Merge branch 'develop' into reducer-dev

This commit is contained in:
Sam Nolan 2022-04-22 11:04:43 -04:00
commit ad8be5273f
26 changed files with 51 additions and 1607 deletions

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@ -6,7 +6,7 @@ import {
errorValueToString,
squiggleExpression,
} from "@quri/squiggle-lang";
import type { samplingParams, exportEnv } from "@quri/squiggle-lang";
import type { samplingParams } from "@quri/squiggle-lang";
import { NumberShower } from "./NumberShower";
import { DistributionChart } from "./DistributionChart";
import { ErrorBox } from "./ErrorBox";
@ -129,9 +129,9 @@ export interface SquiggleChartProps {
/** If the result is a function, how many points along the function it samples */
diagramCount?: number;
/** variables declared before this expression */
environment?: exportEnv;
environment?: unknown;
/** When the environment changes */
onEnvChange?(env: exportEnv): void;
onEnvChange?(env: unknown): void;
/** CSS width of the element */
width?: number;
height?: number;
@ -155,7 +155,7 @@ export const SquiggleChart: React.FC<SquiggleChartProps> = ({
sampleCount: sampleCount,
xyPointLength: outputXYPoints,
};
let expressionResult = run(squiggleString, samplingInputs, environment);
let expressionResult = run(squiggleString, samplingInputs);
let internal: JSX.Element;
if (expressionResult.tag === "Ok") {
onEnvChange(environment);

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@ -2,7 +2,6 @@ import * as React from "react";
import * as ReactDOM from "react-dom";
import { SquiggleChart } from "./SquiggleChart";
import { CodeEditor } from "./CodeEditor";
import type { exportEnv } from "@quri/squiggle-lang";
import styled from "styled-components";
export interface SquiggleEditorProps {
@ -21,9 +20,9 @@ export interface SquiggleEditorProps {
/** If the result is a function, how many points along the function it samples */
diagramCount?: number;
/** The environment, other variables that were already declared */
environment?: exportEnv;
environment?: unknown;
/** when the environment changes. Used again for notebook magic*/
onEnvChange?(env: exportEnv): void;
onEnvChange?(env: unknown): void;
/** The width of the element */
width: number;
}

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@ -20,12 +20,7 @@
],
"suffix": ".bs.js",
"namespace": true,
"bs-dependencies": [
"@glennsl/rescript-jest",
"@glennsl/bs-json",
"rationale",
"bisect_ppx"
],
"bs-dependencies": ["@glennsl/rescript-jest", "rationale", "bisect_ppx"],
"gentypeconfig": {
"language": "typescript",
"module": "commonjs",
@ -37,7 +32,7 @@
},
"refmt": 3,
"warnings": {
"number": "+A-42-48-9-30-4-102-20-27-41"
"number": "+A-42-48-9-30-4"
},
"ppx-flags": [
["../../node_modules/bisect_ppx/ppx", "--exclude-files", ".*_test\\.res$$"]

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@ -31,7 +31,6 @@
"author": "Quantified Uncertainty Research Institute",
"license": "MIT",
"dependencies": {
"@glennsl/bs-json": "^5.0.2",
"bisect_ppx": "^2.7.1",
"jstat": "^1.9.5",
"lodash": "4.17.21",

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@ -1,9 +1,4 @@
import * as _ from "lodash";
import type {
exportEnv,
exportDistribution,
} from "../rescript/ProgramEvaluator.gen";
export type { exportEnv, exportDistribution };
import {
genericDist,
samplingParams,
@ -48,7 +43,6 @@ import {
Constructors_pointwiseLogarithm,
Constructors_pointwisePower,
} from "../rescript/Distributions/DistributionOperation/DistributionOperation.gen";
import { pointSetDistFn } from "../rescript/OldInterpreter/DistPlus.bs";
export type { samplingParams, errorValue };
export let defaultSamplingInputs: samplingParams = {
@ -98,8 +92,7 @@ export type squiggleExpression =
| tagged<"record", { [key: string]: squiggleExpression }>;
export function run(
squiggleString: string,
samplingInputs?: samplingParams,
_environment?: exportEnv
samplingInputs?: samplingParams
): result<squiggleExpression, errorValue> {
let si: samplingParams = samplingInputs
? samplingInputs

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@ -69,7 +69,7 @@ let toPointSet = (
~xyPointLength,
~sampleCount,
~xSelection: GenericDist_Types.Operation.pointsetXSelection=#ByWeight,
unit,
(),
): result<PointSetTypes.pointSetDist, error> => {
switch (t: t) {
| PointSet(pointSet) => Ok(pointSet)
@ -93,7 +93,7 @@ let toPointSet = (
xyPointLength to be a bit longer than the eventual toSparkline downsampling. I chose 3
fairly arbitrarily.
*/
let toSparkline = (t: t, ~sampleCount: int, ~bucketCount: int=20, unit): result<string, error> =>
let toSparkline = (t: t, ~sampleCount: int, ~bucketCount: int=20, ()): result<string, error> =>
t
->toPointSet(~xSelection=#Linear, ~xyPointLength=bucketCount * 3, ~sampleCount, ())
->E.R.bind(r =>
@ -101,10 +101,16 @@ let toSparkline = (t: t, ~sampleCount: int, ~bucketCount: int=20, unit): result<
)
module Truncate = {
let trySymbolicSimplification = (leftCutoff, rightCutoff, t: t): option<t> =>
let trySymbolicSimplification = (
leftCutoff: option<float>,
rightCutoff: option<float>,
t: t,
): option<t> =>
switch (leftCutoff, rightCutoff, t) {
| (None, None, _) => None
| (lc, rc, Symbolic(#Uniform(u))) if lc < rc =>
| (Some(lc), Some(rc), Symbolic(#Uniform(u))) if lc < rc =>
Some(Symbolic(#Uniform(SymbolicDist.Uniform.truncate(Some(lc), Some(rc), u))))
| (lc, rc, Symbolic(#Uniform(u))) =>
Some(Symbolic(#Uniform(SymbolicDist.Uniform.truncate(lc, rc, u))))
| _ => None
}

