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Cleanup and commenting for PR

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This commit is contained in:
Ozzie Gooen 2022-04-08 22:55:06 -04:00
parent 2dc57bedc5
commit 54b6b18d3a
9 changed files with 105 additions and 145 deletions
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23
packages/squiggle-lang/src/js/index.ts
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@ -9,12 +9,12 @@ export type { SamplingInputs, exportEnv, exportDistribution };
export type { t as DistPlus } from "../rescript/OldInterpreter/DistPlus.gen"; export type { t as DistPlus } from "../rescript/OldInterpreter/DistPlus.gen";
import { import {
genericDist, genericDist,
env,
resultDist, resultDist,
resultFloat, resultFloat,
resultString, resultString,
} from "../rescript/TSInterface.gen"; } from "../rescript/TypescriptInterface.gen";
import { import {
env,
Constructors_mean, Constructors_mean,
Constructors_sample, Constructors_sample,
Constructors_pdf, Constructors_pdf,
@ -59,18 +59,9 @@ export function run(
return runAll(squiggleString, si, env); return runAll(squiggleString, si, env);
} }
export function resultMap( //This is clearly not fully typed. I think later we should use a functional library to
r: // provide a better Either type and corresponding functions.
| { type result =
tag: "Ok";
value: any;
}
| {
tag: "Error";
value: any;
},
mapFn: any
):
| { | {
tag: "Ok"; tag: "Ok";
value: any; value: any;
@ -78,7 +69,9 @@ export function resultMap(
| { | {
tag: "Error"; tag: "Error";
value: any; value: any;
} { };
export function resultMap(r: result, mapFn: any): result {
if (r.tag === "Ok") { if (r.tag === "Ok") {
return { tag: "Ok", value: mapFn(r.value) }; return { tag: "Ok", value: mapFn(r.value) };
} else { } else {

