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faustian bargain: create 6 different Danger.dmr functions

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So ugly that it's almost beautiful. Except it's not
This commit is contained in:
NunoSempere 2022-09-05 21:59:53 +02:00
parent c183dbd24b
commit f76de31d26
1 changed files with 278 additions and 65 deletions
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343
packages/squiggle-lang/src/rescript/FunctionRegistry/Library/FR_Danger.res
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@ -278,6 +278,7 @@ module Internals = {
} }
optimalAllocationResult optimalAllocationResult
} }
/*
let diminishingMarginalReturnsForManyFunctionsSkeleton = ( let diminishingMarginalReturnsForManyFunctionsSkeleton = (
lambdas, lambdas,
funds, funds,
@ -285,10 +286,39 @@ module Internals = {
environment, environment,
reducer, reducer,
) => { ) => {
let result = [0.0, 0.0]->castArrayOfFloatsToInternalArrayOfInternals->Ok let applyFunctionAtFloatToFloatOption = (lambda, point: float) => {
// Defined here so that it has access to environment, reducer
let pointAsInternalExpression = castFloatToInternalNumber(point)
let resultAsInternalExpression = Reducer_Expression_Lambda.doLambdaCall(
lambda,
list{pointAsInternalExpression},
environment,
reducer,
)
let result = switch resultAsInternalExpression {
| Ok(IEvNumber(x)) => Ok(x)
| Error(_) =>
Error(
"Error 1 in Danger.diminishingMarginalReturnsForManyFunctions. It's possible that your function doesn't return a number, try definining auxiliaryFunction(x) = mean(yourFunction(x)) and integrate auxiliaryFunction instead",
)
| _ => Error("Error 2 in Danger.diminishingMarginalReturnsForManyFunctions")
}
result
}
let answer =
E.A.fmap(
lambda => applyFunctionAtFloatToFloatOption(lambda, 0.0),
lambdas,
)->E.A.R.firstErrorOrOpen
let result = switch answer {
| Ok(xs) => xs->castArrayOfFloatsToInternalArrayOfInternals->Ok
| Error(b) => Error(b)
}
// let result = [0.0, 0.0]->castArrayOfFloatsToInternalArrayOfInternals->Ok
result result
} }*/
/*
let diminishingMarginalReturnsForManyFunctions = ( let diminishingMarginalReturnsForManyFunctions = (
lambdas, lambdas,
funds, funds,
@ -320,67 +350,66 @@ module Internals = {
} }
result result
} }
let numDivisions = Js.Math.round(funds /. approximateIncrement) let numDivisions = Js.Math.round(funds /. approximateIncrement)
let numDivisionsInt = Belt.Float.toInt(numDivisions) let numDivisionsInt = Belt.Float.toInt(numDivisions)
let increment = funds /. numDivisions let increment = funds /. numDivisions
let arrayOfIncrements = Belt.Array.makeBy(numDivisionsInt, _ => increment) let arrayOfIncrements = Belt.Array.makeBy(numDivisionsInt, _ => increment)
let numLambdas = E.A.length(lambdas) let numLambdas = E.A.length(lambdas)
let initAccumulator: diminishingReturnsAccumulator = Ok({ let initAccumulator: diminishingReturnsAccumulator = Ok({
optimalAllocations: Belt.Array.makeBy(numLambdas, _ => 0.0), optimalAllocations: Belt.Array.makeBy(numLambdas, _ => 0.0),
currentMarginalReturns: E.A.fmap( currentMarginalReturns: E.A.fmap(
lambda => applyFunctionAtFloatToFloatOption(lambda, 0.0), lambda => applyFunctionAtFloatToFloatOption(lambda, 0.0),