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@ -87,7 +87,6 @@ let stepwiseToLinear = (t: t): t =>
// 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: PointSetTypes.distributionType=#PDF,
fn: (float, float) => float,
t1: PointSetTypes.continuousShape,
@ -143,14 +142,9 @@ let updateIntegralCache = (integralCache, t: t): t => {...t, integralCache: inte
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,
)
) => continuousShapes |> E.A.fold_left(combinePointwise(~integralSumCachesFn, fn), empty)
let mapY = (~integralSumCacheFn=_ => None, ~integralCacheFn=_ => None, ~fn, t: t) =>
make(

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@ -34,11 +34,6 @@ let lastY = (t: t) => t |> getShape |> XYShape.T.lastY
let combinePointwise = (
~integralSumCachesFn=(_, _) => None,
~integralCachesFn: (
PointSetTypes.continuousShape,
PointSetTypes.continuousShape,
) => option<PointSetTypes.continuousShape>=(_, _) => None,
fn,
t1: PointSetTypes.discreteShape,
t2: PointSetTypes.discreteShape,
): PointSetTypes.discreteShape => {
@ -62,16 +57,8 @@ let combinePointwise = (
)
}
let reduce = (
~integralSumCachesFn=(_, _) => None,
~integralCachesFn=(_, _) => None,
fn,
discreteShapes,
): PointSetTypes.discreteShape =>
discreteShapes |> E.A.fold_left(
combinePointwise(~integralSumCachesFn, ~integralCachesFn, fn),
empty,
)
let reduce = (~integralSumCachesFn=(_, _) => None, discreteShapes): PointSetTypes.discreteShape =>
discreteShapes |> E.A.fold_left(combinePointwise(~integralSumCachesFn), empty)
let updateIntegralSumCache = (integralSumCache, t: t): t => {
...t,

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@ -164,12 +164,7 @@ module T = Dist({
// 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 mapY = (~integralSumCacheFn=_ => None, ~integralCacheFn=_ => None, ~fn, t: t): t => {
let yMappedDiscrete: PointSetTypes.discreteShape =
t.discrete
|> Discrete.T.mapY(~fn)
@ -271,16 +266,13 @@ let combinePointwise = (
t2: t,
): t => {
let reducedDiscrete =
[t1, t2]
|> E.A.fmap(toDiscrete)
|> E.A.O.concatSomes
|> Discrete.reduce(~integralSumCachesFn, ~integralCachesFn, fn)
[t1, t2] |> E.A.fmap(toDiscrete) |> E.A.O.concatSomes |> Discrete.reduce(~integralSumCachesFn)
let reducedContinuous =
[t1, t2]
|> E.A.fmap(toContinuous)
|> E.A.O.concatSomes
|> Continuous.reduce(~integralSumCachesFn, ~integralCachesFn, fn)
|> Continuous.reduce(~integralSumCachesFn, fn)
let combinedIntegralSum = Common.combineIntegralSums(
integralSumCachesFn,

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@ -59,13 +59,9 @@ let combinePointwise = (
) =>
switch (t1, t2) {
| (Continuous(m1), Continuous(m2)) =>
PointSetTypes.Continuous(
Continuous.combinePointwise(~integralSumCachesFn, ~integralCachesFn, fn, m1, m2),
)
PointSetTypes.Continuous(Continuous.combinePointwise(~integralSumCachesFn, fn, m1, m2))
| (Discrete(m1), Discrete(m2)) =>
PointSetTypes.Discrete(
Discrete.combinePointwise(~integralSumCachesFn, ~integralCachesFn, fn, m1, m2),
)
PointSetTypes.Discrete(Discrete.combinePointwise(~integralSumCachesFn, m1, m2))
| (m1, m2) =>
PointSetTypes.Mixed(
Mixed.combinePointwise(~integralSumCachesFn, ~integralCachesFn, fn, toMixed(m1), toMixed(m2)),
@ -134,11 +130,7 @@ module T = Dist({
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,
) =>
let mapY = (~integralSumCacheFn=_ => None, ~integralCacheFn=_ => None, ~fn) =>
fmap((
Mixed.T.mapY(~integralSumCacheFn, ~integralCacheFn, ~fn),
Discrete.T.mapY(~integralSumCacheFn, ~integralCacheFn, ~fn),

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@ -1,24 +0,0 @@
open ASTTypes
let toString = ASTTypes.Node.toString
let envs = (samplingInputs, environment) => {
samplingInputs: samplingInputs,
environment: environment,
evaluateNode: ASTEvaluator.toLeaf,
}
let toLeaf = (samplingInputs, environment, node: node) =>
ASTEvaluator.toLeaf(envs(samplingInputs, environment), node)
let toPointSetDist = (samplingInputs, environment, node: node) =>
switch toLeaf(samplingInputs, environment, node) {
| Ok(#RenderedDist(pointSetDist)) => Ok(pointSetDist)
| Ok(_) => Error("Rendering failed.")
| Error(e) => Error(e)
}
let runFunction = (samplingInputs, environment, inputs, fn: ASTTypes.Function.t) => {
let params = envs(samplingInputs, environment)
ASTTypes.Function.run(params, inputs, fn)
}

