fix: SampleSet.fromDist works for discrete and mixed
This commit is contained in:
		
							parent
							
								
									462f1c9649
								
							
						
					
					
						commit
						93f4c1e0c2
					
				|  | @ -31,9 +31,9 @@ let isSymbolic = (t: t) => | |||
| 
 | ||||
| let sampleN = (t: t, n) => | ||||
|   switch t { | ||||
|   | PointSet(r) => PointSetDist.sampleNRendered(n, r) | ||||
|   | Symbolic(r) => SymbolicDist.T.sampleN(n, r) | ||||
|   | PointSet(r) => PointSetDist.T.sampleN(r,n) | ||||
|   | SampleSet(r) => SampleSetDist.sampleN(r, n) | ||||
|   | Symbolic(r) => SymbolicDist.T.sampleN(n, r) | ||||
|   } | ||||
| 
 | ||||
| let sample = (t: t) => sampleN(t, 1)->E.A.first |> E.O.toExn("Should not have happened") | ||||
|  |  | |||
|  | @ -270,6 +270,25 @@ module T = Dist({ | |||
|   } | ||||
|   let variance = (t: t): float => | ||||
|     XYShape.Analysis.getVarianceDangerously(t, mean, Analysis.getMeanOfSquares) | ||||
| 
 | ||||
| let doN = (n, fn) => { | ||||
|   let items = Belt.Array.make(n, 0.0) | ||||
|   for x in 0 to n - 1 { | ||||
|     let _ = Belt.Array.set(items, x, fn()) | ||||
|   } | ||||
|   items | ||||
| } | ||||
| 
 | ||||
| let sample = (t: t): float => { | ||||
|   let randomItem = Random.float(1.0) | ||||
|   t |> integralYtoX(randomItem) | ||||
| } | ||||
| 
 | ||||
| let sampleN = (dist, n) => { | ||||
|   let integralCache = integral(dist) | ||||
|   let distWithUpdatedIntegralCache = updateIntegralCache(Some(integralCache), dist) | ||||
|   doN(n, () => sample(distWithUpdatedIntegralCache)) | ||||
| } | ||||
| }) | ||||
| 
 | ||||
| let isNormalized = (t: t): bool => { | ||||
|  |  | |||
|  | @ -223,9 +223,9 @@ module T = Dist({ | |||
|     let getMeanOfSquares = t => t |> shapeMap(XYShape.T.square) |> mean | ||||
|     XYShape.Analysis.getVarianceDangerously(t, mean, getMeanOfSquares) | ||||
|   } | ||||
| }) | ||||
| 
 | ||||
| let sampleN = (t: t, n): array<float> => { | ||||
|   let normalized = t->T.normalize->getShape | ||||
|   let normalized = t->normalize->getShape | ||||
|   Stdlib.Random.sample(normalized.xs, {probs: normalized.ys, size: n}) | ||||
| } | ||||
| }) | ||||
|  |  | |||
|  | @ -33,6 +33,7 @@ module type dist = { | |||
| 
 | ||||
|   let mean: t => float | ||||
|   let variance: t => float | ||||
|   let sampleN: (t, int) => array<float> | ||||
| } | ||||
| 
 | ||||
| module Dist = (T: dist) => { | ||||
|  | @ -64,6 +65,8 @@ module Dist = (T: dist) => { | |||
|     let yToX = T.integralYtoX | ||||
|     let sum = T.integralEndY | ||||
|   } | ||||
| 
 | ||||
|   let sampleN = T.sampleN | ||||
| } | ||||
| 
 | ||||
| module Common = { | ||||
|  |  | |||
|  | @ -270,38 +270,47 @@ module T = Dist({ | |||
|     }) | ||||
|   } | ||||
| 
 | ||||
|   let mean = ({discrete, continuous}: t): float => { | ||||
|   let discreteIntegralSum =({discrete}: t): float => Discrete.T.Integral.sum(discrete) | ||||
|   let continuousIntegralSum =({continuous}: t): float => Continuous.T.Integral.sum(continuous) | ||||
|   let integralSum =(t:t): float => discreteIntegralSum(t) +. continuousIntegralSum(t) | ||||
| 
 | ||||
|   let mean = ({discrete, continuous} as t: t): float => { | ||||
|     let discreteMean = Discrete.T.mean(discrete) | ||||
|     let continuousMean = Continuous.T.mean(continuous) | ||||
| 
 | ||||
|     // the combined mean is the weighted sum of the two: | ||||
|     let discreteIntegralSum = Discrete.T.Integral.sum(discrete) | ||||
|     let continuousIntegralSum = Continuous.T.Integral.sum(continuous) | ||||
|     let totalIntegralSum = discreteIntegralSum +. continuousIntegralSum | ||||
| 
 | ||||
|     (discreteMean *. discreteIntegralSum +. continuousMean *. continuousIntegralSum) /. | ||||
|       totalIntegralSum | ||||
|     (discreteMean *. discreteIntegralSum(t) +. continuousMean *. continuousIntegralSum(t)) /. | ||||
|       integralSum(t) | ||||
|   } | ||||
| 
 | ||||
|   let variance = ({discrete, continuous} as t: t): float => { | ||||
|     // the combined mean is the weighted sum of the two: | ||||
|     let discreteIntegralSum = Discrete.T.Integral.sum(discrete) | ||||
