open Jest open Expect let env: DistributionOperation.env = { sampleCount: 100, xyPointLength: 100, } let { normalDist5, normalDist10, normalDist20, normalDist, uniformDist, betaDist, lognormalDist, cauchyDist, triangularDist, exponentialDist, } = module(GenericDist_Fixtures) let mkNormal = (mean, stdev) => GenericDist_Types.Symbolic(#Normal({mean: mean, stdev: stdev})) let {toFloat, toDist, toString, toError} = module(DistributionOperation.Output) let {run} = module(DistributionOperation) let {fmap} = module(DistributionOperation.Output) let run = run(~env) let outputMap = fmap(~env) let toExt: option<'a> => 'a = E.O.toExt( "Should be impossible to reach (This error is in test file)", ) describe("normalize", () => { test("has no impact on normal dist", () => { let result = run(FromDist(ToDist(Normalize), normalDist5)) expect(result)->toEqual(Dist(normalDist5)) }) }) describe("mean", () => { test("for a normal distribution", () => { let result = DistributionOperation.run(~env, FromDist(ToFloat(#Mean), normalDist5)) expect(result)->toEqual(Float(5.0)) }) }) describe("mixture", () => { test("on two normal distributions", () => { let result = run(Mixture([(normalDist10, 0.5), (normalDist20, 0.5)])) ->outputMap(FromDist(ToFloat(#Mean))) ->toFloat ->toExt expect(result)->toBeCloseTo(15.28) }) }) describe("sparkline", () => { let runTest = ( name: string, dist: GenericDist_Types.genericDist, expected: DistributionOperation.outputType, ) => { test(name, () => { let result = DistributionOperation.run(~env, FromDist(ToString(ToSparkline(20)), dist)) expect(result)->toEqual(expected) }) } runTest( "normal", normalDist, String(`▁▁▁▁▁▂▄▆▇██▇▆▄▂▁▁▁▁▁`), ) runTest( "uniform", uniformDist, String(`████████████████████`), ) runTest("beta", betaDist, String(`▁▄▇████▇▆▅▄▃▃▂▁▁▁▁▁▁`)) runTest( "lognormal", lognormalDist, String(`▁█▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁`), ) runTest( "cauchy", cauchyDist, String(`▁▁▁▁▁▁▁▁▁██▁▁▁▁▁▁▁▁▁`), ) runTest( "triangular", triangularDist, String(`▁▁▂▃▄▅▆▇████▇▆▅▄▃▂▁▁`), ) runTest( "exponential", exponentialDist, String(`█▅▄▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁`), ) }) describe("toPointSet", () => { test("on symbolic normal distribution", () => { let result = run(FromDist(ToDist(ToPointSet), normalDist5)) ->outputMap(FromDist(ToFloat(#Mean))) ->toFloat ->toExt expect(result)->toBeSoCloseTo(5.0, ~digits=0) }) test("on sample set distribution with under 4 points", () => { let result = run(FromDist(ToDist(ToPointSet), SampleSet([0.0, 1.0, 2.0, 3.0])))->outputMap( FromDist(ToFloat(#Mean)), ) expect(result)->toEqual(GenDistError(Other("Converting sampleSet to pointSet failed"))) }) test("on sample set", () => { let result = run(FromDist(ToDist(ToPointSet), normalDist5)) ->outputMap(FromDist(ToDist(ToSampleSet(1000)))) ->outputMap(FromDist(ToDist(ToPointSet))) ->outputMap(FromDist(ToFloat(#Mean))) ->toFloat ->toExt expect(result)->toBeSoCloseTo(5.0, ~digits=-1) }) })