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@ -1,257 +0,0 @@
open ASTTypes
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: node, t2: node) =>
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(
Node.ensureIsRenderedAndGetShape(evaluationParams, t1),
Node.ensureIsRenderedAndGetShape(evaluationParams, t2),
) |> E.R.fmap(((a, b)) => #RenderedDist(PointSetDist.combineAlgebraically(algebraicOp, a, b)))
let nodeScore: node => int = x =>
switch x {
| #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(
ASTTypes.SamplingDistribution.renderIfIsNotSamplingDistribution(evaluationParams, t1),
ASTTypes.SamplingDistribution.renderIfIsNotSamplingDistribution(evaluationParams, t2),
) |> E.R.bind(_, ((a, b)) =>
switch choose(a, b) {
| #Sampling =>
ASTTypes.SamplingDistribution.combineShapesUsingSampling(
evaluationParams,
algebraicOp,
a,
b,
)
| #Analytical => combinationByRendering(evaluationParams, algebraicOp, a, b)
}
)
let operationToLeaf = (
evaluationParams: evaluationParams,
algebraicOp: Operation.algebraicOperation,
t1: node,
t2: node,
): result<node, string> =>
algebraicOp
|> tryAnalyticalSimplification(_, t1, t2)
|> E.R.bind(_, x =>
switch x {
| #SymbolicDist(_) as t => Ok(t)
| _ => combine(evaluationParams, algebraicOp, t1, t2)
}
)
}
module PointwiseCombination = {
//TODO: This is crude and slow. It forces everything to be pointSetDist, even though much
//of the process could happen on symbolic distributions without a conversion to be a pointSetDist.
let pointwiseAdd = (evaluationParams: evaluationParams, t1: node, t2: node) =>
switch (Node.render(evaluationParams, t1), Node.render(evaluationParams, t2)) {
| (Ok(#RenderedDist(rs1)), Ok(#RenderedDist(rs2))) =>
Ok(
#RenderedDist(
PointSetDist.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: node, t2: node) =>
switch // TODO: construct a function that we can easily sample from, to construct
// a RenderedDist. Use the xMin and xMax of the rendered pointSetDists to tell the sampling function where to look.
// TODO: This should work for symbolic distributions too!
(Node.render(evaluationParams, t1), Node.render(evaluationParams, t2)) {
| (Ok(#RenderedDist(rs1)), Ok(#RenderedDist(rs2))) =>
Ok(#RenderedDist(PointSetDist.combinePointwise(fn, rs1, rs2)))
| (Error(e1), _) => Error(e1)
| (_, Error(e2)) => Error(e2)
| _ => Error("Pointwise combination: rendering failed.")
}
let operationToLeaf = (
evaluationParams: evaluationParams,
pointwiseOp: Operation.pointwiseOperation,
t1: node,
t2: node,
) =>
switch pointwiseOp {
| #Add => pointwiseAdd(evaluationParams, t1, t2)
| #Multiply => pointwiseCombine(\"*.", evaluationParams, t1, t2)
| #Power => pointwiseCombine(\"**", evaluationParams, t1, t2)
}
}
module Truncate = {
type simplificationResult = [
| #Solution(ASTTypes.node)
| #Error(string)
| #NoSolution
]
let trySimplification = (leftCutoff, rightCutoff, t): simplificationResult =>
switch (leftCutoff, rightCutoff, t) {
| (None, None, t) => #Solution(t)
| (Some(lc), Some(rc), _) if 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) =>
switch // 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
Node.ensureIsRendered(evaluationParams, t) {
| Ok(#RenderedDist(rs)) =>
Ok(#RenderedDist(PointSetDist.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)
|> (
x =>
switch x {
| #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> =>
switch t {
| #RenderedDist(s) => Ok(#RenderedDist(PointSetDist.T.normalize(s)))
| #SymbolicDist(_) => Ok(t)
| _ => ASTTypes.Node.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)) =>
ASTTypes.Function.run(evaluationParams, args, (argNames, fn))
)
let _runWithEvaluatedInputs = (
evaluationParams: ASTTypes.evaluationParams,
name,
args: array<ASTTypes.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<node, string> =>
switch t {
| #Function(_) => Error("Cannot render a function")
| #SymbolicDist(d) =>
Ok(
#RenderedDist(
SymbolicDist.T.toPointSetDist(evaluationParams.samplingInputs.pointSetDistLength, d),
),
)
| #RenderedDist(_) as t => Ok(t) // already a rendered pointSetDist, we're done here
| _ => ASTTypes.Node.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: ASTTypes.evaluationParams, node: node): result<node, 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) =>
ASTTypes.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))
}

