Remove Old code, restrict convolution to specific types
This commit is contained in:
Sam Nolan
parent
cd41459887
commit
d27b777900
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@ -67,7 +67,7 @@ describe("eval on distribution functions", () => {
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testEval("lognormal(10,2) / lognormal(5,2)", "Ok(Lognormal(5,2.8284271247461903))")
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testEval("lognormal(5, 2) / 2", "Ok(Lognormal(4.306852819440055,2))")
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testEval("2 / lognormal(5, 2)", "Ok(Lognormal(-4.306852819440055,2))")
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testEval("2 / normal(10, 2)", "Ok(Point Set Distribution)")
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testEval("2 / normal(10, 2)", "Ok(Sample Set Distribution)")
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testEval("normal(10, 2) / 2", "Ok(Normal(5,1))")
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})
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describe("truncate", () => {
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@ -77,21 +77,21 @@ describe("eval on distribution functions", () => {
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})
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describe("exp", () => {
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testEval("exp(normal(5,2))", "Ok(Point Set Distribution)")
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testEval("exp(normal(5,2))", "Ok(Sample Set Distribution)")
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})
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describe("pow", () => {
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testEval("pow(3, uniform(5,8))", "Ok(Point Set Distribution)")
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testEval("pow(uniform(5,8), 3)", "Ok(Point Set Distribution)")
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testEval("pow(3, uniform(5,8))", "Ok(Sample Set Distribution)")
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testEval("pow(uniform(5,8), 3)", "Ok(Sample Set Distribution)")
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testEval("pow(uniform(5,8), uniform(9, 10))", "Ok(Sample Set Distribution)")
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})
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describe("log", () => {
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testEval("log(2, uniform(5,8))", "Ok(Point Set Distribution)")
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testEval("log(normal(5,2), 3)", "Ok(Point Set Distribution)")
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testEval("log(2, uniform(5,8))", "Ok(Sample Set Distribution)")
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testEval("log(normal(5,2), 3)", "Ok(Sample Set Distribution)")
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testEval("log(normal(5,2), normal(10,1))", "Ok(Sample Set Distribution)")
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testEval("log(uniform(5,8))", "Ok(Point Set Distribution)")
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testEval("log10(uniform(5,8))", "Ok(Point Set Distribution)")
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testEval("log(uniform(5,8))", "Ok(Sample Set Distribution)")
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testEval("log10(uniform(5,8))", "Ok(Sample Set Distribution)")
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})
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describe("dotLog", () => {
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@ -1,9 +1,4 @@
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import * as _ from "lodash";
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import type {
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exportEnv,
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exportDistribution,
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} from "../rescript/ProgramEvaluator.gen";
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export type { exportEnv, exportDistribution };
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import {
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genericDist,
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samplingParams,
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@ -48,7 +43,6 @@ import {
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Constructors_pointwiseLogarithm,
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Constructors_pointwisePower,
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} from "../rescript/Distributions/DistributionOperation/DistributionOperation.gen";
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import { pointSetDistFn } from "../rescript/OldInterpreter/DistPlus.bs";
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export type { samplingParams, errorValue };
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export let defaultSamplingInputs: samplingParams = {
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@ -99,7 +93,7 @@ export type squiggleExpression =
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export function run(
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squiggleString: string,
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samplingInputs?: samplingParams,
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_environment?: exportEnv
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_environment?: unknown
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): result<squiggleExpression, errorValue> {
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let si: samplingParams = samplingInputs
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? samplingInputs
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@ -158,7 +158,7 @@ module AlgebraicCombination = {
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let runConvolution = (
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toPointSet: toPointSetFn,
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arithmeticOperation: GenericDist_Types.Operation.arithmeticOperation,
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arithmeticOperation: Operation.convolutionOperation,
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t1: t,
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t2: t,
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) =>
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@ -207,15 +207,17 @@ module AlgebraicCombination = {
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| Some(Ok(symbolicDist)) => Ok(Symbolic(symbolicDist))
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| Some(Error(e)) => Error(Other(e))
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| None =>
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switch chooseConvolutionOrMonteCarlo(t1, t2) {
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| #CalculateWithMonteCarlo => runMonteCarlo(toSampleSetFn, arithmeticOperation, t1, t2)
