Merge pull request #20 from QURIresearch/Refactor-Feb-2022

Refactor feb 2022
This commit is contained in:
Ozzie Gooen 2022-02-17 22:26:52 -05:00 committed by GitHub
commit c0c6a45dc7
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
22 changed files with 348 additions and 416 deletions

View File

@ -38,7 +38,7 @@ describe("Lodash", () =>
let toArr = discrete |> E.FloatFloatMap.toArray
makeTest("splitMedium", toArr |> Belt.Array.length, 10)
let (c, discrete) = SampleSet.Internals.T.splitContinuousAndDiscrete(
let (_c, discrete) = SampleSet.Internals.T.splitContinuousAndDiscrete(
makeDuplicatedArray(500),
)
let toArr = discrete |> E.FloatFloatMap.toArray

View File

@ -4,9 +4,9 @@
"homepage": "https://foretold-app.github.io/estiband/",
"private": false,
"scripts": {
"build": "rescript build",
"build": "rescript build -with-deps",
"parcel": "parcel build ./src/js/index.js --no-source-maps --no-autoinstall",
"start": "rescript build -w",
"start": "rescript build -w -with-deps",
"clean": "rescript clean",
"test": "jest",
"test:ci": "yarn jest ./__tests__/Lodash__test.re",

View File

@ -14,7 +14,7 @@ module Inputs = {
type inputs = {
squiggleString: string,
samplingInputs: SamplingInputs.t,
environment: ASTTypes.AST.environment,
environment: ASTTypes.environment,
}
let empty: SamplingInputs.t = {
@ -27,7 +27,7 @@ module Inputs = {
let make = (
~samplingInputs=empty,
~squiggleString,
~environment=ASTTypes.AST.Environment.empty,
~environment=ASTTypes.Environment.empty,
(),
): inputs => {
samplingInputs: samplingInputs,
@ -36,12 +36,12 @@ module Inputs = {
}
}
type \"export" = [
type exported = [
| #DistPlus(DistPlus.t)
| #Float(float)
| #Function(
(array<string>, ASTTypes.AST.node),
ASTTypes.AST.environment,
(array<string>, ASTTypes.node),
ASTTypes.environment,
)
]
@ -53,18 +53,18 @@ module Internals = {
): Inputs.inputs => {
samplingInputs: samplingInputs,
squiggleString: squiggleString,
environment: ASTTypes.AST.Environment.update(environment, str, _ => Some(
environment: ASTTypes.Environment.update(environment, str, _ => Some(
node,
)),
}
type outputs = {
graph: ASTTypes.AST.node,
graph: ASTTypes.node,
pointSetDist: PointSetTypes.pointSetDist,
}
let makeOutputs = (graph, pointSetDist): outputs => {graph: graph, pointSetDist: pointSetDist}
let makeInputs = (inputs: Inputs.inputs): ASTTypes.AST.samplingInputs => {
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,
@ -74,7 +74,7 @@ module Internals = {
let runNode = (inputs, node) =>
AST.toLeaf(makeInputs(inputs), inputs.environment, node)
let runProgram = (inputs: Inputs.inputs, p: ASTTypes.Program.program) => {
let runProgram = (inputs: Inputs.inputs, p: ASTTypes.program) => {
let ins = ref(inputs)
p
|> E.A.fmap(x =>
@ -97,8 +97,8 @@ module Internals = {
DistPlus.make(~pointSetDist, ~squiggleString=Some(inputs.squiggleString), ())
}
let renderIfNeeded = (inputs: Inputs.inputs, node: ASTTypes.AST.node): result<
ASTTypes.AST.node,
let renderIfNeeded = (inputs: Inputs.inputs, node: ASTTypes.node): result<
ASTTypes.node,
string,
> =>
node |> (
@ -121,12 +121,12 @@ let renderIfNeeded = (inputs: Inputs.inputs, node: ASTTypes.AST.node): result<
}
)
// TODO: Consider using ASTTypes.AST.getFloat or similar in this function
// TODO: Consider using ASTTypes.getFloat or similar in this function
let coersionToExportedTypes = (
inputs,
env: ASTTypes.AST.environment,
node: ASTTypes.AST.node,
): result<\"export", string> =>
env: ASTTypes.environment,
node: ASTTypes.node,
): result<exported, string> =>
node
|> renderIfNeeded(inputs)
|> E.R.bind(_, x =>
@ -160,7 +160,7 @@ let evaluateProgram = (inputs: Inputs.inputs) =>
let evaluateFunction = (
inputs: Inputs.inputs,
fn: (array<string>, ASTTypes.AST.node),
fn: (array<string>, ASTTypes.node),
fnInputs,
) => {
let output = AST.runFunction(