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@ -1,233 +0,0 @@
@genType
type rec hash = array<(string, node)>
and node = [
| #SymbolicDist(SymbolicDistTypes.symbolicDist)
| #RenderedDist(PointSetTypes.pointSetDist)
| #Symbol(string)
| #Hash(hash)
| #Array(array<node>)
| #Function(array<string>, node)
| #AlgebraicCombination(Operation.algebraicOperation, node, node)
| #PointwiseCombination(Operation.pointwiseOperation, node, node)
| #Normalize(node)
| #Render(node)
| #Truncate(option<float>, option<float>, node)
| #FunctionCall(string, array<node>)
]
type statement = [
| #Assignment(string, node)
| #Expression(node)
]
type program = array<statement>
type environment = Belt.Map.String.t<node>
type rec evaluationParams = {
samplingInputs: SamplingInputs.samplingInputs,
environment: environment,
evaluateNode: (evaluationParams, node) => Belt.Result.t<node, string>,
}
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"))
}
}
module Node = {
let getFloat = (node: node) =>
node |> (
x =>
switch x {
| #RenderedDist(Discrete({xyShape: {xs: [x], ys: [1.0]}})) => Some(x)
| #SymbolicDist(#Float(x)) => Some(x)
| _ => None
}
)
let evaluate = (evaluationParams: evaluationParams) =>
evaluationParams.evaluateNode(evaluationParams)
let evaluateAndRetry = (evaluationParams, fn, node) =>
node |> evaluationParams.evaluateNode(evaluationParams) |> E.R.bind(_, fn(evaluationParams))
let rec toString: node => string = x =>
switch x {
| #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.Truncate.toString(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(_, ",")) ++
"}")
}
let render = (evaluationParams: evaluationParams, r) => #Render(r) |> evaluate(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 toPointSetDist = (item: node) =>
switch item {
| #RenderedDist(r) => Some(r)
| _ => None
}
let _toFloat = (t: PointSetTypes.pointSetDist) =>
switch t {
| Discrete({xyShape: {xs: [x], ys: [1.0]}}) => Some(#SymbolicDist(#Float(x)))
| _ => None
}
let toFloat = (item: node): result<node, string> =>
item |> toPointSetDist |> E.O.bind(_, _toFloat) |> E.O.toResult("Not valid shape")
}
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: evaluationParams, args: array<node>, t: t) =>
if E.A.length(args) == E.A.length(argumentNames(t)) {
let newEnvironment = Belt.Array.zip(argumentNames(t), args) |> Environment.fromArray
let newEvaluationParams: evaluationParams = {
samplingInputs: evaluationParams.samplingInputs,
environment: Environment.mergeKeepSecond(evaluationParams.environment, newEnvironment),
evaluateNode: evaluationParams.evaluateNode,
}
evaluationParams.evaluateNode(newEvaluationParams, internals(t))
} else {
Error("Wrong number of variables")
}
}
module SamplingDistribution = {
type t = [
| #SymbolicDist(SymbolicDistTypes.symbolicDist)
| #RenderedDist(PointSetTypes.pointSetDist)
]
let isSamplingDistribution: node => bool = x =>
switch x {
| #SymbolicDist(_) => true
| #RenderedDist(_) => true
| _ => false
}
let fromNode: node => result<t, string> = x =>
switch x {
| #SymbolicDist(n) => Ok(#SymbolicDist(n))
| #RenderedDist(n) => Ok(#RenderedDist(n))
| _ => Error("Not valid type")
}
let renderIfIsNotSamplingDistribution = (params, t): result<node, string> =>
!isSamplingDistribution(t)
? switch Node.render(params, t) {
| Ok(r) => Ok(r)
| Error(e) => Error(e)
}
: Ok(t)
let map = (~renderedDistFn, ~symbolicDistFn, node: node) =>
node |> (
x =>
switch x {
| #RenderedDist(r) => Some(renderedDistFn(r))
| #SymbolicDist(s) => Some(symbolicDistFn(s))
| _ => None
}
)
let sampleN = n =>
map(~renderedDistFn=PointSetDist.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,
) |> E.O.toResult("Could not get samples")
let sampleSetDist = samples->E.R.bind(SampleSetDist.make)
let pointSetDist =
sampleSetDist->E.R.bind(r =>
SampleSetDist.toPointSetDist(~samplingInputs=evaluationParams.samplingInputs, ~samples=r)
)
pointSetDist |> E.R.fmap(r => #Normalize(#RenderedDist(r)))
})
}
}

