassFraction,
Continuous.T.toDiscreteProbabilityMassFraction,
));
let minX = mapToAll((Mixed.T.minX, Discrete.T.minX, Continuous.T.minX));
let integral =
mapToAll((
Mixed.T.Integral.get,
Discrete.T.Integral.get,
Continuous.T.Integral.get,
));
let integralEndY =
mapToAll((
Mixed.T.Integral.sum,
Discrete.T.Integral.sum,
Continuous.T.Integral.sum,
));
let integralXtoY = (f) => {
mapToAll((
Mixed.T.Integral.xToY(f),
Discrete.T.Integral.xToY(f),
Continuous.T.Integral.xToY(f),
));
};
let integralYtoX = (f) => {
mapToAll((
Mixed.T.Integral.yToX(f),
Discrete.T.Integral.yToX(f),
Continuous.T.Integral.yToX(f),
));
};
let maxX = mapToAll((Mixed.T.maxX, Discrete.T.maxX, Continuous.T.maxX));
let mapY = (~integralSumCacheFn=previousIntegralSum => None, ~integralCacheFn=previousIntegral=>None, ~fn) =>{
fmap((
Mixed.T.mapY(~integralSumCacheFn, ~integralCacheFn, ~fn),
Discrete.T.mapY(~integralSumCacheFn, ~integralCacheFn, ~fn),
Continuous.T.mapY(~integralSumCacheFn, ~integralCacheFn, ~fn),
));
}
let mean = (t: t): float =>
switch (t) {
| Mixed(m) => Mixed.T.mean(m)
| Discrete(m) => Discrete.T.mean(m)
| Continuous(m) => Continuous.T.mean(m)
};
let variance = (t: t): float =>
switch (t) {
| Mixed(m) => Mixed.T.variance(m)
| Discrete(m) => Discrete.T.variance(m)
| Continuous(m) => Continuous.T.variance(m)
};
});
let pdf = (f: float, t: t) => {
let mixedPoint: DistTypes.mixedPoint = T.xToY(f, t);
mixedPoint.continuous +. mixedPoint.discrete;
};
let inv = T.Integral.yToX;
let cdf = T.Integral.xToY;
let doN = (n, fn) => {
let items = Belt.Array.make(n, 0.0);
for (x in 0 to n - 1) {
let _ = Belt.Array.set(items, x, fn());
();
};
items;
};
let sample = (t: t): float => {
let randomItem = Random.float(1.);
let bar = t |> T.Integral.yToX(randomItem);
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);
doN(n, () => sample(distWithUpdatedIntegralCache));
};
let operate = (distToFloatOp: ExpressionTypes.distToFloatOperation, s): float =>
switch (distToFloatOp) {
| `Pdf(f) => pdf(f, s)
| `Cdf(f) => pdf(f, s)
| `Inv(f) => inv(f, s)
| `Sample => sample(s)
| `Mean => T.mean(s)
};

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type timeUnit = [
| #days
| #hours
| #milliseconds
| #minutes
| #months
| #quarters
| #seconds
| #weeks
| #years
]
type timeVector = {
zero: MomentRe.Moment.t,
unit: timeUnit,
}
type timePoint = {
timeVector: timeVector,
value: float,
}
module TimeUnit = {
let toString = (timeUnit: timeUnit) =>
switch timeUnit {
| #days => "days"
| #hours => "hours"
| #milliseconds => "milliseconds"
| #minutes => "minutes"
| #months => "months"
| #quarters => "quarters"
| #seconds => "seconds"
| #weeks => "weeks"
| #years => "years"
}
let ofString = (timeUnit: string) =>
switch timeUnit {
| "days" => #days
| "hours" => #hours
| "milliseconds" => #milliseconds
| "minutes" => #minutes
| "months" => #months
| "quarters" => #quarters
| "seconds" => #seconds
| "weeks" => #weeks
| "years" => #years
| _ => Js.Exn.raiseError("TimeUnit is unknown")
}
}
module TimePoint = {
let fromTimeVector = (timeVector, value): timePoint => {timeVector: timeVector, value: value}
let toMoment = (timePoint: timePoint) =>
timePoint.timeVector.zero |> MomentRe.Moment.add(
~duration=MomentRe.duration(timePoint.value, timePoint.timeVector.unit),
)
let fromMoment = (timeVector: timeVector, moment: MomentRe.Moment.t) =>
MomentRe.diff(timeVector.zero, moment, timeVector.unit)
}
type timeInVector =
| Time(MomentRe.Moment.t)
| XValue(float)
module RelativeTimePoint = {
let toTime = (timeVector: timeVector, timeInVector: timeInVector) =>
switch timeInVector {
| Time(r) => r
| XValue(r) =>
timeVector.zero |> MomentRe.Moment.add(~duration=MomentRe.duration(r, timeVector.unit))
}
let _timeToX = (time, timeStart, timeUnit) => MomentRe.diff(time, timeStart, timeUnit)
let toXValue = (timeVector: timeVector, timeInVector: timeInVector) =>
switch timeInVector {
| Time(r) => _timeToX(r, timeVector.zero, timeVector.unit)
| XValue(r) => r
}
}

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open DistTypes;
let interpolate =
(xMin: float, xMax: float, yMin: float, yMax: float, xIntended: float)
: float => {
let minProportion = (xMax -. xIntended) /. (xMax -. xMin);
let maxProportion = (xIntended -. xMin) /. (xMax -. xMin);
yMin *. minProportion +. yMax *. maxProportion;
};
// TODO: Make sure that shapes cannot be empty.
let extImp = E.O.toExt("Tried to perform an operation on an empty XYShape.");
module T = {
type t = xyShape;
let toXyShape = (t: t): xyShape => t;
type ts = array(xyShape);
let xs = (t: t) => t.xs;
let ys = (t: t) => t.ys;
let length = (t: t) => E.A.length(t.xs);
let empty = {xs: [||], ys: [||]};
let isEmpty = (t: t) => length(t) == 0;
let minX = (t: t) => t |> xs |> E.A.Sorted.min |> extImp;
let maxX = (t: t) => t |> xs |> E.A.Sorted.max |> extImp;
let firstY = (t: t) => t |> ys |> E.A.first |> extImp;
let lastY = (t: t) => t |> ys |> E.A.last |> extImp;
let xTotalRange = (t: t) => maxX(t) -. minX(t);
let mapX = (fn, t: t): t => {xs: E.A.fmap(fn, t.xs), ys: t.ys};
let mapY = (fn, t: t): t => {xs: t.xs, ys: E.A.fmap(fn, t.ys)};
let zip = ({xs, ys}: t) => Belt.Array.zip(xs, ys);
let fromArray = ((xs, ys)): t => {xs, ys};
let fromArrays = (xs, ys): t => {xs, ys};
let accumulateYs = (fn, p: t) => {
fromArray((p.xs, E.A.accumulate(fn, p.ys)));
};
let concat = (t1: t, t2: t) => {
let cxs = Array.concat([t1.xs, t2.xs]);
let cys = Array.concat([t1.ys, t2.ys]);
{xs: cxs, ys: cys};
};
let fromZippedArray = (pairs: array((float, float))): t =>
pairs |> Belt.Array.unzip |> fromArray;
let equallyDividedXs = (t: t, newLength) => {
E.A.Floats.range(minX(t), maxX(t), newLength);
};
let toJs = (t: t) => {
{"xs": t.xs, "ys": t.ys};
};
};
module Ts = {
type t = T.ts;
let minX = (t: t) => t |> E.A.fmap(T.minX) |> E.A.min |> extImp;
let maxX = (t: t) => t |> E.A.fmap(T.maxX) |> E.A.max |> extImp;
let equallyDividedXs = (t: t, newLength) => {
E.A.Floats.range(minX(t), maxX(t), newLength);
};
let allXs = (t: t) => t |> E.A.fmap(T.xs) |> E.A.Sorted.concatMany;
};
module Pairs = {
let x = fst;
let y = snd;
let first = (t: T.t) => (T.minX(t), T.firstY(t));
let last = (t: T.t) => (T.maxX(t), T.lastY(t));
let getBy = (t: T.t, fn) => t |> T.zip |> E.A.getBy(_, fn);
let firstAtOrBeforeXValue = (xValue, t: T.t) => {
let zipped = T.zip(t);
let firstIndex =
zipped |> Belt.Array.getIndexBy(_, ((x, _)) => x > xValue);
let previousIndex =
switch (firstIndex) {
| None => Some(Array.length(zipped) - 1)
| Some(0) => None
| Some(n) => Some(n - 1)
};
previousIndex |> Belt.Option.flatMap(_, Belt.Array.get(zipped));
};
};
module YtoX = {
let linear = (y: float, t: T.t): float => {
let firstHigherIndex =
E.A.Sorted.binarySearchFirstElementGreaterIndex(T.ys(t), y);
let foundX =
switch (firstHigherIndex) {
| `overMax => T.maxX(t)
| `underMin => T.minX(t)
| `firstHigher(firstHigherIndex) =>
let lowerOrEqualIndex =
firstHigherIndex - 1 < 0 ? 0 : firstHigherIndex - 1;
let (_xs, _ys) = (T.xs(t), T.ys(t));
let needsInterpolation = _ys[lowerOrEqualIndex] != y;
if (needsInterpolation) {
interpolate(
_ys[lowerOrEqualIndex],
_ys[firstHigherIndex],
_xs[lowerOrEqualIndex],
_xs[firstHigherIndex],
y,
);
} else {
_xs[lowerOrEqualIndex];
};
};
foundX;
};
};
module XtoY = {
let stepwiseIncremental = (f, t: T.t) =>
Pairs.firstAtOrBeforeXValue(f, t) |> E.O.fmap(Pairs.y);
let stepwiseIfAtX = (f: float, t: T.t) => {
Pairs.getBy(t, ((x: float, _)) => {x == f}) |> E.O.fmap(Pairs.y);
};
let linear = (x: float, t: T.t): float => {
let firstHigherIndex =
E.A.Sorted.binarySearchFirstElementGreaterIndex(T.xs(t), x);
let n =
switch (firstHigherIndex) {
| `overMax => T.lastY(t)
| `underMin => T.firstY(t)
| `firstHigher(firstHigherIndex) =>
let lowerOrEqualIndex =
firstHigherIndex - 1 < 0 ? 0 : firstHigherIndex - 1;
let (_xs, _ys) = (T.xs(t), T.ys(t));
let needsInterpolation = _xs[lowerOrEqualIndex] != x;
if (needsInterpolation) {
interpolate(
_xs[lowerOrEqualIndex],
_xs[firstHigherIndex],
_ys[lowerOrEqualIndex],
_ys[firstHigherIndex],
x,
);
} else {
_ys[lowerOrEqualIndex];
};
};
n;
};
/* Returns a between-points-interpolating function that can be used with PointwiseCombination.combine.
Interpolation can either be stepwise (using the value on the left) or linear. Extrapolation can be `UseZero or `UseOutermostPoints. */
let continuousInterpolator = (interpolation: DistTypes.interpolationStrategy, extrapolation: DistTypes.extrapolationStrategy): interpolator => {
switch (interpolation, extrapolation) {
| (`Linear, `UseZero) => (t: T.t, leftIndex: int, x: float) => {
if (leftIndex < 0) {
0.0
} else if (leftIndex >= T.length(t) - 1) {
0.0
} else {
let x1 = t.xs[leftIndex];
let x2 = t.xs[leftIndex + 1];
let y1 = t.ys[leftIndex];
let y2 = t.ys[leftIndex + 1];
let fraction = (x -. x1) /. (x2 -. x1);
y1 *. (1. -. fraction) +. y2 *. fraction;
};
}
| (`Linear, `UseOutermostPoints) => (t: T.t, leftIndex: int, x: float) => {
if (leftIndex < 0) {
t.ys[0];
} else if (leftIndex >= T.length(t) - 1) {
t.ys[T.length(t) - 1]
} else {
let x1 = t.xs[leftIndex];
let x2 = t.xs[leftIndex + 1];
let y1 = t.ys[leftIndex];
let y2 = t.ys[leftIndex + 1];
let fraction = (x -. x1) /. (x2 -. x1);
y1 *. (1. -. fraction) +. y2 *. fraction;
};
}
| (`Stepwise, `UseZero) => (t: T.t, leftIndex: int, x: float) => {
if (leftIndex < 0) {
0.0
} else if (leftIndex >= T.length(t) - 1) {
0.0
} else {
t.ys[leftIndex];
}
}
| (`Stepwise, `UseOutermostPoints) => (t: T.t, leftIndex: int, x: float) => {
if (leftIndex < 0) {
t.ys[0];
} else if (leftIndex >= T.length(t) - 1) {
t.ys[T.length(t) - 1]
} else {
t.ys[leftIndex];
}
}
}
};
/* Returns a between-points-interpolating function that can be used with PointwiseCombination.combine.
For discrete distributions, the probability density between points is zero, so we just return zero here. */
let discreteInterpolator: interpolator = (t: T.t, leftIndex: int, x: float) => 0.0;
};
module XsConversion = {
let _replaceWithXs = (newXs: array(float), t: T.t): T.t => {
let newYs = Belt.Array.map(newXs, XtoY.linear(_, t));
{xs: newXs, ys: newYs};
};
let equallyDivideXByMass = (newLength: int, integral: T.t) =>
E.A.Floats.range(0.0, 1.0, newLength)
|> E.A.fmap(YtoX.linear(_, integral));
let proportionEquallyOverX = (newLength: int, t: T.t): T.t => {
T.equallyDividedXs(t, newLength) |> _replaceWithXs(_, t);
};
let proportionByProbabilityMass =
(newLength: int, integral: T.t, t: T.t): T.t => {
integral
|> equallyDivideXByMass(newLength) // creates a new set of xs at evenly spaced percentiles
|> _replaceWithXs(_, t); // linearly interpolates new ys for the new xs
};
};
module Zipped = {
type zipped = array((float, float));
let compareYs = ((_, y1), (_, y2)) => y1 > y2 ? 1 : 0;
let compareXs = ((x1, _), (x2, _)) => x1 > x2 ? 1 : 0;
let sortByY = (t: zipped) => t |> E.A.stableSortBy(_, compareYs);
let sortByX = (t: zipped) => t |> E.A.stableSortBy(_, compareXs);
let filterByX = (testFn: (float => bool), t: zipped) => t |> E.A.filter(((x, _)) => testFn(x));
};
module PointwiseCombination = {
// t1Interpolator and t2Interpolator are functions from XYShape.XtoY, e.g. linearBetweenPointsExtrapolateFlat.
let combine = [%raw {| // : (float => float => float, T.t, T.t, bool) => T.t
// This function combines two xyShapes by looping through both of them simultaneously.
// It always moves on to the next smallest x, whether that's in the first or second input's xs,
// and interpolates the value on the other side, thus accumulating xs and ys.
// This is written in raw JS because this can still be a bottleneck, and using refs for the i and j indices is quite painful.
function(fn, interpolator, t1, t2) {
let t1n = t1.xs.length;
let t2n = t2.xs.length;
let outX = [];
let outY = [];
let i = -1;
let j = -1;
while (i <= t1n - 1 && j <= t2n - 1) {
let x, ya, yb;
if (j == t2n - 1 && i < t1n - 1 ||
t1.xs[i+1] < t2.xs[j+1]) { // if a has to catch up to b, or if b is already done
i++;
x = t1.xs[i];
ya = t1.ys[i];
yb = interpolator(t2, j, x);
} else if (i == t1n - 1 && j < t2n - 1 ||
t1.xs[i+1] > t2.xs[j+1]) { // if b has to catch up to a, or if a is already done
j++;
x = t2.xs[j];
yb = t2.ys[j];
ya = interpolator(t1, i, x);
} else if (i < t1n - 1 && j < t2n && t1.xs[i+1] === t2.xs[j+1]) { // if they happen to be equal, move both ahead
i++;
j++;
x = t1.xs[i];
ya = t1.ys[i];
yb = t2.ys[j];
} else if (i === t1n - 1 && j === t2n - 1) {
// finished!
i = t1n;
j = t2n;
continue;
} else {
console.log("Error!", i, j);
}
outX.push(x);
outY.push(fn(ya, yb));
}
return {xs: outX, ys: outY};
}
|}];
let combineEvenXs =
(
~fn,
~xToYSelection,
sampleCount,
t1: T.t,
t2: T.t,
) => {
switch ((E.A.length(t1.xs), E.A.length(t2.xs))) {
| (0, 0) => T.empty
| (0, _) => t2
| (_, 0) => t1
| (_, _) => {
let allXs = Ts.equallyDividedXs([|t1, t2|], sampleCount);
let allYs = allXs |> E.A.fmap(x => fn(xToYSelection(x, t1), xToYSelection(x, t2)));
T.fromArrays(allXs, allYs);
}
}
};
// TODO: I'd bet this is pretty slow. Maybe it would be faster to intersperse Xs and Ys separately.
let intersperse = (t1: T.t, t2: T.t) => {
E.A.intersperse(T.zip(t1), T.zip(t2)) |> T.fromZippedArray;
};
};
// I'm really not sure this part is actually what we want at this point.
module Range = {
// ((lastX, lastY), (nextX, nextY))
type zippedRange = ((float, float), (float, float));
let toT = T.fromZippedArray;
let nextX = ((_, (nextX, _)): zippedRange) => nextX;
let rangePointAssumingSteps = (((_, lastY), (nextX, _)): zippedRange) => (
nextX,
lastY,
);
let rangeAreaAssumingTriangles =
(((lastX, lastY), (nextX, nextY)): zippedRange) =>
(nextX -. lastX) *. (lastY +. nextY) /. 2.;
//Todo: figure out how to without making new array.
let rangeAreaAssumingTrapezoids =
(((lastX, lastY), (nextX, nextY)): zippedRange) =>
(nextX -. lastX)
*. (Js.Math.min_float(lastY, nextY) +. (lastY +. nextY) /. 2.);
let delta_y_over_delta_x =
(((lastX, lastY), (nextX, nextY)): zippedRange) =>
(nextY -. lastY) /. (nextX -. lastX);
let mapYsBasedOnRanges = (fn, t) =>
Belt.Array.zip(t.xs, t.ys)
|> E.A.toRanges
|> E.R.toOption
|> E.O.fmap(r => r |> Belt.Array.map(_, r => (nextX(r), fn(r))));
// This code is messy, in part because I'm trying to make things easy on garbage collection here.
// It's using triangles instead of trapezoids right now.
let integrateWithTriangles = ({xs, ys}) => {
let length = E.A.length(xs);
let cumulativeY = Belt.Array.make(length, 0.0);
for (x in 0 to E.A.length(xs) - 2) {
let _ =
Belt.Array.set(
cumulativeY,
x + 1,
(xs[x + 1] -. xs[x]) // dx
*. ((ys[x] +. ys[x + 1]) /. 2.) // (1/2) * (avgY)
+. cumulativeY[x],
);
();
};
Some({xs, ys: cumulativeY});
};
let derivative = mapYsBasedOnRanges(delta_y_over_delta_x);
let stepwiseToLinear = ({xs, ys}: T.t): T.t => {
// adds points at the bottom of each step.
let length = E.A.length(xs);
let newXs: array(float) = Belt.Array.makeUninitializedUnsafe(2 * length);
let newYs: array(float) = Belt.Array.makeUninitializedUnsafe(2 * length);
Belt.Array.set(newXs, 0, xs[0] -. epsilon_float) |> ignore;
Belt.Array.set(newYs, 0, 0.) |> ignore;
Belt.Array.set(newXs, 1, xs[0]) |> ignore;
Belt.Array.set(newYs, 1, ys[0]) |> ignore;
for (i in 1 to E.A.length(xs) - 1) {
Belt.Array.set(newXs, i * 2, xs[i] -. epsilon_float) |> ignore;
Belt.Array.set(newYs, i * 2, ys[i-1]) |> ignore;
Belt.Array.set(newXs, i * 2 + 1, xs[i]) |> ignore;
Belt.Array.set(newYs, i * 2 + 1, ys[i]) |> ignore;
();
};
{xs: newXs, ys: newYs};
};
// TODO: I think this isn't needed by any functions anymore.
let stepsToContinuous = t => {
// 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 diff = T.xTotalRange(t) |> (r => r *. 0.00001);
let items =
switch (E.A.toRanges(Belt.Array.zip(t.xs, t.ys))) {
| Ok(items) =>
Some(
items
|> Belt.Array.map(_, rangePointAssumingSteps)
|> T.fromZippedArray
|> PointwiseCombination.intersperse(t |> T.mapX(e => e +. diff)),
)
| _ => Some(t)
};
let first = items |> E.O.fmap(T.zip) |> E.O.bind(_, E.A.get(_, 0));
switch (items, first) {
| (Some(items), Some((0.0, _))) => Some(items)
| (Some(items), Some((firstX, _))) =>
let all = E.A.append([|(firstX, 0.0)|], items |> T.zip);
all |> T.fromZippedArray |> E.O.some;
| _ => None
};
};
};
let pointLogScore = (prediction, answer) =>
switch (answer) {
| 0. => 0.0
| answer => answer *. Js.Math.log2(Js.Math.abs_float(prediction /. answer))
};
let logScorePoint = (sampleCount, t1, t2) =>
PointwiseCombination.combineEvenXs(
~fn=pointLogScore,
~xToYSelection=XtoY.linear,
sampleCount,
t1,
t2,
)
|> Range.integrateWithTriangles
|> E.O.fmap(T.accumulateYs((+.)))
|> E.O.fmap(Pairs.last)
|> E.O.fmap(Pairs.y);
module Analysis = {
let integrateContinuousShape =
(
~indefiniteIntegralStepwise=(p, h1) => h1 *. p,
~indefiniteIntegralLinear=(p, a, b) => a *. p +. b *. p ** 2.0 /. 2.0,
t: DistTypes.continuousShape,
)
: float => {
let xs = t.xyShape.xs;
let ys = t.xyShape.ys;
E.A.reducei(
xs,
0.0,
(acc, _x, i) => {
let areaUnderIntegral =
// TODO Take this switch statement out of the loop body
switch (t.interpolation, i) {
| (_, 0) => 0.0
| (`Stepwise, _) =>
indefiniteIntegralStepwise(xs[i], ys[i - 1])
-. indefiniteIntegralStepwise(xs[i - 1], ys[i - 1])
| (`Linear, _) =>
let x1 = xs[i - 1];
let x2 = xs[i];
if (x1 == x2) {
0.0
} else {
let h1 = ys[i - 1];
let h2 = ys[i];
let b = (h1 -. h2) /. (x1 -. x2);
let a = h1 -. b *. x1;
indefiniteIntegralLinear(x2, a, b)
-. indefiniteIntegralLinear(x1, a, b);
};
};
acc +. areaUnderIntegral;
},
);
};
let getMeanOfSquaresContinuousShape = (t: DistTypes.continuousShape) => {
let indefiniteIntegralLinear = (p, a, b) =>
a *. p ** 3.0 /. 3.0 +. b *. p ** 4.0 /. 4.0;
let indefiniteIntegralStepwise = (p, h1) => h1 *. p ** 3.0 /. 3.0;
integrateContinuousShape(
~indefiniteIntegralStepwise,
~indefiniteIntegralLinear,
t,
);
};
let getVarianceDangerously =
(t: 't, mean: 't => float, getMeanOfSquares: 't => float): float => {
let meanSquared = mean(t) ** 2.0;
let meanOfSquares = getMeanOfSquares(t);
meanOfSquares -. meanSquared;
};
let squareXYShape = T.mapX(x => x ** 2.0)
};