lambdas, lambdas,
)->E.A.R.firstErrorOrOpen, )->E.A.R.firstErrorOrOpen,
}) })
let optimalAllocationEndAccumulator = E.A.reduce(arrayOfIncrements, initAccumulator, ( let optimalAllocationEndAccumulator = E.A.reduce(arrayOfIncrements, initAccumulator, (
acc, acc,
newIncrement, newIncrement,
) => { ) => {
switch acc { switch acc {
| Ok(accInner) => { | Ok(accInner) => {
let oldMarginalReturnsWrapped = accInner.currentMarginalReturns let oldMarginalReturnsWrapped = accInner.currentMarginalReturns
let newAccWrapped = switch oldMarginalReturnsWrapped { let newAccWrapped = switch oldMarginalReturnsWrapped {
| Ok(oldMarginalReturns) => { | Ok(oldMarginalReturns) => {
let indexOfBiggestDMR = findBiggestElementIndex(oldMarginalReturns) let indexOfBiggestDMR = findBiggestElementIndex(oldMarginalReturns)
let newOptimalAllocations = Belt.Array.copy(accInner.optimalAllocations) let newOptimalAllocations = Belt.Array.copy(accInner.optimalAllocations)
let newOptimalAllocationsi = let newOptimalAllocationsi = newOptimalAllocations[indexOfBiggestDMR] +. newIncrement
newOptimalAllocations[indexOfBiggestDMR] +. newIncrement newOptimalAllocations[indexOfBiggestDMR] = newOptimalAllocationsi
newOptimalAllocations[indexOfBiggestDMR] = newOptimalAllocationsi let lambdai = lambdas[indexOfBiggestDMR]
let lambdai = lambdas[indexOfBiggestDMR] let newMarginalResultsLambdai = applyFunctionAtFloatToFloatOption(
let newMarginalResultsLambdai = applyFunctionAtFloatToFloatOption( lambdai,
lambdai, newOptimalAllocationsi,
newOptimalAllocationsi, )
) let newCurrentMarginalReturns = switch newMarginalResultsLambdai {
let newCurrentMarginalReturns = switch newMarginalResultsLambdai { | Ok(value) => {
| Ok(value) => { let result = Belt.Array.copy(oldMarginalReturns)
let result = Belt.Array.copy(oldMarginalReturns) result[indexOfBiggestDMR] = value
result[indexOfBiggestDMR] = value Ok(result)
Ok(result)
}
| Error(b) => Error(b)
}
let newAcc: diminishingReturnsAccumulatorInner = {
optimalAllocations: newOptimalAllocations,
currentMarginalReturns: newCurrentMarginalReturns,
}
Ok(newAcc)
} }
| Error(b) => Error(b) | Error(b) => Error(b)
} }
newAccWrapped
let newAcc: diminishingReturnsAccumulatorInner = {
optimalAllocations: newOptimalAllocations,
currentMarginalReturns: newCurrentMarginalReturns,
}
Ok(newAcc)
} }
| Error(b) => Error(b) | Error(b) => Error(b)
} }
}) newAccWrapped
let optimalAllocationResult = switch optimalAllocationEndAccumulator {
| Ok(inner) => Ok(castArrayOfFloatsToInternalArrayOfInternals(inner.optimalAllocations))
| Error(b) => Error(b)
} }
optimalAllocationResult | Error(b) => Error(b)
}
})
let optimalAllocationResult = switch optimalAllocationEndAccumulator {
| Ok(inner) => Ok(castArrayOfFloatsToInternalArrayOfInternals(inner.optimalAllocations))
| Error(b) => Error(b)
}
optimalAllocationResult
//let result = [0.0, 0.0]->castArrayOfFloatsToInternalArrayOfInternals->Ok //let result = [0.0, 0.0]->castArrayOfFloatsToInternalArrayOfInternals->Ok
// result // result
}*/ }
} }
let library = [ let library = [
@ -556,14 +585,14 @@ let library = [
(), (),
), ),
Function.make( Function.make(
~name="diminishingMarginalReturnsForTwoFunctions", ~name="diminishingMarginalReturnsForFunctions2",