|     let continuousIntegralSum = Continuous.T.Integral.sum(continuous) | ||||
|     let totalIntegralSum = discreteIntegralSum +. continuousIntegralSum | ||||
| 
 | ||||
|     let _discreteIntegralSum = discreteIntegralSum(t) | ||||
|     let _integralSum = integralSum(t) | ||||
|     let getMeanOfSquares = ({discrete, continuous}: t) => { | ||||
|       let discreteMean = discrete |> Discrete.shapeMap(XYShape.T.square) |> Discrete.T.mean | ||||
|       let continuousMean = continuous |> Continuous.Analysis.getMeanOfSquares | ||||
|       (discreteMean *. discreteIntegralSum +. continuousMean *. continuousIntegralSum) /. | ||||
|         totalIntegralSum | ||||
|       let continuousMean = continuous -> Continuous.Analysis.getMeanOfSquares | ||||
|       (discreteMean *. discreteIntegralSum(t) +. continuousMean *. continuousIntegralSum(t)) /. | ||||
|         integralSum(t) | ||||
|     } | ||||
| 
 | ||||
|     switch discreteIntegralSum /. totalIntegralSum { | ||||
|     switch _discreteIntegralSum /. _integralSum { | ||||
|     | 1.0 => Discrete.T.variance(discrete) | ||||
|     | 0.0 => Continuous.T.variance(continuous) | ||||
|     | _ => XYShape.Analysis.getVarianceDangerously(t, mean, getMeanOfSquares) | ||||
|     } | ||||
|   } | ||||
|    | ||||
|   let sampleN = (t: t, n:int): array<float> => { | ||||
|     let discreteIntegralSum = discreteIntegralSum(t); | ||||
|     let integralSum = integralSum(t); | ||||
|     let discreteSampleLength:int = (Js.Int.toFloat(n) *. discreteIntegralSum /. integralSum) -> E.Float.toInt | ||||
|     let continuousSampleLength = n - discreteSampleLength; | ||||
|     let continuousSamples = t.continuous ->Continuous.T.normalize-> Continuous.T.sampleN( continuousSampleLength) | ||||
|     let discreteSamples = t.discrete ->Discrete.T.normalize->Discrete.T.sampleN(discreteSampleLength) | ||||
|     Js.log3("Samples", continuousSamples, discreteSamples); | ||||
|     E.A.concat(discreteSamples, continuousSamples) -> E.A.shuffle | ||||
|   } | ||||
| }) | ||||
| 
 | ||||
| let combineAlgebraically = (op: Operation.convolutionOperation, t1: t, t2: t): t => { | ||||
|  |  | |||
|  | @ -198,6 +198,13 @@ module T = Dist({ | |||
|     | Discrete(m) => Discrete.T.variance(m) | ||||
|     | Continuous(m) => Continuous.T.variance(m) | ||||
|     } | ||||
| 
 | ||||
|   let sampleN = (t: t, int): array<float> => | ||||
|     switch t { | ||||
|     | Mixed(m) => Mixed.T.sampleN(m,int) | ||||
|     | Discrete(m) => Discrete.T.sampleN(m,int) | ||||
|     | Continuous(m) => Continuous.T.sampleN(m,int) | ||||
|     } | ||||
| }) | ||||
| 
 | ||||
| let logScore = (args: PointSetDist_Scoring.scoreArgs): result<float, Operation.Error.t> => | ||||
|  | @ -235,12 +242,6 @@ let isFloat = (t: t) => | |||
|   | _ => false | ||||
|   } | ||||
| 
 | ||||
| let sampleNRendered = (n, dist) => { | ||||
|   let integralCache = T.Integral.get(dist) | ||||
|   let distWithUpdatedIntegralCache = T.updateIntegralCache(Some(integralCache), dist) | ||||
|   doN(n, () => sample(distWithUpdatedIntegralCache)) | ||||
| } | ||||
| 
 | ||||
| let operate = (distToFloatOp: Operation.distToFloatOperation, s): float => | ||||
|   switch distToFloatOp { | ||||
|   | #Pdf(f) => pdf(f, s) | ||||
|  |  | |||
|  | @ -139,7 +139,7 @@ let mixture = (values: array<(t, float)>, intendedLength: int) => { | |||
|     ->Belt.Array.mapWithIndex((i, (_, weight)) => (E.I.toFloat(i), weight /. totalWeight)) | ||||
|     ->XYShape.T.fromZippedArray | ||||
|     ->Discrete.make | ||||
|     ->Discrete.sampleN(intendedLength) | ||||
|     ->Discrete.T.sampleN(intendedLength) | ||||
|   let dists = values->E.A2.fmap(E.Tuple2.first)->E.A2.fmap(T.get) | ||||
|   let samples = | ||||
|     discreteSamples | ||||
|  |  | |||
|  | @ -559,6 +559,7 @@ module A = { | |||
|   let isEmpty = r => length(r) < 1 | ||||
|   let stableSortBy = Belt.SortArray.stableSortBy | ||||
|   let toNoneIfEmpty = r => isEmpty(r) ? None : Some(r) | ||||
|   let shuffle = Belt.Array.shuffle | ||||
|   let toRanges = (a: array<'a>) => | ||||
|     switch a |> Belt.Array.length { | ||||
|     | 0 | ||||
|  |  | |||
		Loading…
	
		Reference in New Issue
	
	Block a user