Added docstrings and cleanup
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@ -2,7 +2,7 @@ open Jest
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open TestHelpers
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open TestHelpers
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let prepareInputs = (ar, minWeight) =>
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let prepareInputs = (ar, minWeight) =>
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E.A.Sorted.Floats.splitContinuousAndDiscreteForMinWeight(ar, minWeight) |> (
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E.A.Sorted.Floats.splitContinuousAndDiscreteForMinWeight(ar, ~minDiscreteWeight=minWeight) |> (
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((c, disc)) => (c, disc |> E.FloatFloatMap.toArray)
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((c, disc)) => (c, disc |> E.FloatFloatMap.toArray)
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)
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)
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@ -33,14 +33,14 @@ describe("Continuous and discrete splits", () => {
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let (_, discrete1) = E.A.Sorted.Floats.splitContinuousAndDiscreteForMinWeight(
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let (_, discrete1) = E.A.Sorted.Floats.splitContinuousAndDiscreteForMinWeight(
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makeDuplicatedArray(10),
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makeDuplicatedArray(10),
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2,
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~minDiscreteWeight=2,
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)
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)
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let toArr1 = discrete1 |> E.FloatFloatMap.toArray
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let toArr1 = discrete1 |> E.FloatFloatMap.toArray
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makeTest("splitMedium at count=10", toArr1 |> Belt.Array.length, 10)
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makeTest("splitMedium at count=10", toArr1 |> Belt.Array.length, 10)
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let (_c, discrete2) = E.A.Sorted.Floats.splitContinuousAndDiscreteForMinWeight(
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let (_c, discrete2) = E.A.Sorted.Floats.splitContinuousAndDiscreteForMinWeight(
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makeDuplicatedArray(500),
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makeDuplicatedArray(500),
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2,
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~minDiscreteWeight=2,
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)
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)
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let toArr2 = discrete2 |> E.FloatFloatMap.toArray
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let toArr2 = discrete2 |> E.FloatFloatMap.toArray
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makeTest("splitMedium at count=500", toArr2 |> Belt.Array.length, 500)
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makeTest("splitMedium at count=500", toArr2 |> Belt.Array.length, 500)
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@ -63,8 +63,11 @@ let toPointSetDist = (
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(),
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(),
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): Internals.Types.outputs => {
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): Internals.Types.outputs => {
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Array.fast_sort(compare, samples)
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Array.fast_sort(compare, samples)
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let minDiscreteToKeep = max(2, E.A.length(samples) / 10);
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let minDiscreteToKeep = MagicNumbers.ToPointSet.minDiscreteToKeep(samples)
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let (continuousPart, discretePart) = E.A.Sorted.Floats.splitContinuousAndDiscreteForMinWeight(samples, minDiscreteToKeep)
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let (continuousPart, discretePart) = E.A.Sorted.Floats.splitContinuousAndDiscreteForMinWeight(
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samples,
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~minDiscreteWeight=minDiscreteToKeep,
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)
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let length = samples |> E.A.length |> float_of_int
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let length = samples |> E.A.length |> float_of_int
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let discrete: PointSetTypes.discreteShape =
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let discrete: PointSetTypes.discreteShape =
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discretePart
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discretePart
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@ -22,3 +22,16 @@ module OpCost = {
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let wildcardCost = 1000
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let wildcardCost = 1000
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let monteCarloCost = Environment.defaultSampleCount
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let monteCarloCost = Environment.defaultSampleCount
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}
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}
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module ToPointSet = {
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/*
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This function chooses the minimum amount of duplicate samples that need
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to exist in order for this to be considered discrete. The tricky thing
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is that there are some operations that create duplicate continuous samples,
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so we can't guarantee that these only will occur because the fundamental
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structure is meant to be discrete. I chose this heuristic because I think
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it would strike a reasonable trade-off, but I’m really unsure what’s
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best right now.
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*/
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let minDiscreteToKeep = samples => max(20, E.A.length(samples) / 50)
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}
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@ -522,7 +522,12 @@ module A = {
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let makeIncrementalDown = (a, b) =>
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let makeIncrementalDown = (a, b) =>
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Array.make(a - b + 1, a) |> Array.mapi((i, c) => c - i) |> Belt.Array.map(_, float_of_int)
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Array.make(a - b + 1, a) |> Array.mapi((i, c) => c - i) |> Belt.Array.map(_, float_of_int)
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let splitContinuousAndDiscreteForDuplicates = (sortedArray: array<float>) => {
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/*
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This function goes through a sorted array and divides it into two different clusters:
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continuous samples and discrete samples. The discrete samples are stored in a mutable map.
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Samples are thought to be discrete if they have any duplicates.
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*/
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let _splitContinuousAndDiscreteForDuplicates = (sortedArray: array<float>) => {
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let continuous: array<float> = []
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let continuous: array<float> = []
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let discrete = FloatFloatMap.empty()
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let discrete = FloatFloatMap.empty()
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Belt.Array.forEachWithIndex(sortedArray, (index, element) => {
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Belt.Array.forEachWithIndex(sortedArray, (index, element) => {
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@ -545,11 +550,18 @@ module A = {
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(continuous, discrete)
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(continuous, discrete)
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}
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}
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/*
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This function works very similarly to splitContinuousAndDiscreteForDuplicates. The one major difference
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is that you can specify a minDiscreteWeight. If the min discreet weight is 4, that would mean that
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at least four elements needed from a specific value for that to be kept as discrete. This is important
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because in some cases, we can expect that some common elements will be generated by regular operations.
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The final continous array will be sorted.
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*/
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let splitContinuousAndDiscreteForMinWeight = (
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let splitContinuousAndDiscreteForMinWeight = (
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sortedArray: array<float>,
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sortedArray: array<float>,
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minDiscreteWeight: int,
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~minDiscreteWeight: int,
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) => {
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) => {
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let (continuous, discrete) = splitContinuousAndDiscreteForDuplicates(sortedArray)
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let (continuous, discrete) = _splitContinuousAndDiscreteForDuplicates(sortedArray)
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let keepFn = v => Belt.Float.toInt(v) >= minDiscreteWeight
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let keepFn = v => Belt.Float.toInt(v) >= minDiscreteWeight
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let (discreteToKeep, discreteToIntegrate) = FloatFloatMap.partition(
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let (discreteToKeep, discreteToIntegrate) = FloatFloatMap.partition(
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((_, v)) => keepFn(v),
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((_, v)) => keepFn(v),
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@ -559,7 +571,6 @@ module A = {
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discreteToIntegrate->FloatFloatMap.toArray
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discreteToIntegrate->FloatFloatMap.toArray
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|> fmap(((k, v)) => Belt.Array.makeBy(Belt.Float.toInt(v), _ => k))
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|> fmap(((k, v)) => Belt.Array.makeBy(Belt.Float.toInt(v), _ => k))
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|> Belt.Array.concatMany
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|> Belt.Array.concatMany
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let newContinuous = concat(continuous, newContinousSamples)
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let newContinuous = concat(continuous, newContinousSamples)
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newContinuous |> Array.fast_sort(floatCompare)
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newContinuous |> Array.fast_sort(floatCompare)
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(newContinuous, discreteToKeep)
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(newContinuous, discreteToKeep)
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