79
packages/squiggle-lang/src/rescript/Distributions/DistributionOperation/DistributionOperation.res
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@ -114,8 +114,8 @@ let rec run = (~env, functionCallInfo: functionCallInfo): outputType => {
->E.R2.fmap(r => Float(r)) ->E.R2.fmap(r => Float(r))
->OutputLocal.fromResult ->OutputLocal.fromResult
| ToString(ToString) => dist->GenericDist.toString->String | ToString(ToString) => dist->GenericDist.toString->String
| ToString(ToSparkline(buckets)) => | ToString(ToSparkline(bucketCount)) =>
GenericDist.toSparkline(dist, ~sampleCount, ~buckets, ()) GenericDist.toSparkline(dist, ~sampleCount, ~bucketCount, ())
->E.R2.fmap(r => String(r)) ->E.R2.fmap(r => String(r))
->OutputLocal.fromResult ->OutputLocal.fromResult
| ToDist(Inspect) => { | ToDist(Inspect) => {
@ -186,42 +186,43 @@ module Output = {
} }
} }
// See comment above GenericDist_Types.Constructors to explain the purpose of this module.
// I tried having another internal module called UsingDists, similar to how its done in
// GenericDist_Types.Constructors. However, this broke GenType for me, so beware.
module Constructors = { module Constructors = {
module C = GenericDist_Types.Constructors.UsingDists; module C = GenericDist_Types.Constructors.UsingDists
open OutputLocal open OutputLocal
let mean = (~env, dist) => C.mean(dist)->run(~env)->toFloatR let mean = (~env, dist) => C.mean(dist)->run(~env)->toFloatR
let sample = (~env, dist) => C.sample(dist)->run(~env)->toFloatR let sample = (~env, dist) => C.sample(dist)->run(~env)->toFloatR
let cdf = (~env, dist, f) => C.cdf(dist, f)->run(~env)->toFloatR let cdf = (~env, dist, f) => C.cdf(dist, f)->run(~env)->toFloatR
let inv = (~env, dist, f) => C.inv(dist, f)->run(~env)->toFloatR let inv = (~env, dist, f) => C.inv(dist, f)->run(~env)->toFloatR
let pdf = (~env, dist, f) => C.pdf(dist, f)->run(~env)->toFloatR let pdf = (~env, dist, f) => C.pdf(dist, f)->run(~env)->toFloatR
let normalize = (~env, dist) => C.normalize(dist)->run(~env)->toDistR let normalize = (~env, dist) => C.normalize(dist)->run(~env)->toDistR
let toPointSet = (~env, dist) => C.toPointSet(dist)->run(~env)->toDistR let toPointSet = (~env, dist) => C.toPointSet(dist)->run(~env)->toDistR
let toSampleSet = (~env, dist, n) => C.toSampleSet(dist, n)->run(~env)->toDistR let toSampleSet = (~env, dist, n) => C.toSampleSet(dist, n)->run(~env)->toDistR
let truncate = (~env, dist, leftCutoff, rightCutoff) => let truncate = (~env, dist, leftCutoff, rightCutoff) =>
C.truncate(dist, leftCutoff, rightCutoff)->run(~env)->toDistR C.truncate(dist, leftCutoff, rightCutoff)->run(~env)->toDistR
let inspect = (~env, dist) => C.inspect(dist)->run(~env)->toDistR let inspect = (~env, dist) => C.inspect(dist)->run(~env)->toDistR
let toString = (~env, dist) => C.toString(dist)->run(~env)->toStringR let toString = (~env, dist) => C.toString(dist)->run(~env)->toStringR
let toSparkline = (~env, dist, buckets) => C.toSparkline(dist, buckets)->run(~env)->toStringR let toSparkline = (~env, dist, bucketCount) => C.toSparkline(dist, bucketCount)->run(~env)->toStringR
let algebraicAdd = (~env, dist1, dist2) => C.algebraicAdd(dist1, dist2)->run(~env)->toDistR let algebraicAdd = (~env, dist1, dist2) => C.algebraicAdd(dist1, dist2)->run(~env)->toDistR
let algebraicMultiply = (~env, dist1, dist2) => let algebraicMultiply = (~env, dist1, dist2) =>
C.algebraicMultiply(dist1, dist2)->run(~env)->toDistR C.algebraicMultiply(dist1, dist2)->run(~env)->toDistR
let algebraicDivide = (~env, dist1, dist2) => let algebraicDivide = (~env, dist1, dist2) => C.algebraicDivide(dist1, dist2)->run(~env)->toDistR
C.algebraicDivide(dist1, dist2)->run(~env)->toDistR let algebraicSubtract = (~env, dist1, dist2) =>
let algebraicSubtract = (~env, dist1, dist2) => C.algebraicSubtract(dist1, dist2)->run(~env)->toDistR
C.algebraicSubtract(dist1, dist2)->run(~env)->toDistR let algebraicLogarithm = (~env, dist1, dist2) =>
let algebraicLogarithm = (~env, dist1, dist2) => C.algebraicLogarithm(dist1, dist2)->run(~env)->toDistR
C.algebraicLogarithm(dist1, dist2)->run(~env)->toDistR let algebraicExponentiate = (~env, dist1, dist2) =>
let algebraicExponentiate = (~env, dist1, dist2) => C.algebraicExponentiate(dist1, dist2)->run(~env)->toDistR
C.algebraicExponentiate(dist1, dist2)->run(~env)->toDistR let pointwiseAdd = (~env, dist1, dist2) => C.pointwiseAdd(dist1, dist2)->run(~env)->toDistR
let pointwiseAdd = (~env, dist1, dist2) => C.pointwiseAdd(dist1, dist2)->run(~env)->toDistR let pointwiseMultiply = (~env, dist1, dist2) =>
let pointwiseMultiply = (~env, dist1, dist2) => C.pointwiseMultiply(dist1, dist2)->run(~env)->toDistR
C.pointwiseMultiply(dist1, dist2)->run(~env)->toDistR let pointwiseDivide = (~env, dist1, dist2) => C.pointwiseDivide(dist1, dist2)->run(~env)->toDistR
let pointwiseDivide = (~env, dist1, dist2) => let pointwiseSubtract = (~env, dist1, dist2) =>
C.pointwiseDivide(dist1, dist2)->run(~env)->toDistR C.pointwiseSubtract(dist1, dist2)->run(~env)->toDistR
let pointwiseSubtract = (~env, dist1, dist2) => let pointwiseLogarithm = (~env, dist1, dist2) =>
C.pointwiseSubtract(dist1, dist2)->run(~env)->toDistR C.pointwiseLogarithm(dist1, dist2)->run(~env)->toDistR
let pointwiseLogarithm = (~env, dist1, dist2) => let pointwiseExponentiate = (~env, dist1, dist2) =>
C.pointwiseLogarithm(dist1, dist2)->run(~env)->toDistR C.pointwiseExponentiate(dist1, dist2)->run(~env)->toDistR
let pointwiseExponentiate = (~env, dist1, dist2) =>
C.pointwiseExponentiate(dist1, dist2)->run(~env)->toDistR
} }

