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Organized AlgebraicCombination functionality into submodules

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This commit is contained in:
Ozzie Gooen 2022-04-27 12:48:46 -04:00
parent d104494f02
commit 6045fe5e62
2 changed files with 157 additions and 129 deletions
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176
packages/squiggle-lang/src/rescript/Distributions/GenericDist/GenericDist.res
View File

@ -147,30 +147,7 @@ let truncate = Truncate.run
TODO: It would be useful to be able to pass in a paramater to get this to run either with convolution or monte carlo.
*/
module AlgebraicCombination = {
let runConvolution = (
toPointSet: toPointSetFn,
arithmeticOperation: Operation.convolutionOperation,
t1: t,
t2: t,
) =>
E.R.merge(toPointSet(t1), toPointSet(t2))->E.R2.fmap(((a, b)) =>
PointSetDist.combineAlgebraically(arithmeticOperation, a, b)
)
let runMonteCarlo = (
toSampleSet: toSampleSetFn,
arithmeticOperation: Operation.algebraicOperation,
t1: t,
t2: t,
): result<t, error> => {
let fn = Operation.Algebraic.toFn(arithmeticOperation)
E.R.merge(toSampleSet(t1), toSampleSet(t2))
->E.R.bind(((t1, t2)) => {
SampleSetDist.map2(~fn, ~t1, ~t2)->E.R2.errMap(x => DistributionTypes.OperationError(x))
})
->E.R2.fmap(r => DistributionTypes.SampleSet(r))
}
module InputValidator = {
/*
It would be good to also do a check to make sure that probability mass for the second
operand, at value 1.0, is 0 (or approximately 0). However, we'd ideally want to check
@ -201,18 +178,55 @@ module AlgebraicCombination = {
}
}
let getInvalidOperationError = (
t1: t,
t2: t,
~toPointSetFn: toPointSetFn,
~arithmeticOperation,
): option<error> => {
let run = (t1: t, t2: t, ~toPointSetFn: toPointSetFn, ~arithmeticOperation): option<error> => {
if arithmeticOperation == #Logarithm {
getLogarithmInputError(t1, t2, ~toPointSetFn)
} else {
None
}
}
}
module StrategyCallOnValidatedInputs = {
let convolution = (
toPointSet: toPointSetFn,
arithmeticOperation: Operation.convolutionOperation,
t1: t,
t2: t,
): result<t, error> =>
E.R.merge(toPointSet(t1), toPointSet(t2))
->E.R2.fmap(((a, b)) => PointSetDist.combineAlgebraically(arithmeticOperation, a, b))
->E.R2.fmap(r => DistributionTypes.PointSet(r))
let monteCarlo = (
toSampleSet: toSampleSetFn,
arithmeticOperation: Operation.algebraicOperation,
t1: t,
t2: t,
): result<t, error> => {
let fn = Operation.Algebraic.toFn(arithmeticOperation)
E.R.merge(toSampleSet(t1), toSampleSet(t2))
->E.R.bind(((t1, t2)) => {
SampleSetDist.map2(~fn, ~t1, ~t2)->E.R2.errMap(x => DistributionTypes.OperationError(x))
})
->E.R2.fmap(r => DistributionTypes.SampleSet(r))
}
let symbolic = (
arithmeticOperation: Operation.algebraicOperation,
t1: t,
t2: t,
): SymbolicDistTypes.analyticalSimplificationResult => {
switch (t1, t2) {
| (DistributionTypes.Symbolic(d1), DistributionTypes.Symbolic(d2)) =>
SymbolicDist.T.tryAnalyticalSimplification(d1, d2, arithmeticOperation)
| _ => #NoSolution
}
}
}
module StrategyChooser = {
type specificStrategy = [#AsSymbolic | #AsMonteCarlo | #AsConvolution]
//I'm (Ozzie) really just guessing here, very little idea what's best
let expectedConvolutionCost: t => int = x =>
@ -225,51 +239,44 @@ module AlgebraicCombination = {
| _ => 1000
}
type calculationStrategy = MonteCarloStrat | ConvolutionStrat(Operation.convolutionOperation)
let chooseConvolutionOrMonteCarloDefault = (
op: Operation.algebraicOperation,
t2: t,
t1: t,
): calculationStrategy =>
switch op {
| #Divide
| #Power
| #Logarithm =>
MonteCarloStrat
| (#Add | #Subtract | #Multiply) as convOp =>
let run = (~t1: t, ~t2: t, ~arithmeticOperation): specificStrategy => {
switch StrategyCallOnValidatedInputs.symbolic(arithmeticOperation, t1, t2) {
| #AnalyticalSolution(_)
| #Error(_) =>
#AsSymbolic
| #NoSolution =>
if Operation.Convolution.canDoAlgebraicOperation(arithmeticOperation) {
expectedConvolutionCost(t1) * expectedConvolutionCost(t2) > 10000
? MonteCarloStrat
: ConvolutionStrat(convOp)
? #AsMonteCarlo
: #AsConvolution
} else {
#AsMonteCarlo
}
}
let tryAnalyticalSimplification = (
arithmeticOperation: Operation.algebraicOperation,