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packages/squiggle-old/src/distPlus/expressionTree/ExpressionTree.re Normal file
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open ExpressionTypes.ExpressionTree;
let toString = ExpressionTreeBasic.toString;
let envs = (samplingInputs, environment) => {
{samplingInputs, environment, evaluateNode: ExpressionTreeEvaluator.toLeaf};
};
let toLeaf = (samplingInputs, environment, node: node) =>
ExpressionTreeEvaluator.toLeaf(envs(samplingInputs, environment), node);
let toShape = (samplingInputs, environment, node: node) => {
switch (toLeaf(samplingInputs, environment, node)) {
| Ok(`RenderedDist(shape)) => Ok(shape)
| Ok(_) => Error("Rendering failed.")
| Error(e) => Error(e)
};
};
let runFunction = (samplingInputs, environment, inputs, fn: PTypes.Function.t) => {
let params = envs(samplingInputs, environment);
PTypes.Function.run(params, inputs, fn);
};

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open ExpressionTypes.ExpressionTree;
let rec toString: node => string =
fun
| `SymbolicDist(d) => SymbolicDist.T.toString(d)
| `RenderedDist(_) => "[renderedShape]"
| `AlgebraicCombination(op, t1, t2) =>
Operation.Algebraic.format(op, toString(t1), toString(t2))
| `PointwiseCombination(op, t1, t2) =>
Operation.Pointwise.format(op, toString(t1), toString(t2))
| `Normalize(t) => "normalize(k" ++ toString(t) ++ ")"
| `Truncate(lc, rc, t) =>
Operation.T.truncateToString(lc, rc, toString(t))
| `Render(t) => toString(t)
| `Symbol(t) => "Symbol: " ++ t
| `FunctionCall(name, args) =>
"[Function call: ("
++ name
++ (args |> E.A.fmap(toString) |> Js.String.concatMany(_, ","))
++ ")]"
| `Function(args, internal) =>
"[Function: ("
++ (args |> Js.String.concatMany(_, ","))
++ toString(internal)
++ ")]"
| `Array(a) =>
"[" ++ (a |> E.A.fmap(toString) |> Js.String.concatMany(_, ",")) ++ "]"
| `Hash(h) =>
"{"
++ (
h
|> E.A.fmap(((name, value)) => name ++ ":" ++ toString(value))
|> Js.String.concatMany(_, ",")
)
++ "}";

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open ExpressionTypes;
open ExpressionTypes.ExpressionTree;
type t = node;
type tResult = node => result(node, string);
/* 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).
In general, this is implemented via convolution. */
module AlgebraicCombination = {
let tryAnalyticalSimplification = (operation, t1: t, t2: t) =>
switch (operation, t1, t2) {
| (operation, `SymbolicDist(d1), `SymbolicDist(d2)) =>
switch (SymbolicDist.T.tryAnalyticalSimplification(d1, d2, operation)) {
| `AnalyticalSolution(symbolicDist) => Ok(`SymbolicDist(symbolicDist))
| `Error(er) => Error(er)
| `NoSolution => Ok(`AlgebraicCombination((operation, t1, t2)))
}
| _ => Ok(`AlgebraicCombination((operation, t1, t2)))
};
let combinationByRendering =
(evaluationParams, algebraicOp, t1: node, t2: node)
: result(node, string) => {
E.R.merge(
Render.ensureIsRenderedAndGetShape(evaluationParams, t1),
Render.ensureIsRenderedAndGetShape(evaluationParams, t2),
)
|> E.R.fmap(((a, b)) =>
`RenderedDist(Shape.combineAlgebraically(algebraicOp, a, b))
);
};
let nodeScore: node => int =
fun
| `SymbolicDist(`Float(_)) => 1
| `SymbolicDist(_) => 1000
| `RenderedDist(Discrete(m)) => m.xyShape |> XYShape.T.length
| `RenderedDist(Mixed(_)) => 1000
| `RenderedDist(Continuous(_)) => 1000
| _ => 1000;
let choose = (t1: node, t2: node) => {
nodeScore(t1) * nodeScore(t2) > 10000 ? `Sampling : `Analytical;
};
let combine =
(evaluationParams, algebraicOp, t1: node, t2: node)
: result(node, string) => {
E.R.merge(
PTypes.SamplingDistribution.renderIfIsNotSamplingDistribution(
evaluationParams,
t1,
),
PTypes.SamplingDistribution.renderIfIsNotSamplingDistribution(
evaluationParams,
t2,
),
)
|> E.R.bind(_, ((a, b)) =>
switch (choose(a, b)) {
| `Sampling =>
PTypes.SamplingDistribution.combineShapesUsingSampling(
evaluationParams,
algebraicOp,
a,
b,
)
| `Analytical =>
combinationByRendering(evaluationParams, algebraicOp, a, b)
}
);
};
let operationToLeaf =
(
evaluationParams: evaluationParams,
algebraicOp: ExpressionTypes.algebraicOperation,
t1: t,
t2: t,
)
: result(node, string) =>
algebraicOp
|> tryAnalyticalSimplification(_, t1, t2)
|> E.R.bind(
_,
fun
| `SymbolicDist(_) as t => Ok(t)
| _ => combine(evaluationParams, algebraicOp, t1, t2),
);
};
module PointwiseCombination = {
let pointwiseAdd = (evaluationParams: evaluationParams, t1: t, t2: t) => {
switch (
Render.render(evaluationParams, t1),
Render.render(evaluationParams, t2),
) {
| (Ok(`RenderedDist(rs1)), Ok(`RenderedDist(rs2))) =>
Ok(
`RenderedDist(
Shape.combinePointwise(
~integralSumCachesFn=(a, b) => Some(a +. b),
~integralCachesFn=
(a, b) =>
Some(
Continuous.combinePointwise(
~distributionType=`CDF,
(+.),
a,
b,
),
),
(+.),
rs1,
rs2,
),
),
)
| (Error(e1), _) => Error(e1)
| (_, Error(e2)) => Error(e2)
| _ => Error("Pointwise combination: rendering failed.")
};
};
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!
switch (
Render.render(evaluationParams, t1),
Render.render(evaluationParams, t2),
) {
| (Ok(`RenderedDist(rs1)), Ok(`RenderedDist(rs2))) =>
Ok(`RenderedDist(Shape.combinePointwise(fn, rs1, rs2)))
| (Error(e1), _) => Error(e1)
| (_, Error(e2)) => Error(e2)
| _ => Error("Pointwise combination: rendering failed.")
};
};
let operationToLeaf =
(
evaluationParams: evaluationParams,
pointwiseOp: pointwiseOperation,
t1: t,
t2: t,
) => {
switch (pointwiseOp) {
| `Add => pointwiseAdd(evaluationParams, t1, t2)
| `Multiply => pointwiseCombine(( *. ), evaluationParams, t1, t2)
| `Exponentiate => pointwiseCombine(( ** ), evaluationParams, t1, t2)
};
};
};
module Truncate = {
let trySimplification = (leftCutoff, rightCutoff, t): simplificationResult => {
switch (leftCutoff, rightCutoff, t) {
| (None, None, t) => `Solution(t)
| (Some(lc), Some(rc), _) when lc > rc =>
`Error(
"Left truncation bound must be smaller than right truncation bound.",
)
| (lc, rc, `SymbolicDist(`Uniform(u))) =>
`Solution(
`SymbolicDist(`Uniform(SymbolicDist.Uniform.truncate(lc, rc, u))),
)
| _ => `NoSolution
};
};
let truncateAsShape =
(evaluationParams: evaluationParams, leftCutoff, rightCutoff, t) => {
// TODO: use named args for xMin/xMax in renderToShape; if we're lucky we can at least get the tail
// of a distribution we otherwise wouldn't get at all
switch (Render.ensureIsRendered(evaluationParams, t)) {
| Ok(`RenderedDist(rs)) =>
Ok(`RenderedDist(Shape.T.truncate(leftCutoff, rightCutoff, rs)))
| Error(e) => Error(e)
| _ => Error("Could not truncate distribution.")
};
};
let operationToLeaf =
(
evaluationParams,
leftCutoff: option(float),
rightCutoff: option(float),
t: node,
)
: result(node, string) => {
t
|> trySimplification(leftCutoff, rightCutoff)
|> (
fun
| `Solution(t) => Ok(t)
| `Error(e) => Error(e)
| `NoSolution =>
truncateAsShape(evaluationParams, leftCutoff, rightCutoff, t)
);
};
};
module Normalize = {
let rec operationToLeaf = (evaluationParams, t: node): result(node, string) => {
Js.log2("normalize", t);
switch (t) {
| `RenderedDist(s) => Ok(`RenderedDist(Shape.T.normalize(s)))
| `SymbolicDist(_) => Ok(t)
| _ => evaluateAndRetry(evaluationParams, operationToLeaf, t)
};
};
};
module FunctionCall = {
let _runHardcodedFunction = (name, evaluationParams, args) =>
TypeSystem.Function.Ts.findByNameAndRun(
HardcodedFunctions.all,
name,
evaluationParams,
args,
);
let _runLocalFunction = (name, evaluationParams: evaluationParams, args) => {
Environment.getFunction(evaluationParams.environment, name)
|> E.R.bind(_, ((argNames, fn)) =>
PTypes.Function.run(evaluationParams, args, (argNames, fn))
);
};
let _runWithEvaluatedInputs =
(
evaluationParams: ExpressionTypes.ExpressionTree.evaluationParams,
name,
args: array(ExpressionTypes.ExpressionTree.node),
) => {
_runHardcodedFunction(name, evaluationParams, args)
|> E.O.default(_runLocalFunction(name, evaluationParams, args));
};
// TODO: This forces things to be floats
let run = (evaluationParams, name, args) => {
args
|> E.A.fmap(a => evaluationParams.evaluateNode(evaluationParams, a))
|> E.A.R.firstErrorOrOpen
|> E.R.bind(_, _runWithEvaluatedInputs(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.samplingInputs.shapeLength,
d,
),
),
)
| `RenderedDist(_) as t => Ok(t) // already a rendered shape, we're done here
| _ => evaluateAndRetry(evaluationParams, operationToLeaf, t)
};
};
};
/* 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,
but most often it will produce a RenderedDist.
This function is used mainly to turn a parse tree into a single RenderedDist
that can then be displayed to the user. */
let rec toLeaf =
(
evaluationParams: ExpressionTypes.ExpressionTree.evaluationParams,
node: t,
)
: result(t, string) => {
switch (node) {
// Leaf nodes just stay leaf nodes
| `SymbolicDist(_)
| `Function(_)
| `RenderedDist(_) => Ok(node)
| `Array(args) =>
args
|> E.A.fmap(toLeaf(evaluationParams))
|> E.A.R.firstErrorOrOpen
|> E.R.fmap(r => `Array(r))
// Operations nevaluationParamsd to be turned into leaves
| `AlgebraicCombination(algebraicOp, t1, t2) =>
AlgebraicCombination.operationToLeaf(
evaluationParams,
algebraicOp,
t1,
t2,
)
| `PointwiseCombination(pointwiseOp, t1, t2) =>
PointwiseCombination.operationToLeaf(
evaluationParams,
pointwiseOp,
t1,
t2,
)
| `Truncate(leftCutoff, rightCutoff, t) =>
Truncate.operationToLeaf(evaluationParams, leftCutoff, rightCutoff, t)
| `Normalize(t) => Normalize.operationToLeaf(evaluationParams, t)
| `Render(t) => Render.operationToLeaf(evaluationParams, t)
| `Hash(t) =>
t
|> E.A.fmap(((name: string, node: node)) =>
toLeaf(evaluationParams, node) |> E.R.fmap(r => (name, r))
)
|> E.A.R.firstErrorOrOpen
|> E.R.fmap(r => `Hash(r))
| `Symbol(r) =>
ExpressionTypes.ExpressionTree.Environment.get(
evaluationParams.environment,
r,
)
|> E.O.toResult("Undeclared variable " ++ r)
|> E.R.bind(_, toLeaf(evaluationParams))
| `FunctionCall(name, args) =>
FunctionCall.run(evaluationParams, name, args)
|> E.R.bind(_, toLeaf(evaluationParams))
}
};