12
packages/squiggle-lang/src/rescript/Distributions/GenericDist/GenericDist.res
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@ -81,11 +81,17 @@ let toPointSet = (
} }
} }
let toSparkline = (t: t, ~sampleCount: int, ~buckets: int=20, unit): result<string, error> => /*
PointSetDist.toSparkline calls "downsampleEquallyOverX", which downsamples it to n=bucketCount.
It first needs a pointSetDist, so we convert to a pointSetDist. In this process we want the
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> =>
t t
->toPointSet(~xSelection=#Linear, ~xyPointLength=buckets * 3, ~sampleCount, ()) ->toPointSet(~xSelection=#Linear, ~xyPointLength=bucketCount * 3, ~sampleCount, ())
->E.R.bind(r => ->E.R.bind(r =>
r->PointSetDist.toSparkline(buckets)->E.R2.errMap(r => Error(GenericDist_Types.Other(r))) r->PointSetDist.toSparkline(bucketCount)->E.R2.errMap(r => Error(GenericDist_Types.Other(r)))
) )
module Truncate = { module Truncate = {

2
packages/squiggle-lang/src/rescript/Distributions/GenericDist/GenericDist.resi
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@ -26,7 +26,7 @@ let toPointSet: (
~xSelection: GenericDist_Types.Operation.pointsetXSelection=?, ~xSelection: GenericDist_Types.Operation.pointsetXSelection=?,
unit, unit,
) => result<PointSetTypes.pointSetDist, error> ) => result<PointSetTypes.pointSetDist, error>
let toSparkline: (t, ~sampleCount: int, ~buckets: int=?, unit) => result<string, error> let toSparkline: (t, ~sampleCount: int, ~bucketCount: int=?, unit) => result<string, error>
let truncate: ( let truncate: (
t, t,