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@ -1,87 +0,0 @@
open PointSetTypes
@genType
type t = PointSetTypes.distPlus
let pointSetDistIntegral = pointSetDist => PointSetDist.T.Integral.get(pointSetDist)
let make = (~pointSetDist, ~squiggleString, ()): t => {
let integral = pointSetDistIntegral(pointSetDist)
{pointSetDist: pointSetDist, integralCache: integral, squiggleString: squiggleString}
}
let update = (~pointSetDist=?, ~integralCache=?, ~squiggleString=?, t: t) => {
pointSetDist: E.O.default(t.pointSetDist, pointSetDist),
integralCache: E.O.default(t.integralCache, integralCache),
squiggleString: E.O.default(t.squiggleString, squiggleString),
}
let updateShape = (pointSetDist, t) => {
let integralCache = pointSetDistIntegral(pointSetDist)
update(~pointSetDist, ~integralCache, t)
}
let toPointSetDist = ({pointSetDist, _}: t) => pointSetDist
let pointSetDistFn = (fn, {pointSetDist}: t) => fn(pointSetDist)
module T = Distributions.Dist({
type t = PointSetTypes.distPlus
type integral = PointSetTypes.distPlus
let toPointSetDist = toPointSetDist
let toContinuous = pointSetDistFn(PointSetDist.T.toContinuous)
let toDiscrete = pointSetDistFn(PointSetDist.T.toDiscrete)
let normalize = (t: t): t => {
let normalizedShape = t |> toPointSetDist |> PointSetDist.T.normalize
t |> updateShape(normalizedShape)
}
let truncate = (leftCutoff, rightCutoff, t: t): t => {
let truncatedShape = t |> toPointSetDist |> PointSetDist.T.truncate(leftCutoff, rightCutoff)
t |> updateShape(truncatedShape)
}
let xToY = (f, t: t) => t |> toPointSetDist |> PointSetDist.T.xToY(f)
let minX = pointSetDistFn(PointSetDist.T.minX)
let maxX = pointSetDistFn(PointSetDist.T.maxX)
let toDiscreteProbabilityMassFraction = pointSetDistFn(
PointSetDist.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<PointSetTypes.continuousShape>, t) =>
update(~integralCache=E.O.default(t.integralCache, integralCache), t)
let downsample = (i, t): t => updateShape(t |> toPointSetDist |> PointSetDist.T.downsample(i), t)
// todo: adjust for limit, maybe?
let mapY = (
~integralSumCacheFn=previousIntegralSum => None,
~integralCacheFn=previousIntegralCache => None,
~fn,
{pointSetDist, _} as t: t,
): t => PointSetDist.T.mapY(~integralSumCacheFn, ~fn, pointSetDist) |> updateShape(_, t)
// get the total of everything
let integralEndY = (t: t) => {
PointSetDist.T.Integral.sum(toPointSetDist(t))
}
// TODO: Fix this below, obviously. Adjust for limits
let integralXtoY = (f, t: t) => {
PointSetDist.T.Integral.xToY(f, toPointSetDist(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) => {
PointSetDist.T.Integral.yToX(f, toPointSetDist(t))
}
let mean = (t: t) => {
PointSetDist.T.mean(t.pointSetDist)
}
let variance = (t: t) => PointSetDist.T.variance(t.pointSetDist)
})

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@ -1,240 +0,0 @@
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) if low <= 0.0 && low < high =>
Ok(#SymbolicDist(SymbolicDist.Normal.from90PercentCI(low, high)))
| (low, high) if 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=x =>
switch x {
| [#Float(a), #Float(b)] => fn(a, b) |> E.R.fmap(r => #SymbolicDist(r))
| e => wrongInputsError(e)
},
(),
)
let makeSymbolicFromOneFloat = (name, fn) =>
Function.T.make(
~name,
~outputType=#SamplingDistribution,
~inputTypes=[#Float],
~run=x =>
switch x {
| [#Float(a)] => fn(a) |> E.R.fmap(r => #SymbolicDist(r))
| e => wrongInputsError(e)
},
(),
)
let makeDistFloat = (name, fn) =>
Function.T.make(
~name,
~outputType=#SamplingDistribution,
~inputTypes=[#SamplingDistribution, #Float],
~run=x =>
switch x {
| [#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=x =>
switch x {
| [#RenderedDist(a), #Float(b)] => fn(a, b)
| e => wrongInputsError(e)
},
(),
)
let makeDist = (name, fn) =>
Function.T.make(
~name,
~outputType=#SamplingDistribution,
~inputTypes=[#SamplingDistribution],
~run=x =>
switch x {
| [#SamplingDist(a)] => fn(a)
| [#RenderedDist(a)] => fn(#RenderedDist(a))
| e => wrongInputsError(e)
},
(),
)
let floatFromDist = (
distToFloatOp: Operation.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) =>
PointSetDist.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(
PointSetDist.T.mapY(
~integralSumCacheFn=integralSumCacheFn(scaleBy),
~integralCacheFn=integralCacheFn(scaleBy),
~fn=fn(scaleBy),
rs,
),
),
)
}
module Multimodal = {
let getByNameResult = 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.bind(((a, b)) =>
E.A.length(b) > E.A.length(a)
? Error("Too many weights provided")
: Ok(
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=x =>
switch x {
| [#Float(a), #Float(b)] => to_(a, b)
| e => wrongInputsError(e)
},
(),
),
Function.T.make(
~name="triangular",
~outputType=#SamplingDistribution,
~inputTypes=[#Float, #Float, #Float],
~run=x =>
switch x {
| [#Float(a), #Float(b), #Float(c)] =>
SymbolicDist.Triangular.make(a, b, c) |> E.R.fmap(r => #SymbolicDist(r))
| e => wrongInputsError(e)
},
(),
),
Function.T.make(
~name="log",
~outputType=#Float,
~inputTypes=[#Float],
~run=x =>
switch x {
| [#Float(a)] => Ok(#SymbolicDist(#Float(Js.Math.log(a))))
| 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=x =>
switch x {
| [#RenderedDist(c)] => Ok(#RenderedDist(c))
| e => wrongInputsError(e)
},
(),
),
Function.T.make(
~name="normalize",
~outputType=#SamplingDistribution,
~inputTypes=[#SamplingDistribution],
~run=x =>
switch x {
| [#SamplingDist(#SymbolicDist(c))] => Ok(#SymbolicDist(c))
| [#SamplingDist(#RenderedDist(c))] => Ok(#RenderedDist(PointSetDist.T.normalize(c)))
| e => wrongInputsError(e)
},
(),
),
makeRenderedDistFloat("scaleExp", (dist, float) => verticalScaling(#Power, dist, float)),
makeRenderedDistFloat("scaleMultiply", (dist, float) => verticalScaling(#Multiply, dist, float)),
makeRenderedDistFloat("scaleLog", (dist, float) => verticalScaling(#Logarithm, dist, float)),
Multimodal._function,
]