180
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type algebraicOperation = [
| `Add
| `Multiply
| `Subtract
| `Divide
| `Exponentiate
];
type pointwiseOperation = [ | `Add | `Multiply | `Exponentiate];
type scaleOperation = [ | `Multiply | `Exponentiate | `Log];
type distToFloatOperation = [
| `Pdf(float)
| `Cdf(float)
| `Inv(float)
| `Mean
| `Sample
];
module ExpressionTree = {
type hash = array((string, node))
and node = [
| `SymbolicDist(SymbolicTypes.symbolicDist)
| `RenderedDist(DistTypes.shape)
| `Symbol(string)
| `Hash(hash)
| `Array(array(node))
| `Function(array(string), node)
| `AlgebraicCombination(algebraicOperation, node, node)
| `PointwiseCombination(pointwiseOperation, node, node)
| `Normalize(node)
| `Render(node)
| `Truncate(option(float), option(float), node)
| `FunctionCall(string, array(node))
];
module Hash = {
type t('a) = array((string, 'a));
let getByName = (t: t('a), name) =>
E.A.getBy(t, ((n, _)) => n == name) |> E.O.fmap(((_, r)) => r);
let getByNameResult = (t: t('a), name) =>
getByName(t, name) |> E.O.toResult(name ++ " expected and not found");
let getByNames = (hash: t('a), names: array(string)) =>
names |> E.A.fmap(name => (name, getByName(hash, name)));
};
// Have nil as option
let getFloat = (node: node) =>
node
|> (
fun
| `RenderedDist(Discrete({xyShape: {xs: [|x|], ys: [|1.0|]}})) =>
Some(x)
| `SymbolicDist(`Float(x)) => Some(x)
| _ => None
);
let toFloatIfNeeded = (node: node) =>
switch (node |> getFloat) {
| Some(float) => `SymbolicDist(`Float(float))
| None => node
};
type samplingInputs = {
sampleCount: int,
outputXYPoints: int,
kernelWidth: option(float),
shapeLength: int,
};
module SamplingInputs = {
type t = {
sampleCount: option(int),
outputXYPoints: option(int),
kernelWidth: option(float),
shapeLength: option(int),
};
let withDefaults = (t: t): samplingInputs => {
sampleCount: t.sampleCount |> E.O.default(10000),
outputXYPoints: t.outputXYPoints |> E.O.default(10000),
kernelWidth: t.kernelWidth,
shapeLength: t.shapeLength |> E.O.default(10000),
};
};
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);
let getFunction = (t: t, str) =>
switch (get(t, str)) {
| Some(`Function(argNames, fn)) => Ok((argNames, fn))
| _ => Error("Function " ++ str ++ " not found")
};
};
type evaluationParams = {
samplingInputs,
environment,
evaluateNode: (evaluationParams, node) => Belt.Result.t(node, string),
};
let evaluateNode = (evaluationParams: evaluationParams) =>
evaluationParams.evaluateNode(evaluationParams);
let evaluateAndRetry = (evaluationParams, fn, node) =>
node
|> evaluationParams.evaluateNode(evaluationParams)
|> E.R.bind(_, fn(evaluationParams));
module Render = {
type t = node;
let render = (evaluationParams: evaluationParams, r) =>
`Render(r) |> evaluateNode(evaluationParams);
let ensureIsRendered = (params, t) =>
switch (t) {
| `RenderedDist(_) => Ok(t)
| _ =>
switch (render(params, t)) {
| Ok(`RenderedDist(r)) => Ok(`RenderedDist(r))
| Ok(_) => Error("Did not render as requested")
| Error(e) => Error(e)
}
};
let ensureIsRenderedAndGetShape = (params, t) =>
switch (ensureIsRendered(params, t)) {
| Ok(`RenderedDist(r)) => Ok(r)
| Ok(_) => Error("Did not render as requested")
| Error(e) => Error(e)
};
let getShape = (item: node) =>
switch (item) {
| `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 = [
| `Solution(ExpressionTree.node)
| `Error(string)
| `NoSolution
];
module Program = {
type statement = [
| `Assignment(string, ExpressionTree.node)
| `Expression(ExpressionTree.node)
];
type program = array(statement);
};

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module MathJsonToMathJsAdt = {
type arg =
| Symbol(string)
| 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) =>
Json.Decode.(
switch (field("mathjs", string, j)) {
| "FunctionNode" =>
let args = j |> field("args", array(run));
let name = j |> optional(field("fn", field("name", string)));
name |> E.O.fmap(name => Fn({name, args: args |> E.A.O.concatSomes}));
| "OperatorNode" =>
let args = j |> field("args", array(run));
Some(
Fn({
name: j |> field("fn", string),
args: args |> E.A.O.concatSomes,
}),
);
| "ConstantNode" =>
optional(field("value", Json.Decode.float), j)
|> E.O.fmap(r => Value(r))
| "ParenthesisNode" => j |> field("content", run)
| "ObjectNode" =>
let properties = j |> field("properties", dict(run));
Js.Dict.entries(properties)
|> E.A.fmap(((key, value)) => value |> E.O.fmap(v => (key, v)))
|> E.A.O.concatSomes
|> Js.Dict.fromArray
|> (r => Some(Object(r)));
| "ArrayNode" =>
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;
}
);
};
module MathAdtToDistDst = {
open MathJsonToMathJsAdt;
let handleSymbol = sym => {
Ok(`Symbol(sym));
};
// TODO: This only works on the top level, which needs to be refactored. Also, I think functions don't need to be done like this anymore.
module MathAdtCleaner = {
let transformWithSymbol = (f: float, s: string) =>
switch (s) {
| "K" => Some(f *. 1000.)
| "M" => Some(f *. 1000000.)
| "B" => Some(f *. 1000000000.)
| "T" => Some(f *. 1000000000000.)
| _ => None
};
let rec run =
fun
| Fn({name: "multiply", args: [|Value(f), Symbol(s)|]}) as doNothing =>
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
|> Js.Dict.entries
|> E.A.fmap(((key, value)) => (key, run(value)))
|> Js.Dict.fromArray,
);
};
let lognormal = (args, parseArgs, nodeParser) =>
switch (args) {
| [|Object(o)|] =>
let g = s =>
Js.Dict.get(o, s)
|> E.O.toResult("Variable was empty")
|> E.R.bind(_, nodeParser);
switch (g("mean"), g("stdev"), g("mu"), g("sigma")) {
| (Ok(mean), Ok(stdev), _, _) =>
Ok(`FunctionCall(("lognormalFromMeanAndStdDev", [|mean, stdev|])))
| (_, _, Ok(mu), Ok(sigma)) =>
Ok(`FunctionCall(("lognormal", [|mu, sigma|])))
| _ =>
Error(
"Lognormal distribution needs either mean and stdev or mu and sigma",
)
};
| _ =>
parseArgs()
|> E.R.fmap((args: array(ExpressionTypes.ExpressionTree.node)) =>
`FunctionCall(("lognormal", args))
)
};
// Error("Dotwise exponentiation needs two operands")
let operationParser =
(
name: 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));
args
|> E.R.bind(_, args => {
switch (name, args) {
| ("add", [|l, r|]) => toOkAlgebraic((`Add, l, r))
| ("add", _) => Error("Addition needs two operands")
| ("unaryMinus", [|l|]) =>
toOkAlgebraic((`Multiply, `SymbolicDist(`Float(-1.0)), l))
| ("subtract", [|l, r|]) => toOkAlgebraic((`Subtract, l, r))
| ("subtract", _) => Error("Subtraction needs two operands")
| ("multiply", [|l, r|]) => toOkAlgebraic((`Multiply, l, r))
| ("multiply", _) => Error("Multiplication needs two operands")
| ("pow", [|l, r|]) => toOkAlgebraic((`Exponentiate, l, r))
| ("pow", _) => Error("Exponentiation needs two operands")
| ("dotMultiply", [|l, r|]) => toOkPointwise((`Multiply, l, r))
| ("dotMultiply", _) =>
Error("Dotwise multiplication needs two operands")
| ("dotPow", [|l, r|]) => toOkPointwise((`Exponentiate, l, r))
| ("dotPow", _) =>
Error("Dotwise exponentiation needs two operands")
| ("rightLogShift", [|l, r|]) => toOkPointwise((`Add, l, r))
| ("rightLogShift", _) =>
Error("Dotwise addition needs two operands")
| ("divide", [|l, r|]) => toOkAlgebraic((`Divide, l, r))
| ("divide", _) => Error("Division needs two operands")
| ("leftTruncate", [|d, `SymbolicDist(`Float(lc))|]) =>
toOkTruncate((Some(lc), None, d))
| ("leftTruncate", _) =>
Error(
"leftTruncate needs two arguments: the expression and the cutoff",
)
| ("rightTruncate", [|d, `SymbolicDist(`Float(rc))|]) =>
toOkTruncate((None, Some(rc), d))
| ("rightTruncate", _) =>
Error(
"rightTruncate needs two arguments: the expression and the cutoff",
)
| (
"truncate",
[|d, `SymbolicDist(`Float(lc)), `SymbolicDist(`Float(rc))|],
) =>
toOkTruncate((Some(lc), Some(rc), d))
| ("truncate", _) =>
Error(
"truncate needs three arguments: the expression and both cutoffs",
)
| _ => Error("This type not currently supported")
}
});
};
let functionParser =
(
nodeParser:
MathJsonToMathJsAdt.arg =>
Belt.Result.t(
ProbExample.ExpressionTypes.ExpressionTree.node,
string,
),
name: string,
args: array(MathJsonToMathJsAdt.arg),
)
: result(ExpressionTypes.ExpressionTree.node, string) => {
let parseArray = ags =>
ags |> E.A.fmap(nodeParser) |> E.A.R.firstErrorOrOpen;
let parseArgs = () => parseArray(args);
switch (name) {
| "lognormal" => lognormal(args, parseArgs, nodeParser)
| "multimodal"
| "add"
| "subtract"
| "multiply"
| "unaryMinus"
| "dotMultiply"
| "dotPow"
| "rightLogShift"
| "divide"
| "pow"
| "leftTruncate"
| "rightTruncate"
| "truncate" => operationParser(name, parseArgs())
| "mm" =>
let weights =
args
|> E.A.last
|> E.O.bind(
_,
fun
| Array(values) => Some(parseArray(values))
| _ => None,
);
let possibleDists =
E.O.isSome(weights)
? Belt.Array.slice(args, ~offset=0, ~len=E.A.length(args) - 1)
: args;
let dists = parseArray(possibleDists);
switch (weights, dists) {
| (Some(Error(r)), _) => Error(r)
| (_, Error(r)) => Error(r)
| (None, Ok(dists)) =>
let hash: ExpressionTypes.ExpressionTree.node =
`FunctionCall(("multimodal", [|`Hash(
[|
("dists", `Array(dists)),
("weights", `Array([||]))
|]
)|]));
Ok(hash);
| (Some(Ok(weights)), Ok(dists)) =>
let hash: ExpressionTypes.ExpressionTree.node =
`FunctionCall(("multimodal", [|`Hash(
[|
("dists", `Array(dists)),
("weights", `Array(weights))
|]
)|]));
Ok(hash);
};
| name =>
parseArgs()
|> E.R.fmap((args: array(ExpressionTypes.ExpressionTree.node)) =>
`FunctionCall((name, args))
)
};
};
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");
};
// | FunctionAssignment({name, args, expression}) => {
// let evaluatedExpression = run(expression);
// `Function(_ => Ok(evaluatedExpression));
// }
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(s) => handleSymbol(s) |> E.R.fmap(r => [|`Expression(r)|])
| 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.Program.program, string) =>
r |> MathAdtCleaner.run |> topLevel;
};
/* The MathJs parser doesn't support '.+' syntax, but we want it because it
would make sense with '.*'. Our workaround is to change this to >>>, which is
logShift in mathJS. We don't expect to use logShift anytime soon, so this tradeoff
seems fine.
*/
let pointwiseToRightLogShift = Js.String.replaceByRe([%re "/\.\+/g"], ">>>");
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
representing the functions/arguments/values/etc. in the string.
The function MathJsonToMathJsAdt then recursively unpacks this JSON into a typed data structure we can use.
Inside of this function, MathAdtToDistDst is called whenever a distribution function is encountered.
*/
let mathJsToJson = str |> pointwiseToRightLogShift |> Mathjs.parseMath;
let mathJsParse =
E.R.bind(mathJsToJson, r => {
switch (MathJsonToMathJsAdt.run(r)) {
| Some(r) => Ok(r)
| None => Error("MathJsParse Error")
}
});
let value = E.R.bind(mathJsParse, MathAdtToDistDst.run);
Js.log2(mathJsParse, value);
value;
};
let fromString = str => {
fromString2(str);
};