74
packages/squiggle-lang/src/rescript/Distributions/GenericDist/GenericDist_Types.res
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@ -98,6 +98,14 @@ module Operation = {
} }
} }
/*
It can be a pain to write out the genericFunctionCallInfo. The constructors help with this.
This code only covers some of genericFunctionCallInfo: many arguments could be called with either a
float or a distribution. The "UsingDists" module assumes that everything is a distribution.
This is a tradeoff of some generality in order to get a bit more simplicity.
I could see having a longer interface in the future, but it could be messy.
Like, algebraicAddDistFloat vs. algebraicAddDistDist
*/
module Constructors = { module Constructors = {
type t = Operation.genericFunctionCallInfo type t = Operation.genericFunctionCallInfo
@ -105,9 +113,9 @@ module Constructors = {
@genType @genType
let mean = (dist): t => FromDist(ToFloat(#Mean), dist) let mean = (dist): t => FromDist(ToFloat(#Mean), dist)
let sample = (dist): t => FromDist(ToFloat(#Sample), dist) let sample = (dist): t => FromDist(ToFloat(#Sample), dist)
let cdf = (dist, f): t => FromDist(ToFloat(#Cdf(f)), dist) let cdf = (dist, x): t => FromDist(ToFloat(#Cdf(x)), dist)
let inv = (dist, f): t => FromDist(ToFloat(#Inv(f)), dist) let inv = (dist, x): t => FromDist(ToFloat(#Inv(x)), dist)
let pdf = (dist, f): t => FromDist(ToFloat(#Pdf(f)), dist) let pdf = (dist, x): t => FromDist(ToFloat(#Pdf(x)), dist)
let normalize = (dist): t => FromDist(ToDist(Normalize), dist) let normalize = (dist): t => FromDist(ToDist(Normalize), dist)
let toPointSet = (dist): t => FromDist(ToDist(ToPointSet), dist) let toPointSet = (dist): t => FromDist(ToDist(ToPointSet), dist)
let toSampleSet = (dist, r): t => FromDist(ToDist(ToSampleSet(r)), dist) let toSampleSet = (dist, r): t => FromDist(ToDist(ToSampleSet(r)), dist)
@ -165,63 +173,3 @@ module Constructors = {
) )
} }
} }
module DistVariant = {
type t =
| Mean(genericDist)
| Sample(genericDist)
| Cdf(genericDist, float)
| Inv(genericDist, float)
| Pdf(genericDist, float)
| Normalize(genericDist)
| ToPointSet(genericDist)
| ToSampleSet(genericDist, int)
| Truncate(genericDist, option<float>, option<float>)
| Inspect(genericDist)
| ToString(genericDist)
| ToSparkline(genericDist, int)
| AlgebraicAdd(genericDist, genericDist)
| AlgebraicMultiply(genericDist, genericDist)
| AlgebraicDivide(genericDist, genericDist)
| AlgebraicSubtract(genericDist, genericDist)
| AlgebraicLogarithm(genericDist, genericDist)
| AlgebraicExponentiate(genericDist, genericDist)
| PointwiseAdd(genericDist, genericDist)
| PointwiseMultiply(genericDist, genericDist)
| PointwiseDivide(genericDist, genericDist)
| PointwiseSubtract(genericDist, genericDist)
| PointwiseLogarithm(genericDist, genericDist)
| PointwiseExponentiate(genericDist, genericDist)
let toGenericFunctionCallInfo = (t: t) =>
switch t {
| Mean(d) => Operation.FromDist(ToFloat(#Mean), d)
| Sample(d) => FromDist(ToFloat(#Mean), d)
| Cdf(d, f) => FromDist(ToFloat(#Cdf(f)), d)
| Inv(d, f) => FromDist(ToFloat(#Inv(f)), d)
| Pdf(d, f) => FromDist(ToFloat(#Pdf(f)), d)
| Normalize(d) => FromDist(ToDist(Normalize), d)
| ToPointSet(d) => FromDist(ToDist(ToPointSet), d)
| ToSampleSet(d, r) => FromDist(ToDist(ToSampleSet(r)), d)
| Truncate(d, left, right) => FromDist(ToDist(Truncate(left, right)), d)
| Inspect(d) => FromDist(ToDist(Inspect), d)
| ToString(d) => FromDist(ToString(ToString), d)
| ToSparkline(d, n) => FromDist(ToString(ToSparkline(n)), d)
| AlgebraicAdd(d1, d2) => FromDist(ToDistCombination(Algebraic, #Add, #Dist(d2)), d1)
| AlgebraicMultiply(d1, d2) => FromDist(ToDistCombination(Algebraic, #Multiply, #Dist(d2)), d1)
| AlgebraicDivide(d1, d2) => FromDist(ToDistCombination(Algebraic, #Divide, #Dist(d2)), d1)
| AlgebraicSubtract(d1, d2) => FromDist(ToDistCombination(Algebraic, #Subtract, #Dist(d2)), d1)
| AlgebraicLogarithm(d1, d2) =>
FromDist(ToDistCombination(Algebraic, #Logarithm, #Dist(d2)), d1)
| AlgebraicExponentiate(d1, d2) =>
FromDist(ToDistCombination(Algebraic, #Exponentiate, #Dist(d2)), d1)
| PointwiseAdd(d1, d2) => FromDist(ToDistCombination(Pointwise, #Add, #Dist(d2)), d1)
| PointwiseMultiply(d1, d2) => FromDist(ToDistCombination(Pointwise, #Multiply, #Dist(d2)), d1)
| PointwiseDivide(d1, d2) => FromDist(ToDistCombination(Pointwise, #Divide, #Dist(d2)), d1)
| PointwiseSubtract(d1, d2) => FromDist(ToDistCombination(Pointwise, #Subtract, #Dist(d2)), d1)
| PointwiseLogarithm(d1, d2) =>
FromDist(ToDistCombination(Pointwise, #Logarithm, #Dist(d2)), d1)
| PointwiseExponentiate(d1, d2) =>
FromDist(ToDistCombination(Pointwise, #Exponentiate, #Dist(d2)), d1)
}
}