View File

@ -1,6 +1,6 @@
open ASTTypes.AST
open ASTTypes
let toString = ASTBasic.toString
let toString = ASTTypes.Node.toString
let envs = (samplingInputs, environment) => {
samplingInputs: samplingInputs,
@ -18,7 +18,7 @@ let toPointSetDist = (samplingInputs, environment, node: node) =>
| Error(e) => Error(e)
}
let runFunction = (samplingInputs, environment, inputs, fn: PTypes.Function.t) => {
let runFunction = (samplingInputs, environment, inputs, fn: ASTTypes.Function.t) => {
let params = envs(samplingInputs, environment)
PTypes.Function.run(params, inputs, fn)
ASTTypes.Function.run(params, inputs, fn)
}

View File

@ -1,27 +0,0 @@
open ASTTypes.AST
// This file exists to manage a dependency cycle. It would be good to refactor later.
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.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(_, ",")) ++
"}")
}

View File

@ -1,5 +1,4 @@
open ASTTypes
open ASTTypes.AST
type t = node
type tResult = node => result<node, string>
@ -25,8 +24,8 @@ module AlgebraicCombination = {
string,
> =>
E.R.merge(
Render.ensureIsRenderedAndGetShape(evaluationParams, t1),
Render.ensureIsRenderedAndGetShape(evaluationParams, t2),
Node.ensureIsRenderedAndGetShape(evaluationParams, t1),
Node.ensureIsRenderedAndGetShape(evaluationParams, t2),
) |> E.R.fmap(((a, b)) => #RenderedDist(PointSetDist.combineAlgebraically(algebraicOp, a, b)))
let nodeScore: node => int = x =>
@ -44,19 +43,24 @@ module AlgebraicCombination = {
let combine = (evaluationParams, algebraicOp, t1: node, t2: node): result<node, string> =>
E.R.merge(
PTypes.SamplingDistribution.renderIfIsNotSamplingDistribution(evaluationParams, t1),
PTypes.SamplingDistribution.renderIfIsNotSamplingDistribution(evaluationParams, t2),
ASTTypes.SamplingDistribution.renderIfIsNotSamplingDistribution(evaluationParams, t1),
ASTTypes.SamplingDistribution.renderIfIsNotSamplingDistribution(evaluationParams, t2),
) |> E.R.bind(_, ((a, b)) =>
switch choose(a, b) {
| #Sampling =>
PTypes.SamplingDistribution.combineShapesUsingSampling(evaluationParams, algebraicOp, a, b)
ASTTypes.SamplingDistribution.combineShapesUsingSampling(
evaluationParams,
algebraicOp,
a,
b,
)
| #Analytical => combinationByRendering(evaluationParams, algebraicOp, a, b)
}
)
let operationToLeaf = (
evaluationParams: evaluationParams,
algebraicOp: ASTTypes.algebraicOperation,
algebraicOp: Operation.algebraicOperation,
t1: t,
t2: t,
): result<node, string> =>
@ -71,8 +75,10 @@ module AlgebraicCombination = {
}
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: t, t2: t) =>
switch (Render.render(evaluationParams, t1), Render.render(evaluationParams, t2)) {
switch (Node.render(evaluationParams, t1), Node.render(evaluationParams, t2)) {
| (Ok(#RenderedDist(rs1)), Ok(#RenderedDist(rs2))) =>
Ok(
#RenderedDist(
@ -96,7 +102,7 @@ module PointwiseCombination = {
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!
(Render.render(evaluationParams, t1), Render.render(evaluationParams, t2)) {