t1: t,
t2: t,
): SymbolicDistTypes.analyticalSimplificationResult => {
switch (t1, t2) {
| (DistributionTypes.Symbolic(d1), DistributionTypes.Symbolic(d2)) =>
SymbolicDist.T.tryAnalyticalSimplification(d1, d2, arithmeticOperation)
| _ => #NoSolution
}
}
let runDefault = (
t1: t,
let runStrategyOnValidatedInputs = (
~t1: t,
~t2: t,
~arithmeticOperation,
~strategy: StrategyChooser.specificStrategy,
~toPointSetFn: toPointSetFn,
~toSampleSetFn: toSampleSetFn,
~arithmeticOperation,
~t2: t,
): result<t, error> => {
switch tryAnalyticalSimplification(arithmeticOperation, t1, t2) {
switch strategy {
| #AsMonteCarlo =>
StrategyCallOnValidatedInputs.monteCarlo(toSampleSetFn, arithmeticOperation, t1, t2)
| #AsSymbolic =>
switch StrategyCallOnValidatedInputs.symbolic(arithmeticOperation, t1, t2) {
| #AnalyticalSolution(symbolicDist) => Ok(Symbolic(symbolicDist))
| #Error(e) => Error(OperationError(e))
| #NoSolution =>
switch chooseConvolutionOrMonteCarloDefault(arithmeticOperation, t1, t2) {
| MonteCarloStrat => runMonteCarlo(toSampleSetFn, arithmeticOperation, t1, t2)
| ConvolutionStrat(convOp) =>
runConvolution(toPointSetFn, convOp, t1, t2)->E.R2.fmap(r => DistributionTypes.PointSet(r))
| #NoSolution => Error(Unreachable)
}
| #AsConvolution =>
switch Operation.Convolution.fromAlgebraicOperation(arithmeticOperation) {
| Some(convOp) => StrategyCallOnValidatedInputs.convolution(toPointSetFn, convOp, t1, t2)
| None => Error(Unreachable)
}
}
}
@ -282,29 +289,38 @@ module AlgebraicCombination = {
~arithmeticOperation: Operation.algebraicOperation,
~t2: t,
): result<t, error> => {
let invalidOperationError = getInvalidOperationError(
t1,
t2,
~toPointSetFn,
let invalidOperationError = InputValidator.run(t1, t2, ~arithmeticOperation, ~toPointSetFn)
switch (invalidOperationError, strategy) {
| (Some(e), _) => Error(e)
| (None, AsDefault) => {
let chooseStrategy = StrategyChooser.run(~arithmeticOperation, ~t1, ~t2)
runStrategyOnValidatedInputs(
~t1,
~t2,
~strategy=chooseStrategy,
~arithmeticOperation,
~toPointSetFn,
~toSampleSetFn,
)
switch (invalidOperationError, strategy, arithmeticOperation) {
| (Some(e), _, _) => Error(e)
| (None, AsDefault, _) =>
runDefault(t1, ~toPointSetFn, ~toSampleSetFn, ~arithmeticOperation, ~t2)
| (None, AsMonteCarlo, _) => runMonteCarlo(toSampleSetFn, arithmeticOperation, t1, t2)
| (None, AsSymbolic, _) =>
switch tryAnalyticalSimplification(arithmeticOperation, t1, t2) {
}
| (None, AsMonteCarlo) =>
StrategyCallOnValidatedInputs.monteCarlo(toSampleSetFn, arithmeticOperation, t1, t2)
| (None, AsSymbolic) =>
switch StrategyCallOnValidatedInputs.symbolic(arithmeticOperation, t1, t2) {
| #AnalyticalSolution(symbolicDist) => Ok(Symbolic(symbolicDist))
| #NoSolution => Error(RequestedStrategyInvalidError(`No analytic solution for inputs`))
| #Error(err) => Error(OperationError(err))
}
| (None, AsConvolution, (#Divide | #Power | #Logarithm) as convOp) => {
let errString = `Can't convolve on ${Operation.Algebraic.toString(convOp)}`
| (None, AsConvolution) =>
switch Operation.Convolution.fromAlgebraicOperation(arithmeticOperation) {
| None => {
let errString = `Convolution not supported for ${Operation.Algebraic.toString(
arithmeticOperation,
)}`
Error(RequestedStrategyInvalidError(errString))
}
| (None, AsConvolution, (#Add | #Subtract | #Multiply) as convOp) =>
runConvolution(toPointSetFn, convOp, t1, t2)->E.R2.fmap(r => DistributionTypes.PointSet(r))
| Some(convOp) => StrategyCallOnValidatedInputs.convolution(toPointSetFn, convOp, t1, t2)
}
}
}
}

12
packages/squiggle-lang/src/rescript/Utility/Operation.res
View File

@ -29,6 +29,18 @@ type distToFloatOperation = [
module Convolution = {
type t = convolutionOperation
//Only a selection of operations are supported by convolution.
let fromAlgebraicOperation = (op: algebraicOperation): option<convolutionOperation> =>
switch op {
| #Add => Some(#Add)
| #Subtract => Some(#Subtract)
| #Multiply => Some(#Multiply)
| #Divide | #Power | #Logarithm => None
}
let canDoAlgebraicOperation = (op: algebraicOperation): bool =>
fromAlgebraicOperation(op)->E.O.isSome
let toFn: (t, float, float) => float = x =>
switch x {
| #Add => \"+."