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| #CalculateWithConvolution =>
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runConvolution(
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toPointSetFn,
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arithmeticOperation,
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t1,
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t2,
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)->E.R2.fmap(r => DistributionTypes.PointSet(r))
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switch arithmeticOperation {
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| #Divide
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| #Power
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| #Logarithm =>
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runMonteCarlo(toSampleSetFn, arithmeticOperation, t1, t2)
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| (#Add | #Subtract | #Multiply) as op =>
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switch chooseConvolutionOrMonteCarlo(t1, t2) {
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| #CalculateWithMonteCarlo => runMonteCarlo(toSampleSetFn, arithmeticOperation, t1, t2)
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| #CalculateWithConvolution =>
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runConvolution(toPointSetFn, op, t1, t2)->E.R2.fmap(r => DistributionTypes.PointSet(r))
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}
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}
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}
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}
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@ -247,7 +247,7 @@ let downsampleEquallyOverX = (length, t): t =>
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/* This simply creates multiple copies of the continuous distribution, scaled and shifted according to
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each discrete data point, and then adds them all together. */
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let combineAlgebraicallyWithDiscrete = (
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op: Operation.algebraicOperation,
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op: Operation.convolutionOperation,
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t1: t,
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t2: PointSetTypes.discreteShape,
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discreteFirst: bool,
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@ -271,8 +271,7 @@ let combineAlgebraicallyWithDiscrete = (
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)
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let combinedIntegralSum = switch op {
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| #Multiply
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| #Divide =>
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| #Multiply =>
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Common.combineIntegralSums((a, b) => Some(a *. b), t1.integralSumCache, t2.integralSumCache)
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| _ => None
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}
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@ -282,7 +281,7 @@ let combineAlgebraicallyWithDiscrete = (
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}
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}
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let combineAlgebraically = (op: Operation.algebraicOperation, t1: t, t2: t) => {
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let combineAlgebraically = (op: Operation.convolutionOperation, t1: t, t2: t) => {
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let s1 = t1 |> getShape
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let s2 = t2 |> getShape
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let t1n = s1 |> XYShape.T.length
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@ -85,7 +85,7 @@ let updateIntegralCache = (integralCache, t: t): t => {
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/* This multiples all of the data points together and creates a new discrete distribution from the results.
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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. */
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let combineAlgebraically = (op: Operation.algebraicOperation, t1: t, t2: t): t => {
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let combineAlgebraically = (op: Operation.convolutionOperation, t1: t, t2: t): t => {
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let t1s = t1 |> getShape
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let t2s = t2 |> getShape
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let t1n = t1s |> XYShape.T.length
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@ -97,7 +97,7 @@ let combineAlgebraically = (op: Operation.algebraicOperation, t1: t, t2: t): t =
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t2.integralSumCache,
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)
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let fn = Operation.Algebraic.toFn(op)
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let fn = Operation.Convolution.toFn(op)
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let xToYMap = E.FloatFloatMap.empty()
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for i in 0 to t1n - 1 {
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@ -226,7 +226,7 @@ module T = Dist({
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}
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})
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let combineAlgebraically = (op: Operation.algebraicOperation, t1: t, t2: t): t => {
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let combineAlgebraically = (op: Operation.convolutionOperation, t1: t, t2: t): t => {
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// Discrete convolution can cause a huge increase in the number of samples,
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// so we'll first downsample.
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@ -96,7 +96,7 @@ let toDiscretePointMassesFromTriangulars = (
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}
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let combineShapesContinuousContinuous = (
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op: Operation.algebraicOperation,
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op: Operation.convolutionOperation,
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s1: PointSetTypes.xyShape,
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s2: PointSetTypes.xyShape,
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): PointSetTypes.xyShape => {
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@ -104,7 +104,6 @@ let combineShapesContinuousContinuous = (
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// if we multiply the two distributions, we should probably use lognormal filters.