(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)
@ -106,7 +112,7 @@ module PointwiseCombination = {
let operationToLeaf = (
evaluationParams: evaluationParams,
pointwiseOp: pointwiseOperation,
pointwiseOp: Operation.pointwiseOperation,
t1: t,
t2: t,
) =>
@ -118,6 +124,12 @@ module PointwiseCombination = {
}
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)
@ -131,8 +143,9 @@ module Truncate = {
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
Render.ensureIsRendered(evaluationParams, t) {
| Ok(#RenderedDist(rs)) => Ok(#RenderedDist(PointSetDist.T.truncate(leftCutoff, rightCutoff, rs)))
Node.ensureIsRendered(evaluationParams, t) {
| Ok(#RenderedDist(rs)) =>
Ok(#RenderedDist(PointSetDist.T.truncate(leftCutoff, rightCutoff, rs)))
| Error(e) => Error(e)
| _ => Error("Could not truncate distribution.")
}
@ -160,7 +173,7 @@ module Normalize = {
switch t {
| #RenderedDist(s) => Ok(#RenderedDist(PointSetDist.T.normalize(s)))
| #SymbolicDist(_) => Ok(t)
| _ => evaluateAndRetry(evaluationParams, operationToLeaf, t)
| _ => ASTTypes.Node.evaluateAndRetry(evaluationParams, operationToLeaf, t)
}
}
@ -170,13 +183,13 @@ module FunctionCall = {
let _runLocalFunction = (name, evaluationParams: evaluationParams, args) =>
Environment.getFunction(evaluationParams.environment, name) |> E.R.bind(_, ((argNames, fn)) =>
PTypes.Function.run(evaluationParams, args, (argNames, fn))
ASTTypes.Function.run(evaluationParams, args, (argNames, fn))
)
let _runWithEvaluatedInputs = (
evaluationParams: ASTTypes.AST.evaluationParams,
evaluationParams: ASTTypes.evaluationParams,
name,
args: array<ASTTypes.AST.node>,
args: array<ASTTypes.node>,
) =>
_runHardcodedFunction(name, evaluationParams, args) |> E.O.default(
_runLocalFunction(name, evaluationParams, args),
@ -195,9 +208,13 @@ module Render = {
switch t {
| #Function(_) => Error("Cannot render a function")
| #SymbolicDist(d) =>
Ok(#RenderedDist(SymbolicDist.T.toPointSetDist(evaluationParams.samplingInputs.pointSetDistLength, d)))
Ok(
#RenderedDist(
SymbolicDist.T.toPointSetDist(evaluationParams.samplingInputs.pointSetDistLength, d),
),
)
| #RenderedDist(_) as t => Ok(t) // already a rendered pointSetDist, we're done here
| _ => evaluateAndRetry(evaluationParams, operationToLeaf, t)
| _ => ASTTypes.Node.evaluateAndRetry(evaluationParams, operationToLeaf, t)
}
}
@ -207,10 +224,7 @@ module Render = {
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.AST.evaluationParams,
node: t,
): result<t, string> =>
let rec toLeaf = (evaluationParams: ASTTypes.evaluationParams, node: t): result<t, string> =>
switch node {
// Leaf nodes just stay leaf nodes
| #SymbolicDist(_)
@ -236,7 +250,7 @@ let rec toLeaf = (
|> E.A.R.firstErrorOrOpen
|> E.R.fmap(r => #Hash(r))
| #Symbol(r) =>
ASTTypes.AST.Environment.get(evaluationParams.environment, r)
ASTTypes.Environment.get(evaluationParams.environment, r)
|> E.O.toResult("Undeclared variable " ++ r)
|> E.R.bind(_, toLeaf(evaluationParams))
| #FunctionCall(name, args) =>