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[@bs.module "./MathjsWrapper.js"]
external parseMathExt: string => Js.Json.t = "parseMath";
let parseMath = (str: string): result(Js.Json.t, string) =>
switch (parseMathExt(str)) {
| exception (Js.Exn.Error(err)) =>
Error(Js.Exn.message(err) |> E.O.default("MathJS Parse Error"))
| exception _ => Error("MathJS Parse Error")
| j => Ok(j)
};

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const math = require("mathjs");
function parseMath(f) {
return JSON.parse(JSON.stringify(math.parse(f)))
};
module.exports = {
parseMath,
};

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open ExpressionTypes;
module Algebraic = {
type t = algebraicOperation;
let toFn: (t, float, float) => float =
fun
| `Add => (+.)
| `Subtract => (-.)
| `Multiply => ( *. )
| `Exponentiate => ( ** )
| `Divide => (/.);
let applyFn = (t, f1, f2) => {
switch (t, f1, f2) {
| (`Divide, _, 0.) => Error("Cannot divide $v1 by zero.")
| _ => Ok(toFn(t, f1, f2))
};
};
let toString =
fun
| `Add => "+"
| `Subtract => "-"
| `Multiply => "*"
| `Exponentiate => ( "**" )
| `Divide => "/";
let format = (a, b, c) => b ++ " " ++ toString(a) ++ " " ++ c;
};
module Pointwise = {
type t = pointwiseOperation;
let toString =
fun
| `Add => "+"
| `Exponentiate => "^"
| `Multiply => "*";
let format = (a, b, c) => b ++ " " ++ toString(a) ++ " " ++ c;
};
module DistToFloat = {
type t = distToFloatOperation;
let format = (operation, value) =>
switch (operation) {
| `Cdf(f) => {j|cdf(x=$f,$value)|j}
| `Pdf(f) => {j|pdf(x=$f,$value)|j}
| `Inv(f) => {j|inv(x=$f,$value)|j}
| `Sample => "sample($value)"
| `Mean => "mean($value)"
};
};
// Note that different logarithms don't really do anything.
module Scale = {
type t = scaleOperation;
let toFn =
fun
| `Multiply => ( *. )
| `Exponentiate => ( ** )
| `Log => ((a, b) => log(a) /. log(b));
let format = (operation: t, value, scaleBy) =>
switch (operation) {
| `Multiply => {j|verticalMultiply($value, $scaleBy) |j}
| `Exponentiate => {j|verticalExponentiate($value, $scaleBy) |j}
| `Log => {j|verticalLog($value, $scaleBy) |j}
};
let toIntegralSumCacheFn =
fun
| `Multiply => ((a, b) => Some(a *. b))
| `Exponentiate => ((_, _) => None)
| `Log => ((_, _) => None);
let toIntegralCacheFn =
fun
| `Multiply => ((a, b) => None) // TODO: this could probably just be multiplied out (using Continuous.scaleBy)
| `Exponentiate => ((_, _) => None)
| `Log => ((_, _) => None);
};
module T = {
let truncateToString =
(left: option(float), right: option(float), nodeToString) => {
let left = left |> E.O.dimap(Js.Float.toString, () => "-inf");
let right = right |> E.O.dimap(Js.Float.toString, () => "inf");
{j|truncate($nodeToString, $left, $right)|j};
};
let toString = nodeToString =>
fun
| `AlgebraicCombination(op, t1, t2) =>
Algebraic.format(op, nodeToString(t1), nodeToString(t2))
| `PointwiseCombination(op, t1, t2) =>
Pointwise.format(op, nodeToString(t1), nodeToString(t2))
| `VerticalScaling(scaleOp, t, scaleBy) =>
Scale.format(scaleOp, nodeToString(t), nodeToString(scaleBy))
| `Normalize(t) => "normalize(k" ++ nodeToString(t) ++ ")"
| `FloatFromDist(floatFromDistOp, t) =>
DistToFloat.format(floatFromDistOp, nodeToString(t))
| `Truncate(lc, rc, t) => truncateToString(lc, rc, nodeToString(t))
| `Render(t) => nodeToString(t)
| _ => ""; // SymbolicDist and RenderedDist are handled in ExpressionTree.toString.
};

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open ExpressionTypes.ExpressionTree;
module Function = {
type t = (array(string), node);
let fromNode: node => option(t) =
node =>
switch (node) {
| `Function(r) => Some(r)
| _ => None
};
let argumentNames = ((a, _): t) => a;
let internals = ((_, b): t) => b;
let run =
(
evaluationParams: ExpressionTypes.ExpressionTree.evaluationParams,
args: array(node),
t: t,
) =>
if (E.A.length(args) == E.A.length(argumentNames(t))) {
let newEnvironment =
Belt.Array.zip(argumentNames(t), 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, internals(t));
} else {
Error("Wrong number of variables");
};
};
module Primative = {
type t = [
| `SymbolicDist(SymbolicTypes.symbolicDist)
| `RenderedDist(DistTypes.shape)
| `Function(array(string), node)
];
let isPrimative: node => bool =
fun
| `SymbolicDist(_)
| `RenderedDist(_)
| `Function(_) => true
| _ => false;
let fromNode: node => option(t) =
fun
| `SymbolicDist(_) as n
| `RenderedDist(_) as n
| `Function(_) as n => Some(n)
| _ => None;
};
module SamplingDistribution = {
type t = [
| `SymbolicDist(SymbolicTypes.symbolicDist)
| `RenderedDist(DistTypes.shape)
];
let isSamplingDistribution: node => bool =
fun
| `SymbolicDist(_) => true
| `RenderedDist(_) => true
| _ => false;
let fromNode: node => result(t, string) =
fun
| `SymbolicDist(n) => Ok(`SymbolicDist(n))
| `RenderedDist(n) => Ok(`RenderedDist(n))
| _ => Error("Not valid type");
let renderIfIsNotSamplingDistribution = (params, t): result(node, string) =>
!isSamplingDistribution(t)
? switch (Render.render(params, t)) {
| Ok(r) => Ok(r)
| Error(e) => Error(e)
}
: Ok(t);
let map = (~renderedDistFn, ~symbolicDistFn, node: node) =>
node
|> (
fun
| `RenderedDist(r) => Some(renderedDistFn(r))
| `SymbolicDist(s) => Some(symbolicDistFn(s))
| _ => None
);
let sampleN = n =>
map(
~renderedDistFn=Shape.sampleNRendered(n),
~symbolicDistFn=SymbolicDist.T.sampleN(n),
);
let getCombinationSamples = (n, algebraicOp, t1: node, t2: node) => {
switch (sampleN(n, t1), sampleN(n, t2)) {
| (Some(a), Some(b)) =>
Some(
Belt.Array.zip(a, b)
|> E.A.fmap(((a, b)) => Operation.Algebraic.toFn(algebraicOp, a, b)),
)
| _ => None
};
};
let combineShapesUsingSampling =
(evaluationParams: evaluationParams, algebraicOp, t1: node, t2: node) => {
let i1 = renderIfIsNotSamplingDistribution(evaluationParams, t1);
let i2 = renderIfIsNotSamplingDistribution(evaluationParams, t2);
E.R.merge(i1, i2)
|> E.R.bind(
_,
((a, b)) => {
let samples =
getCombinationSamples(
evaluationParams.samplingInputs.sampleCount,
algebraicOp,
a,
b,
);
// todo: This bottom part should probably be somewhere else.
let shape =
samples
|> E.O.fmap(
SamplesToShape.fromSamples(
~samplingInputs=evaluationParams.samplingInputs,
),
)
|> E.O.bind(_, r => r.shape)
|> E.O.toResult("No response");
shape |> E.R.fmap(r => `Normalize(`RenderedDist(r)));
},
);
};
};

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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 =>
// )

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packages/squiggle-old/src/distPlus/samplesRenderer/Bandwidth.re Normal file
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//The math here was taken from https://github.com/jasondavies/science.js/blob/master/src/stats/bandwidth.js
let len = x => E.A.length(x) |> float_of_int;
let iqr = x => {
Jstat.percentile(x, 0.75, true) -. Jstat.percentile(x, 0.25, true);
};
// Silverman, B. W. (1986) Density Estimation. London: Chapman and Hall.
let nrd0 = x => {
let hi = Js_math.sqrt(Jstat.variance(x));
let lo = Js_math.minMany_float([|hi, iqr(x) /. 1.34|]);
let e = Js_math.abs_float(x[1]);
let lo' =
switch (lo, hi, e) {
| (lo, _, _) when !Js.Float.isNaN(lo) => lo
| (_, hi, _) when !Js.Float.isNaN(hi) => hi
| (_, _, e) when !Js.Float.isNaN(e) => e
| _ => 1.0
};
0.9 *. lo' *. Js.Math.pow_float(~base=len(x), ~exp=-0.2);
};
// Scott, D. W. (1992) Multivariate Density Estimation: Theory, Practice, and Visualization. Wiley.
let nrd = x => {
let h = iqr(x) /. 1.34;
1.06
*. Js.Math.min_float(Js.Math.sqrt(Jstat.variance(x)), h)
*. Js.Math.pow_float(~base=len(x), ~exp=(-1.0) /. 5.0);
};

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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,
};

164
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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, ());
};