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@ -1,196 +0,0 @@
type node = ASTTypes.node
let getFloat = ASTTypes.Node.getFloat
type samplingDist = [
| #SymbolicDist(SymbolicDistTypes.symbolicDist)
| #RenderedDist(PointSetTypes.pointSetDist)
]
type rec hashType = array<(string, _type)>
and _type = [
| #Float
| #SamplingDistribution
| #RenderedDistribution
| #Array(_type)
| #Hash(hashType)
]
type rec hashTypedValue = array<(string, typedValue)>
and typedValue = [
| #Float(float)
| #RenderedDist(PointSetTypes.pointSetDist)
| #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 = x =>
switch x {
| #SamplingDist(_) => "[sampling dist]"
| #RenderedDist(_) => "[rendered PointSetDist]"
| #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: " ++ ASTTypes.Node.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, _) =>
ASTTypes.SamplingDistribution.renderIfIsNotSamplingDistribution(
evaluationParams,
node,
) |> E.R.bind(_, fromNode)
| (#RenderedDistribution, _) =>
ASTTypes.Node.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, 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> = x =>
switch x {
| #Float(x) => Ok(x)
| _ => Error("Not a float")
}
let toArray: typedValue => result<array<'a>, string> = x =>
switch x {
| #Array(x) => Ok(x)
| _ => Error("Not an array")
}
let toNamed: typedValue => result<hashTypedValue, string> = x =>
switch x {
| #Hash(x) => Ok(x)
| _ => Error("Not a named item")
}
let toDist: typedValue => result<node, string> = x =>
switch x {
| #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: name,
inputTypes: inputTypes,
outputType: outputType,
run: run,
shouldCoerceTypes: 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: ASTTypes.evaluationParams,
inputNodes: inputNodes,
t: t,
) =>
_inputLengthCheck(inputNodes, t)->E.R.bind(
_coerceInputNodes(evaluationParams, t.inputTypes, t.shouldCoerceTypes),
)
let run = (evaluationParams: ASTTypes.evaluationParams, inputNodes: inputNodes, t: t) =>
inputsToTypedValues(evaluationParams, inputNodes, t)->E.R.bind(t.run)
|> (
x =>
switch x {
| 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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@ -1,290 +0,0 @@
module MathJsonToMathJsAdt = {
type rec 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) => {
open 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: 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: name,
args: args,
expression: 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 = x =>
switch x {
| 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: 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<ASTTypes.node>) => #FunctionCall("lognormal", args))
}
// Error("Dotwise exponentiation needs two operands")
let operationParser = (name: string, args: result<array<ASTTypes.node>, string>): result<
ASTTypes.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((#Power, 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((#Power, 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<ASTTypes.node, string>,
name: string,
args: array<MathJsonToMathJsAdt.arg>,
): result<ASTTypes.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(_, x =>
switch x {
| 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: ASTTypes.node = #FunctionCall(
"multimodal",
[#Hash([("dists", #Array(dists)), ("weights", #Array([]))])],
)
Ok(hash)
| (Some(Ok(weights)), Ok(dists)) =>
let hash: ASTTypes.node = #FunctionCall(
"multimodal",
[#Hash([("dists", #Array(dists)), ("weights", #Array(weights))])],
)
Ok(hash)
}
| name => parseArgs() |> E.R.fmap((args: array<ASTTypes.node>) => #FunctionCall(name, args))
}
}
let rec nodeParser: MathJsonToMathJsAdt.arg => result<ASTTypes.node, string> = x =>
switch x {
| 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<ASTTypes.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<ASTTypes.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)
value
}
let fromString = str => fromString2(str)