View File

@ -1,21 +1,3 @@
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 AST = {
type rec hash = array<(string, node)>
and node = [
| #SymbolicDist(SymbolicDistTypes.symbolicDist)
@ -24,66 +6,28 @@ module AST = {
| #Hash(hash)
| #Array(array<node>)
| #Function(array<string>, node)
| #AlgebraicCombination(algebraicOperation, node, node)
| #PointwiseCombination(pointwiseOperation, node, 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>)
]
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 |> (
x =>
switch x {
| #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>,
pointSetDistLength: int,
}
module SamplingInputs = {
type t = {
sampleCount: option<int>,
outputXYPoints: option<int>,
kernelWidth: option<float>,
pointSetDistLength: option<int>,
}
let withDefaults = (t: t): samplingInputs => {
sampleCount: t.sampleCount |> E.O.default(10000),
outputXYPoints: t.outputXYPoints |> E.O.default(10000),
kernelWidth: t.kernelWidth,
pointSetDistLength: t.pointSetDistLength |> E.O.default(10000),
}
}
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
@ -106,23 +50,51 @@ module AST = {
}
}
type rec evaluationParams = {
samplingInputs: samplingInputs,
environment: environment,
evaluateNode: (evaluationParams, node) => Belt.Result.t<node, string>,
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 evaluateNode = (evaluationParams: evaluationParams) =>
let evaluate = (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 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) |> evaluateNode(evaluationParams)
let render = (evaluationParams: evaluationParams, r) => #Render(r) |> evaluate(evaluationParams)
let ensureIsRendered = (params, t) =>
switch t {
@ -142,7 +114,7 @@ module AST = {
| Error(e) => Error(e)
}
let getShape = (item: node) =>
let toPointSetDist = (item: node) =>
switch item {
| #RenderedDist(r) => Some(r)
| _ => None
@ -155,20 +127,106 @@ module AST = {
}
let toFloat = (item: node): result<node, string> =>
item |> getShape |> E.O.bind(_, _toFloat) |> E.O.toResult("Not valid shape")
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")
}
}
type simplificationResult = [
| #Solution(AST.node)
| #Error(string)
| #NoSolution
module SamplingDistribution = {
type t = [
| #SymbolicDist(SymbolicDistTypes.symbolicDist)
| #RenderedDist(PointSetTypes.pointSetDist)
]
module Program = {
type statement = [
| #Assignment(string, AST.node)
| #Expression(AST.node)
]
type program = array<statement>
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,
)
let pointSetDist =
samples
|> E.O.fmap(r =>
SampleSet.toPointSetDist(~samplingInputs=evaluationParams.samplingInputs, ~samples=r, ())
)
|> E.O.bind(_, r => r.pointSetDist)
|> E.O.toResult("No response")
pointSetDist |> E.R.fmap(r => #Normalize(#RenderedDist(r)))
})
}
}

View File

@ -1,138 +0,0 @@
open ASTTypes.AST
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: ASTTypes.AST.evaluationParams,
args: array<node>,
t: t,
) =>
if E.A.length(args) == E.A.length(argumentNames(t)) {
let newEnvironment =
Belt.Array.zip(
argumentNames(t),
args,
) |> ASTTypes.AST.Environment.fromArray
let newEvaluationParams: ASTTypes.AST.evaluationParams = {
samplingInputs: evaluationParams.samplingInputs,
environment: ASTTypes.AST.Environment.mergeKeepSecond(
evaluationParams.environment,
newEnvironment,
),
evaluateNode: evaluationParams.evaluateNode,
}
evaluationParams.evaluateNode(newEvaluationParams, internals(t))
} else {
Error("Wrong number of variables")
}
}
module Primative = {
type t = [
| #SymbolicDist(SymbolicDistTypes.symbolicDist)
| #RenderedDist(PointSetTypes.pointSetDist)
| #Function(array<string>, node)
]
let isPrimative: node => bool = x =>
switch x {
| #SymbolicDist(_)
| #RenderedDist(_)
| #Function(_) => true
| _ => false
}
let fromNode: node => option<t> = x =>
switch x {
| #SymbolicDist(_) as n
| #RenderedDist(_) as n
| #Function(_) as n =>
Some(n)
| _ => None
}
}
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 Render.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,
)
// todo: This bottom part should probably be somewhere else.
// todo: REFACTOR: I'm not sure about the SampleSet line.
let pointSetDist =
samples
|> E.O.fmap(r => SampleSet.toPointSetDist(~samplingInputs=evaluationParams.samplingInputs, ~samples=r, ()))
|> E.O.bind(_, r => r.pointSetDist)
|> E.O.toResult("No response")
pointSetDist |> E.R.fmap(r => #Normalize(#RenderedDist(r)))
})
}
}

View File

@ -84,7 +84,7 @@ let makeDist = (name, fn) =>
)
let floatFromDist = (
distToFloatOp: ASTTypes.distToFloatOperation,
distToFloatOp: Operation.distToFloatOperation,
t: TypeSystem.samplingDist,
): result<node, string> =>
switch t {
@ -111,7 +111,7 @@ let verticalScaling = (scaleOp, rs, scaleBy) => {
}
module Multimodal = {
let getByNameResult = ASTTypes.AST.Hash.getByNameResult
let getByNameResult = Hash.getByNameResult
let _paramsToDistsAndWeights = (r: array<typedValue>) =>
switch r {