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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);
let sample = (t: t) => Jstat.exponential##sample(t.rate);
let mean = (t: t) => Ok(Jstat.exponential##mean(t.rate));
let toString = ({rate}: t) => {j|Exponential($rate)|j};
};
module Cauchy = {
type t = cauchy;
let make = (local, scale): symbolicDist => `Cauchy({local, scale});
let pdf = (x, t: t) => Jstat.cauchy##pdf(x, t.local, t.scale);
let cdf = (x, t: t) => Jstat.cauchy##cdf(x, t.local, t.scale);
let inv = (p, t: t) => Jstat.cauchy##inv(p, t.local, t.scale);
let sample = (t: t) => Jstat.cauchy##sample(t.local, t.scale);
let mean = (_: t) => Error("Cauchy distributions have no mean value.");
let toString = ({local, scale}: t) => {j|Cauchy($local, $scale)|j};
};
module Triangular = {
type t = triangular;
let make = (low, medium, high): result(symbolicDist, string) =>
low < medium && medium < high
? Ok(`Triangular({low, medium, high}))
: Error("Triangular values must be increasing order");
let pdf = (x, t: t) => Jstat.triangular##pdf(x, t.low, t.high, t.medium);
let cdf = (x, t: t) => Jstat.triangular##cdf(x, t.low, t.high, t.medium);
let inv = (p, t: t) => Jstat.triangular##inv(p, t.low, t.high, t.medium);
let sample = (t: t) => Jstat.triangular##sample(t.low, t.high, t.medium);
let mean = (t: t) => Ok(Jstat.triangular##mean(t.low, t.high, t.medium));
let toString = ({low, medium, high}: t) => {j|Triangular($low, $medium, $high)|j};
};
module Normal = {
type t = normal;
let make = (mean, stdev): symbolicDist => `Normal({mean, stdev});
let pdf = (x, t: t) => Jstat.normal##pdf(x, t.mean, t.stdev);
let cdf = (x, t: t) => Jstat.normal##cdf(x, t.mean, t.stdev);
let from90PercentCI = (low, high) => {
let mean = E.A.Floats.mean([|low, high|]);
let stdev = (high -. low) /. (2. *. 1.644854);
`Normal({mean, stdev});
};
let inv = (p, t: t) => Jstat.normal##inv(p, t.mean, t.stdev);
let sample = (t: t) => Jstat.normal##sample(t.mean, t.stdev);
let mean = (t: t) => Ok(Jstat.normal##mean(t.mean, t.stdev));
let toString = ({mean, stdev}: t) => {j|Normal($mean,$stdev)|j};
let add = (n1: t, n2: t) => {
let mean = n1.mean +. n2.mean;
let stdev = sqrt(n1.stdev ** 2. +. n2.stdev ** 2.);
`Normal({mean, stdev});
};
let subtract = (n1: t, n2: t) => {
let mean = n1.mean -. n2.mean;
let stdev = sqrt(n1.stdev ** 2. +. n2.stdev ** 2.);
`Normal({mean, stdev});
};
// TODO: is this useful here at all? would need the integral as well ...
let pointwiseProduct = (n1: t, n2: t) => {
let mean =
(n1.mean *. n2.stdev ** 2. +. n2.mean *. n1.stdev ** 2.)
/. (n1.stdev ** 2. +. n2.stdev ** 2.);
let stdev = 1. /. (1. /. n1.stdev ** 2. +. 1. /. n2.stdev ** 2.);
`Normal({mean, stdev});
};
let operate = (operation: Operation.Algebraic.t, n1: t, n2: t) =>
switch (operation) {
| `Add => Some(add(n1, n2))
| `Subtract => Some(subtract(n1, n2))
| _ => None
};
};
module Beta = {
type t = beta;
let make = (alpha, beta) => `Beta({alpha, beta});
let pdf = (x, t: t) => Jstat.beta##pdf(x, t.alpha, t.beta);
let cdf = (x, t: t) => Jstat.beta##cdf(x, t.alpha, t.beta);
let inv = (p, t: t) => Jstat.beta##inv(p, t.alpha, t.beta);
let sample = (t: t) => Jstat.beta##sample(t.alpha, t.beta);
let mean = (t: t) => Ok(Jstat.beta##mean(t.alpha, t.beta));
let toString = ({alpha, beta}: t) => {j|Beta($alpha,$beta)|j};
};
module Lognormal = {
type t = lognormal;
let make = (mu, sigma) => `Lognormal({mu, sigma});
let pdf = (x, t: t) => Jstat.lognormal##pdf(x, t.mu, t.sigma);
let cdf = (x, t: t) => Jstat.lognormal##cdf(x, t.mu, t.sigma);
let inv = (p, t: t) => Jstat.lognormal##inv(p, t.mu, t.sigma);
let mean = (t: t) => Ok(Jstat.lognormal##mean(t.mu, t.sigma));
let sample = (t: t) => Jstat.lognormal##sample(t.mu, t.sigma);
let toString = ({mu, sigma}: t) => {j|Lognormal($mu,$sigma)|j};
let from90PercentCI = (low, high) => {
let logLow = Js.Math.log(low);
let logHigh = Js.Math.log(high);
let mu = E.A.Floats.mean([|logLow, logHigh|]);
let sigma = (logHigh -. logLow) /. (2.0 *. 1.645);
`Lognormal({mu, sigma});
};
let fromMeanAndStdev = (mean, stdev) => {
let variance = Js.Math.pow_float(~base=stdev, ~exp=2.0);
let meanSquared = Js.Math.pow_float(~base=mean, ~exp=2.0);
let mu =
Js.Math.log(mean) -. 0.5 *. Js.Math.log(variance /. meanSquared +. 1.0);
let sigma =
Js.Math.pow_float(
~base=Js.Math.log(variance /. meanSquared +. 1.0),
~exp=0.5,
);
`Lognormal({mu, sigma});
};
let multiply = (l1, l2) => {
let mu = l1.mu +. l2.mu;
let sigma = l1.sigma +. l2.sigma;
`Lognormal({mu, sigma});
};
let divide = (l1, l2) => {
let mu = l1.mu -. l2.mu;
let sigma = l1.sigma +. l2.sigma;
`Lognormal({mu, sigma});
};
let operate = (operation: Operation.Algebraic.t, n1: t, n2: t) =>
switch (operation) {
| `Multiply => Some(multiply(n1, n2))
| `Divide => Some(divide(n1, n2))
| _ => None
};
};
module Uniform = {
type t = uniform;
let make = (low, high) => `Uniform({low, high});
let pdf = (x, t: t) => Jstat.uniform##pdf(x, t.low, t.high);
let cdf = (x, t: t) => Jstat.uniform##cdf(x, t.low, t.high);
let inv = (p, t: t) => Jstat.uniform##inv(p, t.low, t.high);
let sample = (t: t) => Jstat.uniform##sample(t.low, t.high);
let mean = (t: t) => Ok(Jstat.uniform##mean(t.low, t.high));
let toString = ({low, high}: t) => {j|Uniform($low,$high)|j};
let truncate = (low, high, t: t): t => {
let newLow = max(E.O.default(neg_infinity, low), t.low);
let newHigh = min(E.O.default(infinity, high), t.high);
{low: newLow, high: newHigh};
};
};
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;
let mean = (t: t) => Ok(t);
let sample = (t: t) => t;
let toString = Js.Float.toString;
};
module T = {
let minCdfValue = 0.0001;
let maxCdfValue = 0.9999;
let pdf = (x, dist) =>
switch (dist) {
| `Normal(n) => Normal.pdf(x, n)
| `Triangular(n) => Triangular.pdf(x, n)
| `Exponential(n) => Exponential.pdf(x, n)
| `Cauchy(n) => Cauchy.pdf(x, n)
| `Lognormal(n) => Lognormal.pdf(x, n)
| `Uniform(n) => Uniform.pdf(x, n)
| `Beta(n) => Beta.pdf(x, n)
| `Float(n) => Float.pdf(x, n)
};
let cdf = (x, dist) =>
switch (dist) {
| `Normal(n) => Normal.cdf(x, n)
| `Triangular(n) => Triangular.cdf(x, n)
| `Exponential(n) => Exponential.cdf(x, n)
| `Cauchy(n) => Cauchy.cdf(x, n)
| `Lognormal(n) => Lognormal.cdf(x, n)
| `Uniform(n) => Uniform.cdf(x, n)
| `Beta(n) => Beta.cdf(x, n)
| `Float(n) => Float.cdf(x, n)
};
let inv = (x, dist) =>
switch (dist) {
| `Normal(n) => Normal.inv(x, n)
| `Triangular(n) => Triangular.inv(x, n)
| `Exponential(n) => Exponential.inv(x, n)
| `Cauchy(n) => Cauchy.inv(x, n)
| `Lognormal(n) => Lognormal.inv(x, n)
| `Uniform(n) => Uniform.inv(x, n)
| `Beta(n) => Beta.inv(x, n)
| `Float(n) => Float.inv(x, n)
};
let sample: symbolicDist => float =
fun
| `Normal(n) => Normal.sample(n)
| `Triangular(n) => Triangular.sample(n)
| `Exponential(n) => Exponential.sample(n)
| `Cauchy(n) => Cauchy.sample(n)
| `Lognormal(n) => Lognormal.sample(n)
| `Uniform(n) => Uniform.sample(n)
| `Beta(n) => Beta.sample(n)
| `Float(n) => Float.sample(n);
let doN = (n, fn) => {
let items = Belt.Array.make(n, 0.0);
for (x in 0 to n - 1) {
let _ = Belt.Array.set(items, x, fn());
();
};
items;
};
let sampleN = (n, dist) => {
doN(n, () => sample(dist));
};
let toString: symbolicDist => string =
fun
| `Triangular(n) => Triangular.toString(n)
| `Exponential(n) => Exponential.toString(n)
| `Cauchy(n) => Cauchy.toString(n)
| `Normal(n) => Normal.toString(n)
| `Lognormal(n) => Lognormal.toString(n)
| `Uniform(n) => Uniform.toString(n)
| `Beta(n) => Beta.toString(n)
| `Float(n) => Float.toString(n);
let min: symbolicDist => float =
fun
| `Triangular({low}) => low
| `Exponential(n) => Exponential.inv(minCdfValue, n)
| `Cauchy(n) => Cauchy.inv(minCdfValue, n)
| `Normal(n) => Normal.inv(minCdfValue, n)
| `Lognormal(n) => Lognormal.inv(minCdfValue, n)
| `Uniform({low}) => low
| `Beta(n) => Beta.inv(minCdfValue, n)
| `Float(n) => n;
let max: symbolicDist => float =
fun
| `Triangular(n) => n.high
| `Exponential(n) => Exponential.inv(maxCdfValue, n)
| `Cauchy(n) => Cauchy.inv(maxCdfValue, n)
| `Normal(n) => Normal.inv(maxCdfValue, n)
| `Lognormal(n) => Lognormal.inv(maxCdfValue, n)
| `Beta(n) => Beta.inv(maxCdfValue, n)
| `Uniform({high}) => high
| `Float(n) => n;
let mean: symbolicDist => result(float, string) =
fun
| `Triangular(n) => Triangular.mean(n)
| `Exponential(n) => Exponential.mean(n)
| `Cauchy(n) => Cauchy.mean(n)
| `Normal(n) => Normal.mean(n)
| `Lognormal(n) => Lognormal.mean(n)
| `Beta(n) => Beta.mean(n)
| `Uniform(n) => Uniform.mean(n)
| `Float(n) => Float.mean(n);
let operate = (distToFloatOp: ExpressionTypes.distToFloatOperation, s) =>
switch (distToFloatOp) {
| `Cdf(f) => Ok(cdf(f, s))
| `Pdf(f) => Ok(pdf(f, s))
| `Inv(f) => Ok(inv(f, s))
| `Sample => Ok(sample(s))
| `Mean => mean(s)
};
let interpolateXs =
(~xSelection: [ | `Linear | `ByWeight]=`Linear, dist: symbolicDist, n) => {
switch (xSelection, dist) {
| (`Linear, _) => E.A.Floats.range(min(dist), max(dist), n)
| (`ByWeight, `Uniform(n)) =>
// In `ByWeight mode, uniform distributions get special treatment because we need two x's
// on either side for proper rendering (just left and right of the discontinuities).
let dx = 0.00001 *. (n.high -. n.low);
[|n.low -. dx, n.low +. dx, n.high -. dx, n.high +. dx|];
| (`ByWeight, _) =>
let ys = E.A.Floats.range(minCdfValue, maxCdfValue, n);
ys |> E.A.fmap(y => inv(y, dist));
};
};
/* Calling e.g. "Normal.operate" returns an optional that wraps a result.
If the optional is None, there is no valid analytic solution. If it Some, it
can still return an error if there is a serious problem,
like in the case of a divide by 0.
*/
let tryAnalyticalSimplification =
(
d1: symbolicDist,
d2: symbolicDist,
op: ExpressionTypes.algebraicOperation,
)
: analyticalSimplificationResult =>
switch (d1, d2) {
| (`Float(v1), `Float(v2)) =>
switch (Operation.Algebraic.applyFn(op, v1, v2)) {
| Ok(r) => `AnalyticalSolution(`Float(r))
| Error(n) => `Error(n)
}
| (`Normal(v1), `Normal(v2)) =>
Normal.operate(op, v1, v2)
|> E.O.dimap(r => `AnalyticalSolution(r), () => `NoSolution)
| (`Lognormal(v1), `Lognormal(v2)) =>
Lognormal.operate(op, v1, v2)
|> E.O.dimap(r => `AnalyticalSolution(r), () => `NoSolution)
| _ => `NoSolution
};
let toShape = (sampleCount, d: symbolicDist): DistTypes.shape =>
switch (d) {
| `Float(v) =>
Discrete(
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.make(~integralSumCache=Some(1.0), {xs, ys}));
};
};

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type normal = {
mean: float,
stdev: float,
};
type lognormal = {
mu: float,
sigma: float,
};
type uniform = {
low: float,
high: float,
};
type beta = {
alpha: float,
beta: float,
};
type exponential = {rate: float};
type cauchy = {
local: float,
scale: float,
};
type triangular = {
low: float,
medium: float,
high: float,
};
type symbolicDist = [
| `Normal(normal)
| `Beta(beta)
| `Lognormal(lognormal)
| `Uniform(uniform)
| `Exponential(exponential)
| `Cauchy(cauchy)
| `Triangular(triangular)
| `Float(float) // Dirac delta at x. Practically useful only in the context of multimodals.
];
type analyticalSimplificationResult = [
| `AnalyticalSolution(symbolicDist)
| `Error(string)
| `NoSolution
];

258
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open TypeSystem;
let wrongInputsError = (r: array(typedValue)) => {
let inputs = r |> E.A.fmap(TypedValue.toString) |>Js.String.concatMany(_, ",");
Js.log3("Inputs were", inputs, r);
Error("Wrong inputs. The inputs were:" ++ inputs);
};
let to_: (float, float) => result(node, string) =
(low, high) =>
switch (low, high) {
| (low, high) when low <= 0.0 && low < high =>
Ok(`SymbolicDist(SymbolicDist.Normal.from90PercentCI(low, high)))
| (low, high) when low < high =>
Ok(`SymbolicDist(SymbolicDist.Lognormal.from90PercentCI(low, high)))
| (_, _) => Error("Low value must be less than high value.")
};
let makeSymbolicFromTwoFloats = (name, fn) =>
Function.T.make(
~name,
~outputType=`SamplingDistribution,
~inputTypes=[|`Float, `Float|],
~run=
fun
| [|`Float(a), `Float(b)|] => Ok(`SymbolicDist(fn(a, b)))
| e => wrongInputsError(e),
(),
);
let makeSymbolicFromOneFloat = (name, fn) =>
Function.T.make(
~name,
~outputType=`SamplingDistribution,
~inputTypes=[|`Float|],
~run=
fun
| [|`Float(a)|] => Ok(`SymbolicDist(fn(a)))
| e => wrongInputsError(e),
(),
);
let makeDistFloat = (name, fn) =>
Function.T.make(
~name,
~outputType=`SamplingDistribution,
~inputTypes=[|`SamplingDistribution, `Float|],
~run=
fun
| [|`SamplingDist(a), `Float(b)|] => fn(a, b)
| [|`RenderedDist(a), `Float(b)|] => fn(`RenderedDist(a), b)
| e => wrongInputsError(e),
(),
);
let makeRenderedDistFloat = (name, fn) =>
Function.T.make(
~name,
~outputType=`RenderedDistribution,
~inputTypes=[|`RenderedDistribution, `Float|],
~shouldCoerceTypes=true,
~run=
fun
| [|`RenderedDist(a), `Float(b)|] => fn(a, b)
| e => wrongInputsError(e),
(),
);
let makeDist = (name, fn) =>
Function.T.make(
~name,
~outputType=`SamplingDistribution,
~inputTypes=[|`SamplingDistribution|],
~run=
fun
| [|`SamplingDist(a)|] => fn(a)
| [|`RenderedDist(a)|] => fn(`RenderedDist(a))
| e => wrongInputsError(e),
(),
);
let floatFromDist =
(
distToFloatOp: ExpressionTypes.distToFloatOperation,
t: TypeSystem.samplingDist,
)
: result(node, string) => {
switch (t) {
| `SymbolicDist(s) =>
SymbolicDist.T.operate(distToFloatOp, s)
|> E.R.bind(_, v => Ok(`SymbolicDist(`Float(v))))
| `RenderedDist(rs) =>
Shape.operate(distToFloatOp, rs) |> (v => Ok(`SymbolicDist(`Float(v))))
};
};
let verticalScaling = (scaleOp, rs, scaleBy) => {
// scaleBy has to be a single float, otherwise we'll return an error.
let fn = (secondary, main) =>
Operation.Scale.toFn(scaleOp, main, secondary);
let integralSumCacheFn = Operation.Scale.toIntegralSumCacheFn(scaleOp);
let integralCacheFn = Operation.Scale.toIntegralCacheFn(scaleOp);
Ok(
`RenderedDist(
Shape.T.mapY(
~integralSumCacheFn=integralSumCacheFn(scaleBy),
~integralCacheFn=integralCacheFn(scaleBy),
~fn=fn(scaleBy),
rs,
),
),
);
};
module Multimodal = {
let getByNameResult = ExpressionTypes.ExpressionTree.Hash.getByNameResult;
let _paramsToDistsAndWeights = (r: array(typedValue)) =>
switch (r) {
| [|`Hash(r)|] =>
let dists =
getByNameResult(r, "dists")
->E.R.bind(TypeSystem.TypedValue.toArray)
->E.R.bind(r =>
r
|> E.A.fmap(TypeSystem.TypedValue.toDist)
|> E.A.R.firstErrorOrOpen
);
let weights =
getByNameResult(r, "weights")
->E.R.bind(TypeSystem.TypedValue.toArray)
->E.R.bind(r =>
r
|> E.A.fmap(TypeSystem.TypedValue.toFloat)
|> E.A.R.firstErrorOrOpen
);
E.R.merge(dists, weights)
|> E.R.fmap(((a, b)) =>
E.A.zipMaxLength(a, b)
|> E.A.fmap(((a, b)) =>
(a |> E.O.toExn(""), b |> E.O.default(1.0))
)
);
| _ => Error("Needs items")
};
let _runner: array(typedValue) => result(node, string) =
r => {
let paramsToDistsAndWeights =
_paramsToDistsAndWeights(r)
|> E.R.fmap(
E.A.fmap(((dist, weight)) =>
`FunctionCall((
"scaleMultiply",
[|dist, `SymbolicDist(`Float(weight))|],
))
),
);
let pointwiseSum: result(node, string) =
paramsToDistsAndWeights->E.R.bind(
E.R.errorIfCondition(E.A.isEmpty, "Needs one input"),
)
|> E.R.fmap(r =>
r
|> Js.Array.sliceFrom(1)
|> E.A.fold_left(
(acc, x) => {`PointwiseCombination((`Add, acc, x))},
E.A.unsafe_get(r, 0),
)
);
pointwiseSum;
};
let _function =
Function.T.make(
~name="multimodal",
~outputType=`SamplingDistribution,
~inputTypes=[|
`Hash([|
("dists", `Array(`SamplingDistribution)),
("weights", `Array(`Float)),
|]),
|],
~run=_runner,
(),
);
};
let all = [|
makeSymbolicFromTwoFloats("normal", SymbolicDist.Normal.make),
makeSymbolicFromTwoFloats("uniform", SymbolicDist.Uniform.make),
makeSymbolicFromTwoFloats("beta", SymbolicDist.Beta.make),
makeSymbolicFromTwoFloats("lognormal", SymbolicDist.Lognormal.make),
makeSymbolicFromTwoFloats(
"lognormalFromMeanAndStdDev",
SymbolicDist.Lognormal.fromMeanAndStdev,
),
makeSymbolicFromOneFloat("exponential", SymbolicDist.Exponential.make),
Function.T.make(
~name="to",
~outputType=`SamplingDistribution,
~inputTypes=[|`Float, `Float|],
~run=
fun
| [|`Float(a), `Float(b)|] => to_(a, b)
| e => wrongInputsError(e),
(),
),
Function.T.make(
~name="triangular",
~outputType=`SamplingDistribution,
~inputTypes=[|`Float, `Float, `Float|],
~run=
fun
| [|`Float(a), `Float(b), `Float(c)|] =>
SymbolicDist.Triangular.make(a, b, c)
|> E.R.fmap(r => `SymbolicDist(r))
| e => wrongInputsError(e),
(),
),
makeDistFloat("pdf", (dist, float) => floatFromDist(`Pdf(float), dist)),
makeDistFloat("inv", (dist, float) => floatFromDist(`Inv(float), dist)),
makeDistFloat("cdf", (dist, float) => floatFromDist(`Cdf(float), dist)),
makeDist("mean", dist => floatFromDist(`Mean, dist)),
makeDist("sample", dist => floatFromDist(`Sample, dist)),
Function.T.make(
~name="render",
~outputType=`RenderedDistribution,
~inputTypes=[|`RenderedDistribution|],
~run=
fun
| [|`RenderedDist(c)|] => Ok(`RenderedDist(c))
| e => wrongInputsError(e),
(),
),
Function.T.make(
~name="normalize",
~outputType=`SamplingDistribution,
~inputTypes=[|`SamplingDistribution|],
~run=
fun
| [|`SamplingDist(`SymbolicDist(c))|] => Ok(`SymbolicDist(c))
| [|`SamplingDist(`RenderedDist(c))|] =>
Ok(`RenderedDist(Shape.T.normalize(c)))
| e => wrongInputsError(e),
(),
),
makeRenderedDistFloat("scaleExp", (dist, float) =>
verticalScaling(`Exponentiate, dist, float)
),
makeRenderedDistFloat("scaleMultiply", (dist, float) =>
verticalScaling(`Multiply, dist, float)
),
makeRenderedDistFloat("scaleLog", (dist, float) =>
verticalScaling(`Log, dist, float)
),
Multimodal._function
|];