View File

@ -1,185 +0,0 @@
// 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>,
pointDistLength: option<int>,
}
}
let defaultRecommendedLength = 100
let defaultShouldDownsample = true
type inputs = {
squiggleString: string,
samplingInputs: SamplingInputs.t,
environment: ASTTypes.environment,
}
let empty: SamplingInputs.t = {
sampleCount: None,
outputXYPoints: None,
kernelWidth: None,
pointDistLength: None,
}
let make = (
~samplingInputs=empty,
~squiggleString,
~environment=ASTTypes.Environment.empty,
(),
): inputs => {
samplingInputs: samplingInputs,
squiggleString: squiggleString,
environment: environment,
}
}
type exportDistribution = [
| #DistPlus(DistPlus.t)
| #Float(float)
| #Function(float => Belt.Result.t<DistPlus.t, string>)
]
type exportEnv = array<(string, ASTTypes.node)>
type exportType = {
environment: exportEnv,
exports: array<exportDistribution>,
}
module Internals = {
let addVariable = (
{samplingInputs, squiggleString, environment}: Inputs.inputs,
str,
node,
): Inputs.inputs => {
samplingInputs: samplingInputs,
squiggleString: squiggleString,
environment: ASTTypes.Environment.update(environment, str, _ => Some(node)),
}
type outputs = {
graph: ASTTypes.node,
pointSetDist: PointSetTypes.pointSetDist,
}
let makeOutputs = (graph, shape): outputs => {graph: graph, pointSetDist: shape}
let makeInputs = (inputs: Inputs.inputs): SamplingInputs.samplingInputs => {
sampleCount: inputs.samplingInputs.sampleCount |> E.O.default(10000),
outputXYPoints: inputs.samplingInputs.outputXYPoints |> E.O.default(10000),
kernelWidth: inputs.samplingInputs.kernelWidth,
pointSetDistLength: inputs.samplingInputs.pointDistLength |> E.O.default(10000),
}
let runNode = (inputs, node) => AST.toLeaf(makeInputs(inputs), inputs.environment, node)
let renderIfNeeded = (inputs: Inputs.inputs, node: ASTTypes.node): result<
ASTTypes.node,
string,
> =>
node |> (
x =>
switch x {
| #Normalize(_) as n
| #SymbolicDist(_) as n =>
#Render(n)
|> runNode(inputs)
|> (
x =>
switch x {
| Ok(#RenderedDist(_)) as r => r
| Error(r) => Error(r)
| _ => Error("Didn't render, but intended to")
}
)
| n => Ok(n)
}
)
let outputToDistPlus = (inputs: Inputs.inputs, pointSetDist: PointSetTypes.pointSetDist) =>
DistPlus.make(~pointSetDist, ~squiggleString=Some(inputs.squiggleString), ())
let rec returnDist = (
functionInfo: (array<string>, ASTTypes.node),
inputs: Inputs.inputs,
env: ASTTypes.environment,
) => {
(input: float) => {
let foo: Inputs.inputs = {...inputs, environment: env}
evaluateFunction(foo, functionInfo, [#SymbolicDist(#Float(input))]) |> E.R.bind(_, a =>
switch a {
| #DistPlus(d) => Ok(DistPlus.T.normalize(d))
| n =>
Js.log2("Error here", n)
Error("wrong type")
}
)
}
}
// TODO: Consider using ExpressionTypes.ExpressionTree.getFloat or similar in this function
and coersionToExportedTypes = (inputs, env: ASTTypes.environment, ex: ASTTypes.node): result<
exportDistribution,
string,
> =>
ex
|> 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(outputToDistPlus(inputs, n)))
| #Function(n) => Ok(#Function(returnDist(n, inputs, env)))
| n => Error("Didn't output a rendered distribution. Format:" ++ AST.toString(n))
}
)
and evaluateFunction = (inputs: Inputs.inputs, fn: (array<string>, ASTTypes.node), fnInputs) => {
let output = AST.runFunction(makeInputs(inputs), inputs.environment, fnInputs, fn)
output |> E.R.bind(_, coersionToExportedTypes(inputs, inputs.environment))
}
let runProgram = (inputs: Inputs.inputs, p: ASTTypes.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.A.O.concatSomes
|> E.A.R.firstErrorOrOpen
|> E.R.bind(_, d =>
d
|> E.A.fmap(x => coersionToExportedTypes(inputs, ins.contents.environment, x))
|> E.A.R.firstErrorOrOpen
)
|> E.R.fmap(ex => {
environment: Belt.Map.String.toArray(ins.contents.environment),
exports: ex,
})
}
let inputsToLeaf = (inputs: Inputs.inputs) =>
Parser.fromString(inputs.squiggleString) |> E.R.bind(_, g => runProgram(inputs, g))
}
@genType
let runAll: (string, Inputs.SamplingInputs.t, exportEnv) => result<exportType, string> = (
squiggleString,
samplingInputs,
environment,
) => {
let inputs = Inputs.make(
~samplingInputs,
~squiggleString,
~environment=Belt.Map.String.fromArray(environment),
(),
)
Internals.inputsToLeaf(inputs)
}

View File

@ -72,7 +72,7 @@ let dispatchMacroCall = (
let doExportVariableExpression = (bindings: ExpressionT.bindings) => {
let emptyDictionary: Js.Dict.t<ExpressionValue.expressionValue> = Js.Dict.empty()
let reducedBindings = bindings->Belt.Map.String.keep((key, value) =>
let reducedBindings = bindings->Belt.Map.String.keep((_key, value) =>
switch value {
| ExpressionT.EValue(_) => true
| _ => false

View File

@ -15,7 +15,7 @@ type t = expression
*/
let rec toString = expression =>
switch expression {
| T.EBindings(bindings) => "$$bound"
| T.EBindings(_) => "$$bound"
| T.EList(aList) =>
`(${Belt.List.map(aList, aValue => toString(aValue))
->Extra.List.interperse(" ")

View File

@ -12,7 +12,7 @@ type answer = {"value": unit}
Rescript cannot type cast on basic values passed on their own.
This is why we call evalua inside Javascript and wrap the result in an Object
*/
let eval__ = %raw(`function (expr) { return {value: Mathjs.evaluate(expr)}; }`)
let eval__: string => 'a = %raw(`function (expr) { return {value: Mathjs.evaluate(expr)}; }`)
/*
Call MathJs evaluate and return as a variant