View File

@ -1,5 +1,5 @@
type node = ASTTypes.AST.node
let getFloat = ASTTypes.AST.getFloat
type node = ASTTypes.node
let getFloat = ASTTypes.Node.getFloat
type samplingDist = [
| #SymbolicDist(SymbolicDistTypes.symbolicDist)
@ -61,7 +61,7 @@ module TypedValue = {
|> 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: " ++ ASTBasic.toString(e))
| e => Error("Wrong type: " ++ ASTTypes.Node.toString(e))
}
// todo: Arrays and hashes
@ -73,12 +73,12 @@ module TypedValue = {
| _ => Error("Type Error: Expected float.")
}
| (#SamplingDistribution, _) =>
PTypes.SamplingDistribution.renderIfIsNotSamplingDistribution(
ASTTypes.SamplingDistribution.renderIfIsNotSamplingDistribution(
evaluationParams,
node,
) |> E.R.bind(_, fromNode)
| (#RenderedDistribution, _) =>
ASTTypes.AST.Render.render(evaluationParams, node) |> E.R.bind(_, fromNode)
ASTTypes.Node.render(evaluationParams, node) |> E.R.bind(_, fromNode)
| (#Array(_type), #Array(b)) =>
b
|> E.A.fmap(fromNodeWithTypeCoercion(evaluationParams, _type))
@ -89,7 +89,7 @@ module TypedValue = {
named |> E.A.fmap(((name, intendedType)) => (
name,
intendedType,
ASTTypes.AST.Hash.getByName(r, name),
Hash.getByName(r, name),
))
let typedHash =
keyValues
@ -172,7 +172,7 @@ module Function = {
|> E.A.R.firstErrorOrOpen
let inputsToTypedValues = (
evaluationParams: ASTTypes.AST.evaluationParams,
evaluationParams: ASTTypes.evaluationParams,
inputNodes: inputNodes,
t: t,
) =>
@ -181,7 +181,7 @@ module Function = {
)
let run = (
evaluationParams: ASTTypes.AST.evaluationParams,
evaluationParams: ASTTypes.evaluationParams,
inputNodes: inputNodes,
t: t,
) =>

View File

@ -122,7 +122,7 @@ module MathAdtToDistDst = {
| _ => Error("Lognormal distribution needs either mean and stdev or mu and sigma")
}
| _ =>
parseArgs() |> E.R.fmap((args: array<ASTTypes.AST.node>) =>
parseArgs() |> E.R.fmap((args: array<ASTTypes.node>) =>
#FunctionCall("lognormal", args)
)
}
@ -130,8 +130,8 @@ module MathAdtToDistDst = {
// Error("Dotwise exponentiation needs two operands")
let operationParser = (
name: string,
args: result<array<ASTTypes.AST.node>, string>,
): result<ASTTypes.AST.node, 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))
@ -170,12 +170,12 @@ module MathAdtToDistDst = {
let functionParser = (
nodeParser: MathJsonToMathJsAdt.arg => Belt.Result.t<
ASTTypes.AST.node,
ASTTypes.node,
string,
>,
name: string,
args: array<MathJsonToMathJsAdt.arg>,
): result<ASTTypes.AST.node, string> => {
): result<ASTTypes.node, string> => {
let parseArray = ags => ags |> E.A.fmap(nodeParser) |> E.A.R.firstErrorOrOpen
let parseArgs = () => parseArray(args)
switch name {
@ -212,27 +212,27 @@ module MathAdtToDistDst = {
| (Some(Error(r)), _) => Error(r)
| (_, Error(r)) => Error(r)
| (None, Ok(dists)) =>
let hash: ASTTypes.AST.node = #FunctionCall(
let hash: ASTTypes.node = #FunctionCall(
"multimodal",
[#Hash([("dists", #Array(dists)), ("weights", #Array([]))])],
)
Ok(hash)
| (Some(Ok(weights)), Ok(dists)) =>
let hash: ASTTypes.AST.node = #FunctionCall(
let hash: ASTTypes.node = #FunctionCall(
"multimodal",
[#Hash([("dists", #Array(dists)), ("weights", #Array(weights))])],
)
Ok(hash)
}
| name =>
parseArgs() |> E.R.fmap((args: array<ASTTypes.AST.node>) =>
parseArgs() |> E.R.fmap((args: array<ASTTypes.node>) =>
#FunctionCall(name, args)
)
}
}
let rec nodeParser: MathJsonToMathJsAdt.arg => result<
ASTTypes.AST.node,
ASTTypes.node,
string,
> = x =>
switch x {
@ -246,7 +246,7 @@ module MathAdtToDistDst = {
// let evaluatedExpression = run(expression);
// `Function(_ => Ok(evaluatedExpression));
// }
let rec topLevel = (r): result<ASTTypes.Program.program, string> =>
let rec topLevel = (r): result<ASTTypes.program, string> =>
switch r {
| FunctionAssignment({name, args, expression}) =>
switch nodeParser(expression) {
@ -267,7 +267,7 @@ module MathAdtToDistDst = {
blocks |> E.A.fmap(b => topLevel(b)) |> E.A.R.firstErrorOrOpen |> E.R.fmap(E.A.concatMany)
}
let run = (r): result<ASTTypes.Program.program, string> =>
let run = (r): result<ASTTypes.program, string> =>
r |> MathAdtCleaner.run |> topLevel
}