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packages/squiggle-old/src/distPlus/typeSystem/TypeSystem.re Normal file
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type node = ExpressionTypes.ExpressionTree.node;
let getFloat = ExpressionTypes.ExpressionTree.getFloat;
type samplingDist = [
| `SymbolicDist(SymbolicTypes.symbolicDist)
| `RenderedDist(DistTypes.shape)
];
type hashType = array((string, _type))
and _type = [
| `Float
| `SamplingDistribution
| `RenderedDistribution
| `Array(_type)
| `Hash(hashType)
];
type hashTypedValue = array((string, typedValue))
and typedValue = [
| `Float(float)
| `RenderedDist(DistTypes.shape)
| `SamplingDist(samplingDist)
| `Array(array(typedValue))
| `Hash(hashTypedValue)
];
type _function = {
name: string,
inputTypes: array(_type),
outputType: _type,
run: array(typedValue) => result(node, string),
shouldCoerceTypes: bool,
};
type functions = array(_function);
type inputNodes = array(node);
module TypedValue = {
let rec toString: typedValue => string =
fun
| `SamplingDist(_) => "[sampling dist]"
| `RenderedDist(_) => "[rendered Shape]"
| `Float(f) => "Float: " ++ Js.Float.toString(f)
| `Array(a) =>
"[" ++ (a |> E.A.fmap(toString) |> Js.String.concatMany(_, ",")) ++ "]"
| `Hash(v) =>
"{"
++ (
v
|> E.A.fmap(((name, value)) => name ++ ":" ++ toString(value))
|> Js.String.concatMany(_, ",")
)
++ "}";
let rec fromNode = (node: node): result(typedValue, string) =>
switch (node) {
| `SymbolicDist(`Float(r)) => Ok(`Float(r))
| `SymbolicDist(s) => Ok(`SamplingDist(`SymbolicDist(s)))
| `RenderedDist(s) => Ok(`RenderedDist(s))
| `Array(r) =>
r
|> E.A.fmap(fromNode)
|> E.A.R.firstErrorOrOpen
|> E.R.fmap(r => `Array(r))
| `Hash(hash) =>
hash
|> E.A.fmap(((name, t)) => fromNode(t) |> E.R.fmap(r => (name, r)))
|> E.A.R.firstErrorOrOpen
|> E.R.fmap(r => `Hash(r))
| e => Error("Wrong type: " ++ ExpressionTreeBasic.toString(e))
};
// todo: Arrays and hashes
let rec fromNodeWithTypeCoercion = (evaluationParams, _type: _type, node) => {
switch (_type, node) {
| (`Float, _) =>
switch (getFloat(node)) {
| Some(a) => Ok(`Float(a))
| _ => Error("Type Error: Expected float.")
}
| (`SamplingDistribution, _) =>
PTypes.SamplingDistribution.renderIfIsNotSamplingDistribution(
evaluationParams,
node,
)
|> E.R.bind(_, fromNode)
| (`RenderedDistribution, _) =>{
ExpressionTypes.ExpressionTree.Render.render(evaluationParams, node)
|> E.R.bind(_, fromNode);
}
| (`Array(_type), `Array(b)) =>
b
|> E.A.fmap(fromNodeWithTypeCoercion(evaluationParams, _type))
|> E.A.R.firstErrorOrOpen
|> E.R.fmap(r => `Array(r))
| (`Hash(named), `Hash(r)) =>
let keyValues =
named
|> E.A.fmap(((name, intendedType)) =>
(
name,
intendedType,
ExpressionTypes.ExpressionTree.Hash.getByName(r, name),
)
);
let typedHash =
keyValues
|> E.A.fmap(((name, intendedType, optionNode)) =>
switch (optionNode) {
| Some(node) =>
fromNodeWithTypeCoercion(evaluationParams, intendedType, node)
|> E.R.fmap(node => (name, node))
| None => Error("Hash parameter not present in hash.")
}
)
|> E.A.R.firstErrorOrOpen
|> E.R.fmap(r => `Hash(r));
typedHash;
| _ => Error("fromNodeWithTypeCoercion error, sorry.")
};
};
let toFloat: typedValue => result(float, string) =
fun
| `Float(x) => Ok(x)
| _ => Error("Not a float");
let toArray: typedValue => result(array('a), string) =
fun
| `Array(x) => Ok(x)
| _ => Error("Not an array");
let toNamed: typedValue => result(hashTypedValue, string) =
fun
| `Hash(x) => Ok(x)
| _ => Error("Not a named item");
let toDist: typedValue => result(node,string) =
fun
| `SamplingDist(`SymbolicDist(c)) => Ok(`SymbolicDist(c))
| `SamplingDist(`RenderedDist(c)) => Ok(`RenderedDist(c))
| `RenderedDist(c) => Ok(`RenderedDist(c))
| `Float(x) => Ok(`SymbolicDist(`Float(x)))
| x => Error("Cannot be converted into a distribution: " ++ toString(x));
};
module Function = {
type t = _function;
type ts = functions;
module T = {
let make =
(~name, ~inputTypes, ~outputType, ~run, ~shouldCoerceTypes=true, _): t => {
name,
inputTypes,
outputType,
run,
shouldCoerceTypes,
};
let _inputLengthCheck = (inputNodes: inputNodes, t: t) => {
let expectedLength = E.A.length(t.inputTypes);
let actualLength = E.A.length(inputNodes);
expectedLength == actualLength
? Ok(inputNodes)
: Error(
"Wrong number of inputs. Expected"
++ (expectedLength |> E.I.toString)
++ ". Got:"
++ (actualLength |> E.I.toString),
);
};
let _coerceInputNodes =
(evaluationParams, inputTypes, shouldCoerce, inputNodes) =>
Belt.Array.zip(inputTypes, inputNodes)
|> E.A.fmap(((def, input)) =>
shouldCoerce
? TypedValue.fromNodeWithTypeCoercion(
evaluationParams,
def,
input,
)
: TypedValue.fromNode(input)
)
|> E.A.R.firstErrorOrOpen;
let inputsToTypedValues =
(
evaluationParams: ExpressionTypes.ExpressionTree.evaluationParams,
inputNodes: inputNodes,
t: t,
) => {
_inputLengthCheck(inputNodes, t)
->E.R.bind(
_coerceInputNodes(
evaluationParams,
t.inputTypes,
t.shouldCoerceTypes,
),
)
};
let run =
(
evaluationParams: ExpressionTypes.ExpressionTree.evaluationParams,
inputNodes: inputNodes,
t: t,
) => {
inputsToTypedValues(evaluationParams, inputNodes, t)->E.R.bind(t.run)
|> (
fun
| Ok(i) => Ok(i)
| Error(r) => {
Error("Function " ++ t.name ++ " error: " ++ r);
}
);
};
};
module Ts = {
let findByName = (ts: ts, n: string) =>
ts |> Belt.Array.getBy(_, ({name}) => name == n);
let findByNameAndRun = (ts: ts, n: string, evaluationParams, inputTypes) =>
findByName(ts, n) |> E.O.fmap(T.run(evaluationParams, inputTypes));
};
};