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let t1m = toDiscretePointMassesFromTriangulars(s1)
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let t2m = switch op {
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| #Divide => toDiscretePointMassesFromTriangulars(~inverse=true, s2)
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| _ => toDiscretePointMassesFromTriangulars(~inverse=false, s2)
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}
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@ -112,9 +111,6 @@ let combineShapesContinuousContinuous = (
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| #Add => (m1, m2) => m1 +. m2
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| #Subtract => (m1, m2) => m1 -. m2
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| #Multiply => (m1, m2) => m1 *. m2
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| #Divide => (m1, mInv2) => m1 *. mInv2
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| #Power => (m1, mInv2) => m1 ** mInv2
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| #Logarithm => (m1, m2) => log(m1) /. log(m2)
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} // note: here, mInv2 = mean(1 / t2) ~= 1 / mean(t2)
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// TODO: Variances are for exponentatiation or logarithms are almost totally made up and very likely very wrong.
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@ -123,9 +119,6 @@ let combineShapesContinuousContinuous = (
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| #Add => (v1, v2, _, _) => v1 +. v2
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| #Subtract => (v1, v2, _, _) => v1 +. v2
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| #Multiply => (v1, v2, m1, m2) => v1 *. v2 +. v1 *. m2 ** 2. +. v2 *. m1 ** 2.
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| #Power => (v1, v2, m1, m2) => v1 *. v2 +. v1 *. m2 ** 2. +. v2 *. m1 ** 2.
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| #Logarithm => (v1, v2, m1, m2) => v1 *. v2 +. v1 *. m2 ** 2. +. v2 *. m1 ** 2.
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| #Divide => (v1, vInv2, m1, mInv2) => v1 *. vInv2 +. v1 *. mInv2 ** 2. +. vInv2 *. m1 ** 2.
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}
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// TODO: If operating on two positive-domain distributions, we should take that into account
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@ -199,13 +192,13 @@ let toDiscretePointMassesFromDiscrete = (s: PointSetTypes.xyShape): pointMassesW
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}
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let combineShapesContinuousDiscrete = (
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op: Operation.algebraicOperation,
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op: Operation.convolutionOperation,
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continuousShape: PointSetTypes.xyShape,
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discreteShape: PointSetTypes.xyShape,
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discreteFirst: bool,
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): PointSetTypes.xyShape => {
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// each x pair is added/subtracted
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let opFunc = Operation.Algebraic.toFn(op)
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let opFunc = Operation.Convolution.toFn(op)
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let fn = discreteFirst ? (a, b) => opFunc(b, a) : opFunc
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let discretePoints = Belt.Array.zip(discreteShape.xs, discreteShape.ys)
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@ -217,10 +210,7 @@ let combineShapesContinuousDiscrete = (
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discretePoints->E.A2.fmap(((dx, dy)) =>
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continuousPoints->E.A2.fmap(((cx, cy)) => (fn(cx, dx), cy *. dy))
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)
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| #Multiply
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| #Power
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| #Logarithm
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| #Divide =>
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| #Multiply =>
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discretePoints->E.A2.fmap(((dx, dy)) =>
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continuousPoints->E.A2.fmap(((cx, cy)) => (fn(cx, dx), cy *. dy /. dx))
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)
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@ -34,8 +34,7 @@ let toMixed = mapToAll((
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),
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))
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//TODO WARNING: The combineAlgebraicallyWithDiscrete will break for subtraction and division, like, discrete - continous
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let combineAlgebraically = (op: Operation.algebraicOperation, t1: t, t2: t): t =>
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let combineAlgebraically = (op: Operation.convolutionOperation, t1: t, t2: t): t =>
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switch (t1, t2) {
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| (Continuous(m1), Continuous(m2)) =>
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Continuous.combineAlgebraically(op, m1, m2) |> Continuous.T.toPointSetDist
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@ -1,24 +0,0 @@
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open ASTTypes
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let toString = ASTTypes.Node.toString
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let envs = (samplingInputs, environment) => {
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samplingInputs: samplingInputs,
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environment: environment,
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evaluateNode: ASTEvaluator.toLeaf,
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}
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let toLeaf = (samplingInputs, environment, node: node) =>
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ASTEvaluator.toLeaf(envs(samplingInputs, environment), node)
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let toPointSetDist = (samplingInputs, environment, node: node) =>
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switch toLeaf(samplingInputs, environment, node) {
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| Ok(#RenderedDist(pointSetDist)) => Ok(pointSetDist)
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| Ok(_) => Error("Rendering failed.")