View File

@ -96,12 +96,10 @@ let toDiscretePointMassesFromTriangulars = (
}
let combineShapesContinuousContinuous = (
op: ASTTypes.algebraicOperation,
op: Operation.algebraicOperation,
s1: PointSetTypes.xyShape,
s2: PointSetTypes.xyShape,
): PointSetTypes.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.
@ -194,13 +192,13 @@ let toDiscretePointMassesFromDiscrete = (s: PointSetTypes.xyShape): pointMassesW
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)
let variances: array<float> = Belt.Array.makeBy(n, _ => 0.0)
{n: n, masses: masses, means: means, variances: variances}
}
let combineShapesContinuousDiscrete = (
op: ASTTypes.algebraicOperation,
op: Operation.algebraicOperation,
continuousShape: PointSetTypes.xyShape,
discreteShape: PointSetTypes.xyShape,
): PointSetTypes.xyShape => {

View File

@ -211,7 +211,7 @@ module T = Dist({
/* 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: ASTTypes.algebraicOperation,
op: Operation.algebraicOperation,
t1: t,
t2: PointSetTypes.discreteShape,
) => {
@ -244,7 +244,7 @@ let combineAlgebraicallyWithDiscrete = (
}
}
let combineAlgebraically = (op: ASTTypes.algebraicOperation, t1: t, t2: t) => {
let combineAlgebraically = (op: Operation.algebraicOperation, t1: t, t2: t) => {
let s1 = t1 |> getShape
let s2 = t2 |> getShape
let t1n = s1 |> XYShape.T.length

View File

@ -85,7 +85,7 @@ let updateIntegralCache = (integralCache, t: t): t => {
/* 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: ASTTypes.algebraicOperation, t1: t, t2: t): t => {
let combineAlgebraically = (op: Operation.algebraicOperation, t1: t, t2: t): t => {
let t1s = t1 |> getShape
let t2s = t2 |> getShape
let t1n = t1s |> XYShape.T.length

View File

@ -227,7 +227,7 @@ module T = Dist({
}
})
let combineAlgebraically = (op: ASTTypes.algebraicOperation, t1: t, t2: t): t => {
let combineAlgebraically = (op: Operation.algebraicOperation, t1: t, t2: t): t => {
// Discrete convolution can cause a huge increase in the number of samples,
// so we'll first downsample.
@ -240,9 +240,6 @@ let combineAlgebraically = (op: ASTTypes.algebraicOperation, t1: t, t2: t): 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)