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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, x =>
switch x {
| 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)
}
module Int = {
let max = (i1: int, i2: int) => i1 > i2 ? i1 : i2
}
/* Utils */
module U = {
let isEqual = (a, b) => a == b
let toA = a => [a]
let id = e => e
}
module O = {
let dimap = (sFn, rFn, e) =>
switch e {
| Some(r) => sFn(r)
| None => rFn()
}
()
let fmap = Rationale.Option.fmap
let bind = Rationale.Option.bind
let default = Rationale.Option.default
let isSome = Rationale.Option.isSome
let isNone = Rationale.Option.isNone
let toExn = Rationale.Option.toExn
let some = Rationale.Option.some
let firstSome = Rationale.Option.firstSome
let toExt = Rationale.Option.toExn
let flatApply = (fn, b) => Rationale.Option.apply(fn, Some(b)) |> Rationale.Option.flatten
let toBool = opt =>
switch opt {
| Some(_) => true
| _ => false
}
let ffmap = (fn, r) =>
switch r {
| Some(sm) => fn(sm)
| _ => None
}
let toString = opt =>
switch opt {
| Some(s) => s
| _ => ""
}
let toResult = (error, e) =>
switch e {
| Some(r) => Belt.Result.Ok(r)
| None => Error(error)
}
let compare = (compare, f1: option<float>, f2: option<float>) =>
switch (f1, f2) {
| (Some(f1), Some(f2)) => Some(compare(f1, f2) ? f1 : f2)
| (Some(f1), None) => Some(f1)
| (None, Some(f2)) => Some(f2)
| (None, None) => None
}
let min = compare(\"<")
let max = compare(\">")
module React = {
let defaultNull = default(React.null)
let fmapOrNull = fn => \"||>"(fmap(fn), default(React.null))
let flatten = default(React.null)
}
}
/* Functions */
module F = {
let apply = (a, e) => a |> e
let flatten2Callbacks = (fn1, fn2, fnlast) =>
fn1(response1 => fn2(response2 => fnlast(response1, response2)))
let flatten3Callbacks = (fn1, fn2, fn3, fnlast) =>
fn1(response1 => fn2(response2 => fn3(response3 => fnlast(response1, response2, response3))))
let flatten4Callbacks = (fn1, fn2, fn3, fn4, fnlast) =>
fn1(response1 =>
fn2(response2 =>
fn3(response3 => fn4(response4 => fnlast(response1, response2, response3, response4)))
)
)
}
module Bool = {
type t = bool
let toString = (t: t) => t ? "TRUE" : "FALSE"
let fromString = str => str == "TRUE" ? true : false
module O = {
let toBool = opt =>
switch opt {
| Some(true) => true
| _ => false
}
}
}
module Float = {
let with2DigitsPrecision = Js.Float.toPrecisionWithPrecision(_, ~digits=2)
let with3DigitsPrecision = Js.Float.toPrecisionWithPrecision(_, ~digits=3)
let toFixed = Js.Float.toFixed
let toString = Js.Float.toString
}
module I = {
let increment = n => n + 1
let decrement = n => n - 1
let toString = Js.Int.toString
}
/* R for Result */
module R = {
let result = Rationale.Result.result
let id = e => e |> result(U.id, U.id)
let fmap = Rationale.Result.fmap
let bind = Rationale.Result.bind
let toExn = Belt.Result.getExn
let default = (default, res: Belt.Result.t<'a, 'b>) =>
switch res {
| Ok(r) => r
| Error(_) => default
}
let merge = (a, b) =>
switch (a, b) {
| (Error(e), _) => Error(e)
| (_, Error(e)) => Error(e)
| (Ok(a), Ok(b)) => Ok((a, b))
}
let toOption = (e: Belt.Result.t<'a, 'b>) =>
switch e {
| Ok(r) => Some(r)
| Error(_) => None
}
let errorIfCondition = (errorCondition, errorMessage, r) =>
errorCondition(r) ? Error(errorMessage) : Ok(r)
}
let safe_fn_of_string = (fn, s: string): option<'a> =>
try Some(fn(s)) catch {
| _ => None
}
module S = {
let safe_float = float_of_string->safe_fn_of_string
let safe_int = int_of_string->safe_fn_of_string
let default = (defaultStr, str) => str == "" ? defaultStr : str
}
module J = {
let toString = \"||>"(Js.Json.decodeString, O.default(""))
let fromString = Js.Json.string
let fromNumber = Js.Json.number
module O = {
let fromString = (str: string) =>
switch str {
| "" => None
| _ => Some(Js.Json.string(str))
}
let toString = (str: option<'a>) =>
switch str {
| Some(str) => Some(str |> \"||>"(Js.Json.decodeString, O.default("")))
| _ => None
}
}
}
module M = {
let format = MomentRe.Moment.format
let format_standard = "MMM DD, YYYY HH:mm"
let format_simple = "L"
/* TODO: Figure out better name */
let goFormat_simple = MomentRe.Moment.format(format_simple)
let goFormat_standard = MomentRe.Moment.format(format_standard)
let toUtc = MomentRe.momentUtc
let toJSON = MomentRe.Moment.toJSON
let momentDefaultFormat = MomentRe.momentDefaultFormat
}
module JsDate = {
let fromString = Js.Date.fromString
let now = Js.Date.now
let make = Js.Date.make
let valueOf = Js.Date.valueOf
}
/* List */
module L = {
let fmap = List.map
let get = Belt.List.get
let toArray = Array.of_list
let fmapi = List.mapi
let concat = List.concat
let drop = Rationale.RList.drop
let remove = Rationale.RList.remove
let find = List.find
let filter = List.filter
let for_all = List.for_all
let exists = List.exists
let sort = List.sort
let length = List.length
let filter_opt = Rationale.RList.filter_opt
let uniqBy = Rationale.RList.uniqBy
let join = Rationale.RList.join
let head = Rationale.RList.head
let uniq = Rationale.RList.uniq
let flatten = List.flatten
let last = Rationale.RList.last
let append = List.append
let getBy = Belt.List.getBy
let dropLast = Rationale.RList.dropLast
let contains = Rationale.RList.contains
let without = Rationale.RList.without
let update = Rationale.RList.update
let iter = List.iter
let findIndex = Rationale.RList.findIndex
}
/* A for Array */
module A = {
let fmap = Array.map
let fmapi = Array.mapi
let to_list = Array.to_list
let of_list = Array.of_list
let length = Array.length
let append = Array.append
// let empty = [||];
let unsafe_get = Array.unsafe_get
let get = Belt.Array.get
let getBy = Belt.Array.getBy
let last = a => get(a, length(a) - 1)
let first = get(_, 0)
let hasBy = (r, fn) => Belt.Array.getBy(r, fn) |> O.isSome
let fold_left = Array.fold_left
let fold_right = Array.fold_right
let concatMany = Belt.Array.concatMany
let keepMap = Belt.Array.keepMap
let init = Array.init
let reduce = Belt.Array.reduce
let reducei = Belt.Array.reduceWithIndex
let isEmpty = r => length(r) < 1
let min = a => get(a, 0) |> O.fmap(first => Belt.Array.reduce(a, first, (i, j) => i < j ? i : j))
let max = a => get(a, 0) |> O.fmap(first => Belt.Array.reduce(a, first, (i, j) => i > j ? i : j))
let stableSortBy = Belt.SortArray.stableSortBy
let toRanges = (a: array<'a>) =>
switch a |> Belt.Array.length {
| 0
| 1 =>
Belt.Result.Error("Must be at least 2 elements")
| n =>
Belt.Array.makeBy(n - 1, r => r)
|> Belt.Array.map(_, index => (
Belt.Array.getUnsafe(a, index),
Belt.Array.getUnsafe(a, index + 1),
))
|> Rationale.Result.return
}
// This zips while taking the longest elements of each array.
let zipMaxLength = (array1, array2) => {
let maxLength = Int.max(length(array1), length(array2))
let result = maxLength |> Belt.Array.makeUninitializedUnsafe
for i in 0 to maxLength - 1 {
Belt.Array.set(result, i, (get(array1, i), get(array2, i))) |> ignore
}
result
}
let asList = (f: list<'a> => list<'a>, r: array<'a>) => r |> to_list |> f |> of_list
/* TODO: Is there a better way of doing this? */
let uniq = r => asList(L.uniq, r)
//intersperse([1,2,3], [10,11,12]) => [1,10,2,11,3,12]
let intersperse = (a: array<'a>, b: array<'a>) => {
let items: ref<array<'a>> = ref([])
Belt.Array.forEachWithIndex(a, (i, item) =>
switch Belt.Array.get(b, i) {
| Some(r) => items := append(items.contents, [item, r])
| None => items := append(items.contents, [item])
}
)
items.contents
}
// This is like map, but
//accumulate((a,b) => a + b, [1,2,3]) => [1, 3, 5]
let accumulate = (fn: ('a, 'a) => 'a, items: array<'a>) => {
let length = items |> length
let empty = Belt.Array.make(length, items |> unsafe_get(_, 0))
Belt.Array.forEachWithIndex(items, (index, element) => {
let item = switch index {
| 0 => element
| index => fn(element, unsafe_get(empty, index - 1))
}
let _ = Belt.Array.set(empty, index, item)
})
empty
}
// @todo: Is -1 still the indicator that this is false (as is true with
// @todo: js findIndex)? Wasn't sure.
let findIndex = (e, i) =>
Js.Array.findIndex(e, i) |> (
r =>
switch r {
| -1 => None
| r => Some(r)
}
)
let filter = (o, e) => Js.Array.filter(o, e)
module O = {
let concatSomes = (optionals: array<option<'a>>): array<'a> =>
optionals
|> Js.Array.filter(Rationale.Option.isSome)
|> Js.Array.map(Rationale.Option.toExn("Warning: This should not have happened"))
let defaultEmpty = (o: option<array<'a>>): array<'a> =>
switch o {
| Some(o) => o
| None => []
}
}
module R = {
let firstErrorOrOpen = (results: array<Belt.Result.t<'a, 'b>>): Belt.Result.t<
array<'a>,
'b,
> => {
let bringErrorUp = switch results |> Belt.Array.getBy(_, Belt.Result.isError) {
| Some(Belt.Result.Error(err)) => Belt.Result.Error(err)
| Some(Belt.Result.Ok(_)) => Belt.Result.Ok(results)
| None => Belt.Result.Ok(results)
}
let forceOpen = (r: array<Belt.Result.t<'a, 'b>>): array<'a> =>
r |> Belt.Array.map(_, r => Belt.Result.getExn(r))
bringErrorUp |> Belt.Result.map(_, forceOpen)
}
}
module Sorted = {
let min = first
let max = last
let range = (~min=min, ~max=max, a) =>
switch (min(a), max(a)) {
| (Some(min), Some(max)) => Some(max -. min)
| _ => None
}
let binarySearchFirstElementGreaterIndex = (ar: array<'a>, el: 'a) => {
let el = Belt.SortArray.binarySearchBy(ar, el, compare)
let el = el < 0 ? el * -1 - 1 : el
switch el {
| e if e >= length(ar) => #overMax
| e if e == 0 => #underMin
| e => #firstHigher(e)
}
}
let concat = (t1: array<'a>, t2: array<'a>) => {
let ts = Belt.Array.concat(t1, t2)
ts |> Array.fast_sort(compare)
ts
}
let concatMany = (t1: array<array<'a>>) => {
let ts = Belt.Array.concatMany(t1)
ts |> Array.fast_sort(compare)
ts
}
module Floats = {
let makeIncrementalUp = (a, b) =>
Array.make(b - a + 1, a) |> Array.mapi((i, c) => c + i) |> Belt.Array.map(_, float_of_int)
let makeIncrementalDown = (a, b) =>
Array.make(a - b + 1, a) |> Array.mapi((i, c) => c - i) |> Belt.Array.map(_, float_of_int)
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 if 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 Floats = {
let sum = Belt.Array.reduce(_, 0., (i, j) => i +. j)
let mean = a => sum(a) /. (Array.length(a) |> float_of_int)
let random = Js.Math.random_int
exception RangeError(string)
let range = (min: float, max: float, n: int): array<float> =>
switch n {
| 0 => []
| 1 => [min]
| 2 => [min, max]
| _ if min == max => Belt.Array.make(n, min)
| _ if n < 0 => raise(RangeError("n must be greater than 0"))
| _ if min > max => raise(RangeError("Min value is less then max value"))
| _ =>
let diff = (max -. min) /. Belt.Float.fromInt(n - 1)
Belt.Array.makeBy(n, i => min +. Belt.Float.fromInt(i) *. diff)
}
}
}
module JsArray = {
let concatSomes = (optionals: Js.Array.t<option<'a>>): Js.Array.t<'a> =>
optionals
|> Js.Array.filter(Rationale.Option.isSome)
|> Js.Array.map(Rationale.Option.toExn("Warning: This should not have happened"))
let filter = Js.Array.filter
}

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// Todo: Another way of doing this is with [@bs.scope "normal"], which may be more elegant
type normal = {
.
[@bs.meth] "pdf": (float, float, float) => float,
[@bs.meth] "cdf": (float, float, float) => float,
[@bs.meth] "inv": (float, float, float) => float,
[@bs.meth] "sample": (float, float) => float,
[@bs.meth] "mean": (float, float) => float,
};
type lognormal = {
.
[@bs.meth] "pdf": (float, float, float) => float,
[@bs.meth] "cdf": (float, float, float) => float,
[@bs.meth] "inv": (float, float, float) => float,
[@bs.meth] "sample": (float, float) => float,
[@bs.meth] "mean": (float, float) => float,
};
type uniform = {
.
[@bs.meth] "pdf": (float, float, float) => float,
[@bs.meth] "cdf": (float, float, float) => float,
[@bs.meth] "inv": (float, float, float) => float,
[@bs.meth] "sample": (float, float) => float,
[@bs.meth] "mean": (float, float) => float,
};
type beta = {
.
[@bs.meth] "pdf": (float, float, float) => float,
[@bs.meth] "cdf": (float, float, float) => float,
[@bs.meth] "inv": (float, float, float) => float,
[@bs.meth] "sample": (float, float) => float,
[@bs.meth] "mean": (float, float) => float,
};
type exponential = {
.
[@bs.meth] "pdf": (float, float) => float,
[@bs.meth] "cdf": (float, float) => float,
[@bs.meth] "inv": (float, float) => float,
[@bs.meth] "sample": float => float,
[@bs.meth] "mean": float => float,
};
type cauchy = {
.
[@bs.meth] "pdf": (float, float, float) => float,
[@bs.meth] "cdf": (float, float, float) => float,
[@bs.meth] "inv": (float, float, float) => float,
[@bs.meth] "sample": (float, float) => float,
};
type triangular = {
.
[@bs.meth] "pdf": (float, float, float, float) => float,
[@bs.meth] "cdf": (float, float, float, float) => float,
[@bs.meth] "inv": (float, float, float, float) => float,
[@bs.meth] "sample": (float, float, float) => float,
[@bs.meth] "mean": (float, float, float) => float,
};
// Pareto doesn't have sample for some reason
type pareto = {
.
[@bs.meth] "pdf": (float, float, float) => float,
[@bs.meth] "cdf": (float, float, float) => float,
[@bs.meth] "inv": (float, float, float) => float,
};
type poisson = {
.
[@bs.meth] "pdf": (float, float) => float,
[@bs.meth] "cdf": (float, float) => float,
[@bs.meth] "sample": float => float,
[@bs.meth] "mean": float => float,
};
type weibull = {
.
[@bs.meth] "pdf": (float, float, float) => float,
[@bs.meth] "cdf": (float, float, float) => float,
[@bs.meth] "inv": (float, float, float) => float,
[@bs.meth] "sample": (float, float) => float,
[@bs.meth] "mean": (float, float) => float,
};
type binomial = {
.
[@bs.meth] "pdf": (float, float, float) => float,
[@bs.meth] "cdf": (float, float, float) => float,
};
[@bs.module "jstat"] external normal: normal = "normal";
[@bs.module "jstat"] external lognormal: lognormal = "lognormal";
[@bs.module "jstat"] external uniform: uniform = "uniform";
[@bs.module "jstat"] external beta: beta = "beta";
[@bs.module "jstat"] external exponential: exponential = "exponential";
[@bs.module "jstat"] external cauchy: cauchy = "cauchy";
[@bs.module "jstat"] external triangular: triangular = "triangular";
[@bs.module "jstat"] external poisson: poisson = "poisson";
[@bs.module "jstat"] external pareto: pareto = "pareto";
[@bs.module "jstat"] external weibull: weibull = "weibull";
[@bs.module "jstat"] external binomial: binomial = "binomial";
[@bs.module "jstat"] external sum: array(float) => float = "sum";
[@bs.module "jstat"] external product: array(float) => float = "product";
[@bs.module "jstat"] external min: array(float) => float = "min";
[@bs.module "jstat"] external max: array(float) => float = "max";
[@bs.module "jstat"] external mean: array(float) => float = "mean";
[@bs.module "jstat"] external geomean: array(float) => float = "geomean";
[@bs.module "jstat"] external mode: array(float) => float = "mode";
[@bs.module "jstat"] external variance: array(float) => float = "variance";
[@bs.module "jstat"] external deviation: array(float) => float = "deviation";
[@bs.module "jstat"] external stdev: array(float) => float = "stdev";
[@bs.module "jstat"]
external quartiles: (array(float)) => array(float) = "quartiles";
[@bs.module "jstat"]
external quantiles: (array(float), array(float)) => array(float) = "quantiles";
[@bs.module "jstat"]
external percentile: (array(float), float, bool) => float = "percentile";

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[@bs.module "lodash"] external min: array('a) => 'a = "min";
[@bs.module "lodash"] external max: array('a) => 'a = "max";
[@bs.module "lodash"] external uniq: array('a) => array('a) = "uniq";
[@bs.module "lodash"]
external countBy: (array('a), 'a => 'b) => Js.Dict.t(int) = "countBy";

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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>Squiggle Language</title>
<link href="https://fonts.googleapis.com/css?family=Lato:300,400,700,900" rel="stylesheet">
<link href="./styles/index.css" rel="stylesheet">
<script src="./Index.bs.js" defer></script>
</head>
<body>
<div id="app" style="height: 100%"></div>
</body>
</html>

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module Styles = {
open CssJs
let h3 = style(. [ fontSize(#em(1.5)), marginBottom(#em(1.5)) ])
let card = style(. [ marginTop(#em(2.)), marginBottom(#em(2.)) ])
}
module Table = {
module TableStyles = {
open CssJs
let row = style(. [ display(#flex), height(#em(4.)) ])
let col = (~f=1.0, ()) => style(. [ flex(#num(f)) ])
}
@react.component
let make = () => <> </>
}
@react.component
let make = () => <div> <div style=Styles.card> <Table /> </div> </div>

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@tailwind base;
@tailwind components;
@tailwind utilities;

