Refactoring GenericOperation to prefer -> operator
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@ -37,9 +37,9 @@ describe("mixture", () => {
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test("on two normal distributions", () => {
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let result =
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run(#mixture([(normalDist10, 0.5), (normalDist20, 0.5)]))
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|> fmap(#fromDist(#toFloat(#Mean)))
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|> toFloat
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|> toExt
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->fmap(#fromDist(#toFloat(#Mean)))
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->toFloat
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->toExt
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expect(result)->toBeCloseTo(15.28)
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})
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})
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@ -48,15 +48,15 @@ describe("toPointSet", () => {
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test("on symbolic normal distribution", () => {
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let result =
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run(#fromDist(#toDist(#toPointSet), normalDist))
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|> fmap(#fromDist(#toFloat(#Mean)))
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|> toFloat
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|> toExt
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->fmap(#fromDist(#toFloat(#Mean)))
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->toFloat
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->toExt
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expect(result)->toBeCloseTo(5.09)
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})
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test("on sample set distribution with under 4 points", () => {
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let result =
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run(#fromDist(#toDist(#toPointSet), #SampleSet([0.0, 1.0, 2.0, 3.0]))) |> fmap(
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run(#fromDist(#toDist(#toPointSet), #SampleSet([0.0, 1.0, 2.0, 3.0])))->fmap(
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#fromDist(#toFloat(#Mean)),
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)
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expect(result)->toEqual(#Error(Other("Converting sampleSet to pointSet failed")))
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@ -65,11 +65,11 @@ describe("toPointSet", () => {
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test("on sample set", () => {
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let result =
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run(#fromDist(#toDist(#toPointSet), normalDist))
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|> fmap(#fromDist(#toDist(#toSampleSet(1000))))
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|> fmap(#fromDist(#toDist(#toPointSet)))
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|> fmap(#fromDist(#toFloat(#Mean)))
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|> toFloat
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|> toExt
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->fmap(#fromDist(#toDist(#toSampleSet(1000))))
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->fmap(#fromDist(#toDist(#toPointSet)))
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->fmap(#fromDist(#toFloat(#Mean)))
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->toFloat
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->toExt
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expect(result)->toBeCloseTo(5.09)
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})
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})
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@ -6,7 +6,7 @@ type toSampleSetFn = t => result<array<float>, error>
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type scaleMultiplyFn = (t, float) => result<t, error>
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type pointwiseAddFn = (t, t) => result<t, error>
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let sampleN = (n, t: t) =>
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let sampleN = (t: t, n) =>
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switch t {
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| #PointSet(r) => Ok(PointSetDist.sampleNRendered(n, r))
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| #Symbolic(r) => Ok(SymbolicDist.T.sampleN(n, r))
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@ -53,7 +53,7 @@ let defaultSamplingInputs: SamplingInputs.samplingInputs = {
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kernelWidth: None,
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}
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let toPointSet = (xyPointLength, t: t): result<PointSetTypes.pointSetDist, error> => {
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let toPointSet = (t, xyPointLength): result<PointSetTypes.pointSetDist, error> => {
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switch t {
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| #PointSet(pointSet) => Ok(pointSet)
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| #Symbolic(r) => Ok(SymbolicDist.T.toPointSetDist(xyPointLength, r))
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@ -5,7 +5,7 @@ type toSampleSetFn = t => result<array<float>, error>
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type scaleMultiplyFn = (t, float) => result<t, error>
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type pointwiseAddFn = (t, t) => result<t, error>
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let sampleN: (int, t) => result<array<float>, error>
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let sampleN: (t, int) => result<array<float>, error>
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let fromFloat: float => t
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@ -15,7 +15,7 @@ let normalize: t => t
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let operationToFloat: (toPointSetFn, Operation.distToFloatOperation, t) => result<float, error>
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let toPointSet: (int, t) => result<PointSetTypes.pointSetDist, error>
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let toPointSet: (t, int) => result<PointSetTypes.pointSetDist, error>
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let truncate: (toPointSetFn, option<float>, option<float>, t) => result<t, error>
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@ -16,6 +16,7 @@ type outputType = [
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| #String(string)
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]
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module Output = {
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let toDist = (o: outputType) =>
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switch o {
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@ -82,13 +83,14 @@ let rec run = (extra, fnName: operation): outputType => {
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reCall(
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~fnName=#fromDist(#toDistCombination(#Pointwise, #Multiply, #Float(weight)), r),
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(),
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) |> outputToDistResult