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| Error(e) => Error(e)
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}
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let runFunction = (samplingInputs, environment, inputs, fn: ASTTypes.Function.t) => {
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let params = envs(samplingInputs, environment)
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ASTTypes.Function.run(params, inputs, fn)
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}
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@ -1,257 +0,0 @@
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open ASTTypes
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type tResult = node => result<node, string>
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/* Given two random variables A and B, this returns the distribution
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of a new variable that is the result of the operation on A and B.
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For instance, normal(0, 1) + normal(1, 1) -> normal(1, 2).
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In general, this is implemented via convolution. */
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module AlgebraicCombination = {
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let tryAnalyticalSimplification = (operation, t1: node, t2: node) =>
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switch (operation, t1, t2) {
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| (operation, #SymbolicDist(d1), #SymbolicDist(d2)) =>
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switch SymbolicDist.T.tryAnalyticalSimplification(d1, d2, operation) {
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| #AnalyticalSolution(symbolicDist) => Ok(#SymbolicDist(symbolicDist))
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| #Error(er) => Error(er)
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| #NoSolution => Ok(#AlgebraicCombination(operation, t1, t2))
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}
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| _ => Ok(#AlgebraicCombination(operation, t1, t2))
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}
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let combinationByRendering = (evaluationParams, algebraicOp, t1: node, t2: node): result<
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node,
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string,
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> =>
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E.R.merge(
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Node.ensureIsRenderedAndGetShape(evaluationParams, t1),
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Node.ensureIsRenderedAndGetShape(evaluationParams, t2),
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) |> E.R.fmap(((a, b)) => #RenderedDist(PointSetDist.combineAlgebraically(algebraicOp, a, b)))
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let nodeScore: node => int = x =>
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switch x {
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| #SymbolicDist(#Float(_)) => 1
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| #SymbolicDist(_) => 1000
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| #RenderedDist(Discrete(m)) => m.xyShape |> XYShape.T.length
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| #RenderedDist(Mixed(_)) => 1000
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| #RenderedDist(Continuous(_)) => 1000
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| _ => 1000
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}
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let choose = (t1: node, t2: node) =>
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nodeScore(t1) * nodeScore(t2) > 10000 ? #Sampling : #Analytical
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let combine = (evaluationParams, algebraicOp, t1: node, t2: node): result<node, string> =>
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E.R.merge(
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ASTTypes.SamplingDistribution.renderIfIsNotSamplingDistribution(evaluationParams, t1),
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ASTTypes.SamplingDistribution.renderIfIsNotSamplingDistribution(evaluationParams, t2),
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) |> E.R.bind(_, ((a, b)) =>
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switch choose(a, b) {
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| #Sampling =>
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ASTTypes.SamplingDistribution.combineShapesUsingSampling(
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evaluationParams,
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algebraicOp,
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a,
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b,
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)
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| #Analytical => combinationByRendering(evaluationParams, algebraicOp, a, b)
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}
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)
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let operationToLeaf = (
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evaluationParams: evaluationParams,
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algebraicOp: Operation.algebraicOperation,
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t1: node,
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t2: node,
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): result<node, string> =>
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algebraicOp
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|> tryAnalyticalSimplification(_, t1, t2)
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|> E.R.bind(_, x =>
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switch x {
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| #SymbolicDist(_) as t => Ok(t)
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| _ => combine(evaluationParams, algebraicOp, t1, t2)
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}
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)
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}
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module PointwiseCombination = {
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//TODO: This is crude and slow. It forces everything to be pointSetDist, even though much
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//of the process could happen on symbolic distributions without a conversion to be a pointSetDist.