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module.exports = {
prefix: '',
important: false,
separator: ':',
theme: {
screens: {
sm: '640px',
md: '768px',
lg: '1024px',
xl: '1280px',
},
colors: {
transparent: 'transparent',
black: '#000',
white: '#fff',
gray: {
100: '#f7fafc',
200: '#edf2f7',
300: '#e2e8f0',
400: '#cbd5e0',
500: '#a0aec0',
600: '#718096',
700: '#4a5568',
800: '#2d3748',
900: '#1a202c',
},
red: {
100: '#fff5f5',
200: '#fed7d7',
300: '#feb2b2',
400: '#fc8181',
500: '#f56565',
600: '#e53e3e',
700: '#c53030',
800: '#9b2c2c',
900: '#742a2a',
},
orange: {
100: '#fffaf0',
200: '#feebc8',
300: '#fbd38d',
400: '#f6ad55',
500: '#ed8936',
600: '#dd6b20',
700: '#c05621',
800: '#9c4221',
900: '#7b341e',
},
yellow: {
100: '#fffff0',
200: '#fefcbf',
300: '#faf089',
400: '#f6e05e',
500: '#ecc94b',
600: '#d69e2e',
700: '#b7791f',
800: '#975a16',
900: '#744210',
},
green: {
100: '#f0fff4',
200: '#c6f6d5',
300: '#9ae6b4',
400: '#68d391',
500: '#48bb78',
600: '#38a169',
700: '#2f855a',
800: '#276749',
900: '#22543d',
},
teal: {
100: '#e6fffa',
200: '#b2f5ea',
300: '#81e6d9',
400: '#4fd1c5',
500: '#38b2ac',
600: '#319795',
700: '#2c7a7b',
800: '#285e61',
900: '#234e52',
},
blue: {
100: '#ebf8ff',
200: '#bee3f8',
300: '#90cdf4',
400: '#63b3ed',
500: '#4299e1',
600: '#3182ce',
700: '#2b6cb0',
800: '#2c5282',
900: '#2a4365',
},
indigo: {
100: '#ebf4ff',
200: '#c3dafe',
300: '#a3bffa',
400: '#7f9cf5',
500: '#667eea',
600: '#5a67d8',
700: '#4c51bf',
800: '#434190',
900: '#3c366b',
},
purple: {
100: '#faf5ff',
200: '#e9d8fd',
300: '#d6bcfa',
400: '#b794f4',
500: '#9f7aea',
600: '#805ad5',
700: '#6b46c1',
800: '#553c9a',
900: '#44337a',
},
pink: {
100: '#fff5f7',
200: '#fed7e2',
300: '#fbb6ce',
400: '#f687b3',
500: '#ed64a6',
600: '#d53f8c',
700: '#b83280',
800: '#97266d',
900: '#702459',
},
},
spacing: {
px: '1px',
'0': '0',
'1': '0.25rem',
'2': '0.5rem',
'3': '0.75rem',
'4': '1rem',
'5': '1.25rem',
'6': '1.5rem',
'8': '2rem',
'10': '2.5rem',
'12': '3rem',
'16': '4rem',
'20': '5rem',
'24': '6rem',
'32': '8rem',
'40': '10rem',
'48': '12rem',
'56': '14rem',
'64': '16rem',
},
backgroundColor: theme => theme('colors'),
backgroundPosition: {
bottom: 'bottom',
center: 'center',
left: 'left',
'left-bottom': 'left bottom',
'left-top': 'left top',
right: 'right',
'right-bottom': 'right bottom',
'right-top': 'right top',
top: 'top',
},
backgroundSize: {
auto: 'auto',
cover: 'cover',
contain: 'contain',
},
borderColor: theme => ({
...theme('colors'),
default: theme('colors.gray.300', 'currentColor'),
}),
borderRadius: {
none: '0',
sm: '0.125rem',
default: '0.25rem',
md: '0.375rem',
lg: '0.5rem',
full: '9999px',
},
borderWidth: {
default: '1px',
'0': '0',
'2': '2px',
'4': '4px',
'8': '8px',
},
boxShadow: {
xs: '0 0 0 1px rgba(0, 0, 0, 0.05)',
sm: '0 1px 2px 0 rgba(0, 0, 0, 0.05)',
default: '0 1px 3px 0 rgba(0, 0, 0, 0.1), 0 1px 2px 0 rgba(0, 0, 0, 0.06)',
md: '0 4px 6px -1px rgba(0, 0, 0, 0.1), 0 2px 4px -1px rgba(0, 0, 0, 0.06)',
lg: '0 10px 15px -3px rgba(0, 0, 0, 0.1), 0 4px 6px -2px rgba(0, 0, 0, 0.05)',
xl: '0 20px 25px -5px rgba(0, 0, 0, 0.1), 0 10px 10px -5px rgba(0, 0, 0, 0.04)',
'2xl': '0 25px 50px -12px rgba(0, 0, 0, 0.25)',
inner: 'inset 0 2px 4px 0 rgba(0, 0, 0, 0.06)',
outline: '0 0 0 3px rgba(66, 153, 225, 0.5)',
none: 'none',
},
container: {},
cursor: {
auto: 'auto',
default: 'default',
pointer: 'pointer',
wait: 'wait',
text: 'text',
move: 'move',
'not-allowed': 'not-allowed',
},
fill: {
current: 'currentColor',
},
flex: {
'1': '1 1 0%',
auto: '1 1 auto',
initial: '0 1 auto',
none: 'none',
},
flexGrow: {
'0': '0',
default: '1',
},
flexShrink: {
'0': '0',
default: '1',
},
fontFamily: {
sans: [
'system-ui',
'-apple-system',
'BlinkMacSystemFont',
'"Segoe UI"',
'Roboto',
'"Helvetica Neue"',
'Arial',
'"Noto Sans"',
'sans-serif',
'"Apple Color Emoji"',
'"Segoe UI Emoji"',
'"Segoe UI Symbol"',
'"Noto Color Emoji"',
],
serif: ['Georgia', 'Cambria', '"Times New Roman"', 'Times', 'serif'],
mono: ['Menlo', 'Monaco', 'Consolas', '"Liberation Mono"', '"Courier New"', 'monospace'],
},
fontSize: {
xs: '0.75rem',
sm: '0.875rem',
base: '1rem',
lg: '1.125rem',
xl: '1.25rem',
'2xl': '1.5rem',
'3xl': '1.875rem',
'4xl': '2.25rem',
'5xl': '3rem',
'6xl': '4rem',
},
fontWeight: {
hairline: '100',
thin: '200',
light: '300',
normal: '400',
medium: '500',
semibold: '600',
bold: '700',
extrabold: '800',
black: '900',
},
height: theme => ({
auto: 'auto',
...theme('spacing'),
full: '100%',
screen: '100vh',
}),
inset: {
'0': '0',
auto: 'auto',
},
letterSpacing: {
tighter: '-0.05em',
tight: '-0.025em',
normal: '0',
wide: '0.025em',
wider: '0.05em',
widest: '0.1em',
},
lineHeight: {
none: '1',
tight: '1.25',
snug: '1.375',
normal: '1.5',
relaxed: '1.625',
loose: '2',
'3': '.75rem',
'4': '1rem',
'5': '1.25rem',
'6': '1.5rem',
'7': '1.75rem',
'8': '2rem',
'9': '2.25rem',
'10': '2.5rem',
},
listStyleType: {
none: 'none',
disc: 'disc',
decimal: 'decimal',
},
margin: (theme, { negative }) => ({
auto: 'auto',
...theme('spacing'),
...negative(theme('spacing')),
}),
maxHeight: {
full: '100%',
screen: '100vh',
},
maxWidth: (theme, { breakpoints }) => ({
none: 'none',
xs: '20rem',
sm: '24rem',
md: '28rem',
lg: '32rem',
xl: '36rem',
'2xl': '42rem',
'3xl': '48rem',
'4xl': '56rem',
'5xl': '64rem',
'6xl': '72rem',
full: '100%',
...breakpoints(theme('screens')),
}),
minHeight: {
'0': '0',
full: '100%',
screen: '100vh',
},
minWidth: {
'0': '0',
full: '100%',
},
objectPosition: {
bottom: 'bottom',
center: 'center',
left: 'left',
'left-bottom': 'left bottom',
'left-top': 'left top',
right: 'right',
'right-bottom': 'right bottom',
'right-top': 'right top',
top: 'top',
},
opacity: {
'0': '0',
'25': '0.25',
'50': '0.5',
'75': '0.75',
'100': '1',
},
order: {
first: '-9999',
last: '9999',
none: '0',
'1': '1',
'2': '2',
'3': '3',
'4': '4',
'5': '5',
'6': '6',
'7': '7',
'8': '8',
'9': '9',
'10': '10',
'11': '11',
'12': '12',
},
padding: theme => theme('spacing'),
placeholderColor: theme => theme('colors'),
stroke: {
current: 'currentColor',
},
strokeWidth: {
'0': '0',
'1': '1',
'2': '2',
},
textColor: theme => theme('colors'),
width: theme => ({
auto: 'auto',
...theme('spacing'),
'1/2': '50%',
'1/3': '33.333333%',
'2/3': '66.666667%',
'1/4': '25%',
'2/4': '50%',
'3/4': '75%',
'1/5': '20%',
'2/5': '40%',
'3/5': '60%',
'4/5': '80%',
'1/6': '16.666667%',
'2/6': '33.333333%',
'3/6': '50%',
'4/6': '66.666667%',
'5/6': '83.333333%',
'1/12': '8.333333%',
'2/12': '16.666667%',
'3/12': '25%',
'4/12': '33.333333%',
'5/12': '41.666667%',
'6/12': '50%',
'7/12': '58.333333%',
'8/12': '66.666667%',
'9/12': '75%',
'10/12': '83.333333%',
'11/12': '91.666667%',
full: '100%',
screen: '100vw',
}),
zIndex: {
auto: 'auto',
'0': '0',
'10': '10',
'20': '20',
'30': '30',
'40': '40',
'50': '50',
},
gap: theme => theme('spacing'),
gridTemplateColumns: {
none: 'none',
'1': 'repeat(1, minmax(0, 1fr))',
'2': 'repeat(2, minmax(0, 1fr))',
'3': 'repeat(3, minmax(0, 1fr))',
'4': 'repeat(4, minmax(0, 1fr))',
'5': 'repeat(5, minmax(0, 1fr))',
'6': 'repeat(6, minmax(0, 1fr))',
'7': 'repeat(7, minmax(0, 1fr))',
'8': 'repeat(8, minmax(0, 1fr))',
'9': 'repeat(9, minmax(0, 1fr))',
'10': 'repeat(10, minmax(0, 1fr))',
'11': 'repeat(11, minmax(0, 1fr))',
'12': 'repeat(12, minmax(0, 1fr))',
},
gridColumn: {
auto: 'auto',
'span-1': 'span 1 / span 1',
'span-2': 'span 2 / span 2',
'span-3': 'span 3 / span 3',
'span-4': 'span 4 / span 4',
'span-5': 'span 5 / span 5',
'span-6': 'span 6 / span 6',
'span-7': 'span 7 / span 7',
'span-8': 'span 8 / span 8',
'span-9': 'span 9 / span 9',
'span-10': 'span 10 / span 10',
'span-11': 'span 11 / span 11',
'span-12': 'span 12 / span 12',
},
gridColumnStart: {
auto: 'auto',
'1': '1',
'2': '2',
'3': '3',
'4': '4',
'5': '5',
'6': '6',
'7': '7',
'8': '8',
'9': '9',
'10': '10',
'11': '11',
'12': '12',
'13': '13',
},
gridColumnEnd: {
auto: 'auto',
'1': '1',
'2': '2',
'3': '3',
'4': '4',
'5': '5',
'6': '6',
'7': '7',
'8': '8',
'9': '9',
'10': '10',
'11': '11',
'12': '12',
'13': '13',
},
gridTemplateRows: {
none: 'none',
'1': 'repeat(1, minmax(0, 1fr))',
'2': 'repeat(2, minmax(0, 1fr))',
'3': 'repeat(3, minmax(0, 1fr))',
'4': 'repeat(4, minmax(0, 1fr))',
'5': 'repeat(5, minmax(0, 1fr))',
'6': 'repeat(6, minmax(0, 1fr))',
},
gridRow: {
auto: 'auto',
'span-1': 'span 1 / span 1',
'span-2': 'span 2 / span 2',
'span-3': 'span 3 / span 3',
'span-4': 'span 4 / span 4',
'span-5': 'span 5 / span 5',
'span-6': 'span 6 / span 6',
},
gridRowStart: {
auto: 'auto',
'1': '1',
'2': '2',
'3': '3',
'4': '4',
'5': '5',
'6': '6',
'7': '7',
},
gridRowEnd: {
auto: 'auto',
'1': '1',
'2': '2',
'3': '3',
'4': '4',
'5': '5',
'6': '6',
'7': '7',
},
transformOrigin: {
center: 'center',
top: 'top',
'top-right': 'top right',
right: 'right',
'bottom-right': 'bottom right',
bottom: 'bottom',
'bottom-left': 'bottom left',
left: 'left',
'top-left': 'top left',
},
scale: {
'0': '0',
'50': '.5',
'75': '.75',
'90': '.9',
'95': '.95',
'100': '1',
'105': '1.05',
'110': '1.1',
'125': '1.25',
'150': '1.5',
},
rotate: {
'-180': '-180deg',
'-90': '-90deg',
'-45': '-45deg',
'0': '0',
'45': '45deg',
'90': '90deg',
'180': '180deg',
},
translate: (theme, { negative }) => ({
...theme('spacing'),
...negative(theme('spacing')),
'-full': '-100%',
'-1/2': '-50%',
'1/2': '50%',
full: '100%',
}),
skew: {
'-12': '-12deg',
'-6': '-6deg',
'-3': '-3deg',
'0': '0',
'3': '3deg',
'6': '6deg',
'12': '12deg',
},
transitionProperty: {
none: 'none',
all: 'all',
default: 'background-color, border-color, color, fill, stroke, opacity, box-shadow, transform',
colors: 'background-color, border-color, color, fill, stroke',
opacity: 'opacity',
shadow: 'box-shadow',
transform: 'transform',
},
transitionTimingFunction: {
linear: 'linear',
in: 'cubic-bezier(0.4, 0, 1, 1)',
out: 'cubic-bezier(0, 0, 0.2, 1)',
'in-out': 'cubic-bezier(0.4, 0, 0.2, 1)',
},
transitionDuration: {
'75': '75ms',
'100': '100ms',
'150': '150ms',
'200': '200ms',
'300': '300ms',
'500': '500ms',
'700': '700ms',
'1000': '1000ms',
},
},
variants: {
accessibility: ['responsive', 'focus'],
alignContent: ['responsive'],
alignItems: ['responsive'],
alignSelf: ['responsive'],
appearance: ['responsive'],
backgroundAttachment: ['responsive'],
backgroundColor: ['responsive', 'hover', 'focus'],
backgroundPosition: ['responsive'],
backgroundRepeat: ['responsive'],
backgroundSize: ['responsive'],
borderCollapse: ['responsive'],
borderColor: ['responsive', 'hover', 'focus'],
borderRadius: ['responsive'],
borderStyle: ['responsive'],
borderWidth: ['responsive'],
boxShadow: ['responsive', 'hover', 'focus'],
boxSizing: ['responsive'],
cursor: ['responsive'],
display: ['responsive'],
fill: ['responsive'],
flex: ['responsive'],
flexDirection: ['responsive'],
flexGrow: ['responsive'],
flexShrink: ['responsive'],
flexWrap: ['responsive'],
float: ['responsive'],
clear: ['responsive'],
fontFamily: ['responsive'],
fontSize: ['responsive'],
fontSmoothing: ['responsive'],
fontStyle: ['responsive'],
fontWeight: ['responsive', 'hover', 'focus'],
height: ['responsive'],
inset: ['responsive'],
justifyContent: ['responsive'],
letterSpacing: ['responsive'],
lineHeight: ['responsive'],
listStylePosition: ['responsive'],
listStyleType: ['responsive'],
margin: ['responsive'],
maxHeight: ['responsive'],
maxWidth: ['responsive'],
minHeight: ['responsive'],
minWidth: ['responsive'],
objectFit: ['responsive'],
objectPosition: ['responsive'],
opacity: ['responsive', 'hover', 'focus'],
order: ['responsive'],
outline: ['responsive', 'focus'],
overflow: ['responsive'],
padding: ['responsive'],
placeholderColor: ['responsive', 'focus'],
pointerEvents: ['responsive'],
position: ['responsive'],
resize: ['responsive'],
stroke: ['responsive'],
strokeWidth: ['responsive'],
tableLayout: ['responsive'],
textAlign: ['responsive'],
textColor: ['responsive', 'hover', 'focus'],
textDecoration: ['responsive', 'hover', 'focus'],
textTransform: ['responsive'],
userSelect: ['responsive'],
verticalAlign: ['responsive'],
visibility: ['responsive'],
whitespace: ['responsive'],
width: ['responsive'],
wordBreak: ['responsive'],
zIndex: ['responsive'],
gap: ['responsive'],
gridAutoFlow: ['responsive'],
gridTemplateColumns: ['responsive'],
gridColumn: ['responsive'],
gridColumnStart: ['responsive'],
gridColumnEnd: ['responsive'],
gridTemplateRows: ['responsive'],
gridRow: ['responsive'],
gridRowStart: ['responsive'],
gridRowEnd: ['responsive'],
transform: ['responsive'],
transformOrigin: ['responsive'],
scale: ['responsive', 'hover', 'focus'],
rotate: ['responsive', 'hover', 'focus'],
translate: ['responsive', 'hover', 'focus'],
skew: ['responsive', 'hover', 'focus'],
transitionProperty: ['responsive'],
transitionTimingFunction: ['responsive'],
transitionDuration: ['responsive'],
},
corePlugins: {},
plugins: [],
}

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@react.component
let make = (
~disabled: bool=?,
~ghost: bool=?,
~href: string=?,
~htmlType: @string [#button | #submit | #submit]=?,
~icon: 'a=?,
~shape: @string [#circle | #round]=?,
~size: @string [#small | #large]=?,
~target: string=?,
~loading: bool=?,
~_type: @string
[
| #primary
| #default
| #dashed
| #danger
| #link
| #ghost
]=?,
~onClick: ReactEvent.Mouse.t => unit=?,
~block: bool=?,
~children: React.element=?,
~className: string=?,
~id: string=?,
~testId: string=?,
) =>
ReasonReact.cloneElement(
<AntButton
_type
disabled
ghost
href
htmlType
icon={Antd_Utils.tts(Antd_Icon.iconToJsSafe(~icon, ()))}
shape
size
target
onClick
block
loading
className
id>
children
</AntButton>,
~props={"data-testid": testId},
[],
)

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