View File

@ -1,6 +1,7 @@
open Distributions
type t = PointSetTypes.pointSetDist
let mapToAll = ((fn1, fn2, fn3), t: t) =>
switch t {
| Mixed(m) => fn1(m)
@ -33,7 +34,7 @@ let toMixed = mapToAll((
),
))
let combineAlgebraically = (op: ASTTypes.algebraicOperation, t1: t, t2: t): t =>
let combineAlgebraically = (op: Operation.algebraicOperation, t1: t, t2: t): t =>
switch (t1, t2) {
| (Continuous(m1), Continuous(m2)) =>
Continuous.combineAlgebraically(op, m1, m2) |> Continuous.T.toPointSetDist
@ -77,9 +78,6 @@ module T = Dist({
let toPointSetDist = (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)
@ -93,8 +91,6 @@ module T = Dist({
t,
)
let toDiscreteProbabilityMassFraction = t => 0.0
let normalize = fmap((Mixed.T.normalize, Discrete.T.normalize, Continuous.T.normalize))
let updateIntegralCache = (integralCache, t: t): t =>
@ -197,7 +193,7 @@ let sampleNRendered = (n, dist) => {
doN(n, () => sample(distWithUpdatedIntegralCache))
}
let operate = (distToFloatOp: ASTTypes.distToFloatOperation, s): float =>
let operate = (distToFloatOp: Operation.distToFloatOperation, s): float =>
switch distToFloatOp {
| #Pdf(f) => pdf(f, s)
| #Cdf(f) => pdf(f, s)

View File

@ -159,7 +159,7 @@ module XtoY = {
y1 *. (1. -. fraction) +. y2 *. fraction
}
| (#Stepwise, #UseZero) =>
(t: T.t, leftIndex: int, x: float) =>
(t: T.t, leftIndex: int, _x: float) =>
if leftIndex < 0 {
0.0
} else if leftIndex >= T.length(t) - 1 {
@ -168,7 +168,7 @@ module XtoY = {
t.ys[leftIndex]
}
| (#Stepwise, #UseOutermostPoints) =>
(t: T.t, leftIndex: int, x: float) =>
(t: T.t, leftIndex: int, _x: float) =>
if leftIndex < 0 {
t.ys[0]
} else if leftIndex >= T.length(t) - 1 {

View File

@ -80,7 +80,7 @@ module Internals = {
let toPointSetDist = (
~samples: Internals.T.t,
~samplingInputs: ASTTypes.AST.samplingInputs,
~samplingInputs: SamplingInputs.samplingInputs,
(),
) => {
Array.fast_sort(compare, samples)

View File

@ -272,7 +272,7 @@ module T = {
| #Float(n) => Float.mean(n)
}
let operate = (distToFloatOp: ASTTypes.distToFloatOperation, s) =>
let operate = (distToFloatOp: Operation.distToFloatOperation, s) =>
switch distToFloatOp {
| #Cdf(f) => Ok(cdf(f, s))
| #Pdf(f) => Ok(pdf(f, s))
@ -302,7 +302,7 @@ module T = {
let tryAnalyticalSimplification = (
d1: symbolicDist,
d2: symbolicDist,
op: ASTTypes.algebraicOperation,
op: Operation.algebraicOperation,
): analyticalSimplificationResult =>
switch (d1, d2) {
| (#Float(v1), #Float(v2)) =>

View File

@ -0,0 +1,8 @@
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)))

View File

@ -1,4 +1,21 @@
open ASTTypes
// This file has no dependencies. It's used outside of the interpreter, but the interpreter depends on it.
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 Algebraic = {
type t = algebraicOperation
@ -80,28 +97,16 @@ module Scale = {
let toIntegralCacheFn = x =>
switch x {
| #Multiply => (a, b) => None // TODO: this could probably just be multiplied out (using Continuous.scaleBy)
| #Multiply => (_, _) => 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) => {
module Truncate = {
let toString = (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)`
}
let toString = (nodeToString, x) =>
switch x {
| #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 AST.toString.
}

View File

@ -0,0 +1,21 @@
type samplingInputs = {
sampleCount: int,
outputXYPoints: int,
kernelWidth: option<float>,
pointSetDistLength: int,
}
module SamplingInputs = {
type t = {
sampleCount: option<int>,
outputXYPoints: option<int>,
kernelWidth: option<float>,
pointSetDistLength: option<int>,
}
let withDefaults = (t: t): samplingInputs => {
sampleCount: t.sampleCount |> E.O.default(10000),
outputXYPoints: t.outputXYPoints |> E.O.default(10000),
kernelWidth: t.kernelWidth,
pointSetDistLength: t.pointSetDistLength |> E.O.default(10000),
}
}