55 lines
2.2 KiB
Plaintext
55 lines
2.2 KiB
Plaintext
open Jest
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open Expect
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let expectErrorToBeBounded = (received, expected, ~epsilon) => {
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let distance = Js.Math.abs_float(received -. expected)
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let expectedAbs = Js.Math.abs_float(expected)
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let normalizingDenom = Js.Math.max_float(
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expectedAbs,
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epsilon < 1.0 ? epsilon ** 2.0 : epsilon ** -2.0,
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)
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let error = distance /. normalizingDenom
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error->expect->toBeLessThan(epsilon)
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}
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let makeTest = (~only=false, str, item1, item2) =>
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only
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? Only.test(str, () => expect(item1)->toEqual(item2))
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: test(str, () => expect(item1)->toEqual(item2))
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let {toFloat, toDist, toString, toError, fmap} = module(DistributionOperation.Output)
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let fnImage = (theFn, inps) => Js.Array.map(theFn, inps)
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let env: DistributionOperation.env = {
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sampleCount: 10000,
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xyPointLength: 1000,
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}
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let run = DistributionOperation.run(~env)
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let outputMap = fmap(~env)
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let unreachableInTestFileMessage = "Should be impossible to reach (This error is in test file)"
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let toExtFloat: option<float> => float = E.O.toExt(unreachableInTestFileMessage)
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let toExtDist: option<DistributionTypes.genericDist> => DistributionTypes.genericDist = E.O.toExt(
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unreachableInTestFileMessage,
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)
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// let toExt: option<'a> => 'a = E.O.toExt(unreachableInTestFileMessage)
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let unpackFloat = x => x->toFloat->toExtFloat
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let unpackDist = y => y->toDist->toExtDist
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let mkNormal = (mean, stdev) => DistributionTypes.Symbolic(#Normal({mean: mean, stdev: stdev}))
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let mkBeta = (alpha, beta) => DistributionTypes.Symbolic(#Beta({alpha: alpha, beta: beta}))
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let mkExponential = rate => DistributionTypes.Symbolic(#Exponential({rate: rate}))
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let mkUniform = (low, high) => DistributionTypes.Symbolic(#Uniform({low: low, high: high}))
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let mkCauchy = (local, scale) => DistributionTypes.Symbolic(#Cauchy({local: local, scale: scale}))
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let mkLognormal = (mu, sigma) => DistributionTypes.Symbolic(#Lognormal({mu: mu, sigma: sigma}))
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let normalMake = SymbolicDist.Normal.make
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let betaMake = SymbolicDist.Beta.make
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let exponentialMake = SymbolicDist.Exponential.make
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let uniformMake = SymbolicDist.Uniform.make
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let cauchyMake = SymbolicDist.Cauchy.make
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let lognormalMake = SymbolicDist.Lognormal.make
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let triangularMake = SymbolicDist.Triangular.make
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let floatMake = SymbolicDist.Float.make
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