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) -> outputToDistResult
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let pointwiseAdd = (r1, r2) =>
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reCall(
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~fnName=#fromDist(#toDistCombination(#Pointwise, #Add, #Dist(r2)), r1),
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(),
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) |> outputToDistResult
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) -> outputToDistResult
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let fromDistFn = (subFn: GenericDist_Types.Operation.fromDist, dist: genericDist) =>
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switch subFn {
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@ -96,21 +98,21 @@ let rec run = (extra, fnName: operation): outputType => {
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GenericDist.operationToFloat(toPointSet, fnName, dist)
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|> E.R.fmap(r => #Float(r))
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|> fromResult
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| #toString => dist |> GenericDist.toString |> (r => #String(r))
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| #toString => dist -> GenericDist.toString -> (r => #String(r))
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| #toDist(#consoleLog) => {
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Js.log2("Console log requested: ", dist)
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#Dist(dist)
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}
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| #toDist(#normalize) => dist |> GenericDist.normalize |> (r => #Dist(r))
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| #toDist(#normalize) => dist -> GenericDist.normalize -> (r => #Dist(r))
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| #toDist(#truncate(left, right)) =>
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dist |> GenericDist.truncate(toPointSet, left, right) |> E.R.fmap(r => #Dist(r)) |> fromResult
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| #toDist(#toPointSet) =>
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dist
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|> GenericDist.toPointSet(xyPointLength)
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-> GenericDist.toPointSet(xyPointLength)
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|> E.R.fmap(r => #Dist(#PointSet(r)))
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|> fromResult
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| #toDist(#toSampleSet(n)) =>
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dist |> GenericDist.sampleN(n) |> E.R.fmap(r => #Dist(#SampleSet(r))) |> fromResult
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dist -> GenericDist.sampleN(n) |> E.R.fmap(r => #Dist(#SampleSet(r))) |> fromResult
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| #toDistCombination(#Algebraic, _, #Float(_)) => #Error(NotYetImplemented)
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| #toDistCombination(#Algebraic, operation, #Dist(dist2)) =>
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dist
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@ -142,8 +144,8 @@ let runFromFloat = (extra, fnName, float) => run(extra, #fromFloat(fnName, float
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let fmap = (
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extra,
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fn: GenericDist_Types.Operation.singleParamaterFunction,
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input: outputType,
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fn: GenericDist_Types.Operation.singleParamaterFunction,
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): outputType => {
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let newFnCall: result<operation, error> = switch (fn, input) {
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| (#fromDist(fromDist), #Dist(o)) => Ok(#fromDist(fromDist, o))
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@ -17,7 +17,7 @@ let runFromDist: (
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GenericDist_Types.genericDist,
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) => outputType
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let runFromFloat: (params, GenericDist_Types.Operation.fromDist, float) => outputType
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let fmap: (params, GenericDist_Types.Operation.singleParamaterFunction, outputType) => outputType
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let fmap: (params, outputType, GenericDist_Types.Operation.singleParamaterFunction) => outputType
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module Output: {
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let toDist: outputType => option<GenericDist_Types.genericDist>
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@ -78,11 +78,11 @@ module Operation = {
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| #toFloat(#Cdf(r)) => `cdf(${E.Float.toFixed(r)})`
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| #toFloat(#Inv(r)) => `inv(${E.Float.toFixed(r)})`
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| #toFloat(#Mean) => `mean`
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| #toFloat(#Pdf(r)) => `pdf${E.Float.toFixed(r)}`
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| #toFloat(#Pdf(r)) => `pdf(${E.Float.toFixed(r)})`
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| #toFloat(#Sample) => `sample`
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| #toDist(#normalize) => `normalize`
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| #toDist(#toPointSet) => `toPointSet`
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| #toDist(#toSampleSet(r)) => `toSampleSet${E.I.toString(r)}`
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| #toDist(#toSampleSet(r)) => `toSampleSet(${E.I.toString(r)})`
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| #toDist(#truncate(_, _)) => `truncate`
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| #toDist(#consoleLog) => `consoleLog`
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| #toString => `toString`
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@ -31,6 +31,8 @@ graph TD
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D --> Cauchy(Cauchy)
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```
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## Diagram of Generic Distribution Types
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## Todo
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- [ ] Lots of cleanup
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- [ ] Simple test story
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@ -41,4 +43,6 @@ graph TD
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- [ ] Remove most of DistPlus, much of which is not needed anymore
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- [ ] More functions for Sample Set, which is very minimal now
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- [ ] Allow these functions to be run on web workers
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- [ ] Refactor interpreter to use GenericDist. This might not be necessary, as the new reducer-inspired interpreter is integrated.
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- [ ] Refactor interpreter to use GenericDist. This might not be necessary, as the new reducer-inspired interpreter is integrated.
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## More todos
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