~nameSpace, ~nameSpace,
~output=EvtArray, ~output=EvtArray,
~requiresNamespace=false, ~requiresNamespace=false,
~examples=[`Danger.diminishingMarginalReturnsForTwoFunctions({|x| x+1}, {|y| 10}, 100, 0.01)`], ~examples=[`Danger.diminishingMarginalReturnsForFunctions2({|x| x+1}, {|y| 10}, 100, 0.01)`],
~definitions=[ ~definitions=[
FnDefinition.make( FnDefinition.make(
~name="diminishingMarginalReturnsForTwoFunctions", ~name="diminishingMarginalReturnsForFunctions2",
~inputs=[FRTypeLambda, FRTypeLambda, FRTypeNumber, FRTypeNumber], ~inputs=[FRTypeLambda, FRTypeLambda, FRTypeNumber, FRTypeNumber],
~run=(inputs, _, env, reducer) => ~run=(inputs, _, env, reducer) =>
switch inputs { switch inputs {
@ -573,15 +602,14 @@ let library = [
IEvNumber(funds), IEvNumber(funds),
IEvNumber(approximateIncrement), IEvNumber(approximateIncrement),
] => ] =>
Internals.diminishingMarginalReturnsForTwoFunctions( Internals.diminishingMarginalReturnsForManyFunctions(
lambda1, [lambda1, lambda2],
lambda2,
funds, funds,
approximateIncrement, approximateIncrement,
env, env,
reducer, reducer,
) )
| _ => Error("Error in Danger.diminishingMarginalReturnsForTwoFunctions") | _ => Error("Error in Danger.diminishingMarginalReturnsForFunctions2")
}, },
(), (),
), ),
@ -594,7 +622,7 @@ let library = [
~output=EvtArray, ~output=EvtArray,
~requiresNamespace=false, ~requiresNamespace=false,
~examples=[ ~examples=[
`Danger.diminishingMarginalReturnsForFunctions3({|x| x+1}, {|y| 10}, {|z| 20-2x}, 100, 0.01)`, `Danger.diminishingMarginalReturnsForFunctions3({|x| x+1}, {|y| 10}, {|z| 20-2*z}, 100, 0.01)`,
], ],
~definitions=[ ~definitions=[
FnDefinition.make( FnDefinition.make(
@ -609,7 +637,7 @@ let library = [
IEvNumber(funds), IEvNumber(funds),
IEvNumber(approximateIncrement), IEvNumber(approximateIncrement),
] => ] =>
Internals.diminishingMarginalReturnsForManyFunctionsSkeleton( Internals.diminishingMarginalReturnsForManyFunctions(
[lambda1, lambda2, lambda3], [lambda1, lambda2, lambda3],
funds, funds,
approximateIncrement, approximateIncrement,
@ -623,7 +651,192 @@ let library = [
], ],
(), (),
), ),
/* The following will compile, but not work, because of this bug: <https://github.com/quantified-uncertainty/squiggle/issues/558> Instead, I am creating different functions for different numbers of inputs Function.make(
~name="diminishingMarginalReturnsForFunctions4",
~nameSpace,
~output=EvtArray,
~requiresNamespace=false,
~examples=[
`Danger.diminishingMarginalReturnsForFunctions4({|x| x+1}, {|y| 10}, {|z| 20-2*z}, {|a| 15-a}, 100, 0.01)`,
],
~definitions=[
FnDefinition.make(
~name="diminishingMarginalReturnsForFunctions4",
~inputs=[
FRTypeLambda,
FRTypeLambda,
FRTypeLambda,
FRTypeLambda,
FRTypeNumber,
FRTypeNumber,
],
~run=(inputs, _, env, reducer) =>
switch inputs {
| [
IEvLambda(lambda1),
IEvLambda(lambda2),
IEvLambda(lambda3),
IEvLambda(lambda4),
IEvNumber(funds),
IEvNumber(approximateIncrement),
] =>
Internals.diminishingMarginalReturnsForManyFunctions(
[lambda1, lambda2, lambda3, lambda4],
funds,
approximateIncrement,
env,
reducer,
)
| _ => Error("Error in Danger.diminishingMarginalReturnsForFunctions4")
},
(),
),
],
(),
),
Function.make(