4
packages/squiggle-lang/src/rescript/Distributions/PointSetDist/PointSetDist.res
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@ -203,8 +203,8 @@ let operate = (distToFloatOp: Operation.distToFloatOperation, s): float =>
| #Mean => T.mean(s) | #Mean => T.mean(s)
} }
let toSparkline = (t: t, n) => let toSparkline = (t: t, bucketCount) =>
T.toContinuous(t) T.toContinuous(t)
->E.O2.fmap(Continuous.downsampleEquallyOverX(n)) ->E.O2.fmap(Continuous.downsampleEquallyOverX(bucketCount))
->E.O2.toResult("toContinous Error: Could not convert into continuous distribution") ->E.O2.toResult("toContinous Error: Could not convert into continuous distribution")
->E.R2.fmap(r => Continuous.getShape(r).ys->Sparklines.create()) ->E.R2.fmap(r => Continuous.getShape(r).ys->Sparklines.create())

9
packages/squiggle-lang/src/rescript/Distributions/SampleSetDist/SampleSet.res
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@ -146,11 +146,20 @@ let toPointSetDist = (
samplesParse samplesParse
} }
//Randomly get one sample from the distribution
let sample = (t: t): float => { let sample = (t: t): float => {
let i = E.Int.random(~min=0, ~max=E.A.length(t) - 1) let i = E.Int.random(~min=0, ~max=E.A.length(t) - 1)
E.A.unsafe_get(t, i) E.A.unsafe_get(t, i)
} }
/*
If asked for a length of samples shorter or equal the length of the distribution,
return this first n samples of this distribution.
Else, return n random samples of the distribution.
The former helps in cases where multiple distributions are correlated.
However, if n > length(t), then there's no clear right answer, so we just randomly
sample everything.
*/
let sampleN = (t: t, n) => { let sampleN = (t: t, n) => {
if n <= E.A.length(t) { if n <= E.A.length(t) {
E.A.slice(t, ~offset=0, ~len=n) E.A.slice(t, ~offset=0, ~len=n)

21
packages/squiggle-lang/src/rescript/TSInterface.res
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@ -1,21 +0,0 @@
@genType
type functionCallInfo = GenericDist_Types.Operation.genericFunctionCallInfo;
@genType
type env = DistributionOperation.env;
@genType
type genericDist = GenericDist_Types.genericDist;
@genType
type error = GenericDist_Types.error;
@genType
let runDistributionOperation = DistributionOperation.run;
@genType
type resultDist = result<genericDist, error>
@genType
type resultFloat = result<float, error>
@genType
type resultString = result<string, error>

24
packages/squiggle-lang/src/rescript/TypescriptInterface.res Normal file
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@ -0,0 +1,24 @@
/*
This is meant as a file to contain @genType declarations as needed for Typescript.
I would ultimately want to have all @genType declarations here, vs. other files, but
@genType doesn't play as nicely with renaming Modules and functions as
would be preferable.
The below few seem to work fine. In the future there's definitely more work to do here.
*/
@genType
type env = DistributionOperation.env
@genType
type genericDist = GenericDist_Types.genericDist
@genType
type error = GenericDist_Types.error
@genType
type resultDist = result<genericDist, error>
@genType
type resultFloat = result<float, error>
@genType
type resultString = result<string, error>