Fleshed out AlgebraicCombination

packages/squiggle-lang/src/rescript/pointSetDist/AlgebraicShapeCombination.res

@@ -115,6 +115,7 @@ let combineShapesContinuousContinuous = (
   | #Multiply => (m1, m2) => m1 *. m2
   | #Divide => (m1, mInv2) => m1 *. mInv2
   | #Exponentiate => (m1, mInv2) => m1 ** mInv2
+  | #Log => (m1, m2) => log(m1) /. log(m2)
   } // note: here, mInv2 = mean(1 / t2) ~= 1 / mean(t2)
 
   // TODO: I don't know what the variances are for exponentatiation
@@ -232,6 +233,7 @@ let combineShapesContinuousDiscrete = (
     }
   | #Multiply
   | #Exponentiate
+  | #Log
   | #Divide =>
     for j in 0 to t2n - 1 {
       // creates a new continuous shape for each one of the discrete points, and collects them in outXYShapes.

packages/squiggle-lang/src/rescript/pointSetDist/PointSetDist.res

@@ -41,7 +41,8 @@ let combineAlgebraically = (op: Operation.algebraicOperation, t1: t, t2: t): t =
   | (Continuous(m1), Discrete(m2))
   | (Discrete(m2), Continuous(m1)) =>
     Continuous.combineAlgebraicallyWithDiscrete(op, m1, m2) |> Continuous.T.toPointSetDist
-  | (Discrete(m1), Discrete(m2)) => Discrete.combineAlgebraically(op, m1, m2) |> Discrete.T.toPointSetDist
+  | (Discrete(m1), Discrete(m2)) =>
+    Discrete.combineAlgebraically(op, m1, m2) |> Discrete.T.toPointSetDist
   | (m1, m2) => Mixed.combineAlgebraically(op, toMixed(m1), toMixed(m2)) |> Mixed.T.toPointSetDist
   }
 

packages/squiggle-lang/src/rescript/sci.res

@@ -55,12 +55,6 @@ module OperationType = {
     | #Sample(int)
   ]
 
-  type scale = [
-    | #Multiply
-    | #Exponentiate
-    | #Log
-  ]
-
   type t = [
     | #toFloat(toFloat)
     | #toDist(toDist)
@@ -73,6 +67,7 @@ type operation = OperationType.t
 module T = {
   type t = genericDist
   type toPointSetFn = genericDist => result<PointSetTypes.pointSetDist, error>
+  type toSampleSetFn = genericDist => result<array<float>, error>
   let sampleN = (n, t: t) => {
     switch t {
     | #PointSet(r) => Ok(PointSetDist.sampleNRendered(n, r))
@@ -81,7 +76,7 @@ module T = {
     }
   }
 
-  let toFloat = (toPointSet: toPointSetFn, fnName, t: genericDist) => {
+  let toFloat = (toPointSet: toPointSetFn, fnName, t: genericDist): result<float, error> => {
     switch t {
     | #Symbolic(r) if Belt.Result.isOk(SymbolicDist.T.operate(fnName, r)) =>
       switch SymbolicDist.T.operate(fnName, r) {
@@ -104,7 +99,7 @@ module T = {
     kernelWidth: None,
   }
 
-  let toPointSet = (xyPointLength, t: t) => {
+  let toPointSet = (xyPointLength, t: t): result<PointSetTypes.pointSetDist, error> => {
     switch t {
     | #PointSet(pointSet) => Ok(pointSet)
     | #Symbolic(r) => Ok(SymbolicDist.T.toPointSetDist(xyPointLength, r))
@@ -122,16 +117,82 @@ module T = {
     }
   }
 
-  let algebraicCombination = (operation, sampleCount, dist1: t, dist2: t) => {
+  module AlgebraicCombination = {
-    let dist1 = sampleN(sampleCount, dist1)
+    let tryAnalyticalSimplification = (operation: OperationType.combination, t1: t, t2: t): option<
-    let dist2 = sampleN(sampleCount, dist2)
+      result<SymbolicDistTypes.symbolicDist, string>,
-    let samples = E.R.merge(dist1, dist2) |> E.R.fmap(((d1, d2)) => {
+    > =>
-      Belt.Array.zip(d1, d2) |> E.A.fmap(((a, b)) => Operation.Algebraic.toFn(operation, a, b))
+      switch (operation, t1, t2) {
-    })
+      | (operation, #Symbolic(d1), #Symbolic(d2)) =>
-    samples |> E.R.fmap(r => #SampleSet(r))
+        switch SymbolicDist.T.tryAnalyticalSimplification(d1, d2, operation) {
+        | #AnalyticalSolution(symbolicDist) => Some(Ok(symbolicDist))
+        | #Error(er) => Some(Error(er))
+        | #NoSolution => None
+        }
+      | _ => None
       }
 