~name="diminishingMarginalReturnsForFunctions5",
~nameSpace,
~output=EvtArray,
~requiresNamespace=false,
~examples=[
`Danger.diminishingMarginalReturnsForFunctions5({|x| x+1}, {|y| 10}, {|z| 20-2*z}, {|a| 15-a}, {|b| 17-b}, 100, 0.01)`,
],
~definitions=[
FnDefinition.make(
~name="diminishingMarginalReturnsForFunctions5",
~inputs=[
FRTypeLambda,
FRTypeLambda,
FRTypeLambda,
FRTypeLambda,
FRTypeLambda,
FRTypeNumber,
FRTypeNumber,
],
~run=(inputs, _, env, reducer) =>
switch inputs {
| [
IEvLambda(lambda1),
IEvLambda(lambda2),
IEvLambda(lambda3),
IEvLambda(lambda4),
IEvLambda(lambda5),
IEvNumber(funds),
IEvNumber(approximateIncrement),
] =>
Internals.diminishingMarginalReturnsForManyFunctions(
[lambda1, lambda2, lambda3, lambda4, lambda5],
funds,
approximateIncrement,
env,
reducer,
)
| _ => Error("Error in Danger.diminishingMarginalReturnsForFunctions5")
},
(),
),
],
(),
),
Function.make(
~name="diminishingMarginalReturnsForFunctions6",
~nameSpace,
~output=EvtArray,
~requiresNamespace=false,
~examples=[
`Danger.diminishingMarginalReturnsForFunctions6({|x| x+1}, {|y| 10}, {|z| 20-2*z}, {|a| 15-a}, {|b| 17-b}, {|c| 19-c}, 100, 0.01)`,
],
~definitions=[
FnDefinition.make(
~name="diminishingMarginalReturnsForFunctions6",
~inputs=[
FRTypeLambda,
FRTypeLambda,
FRTypeLambda,
FRTypeLambda,
FRTypeLambda,
FRTypeLambda,
FRTypeNumber,
FRTypeNumber,
],
~run=(inputs, _, env, reducer) =>
switch inputs {
| [
IEvLambda(lambda1),
IEvLambda(lambda2),
IEvLambda(lambda3),
IEvLambda(lambda4),
IEvLambda(lambda5),
IEvLambda(lambda6),
IEvNumber(funds),
IEvNumber(approximateIncrement),
] =>
Internals.diminishingMarginalReturnsForManyFunctions(
[lambda1, lambda2, lambda3, lambda4, lambda5, lambda6],
funds,
approximateIncrement,
env,
reducer,
)
| _ => Error("Error in Danger.diminishingMarginalReturnsForFunctions6")
},
(),
),
],
(),
),
Function.make(
~name="diminishingMarginalReturnsForFunctions7",
~nameSpace,
~output=EvtArray,
~requiresNamespace=false,
~examples=[
`Danger.diminishingMarginalReturnsForFunctions7({|x| x+1}, {|y| 10}, {|z| 20-2*z}, {|a| 15-a}, {|b| 17-b}, {|c| 19-c}, {|d| 20-d/2}, 100, 0.01)`,
],
~definitions=[
FnDefinition.make(
~name="diminishingMarginalReturnsForFunctions7",
~inputs=[
FRTypeLambda,
FRTypeLambda,
FRTypeLambda,
FRTypeLambda,
FRTypeLambda,
FRTypeLambda,
FRTypeLambda,
FRTypeNumber,
FRTypeNumber,
],
~run=(inputs, _, env, reducer) =>
switch inputs {
| [
IEvLambda(lambda1),
IEvLambda(lambda2),
IEvLambda(lambda3),
IEvLambda(lambda4),
IEvLambda(lambda5),
IEvLambda(lambda6),
IEvLambda(lambda7),
IEvNumber(funds),
IEvNumber(approximateIncrement),
] =>
Internals.diminishingMarginalReturnsForManyFunctions(
[lambda1, lambda2, lambda3, lambda4, lambda5, lambda6, lambda7],
funds,
approximateIncrement,
env,
reducer,
)
| _ => Error("Error in Danger.diminishingMarginalReturnsForFunctions4")
},
(),
),
],
(),
),
// The following will compile, but not work, because of this bug: <https://github.com/quantified-uncertainty/squiggle/issues/558> Instead, I am creating different functions for different numbers of inputs
/*
Function.make( Function.make(
~name="diminishingMarginalReturnsForManyFunctions", ~name="diminishingMarginalReturnsForManyFunctions",
~nameSpace, ~nameSpace,