View File

@ -126,7 +126,7 @@ module Helpers = {
| Error(err) => GenDistError(ArgumentError(err))
}
}
| Some(EvDistribution(b)) =>
| Some(EvDistribution(_)) =>
switch parseDistributionArray(args) {
| Ok(distributions) => mixtureWithDefaultWeights(distributions)
| Error(err) => GenDistError(ArgumentError(err))
@ -226,7 +226,7 @@ let dispatchToGenericOutput = (call: ExpressionValue.functionCall): option<
Helpers.twoDiststoDistFn(Algebraic, "log", a, GenericDist.fromFloat(10.0))->Some
| ("unaryMinus", [EvDistribution(a)]) =>
Helpers.twoDiststoDistFn(Algebraic, "multiply", a, GenericDist.fromFloat(-1.0))->Some
| (("add" | "multiply" | "subtract" | "divide" | "pow" | "log") as arithmetic, [a, b] as args) =>
| (("add" | "multiply" | "subtract" | "divide" | "pow" | "log") as arithmetic, [_, _] as args) =>
Helpers.catchAndConvertTwoArgsToDists(args)->E.O2.fmap(((fst, snd)) =>
Helpers.twoDiststoDistFn(Algebraic, arithmetic, fst, snd)
)
@ -237,7 +237,7 @@ let dispatchToGenericOutput = (call: ExpressionValue.functionCall): option<
| "dotDivide"
| "dotPow"
| "dotLog") as arithmetic,
[a, b] as args,
[_, _] as args,
) =>
Helpers.catchAndConvertTwoArgsToDists(args)->E.O2.fmap(((fst, snd)) =>
Helpers.twoDiststoDistFn(Pointwise, arithmetic, fst, snd)

View File

@ -28,7 +28,7 @@ module Int = {
}
/* Utils */
module U = {
let isEqual = (a, b) => a == b
let isEqual = \"=="
let toA = a => [a]
let id = e => e
}
@ -340,8 +340,6 @@ module A = {
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 {
@ -448,8 +446,11 @@ module A = {
| (Some(min), Some(max)) => Some(max -. min)
| _ => None
}
let floatCompare: (float, float) => int = compare
let binarySearchFirstElementGreaterIndex = (ar: array<'a>, el: 'a) => {
let el = Belt.SortArray.binarySearchBy(ar, el, compare)
let el = Belt.SortArray.binarySearchBy(ar, el, floatCompare)
let el = el < 0 ? el * -1 - 1 : el
switch el {
| e if e >= length(ar) => #overMax
@ -460,13 +461,13 @@ module A = {
let concat = (t1: array<'a>, t2: array<'a>) => {
let ts = Belt.Array.concat(t1, t2)
ts |> Array.fast_sort(compare)
ts |> Array.fast_sort(floatCompare)
ts
}
let concatMany = (t1: array<array<'a>>) => {
let ts = Belt.Array.concatMany(t1)
ts |> Array.fast_sort(compare)
ts |> Array.fast_sort(floatCompare)
ts
}
@ -525,6 +526,9 @@ module A = {
let diff = (max -. min) /. Belt.Float.fromInt(n - 1)
Belt.Array.makeBy(n, i => min +. Belt.Float.fromInt(i) *. diff)
}
let min = Js.Math.minMany_float
let max = Js.Math.maxMany_float
}
}

View File

@ -16,7 +16,7 @@ let create = (relativeHeights: array<float>, ~maximum=?, ()) => {
if E.A.length(relativeHeights) === 0 {
""
} else {
let maximum = maximum->E.O2.default(E.A.max(relativeHeights)->E.O2.toExn(""))
let maximum = maximum->E.O2.default(E.A.Floats.max(relativeHeights))
relativeHeights
->E.A2.fmap(_heightToTickIndex(maximum))

View File

@ -60,8 +60,8 @@ module T = {
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 minX = (t: t) => t |> E.A.fmap(T.minX) |> E.A.Floats.min
let maxX = (t: t) => t |> E.A.fmap(T.maxX) |> E.A.Floats.max
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
}
@ -199,7 +199,7 @@ module XtoY = {
/* 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
let discreteInterpolator: interpolator = (_: T.t, _: int, _: float) => 0.0
}
module XsConversion = {
@ -220,8 +220,8 @@ module XsConversion = {
module Zipped = {
type zipped = array<(float, float)>
let compareYs = ((_, y1), (_, y2)) => y1 > y2 ? 1 : 0
let compareXs = ((x1, _), (x2, _)) => x1 > x2 ? 1 : 0
let compareYs = ((_, y1): (float, float), (_, y2): (float, float)) => y1 > y2 ? 1 : 0
let compareXs = ((x1, _): (float, float), (x2, _): (float, float)) => 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))
@ -229,7 +229,7 @@ module Zipped = {
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
let combine: ((float, float) => float, interpolator, T.t, T.t) => T.t = %raw(`
// 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.

View File

@ -1928,11 +1928,6 @@
resolved "https://registry.yarnpkg.com/@gar/promisify/-/promisify-1.1.3.tgz#555193ab2e3bb3b6adc3d551c9c030d9e860daf6"
integrity sha512-k2Ty1JcVojjJFwrg/ThKi2ujJ7XNLYaFGNB/bWT9wGR+oSMJHMa5w+CUq6p/pVrKeNNgA7pCqEcjSnHVoqJQFw==
"@glennsl/bs-json@^5.0.2":
version "5.0.4"
resolved "https://registry.yarnpkg.com/@glennsl/bs-json/-/bs-json-5.0.4.tgz#8a80906f3b5e04d78dc06722e5987ff6499c89a8"
integrity sha512-Th9DetZjRlMZrb74kgGJ44oWcoFyOTE884WlSuXft0Cd+J09vHRxiB7eVyK7Gthb4cSevsBBJDHYAbGGL25wPw==
"@glennsl/rescript-jest@^0.9.0":
version "0.9.1"
resolved "https://registry.yarnpkg.com/@glennsl/rescript-jest/-/rescript-jest-0.9.1.tgz#a85a6f0e4c3b79010b5a917c3652aa70d374e4d1"