make lint happy

Value: [1e-9 to 1e-5]
This commit is contained in:
Quinn Dougherty 2022-05-02 11:55:42 -04:00
parent e2762a0f62
commit d595285078
6 changed files with 14 additions and 10 deletions

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@ -164,7 +164,7 @@ module T = Dist({
}
let integralEndY = (t: t) => t.integralSumCache |> E.O.default(t |> integral |> Continuous.lastY)
let integralEndYResult = (t: t) => t -> integralEndY -> Ok
let integralEndYResult = (t: t) => t->integralEndY->Ok
let minX = shapeFn(XYShape.T.minX)
let maxX = shapeFn(XYShape.T.maxX)
let toDiscreteProbabilityMassFraction = _ => 1.0
@ -230,8 +230,9 @@ module T = Dist({
}
let logScore = (base: t, reference: t) => {
combinePointwise(~fn=PointSetDist_Scoring.LogScoring.logScore, base, reference)
|> E.R2.bind(integralEndYResult)
combinePointwise(~fn=PointSetDist_Scoring.LogScoring.logScore, base, reference) |> E.R2.bind(
integralEndYResult,
)
// |> (r => Ok(r))
}
})

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@ -33,7 +33,7 @@ module type dist = {
let mean: t => float
let variance: t => float
let logScore: (t,t) => result<float, Operation.Error.t>
let logScore: (t, t) => result<float, Operation.Error.t>
}
module Dist = (T: dist) => {

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@ -44,7 +44,11 @@ let combinePointwise = (
t2: t,
): result<t, 'e> => {
let reducedDiscrete =
[t1, t2] |> E.A.fmap(toDiscrete) |> E.A.O.concatSomes |> Discrete.reduce(~integralSumCachesFn, fn) |> E.R.toExn("foo")
[t1, t2]
|> E.A.fmap(toDiscrete)
|> E.A.O.concatSomes
|> Discrete.reduce(~integralSumCachesFn, fn)
|> E.R.toExn("foo")
let reducedContinuous =
[t1, t2]

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@ -4,4 +4,4 @@ module LogScoring = {
let logScore = (a: float, b: float): result<float, Operation.Error.t> => Ok(
Js.Math.log2(Js.Math.abs_float(a /. b)),
)
}
}

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@ -212,9 +212,8 @@ let dispatchToGenericOutput = (call: ExpressionValue.functionCall): option<
a,
)->Some
| ("normalize", [EvDistribution(dist)]) => Helpers.toDistFn(Normalize, dist)
| ("logScore", [EvDistribution(a), EvDistribution(b)]) => Some(
runGenericOperation(FromDist(ToScore(LogScore(b)), a)),
)
| ("logScore", [EvDistribution(a), EvDistribution(b)]) =>
Some(runGenericOperation(FromDist(ToScore(LogScore(b)), a)))
| ("isNormalized", [EvDistribution(dist)]) => Helpers.toBoolFn(IsNormalized, dist)
| ("toPointSet", [EvDistribution(dist)]) => Helpers.toDistFn(ToPointSet, dist)
| ("scaleLog", [EvDistribution(dist)]) =>

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@ -96,7 +96,7 @@ module T = {
let fromZippedArray = (pairs: array<(float, float)>): t => pairs |> Belt.Array.unzip |> fromArray
let equallyDividedXs = (t: t, newLength) => E.A.Floats.range(minX(t), maxX(t), newLength)
let toJs = (t: t) => {"xs": t.xs, "ys": t.ys}
let filterYValues = (fn, t: t): t => t |> zip |> E.A.filter(((_,y)) => fn(y)) |> fromZippedArray
let filterYValues = (fn, t: t): t => t |> zip |> E.A.filter(((_, y)) => fn(y)) |> fromZippedArray
module Validator = {
let fnName = "XYShape validate"