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let pointwiseAdd = (evaluationParams: evaluationParams, t1: node, t2: node) =>
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switch (Node.render(evaluationParams, t1), Node.render(evaluationParams, t2)) {
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| (Ok(#RenderedDist(rs1)), Ok(#RenderedDist(rs2))) =>
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Ok(
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#RenderedDist(
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PointSetDist.combinePointwise(
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~integralSumCachesFn=(a, b) => Some(a +. b),
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~integralCachesFn=(a, b) => Some(
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Continuous.combinePointwise(~distributionType=#CDF, \"+.", a, b),
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),
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\"+.",
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rs1,
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rs2,
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),
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),
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)
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| (Error(e1), _) => Error(e1)
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| (_, Error(e2)) => Error(e2)
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| _ => Error("Pointwise combination: rendering failed.")
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}
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let pointwiseCombine = (fn, evaluationParams: evaluationParams, t1: node, t2: node) =>
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switch // TODO: construct a function that we can easily sample from, to construct
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// a RenderedDist. Use the xMin and xMax of the rendered pointSetDists to tell the sampling function where to look.
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// TODO: This should work for symbolic distributions too!
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(Node.render(evaluationParams, t1), Node.render(evaluationParams, t2)) {
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| (Ok(#RenderedDist(rs1)), Ok(#RenderedDist(rs2))) =>
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Ok(#RenderedDist(PointSetDist.combinePointwise(fn, rs1, rs2)))
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| (Error(e1), _) => Error(e1)
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| (_, Error(e2)) => Error(e2)
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| _ => Error("Pointwise combination: rendering failed.")
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}
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let operationToLeaf = (
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evaluationParams: evaluationParams,
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pointwiseOp: Operation.pointwiseOperation,
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t1: node,
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t2: node,
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) =>
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switch pointwiseOp {
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| #Add => pointwiseAdd(evaluationParams, t1, t2)
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| #Multiply => pointwiseCombine(\"*.", evaluationParams, t1, t2)
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| #Power => pointwiseCombine(\"**", evaluationParams, t1, t2)
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}
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}
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module Truncate = {
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type simplificationResult = [
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| #Solution(ASTTypes.node)
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| #Error(string)
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| #NoSolution
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]
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|
||||
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))
|
||||
}
|
||||
|
|
@ -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)))
|
||||
})
|
||||
}
|
||||
}
|
||||
|
|
@ -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)
|
||||
})
|
||||
|
|
@ -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,
|
||||
]
|
||||
|
|
@ -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))
|
||||
}
|
||||
}
|
||||
|
|
@ -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)
|
||||
|
|
@ -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)
|
||||
}
|
||||
|
|
@ -9,6 +9,13 @@ type algebraicOperation = [
|
|||
| #Power
|
||||
| #Logarithm
|
||||
]
|
||||
|
||||
type convolutionOperation = [
|
||||
| #Add
|
||||
| #Multiply
|
||||
| #Subtract
|
||||
]
|
||||
|
||||
@genType
|
||||
type pointwiseOperation = [#Add | #Multiply | #Power]
|
||||
type scaleOperation = [#Multiply | #Power | #Logarithm | #Divide]
|
||||
|
|
@ -20,6 +27,16 @@ type distToFloatOperation = [
|
|||
| #Sample
|
||||
]
|
||||
|
||||
module Convolution = {
|
||||
type t = convolutionOperation
|
||||
let toFn: (t, float, float) => float = x =>
|
||||
switch x {
|
||||
| #Add => \"+."
|
||||
| #Subtract => \"-."
|
||||
| #Multiply => \"*."
|
||||
}
|
||||
}
|
||||
|
||||
module Algebraic = {
|
||||
type t = algebraicOperation
|
||||
let toFn: (t, float, float) => float = x =>
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user