KLDivergence on discretes is passing

Value: [1e-3 to 2e-1]

packages/squiggle-lang/__tests__/Distributions/KlDivergence_test.res

@@ -68,9 +68,9 @@ describe("kl divergence on discrete distributions", () => {
   let float1 = 1.0
   let float2 = 2.0
   let float3 = 3.0
-  let point1 = mkDirac(float1)
-  let point2 = mkDirac(float2)
-  let point3 = mkDirac(float3)
+  let point1 = mkDelta(float1)
+  let point2 = mkDelta(float2)
+  let point3 = mkDelta(float3)
   test("finite kl divergence", () => {
     let answer = [(point1, 1e0), (point2, 1e0)]->mixture->run
     let prediction = [(point1, 1e0), (point2, 1e0), (point3, 1e0)]->mixture->run
@@ -94,7 +94,7 @@ describe("kl divergence on discrete distributions", () => {
     | _ => raise(MixtureFailed)
     }
     switch kl {
-    | Ok(kl') => kl'->expect->toEqual(neg_infinity)
+    | Ok(kl') => kl'->expect->toEqual(infinity)
     | Error(err) =>
       Js.Console.log(DistributionTypes.Error.toString(err))
       raise(KlFailed)
@@ -102,9 +102,9 @@ describe("kl divergence on discrete distributions", () => {
   })
 })
 
-describe("combine along support test", () => {
+describe("combineAlongSupportOfSecondArgument", () => {
   // This tests the version of the function that we're NOT using. Haven't deleted the test in case we use the code later.
-  test("combine along support test", _ => {
+  test("test on two uniforms", _ => {
     let combineAlongSupportOfSecondArgument = XYShape.PointwiseCombination.combineAlongSupportOfSecondArgument0
     let lowAnswer = 0.0
     let highAnswer = 1.0

packages/squiggle-lang/__tests__/TestHelpers.res

@@ -51,7 +51,7 @@ let mkExponential = rate => DistributionTypes.Symbolic(#Exponential({rate: rate}
 let mkUniform = (low, high) => DistributionTypes.Symbolic(#Uniform({low: low, high: high}))
 let mkCauchy = (local, scale) => DistributionTypes.Symbolic(#Cauchy({local: local, scale: scale}))
 let mkLognormal = (mu, sigma) => DistributionTypes.Symbolic(#Lognormal({mu: mu, sigma: sigma}))
-let mkDirac = x => DistributionTypes.Symbolic(#Float(x))
+let mkDelta = x => DistributionTypes.Symbolic(#Float(x))
 
 let normalMake = SymbolicDist.Normal.make
 let betaMake = SymbolicDist.Beta.make

packages/squiggle-lang/src/rescript/Distributions/PointSetDist/Discrete.res

@@ -50,7 +50,7 @@ let combinePointwise = (
 
   make(
     combiner(fn, XYShape.XtoY.discreteInterpolator, t1.xyShape, t2.xyShape)->E.R.toExn(
-      "Addition operation should never fail",
+      "Logically unreachable?",
       _,
     ),
   )->Ok
@@ -163,7 +163,6 @@ module T = Dist({
     }
 
   let integralEndY = (t: t) => t.integralSumCache |> E.O.default(t |> integral |> Continuous.lastY)
-  let integralEndYResult = (t: t) => t->integralEndY->Ok
   let minX = shapeFn(XYShape.T.minX)
   let maxX = shapeFn(XYShape.T.maxX)
   let toDiscreteProbabilityMassFraction = _ => 1.0
@@ -229,25 +228,10 @@ module T = Dist({
   }
 
   let klDivergence = (prediction: t, answer: t) => {
-    let massOrZero = (t: t, x: float): float => {
-      let i = E.A.findIndex(x' => x' == x, t.xyShape.xs)
-      switch i {
-      | None => 0.0
-      | Some(i') => t.xyShape.ys[i']
-      }
-    }
-    let predictionNewYs = E.A.fmap(massOrZero(answer), prediction.xyShape.xs)
-    let integrand = XYShape.PointwiseCombination.combine(
-      PointSetDist_Scoring.KLDivergence.integrand,
-      XYShape.XtoY.continuousInterpolator(#Stepwise, #UseZero),
-      {XYShape.xs: answer.xyShape.xs, XYShape.ys: predictionNewYs},
-      answer.xyShape,
-    )
-    let xyShapeToDiscrete: XYShape.xyShape => t = xyShape => {
-      xyShape: xyShape,
-      integralSumCache: None,
-      integralCache: None,
-    }
-    integrand->E.R2.fmap(x => x->xyShapeToDiscrete->integralEndY)
+    combinePointwise(
+      ~fn=PointSetDist_Scoring.KLDivergence.integrand,
+      prediction,
+      answer,
+    )->E.R2.fmap(integralEndY)
   }
 })

packages/squiggle-lang/src/rescript/Distributions/PointSetDist/Mixed.res

@@ -302,9 +302,10 @@ module T = Dist({
   }
 
   let klDivergence = (prediction: t, answer: t) => {
-    combinePointwise(PointSetDist_Scoring.KLDivergence.integrand, prediction, answer) |> E.R.fmap(
-      integralEndY,
-    )
+    Error(Operation.NotYetImplemented)
+    //    combinePointwise(PointSetDist_Scoring.KLDivergence.integrand, prediction, answer) |> E.R.fmap(
+    //     integralEndY,
+    //   )
   }
 })
 

packages/squiggle-lang/src/rescript/Distributions/PointSetDist/PointSetDist_Scoring.res

@@ -7,6 +7,8 @@ module KLDivergence = {
     // We decided that negative infinity, not an error at answerElement = 0.0, is a desirable value.
     if answerElement == 0.0 {
       Ok(0.0)
+    } else if predictionElement == 0.0 {
+      Ok(infinity)
     } else {
       let quot = predictionElement /. answerElement
       quot < 0.0 ? Error(Operation.ComplexNumberError) : Ok(-.answerElement *. logFn(quot))