Last cleanup
Value: [1e-5 to 1e-3]
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@ -300,12 +300,6 @@ module T = Dist({
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| _ => XYShape.Analysis.getVarianceDangerously(t, mean, getMeanOfSquares)
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}
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}
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// let klDivergence = (prediction: t, answer: t) => {
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// let klDiscretePart = Discrete.T.klDivergence(prediction.discrete, answer.discrete)
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// let klContinuousPart = Continuous.T.klDivergence(prediction.continuous, answer.continuous)
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// E.R.merge(klDiscretePart, klContinuousPart)->E.R2.fmap(t => fst(t) +. snd(t))
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// }
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})
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let combineAlgebraically = (op: Operation.convolutionOperation, t1: t, t2: t): t => {
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@ -34,9 +34,9 @@ module WithDistAnswer = {
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Operation.Error.t,
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> =>
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switch (estimate, answer) {
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| (Continuous(_), Continuous(_)) =>
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| (Continuous(_), Continuous(_))
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| (Discrete(_), Discrete(_)) =>
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combineFn(integrand, estimate, answer)->E.R2.fmap(integrateFn)
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| (Discrete(_), Discrete(_)) => combineFn(integrand, estimate, answer)->E.R2.fmap(integrateFn)
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| (_, _) =>
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let esti = estimate->toMixedFn
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let answ = answer->toMixedFn
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@ -491,22 +491,6 @@ module PointwiseCombination = {
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let newYs = E.A.fmap(x => XtoY.linear(x, t), newXs)
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{xs: newXs, ys: newYs}
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}
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// This function is used for klDivergence
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let combineAlongSupportOfSecondArgument: (
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interpolator,
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(float, float) => result<float, Operation.Error.t>,
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T.t,
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T.t,
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) => result<T.t, Operation.Error.t> = (interpolator, fn, prediction, answer) => {
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let combineWithFn = (answerX: float, i: int) => {
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let answerY = answer.ys[i]
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// let predictionY = XtoY.linear(answerX, prediction)
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let predictionY = interpolator(prediction, i, answerX)
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fn(predictionY, answerY)
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}
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let newYsWithError = Js.Array.mapi((x, i) => combineWithFn(x, i), answer.xs)
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E.A.R.firstErrorOrOpen(newYsWithError)->E.R2.fmap(ys => {xs: answer.xs, ys: ys})
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}
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let addCombine = (interpolator: interpolator, t1: T.t, t2: T.t): T.t =>
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combine(interpolator, (a, b) => Ok(a +. b), t1, t2)->E.R.toExn(
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