/* This is the most basic file in our invariants family of tests. See document in https://github.com/quantified-uncertainty/squiggle/pull/238 for details Note: digits parameter should be higher than -4. */ open Jest open Expect open TestHelpers let { algebraicAdd, algebraicMultiply, algebraicDivide, algebraicSubtract, algebraicLogarithm, algebraicPower, } = module(DistributionOperation.Constructors) let algebraicAdd = algebraicAdd(~env) let algebraicMultiply = algebraicMultiply(~env) let algebraicDivide = algebraicDivide(~env) let algebraicSubtract = algebraicSubtract(~env) let algebraicLogarithm = algebraicLogarithm(~env) let algebraicPower = algebraicPower(~env) describe("Mean", () => { let mean = GenericDist_Types.Constructors.UsingDists.mean let runMean: result => float = distR => { switch distR->E.R2.fmap(mean)->E.R2.fmap(run)->E.R2.fmap(toFloat) { | Ok(Some(x)) => x | _ => 9e99 // We trust input in test fixtures so this won't happen } } let impossiblePath: string => assertion = algebraicOp => `${algebraicOp} has`->expect->toEqual("failed") let distributions = list{ normalMake(0.0, 1e0), betaMake(2e0, 4e0), exponentialMake(1.234e0), uniformMake(7e0, 1e1), // cauchyMake(1e0, 1e0), lognormalMake(1e0, 1e0), triangularMake(1e0, 1e1, 5e1), Ok(floatMake(1e1)), } let combinations = E.L.combinations2(distributions) let zipDistsDists = E.L.zip(distributions, distributions) let digits = -4 let testOperationMean = ( distOp: (DistributionTypes.genericDist, DistributionTypes.genericDist) => result, description: string, floatOp: (float, float) => float, dist1': result, dist2': result ) => { let dist1 = dist1'->E.R2.fmap(x=>DistributionTypes.Symbolic(x))->E.R2.fmap2(s=>DistributionTypes.Other(s)) let dist2 = dist2'->E.R2.fmap(x=>DistributionTypes.Symbolic(x))->E.R2.fmap2(s=>DistributionTypes.Other(s)) let received = E.R.liftJoin2(distOp, dist1, dist2) ->E.R2.fmap(mean) ->E.R2.fmap(run) ->E.R2.fmap(toFloat) let expected = floatOp(runMean(dist1), runMean(dist2)) switch received { | Error(err) => impossiblePath(description) | Ok(x) => switch x { | None => impossiblePath(description) | Some(x) => x->expect->toBeSoCloseTo(expected, ~digits) } } } describe("addition", () => { let testAdditionMean = testOperationMean(algebraicAdd, "algebraicAdd", (x,y)=>x+.y) testAll("homogeneous addition", zipDistsDists, dists => { let (dist1, dist2) = dists testAdditionMean(dist1, dist2) }) testAll("heterogeneous addition (1)", combinations, dists => { let (dist1, dist2) = dists testAdditionMean(dist1, dist2) }) testAll("heterogeneous addition (commuted of 1 (or; 2))", combinations, dists => { let (dist1, dist2) = dists testAdditionMean(dist2, dist1) }) }) describe("subtraction", () => { let testSubtractionMean = testOperationMean(algebraicSubtract, "algebraicSubtract", (x,y)=>x-.y) testAll("homogeneous subtraction", zipDistsDists, dists => { let (dist1, dist2) = dists testSubtractionMean(dist1, dist2) }) testAll("heterogeneous subtraction (1)", combinations, dists => { let (dist1, dist2) = dists testSubtractionMean(dist1, dist2) }) testAll("heterogeneous subtraction (commuted of 1 (or; 2))", combinations, dists => { let (dist1, dist2) = dists testSubtractionMean(dist2, dist1) }) }) describe("multiplication", () => { let testMultiplicationMean = testOperationMean(algebraicMultiply, "algebraicMultiply", (x,y)=>x*.y) testAll("homogeneous subtraction", zipDistsDists, dists => { let (dist1, dist2) = dists testMultiplicationMean(dist1, dist2) }) testAll("heterogeneoous subtraction (1)", combinations, dists => { let (dist1, dist2) = dists testMultiplicationMean(dist1, dist2) }) testAll("heterogeneoous subtraction (commuted of 1 (or; 2))", combinations, dists => { let (dist1, dist2) = dists testMultiplicationMean(dist2, dist1) }) }) })