-  let pointwiseCombination = (toPointSet: toPointSetFn, operation, t1: t, t2: t) => {
+    let runConvolution = (
+      toPointSet: toPointSetFn,
+      operation: OperationType.combination,
+      t1: t,
+      t2: t,
+    ) =>
+      E.R.merge(toPointSet(t1), toPointSet(t2)) |> E.R.fmap(((a, b)) =>
+        PointSetDist.combineAlgebraically(operation, a, b)
+      )
+
+    let runMonteCarlo = (
+      toSampleSet: toSampleSetFn,
+      operation: OperationType.combination,
+      t1: t,
+      t2: t,
+    ) => {
+      E.R.merge(toSampleSet(t1), toSampleSet(t2)) |> E.R.fmap(((a, b)) => {
+        Belt.Array.zip(a, b) |> E.A.fmap(((a, b)) => Operation.Algebraic.toFn(operation, a, b))
+      })
+    }
+
+    //I'm (Ozzie) really just guessing here, very little idea what's best
+    let expectedConvolutionCost: t => int = x =>
+      switch x {
+      | #Symbolic(#Float(_)) => 1
+      | #Symbolic(_) => 1000
+      | #PointSet(Discrete(m)) => m.xyShape |> XYShape.T.length
+      | #PointSet(Mixed(_)) => 1000
+      | #PointSet(Continuous(_)) => 1000
+      | _ => 1000
+      }
+
+    let chooseConvolutionOrMonteCarlo = (t1: t, t2: t) =>
+      expectedConvolutionCost(t1) * expectedConvolutionCost(t2) > 10000
+        ? #CalculateWithMonteCarlo
+        : #CalculateWithConvolution
+
+    let run = (
+      toPointSet: toPointSetFn,
+      toSampleSet: toSampleSetFn,
+      algebraicOp,
+      t1: t,
+      t2: t,
+    ): result<t, error> => {
+      switch tryAnalyticalSimplification(algebraicOp, t1, t2) {
+      | Some(Ok(symbolicDist)) => Ok(#Symbolic(symbolicDist))
+      | Some(Error(e)) => Error(Other(e))
+      | None =>
+        switch chooseConvolutionOrMonteCarlo(t1, t2) {
+        | #CalculateWithMonteCarlo =>
+          runMonteCarlo(toSampleSet, algebraicOp, t1, t2) |> E.R.fmap(r => #SampleSet(r))
+        | #CalculateWithConvolution =>
+          runConvolution(toPointSet, algebraicOp, t1, t2) |> E.R.fmap(r => #PointSet(r))
+        }
+      }
+    }
+  }
+
+  let pointwiseCombination = (toPointSet: toPointSetFn, operation, t1: t, t2: t): result<
+    t,
+    error,
+  > => {
     E.R.merge(toPointSet(t1), toPointSet(t2))
     |> E.R.fmap(((t1, t2)) =>
       PointSetDist.combinePointwise(OperationType.combinationToFn(operation), t1, t2)
@@ -144,11 +205,12 @@ module T = {
     operation: OperationType.combination,
     t: t,
     f: float,
-  ) => {
+  ): result<t, error> => {
     switch operation {
     | #Add | #Subtract => Error(DistributionVerticalShiftIsInvalid)
     | (#Multiply | #Divide | #Exponentiate | #Log) as operation =>
       toPointSet(t) |> E.R.fmap(t => {
+        //TODO: Move to PointSet codebase
         let fn = (secondary, main) => Operation.Scale.toFn(operation, main, secondary)
         let integralSumCacheFn = Operation.Scale.toIntegralSumCacheFn(operation)
         let integralCacheFn = Operation.Scale.toIntegralCacheFn(operation)
@@ -159,7 +221,7 @@ module T = {
           t,
         )
       })
-    }
+    } |> E.R.fmap(r => #PointSet(r))
   }
 }
 
@@ -188,10 +250,10 @@ module OmniRunner = {
     | Error(e) => #Error(e)
     }
 
-  let rec applyFnInternal = (wrapped: wrapped, fnName: operation): outputType => {
+  let rec run = (wrapped: wrapped, fnName: operation): outputType => {
     let (value, {sampleCount, xyPointLength} as extra) = wrapped
     let reCall = (~value=value, ~extra=extra, ~fnName=fnName, ()) => {
-      applyFnInternal((value, extra), fnName)
+      run((value, extra), fnName)
     }
     let toPointSet = r => {
       switch reCall(~value=r, ~fnName=#toDist(#toPointSet), ()) {
@@ -200,8 +262,14 @@ module OmniRunner = {
       | _ => Error(Other("Impossible error"))
       }
     }
-    let toPointSetAndReCall = v => toPointSet(v) |> E.R.fmap(r => reCall(~value=#PointSet(r), ()))
+    let toSampleSet = r => {
-    let newVal: outputType = switch (fnName, value) {
+      switch reCall(~value=r, ~fnName=#toDist(#toSampleSet(sampleCount)), ()) {
+      | #Dist(#SampleSet(p)) => Ok(p)
+      | #Error(r) => Error(r)
+      | _ => Error(Other("Impossible error"))
+      }
+    }
+    switch (fnName, value) {
     // | (#toFloat(n), v) => toFloat(toPointSet, v, n)
     | (#toFloat(fnName), _) =>
       T.toFloat(toPointSet, fnName, value) |> E.R.fmap(r => #Float(r)) |> fromResult
@@ -214,17 +282,16 @@ module OmniRunner = {
       value |> T.sampleN(n) |> E.R.fmap(r => #Dist(#SampleSet(r))) |> fromResult
     | (#toDistCombination(#Algebraic, _, #Float(_)), _) => #Error(NotYetImplemented)
     | (#toDistCombination(#Algebraic, operation, #Dist(p2)), p1) =>
-      T.algebraicCombination(operation, sampleCount, p1, p2)
+      T.AlgebraicCombination.run(toPointSet, toSampleSet, operation, p1, p2)
       |> E.R.fmap(r => #Dist(r))
       |> fromResult
     | (#toDistCombination(#Pointwise, operation, #Dist(p2)), p1) =>
       T.pointwiseCombination(toPointSet, operation, p1, p2) |> E.R.fmap(r => #Dist(r)) |> fromResult
     | (#toDistCombination(#Pointwise, operation, #Float(f)), _) =>
       T.pointwiseCombinationFloat(toPointSet, operation, value, f)
-      |> E.R.fmap(r => #Dist(#PointSet(r)))
+      |> E.R.fmap(r => #Dist(r))
       |> fromResult
     }
-    newVal
   }
 }