tweak: more cleanup
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@ -1,4 +1,4 @@
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/* Notes: See commit 5ce0a6979d9f95d77e4ddbdffc40009de73821e3 for last commit which has helper functions. These might be useful when coming back to this code after a long time. */
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/* Notes: See commit 5ce0a6979d9f95d77e4ddbdffc40009de73821e3 for last commit which has more detailed helper functions. These might be useful when coming back to this code after a long time. */
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open FunctionRegistry_Core
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open FunctionRegistry_Helpers
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@ -83,7 +83,7 @@ module Integration = {
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}
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result
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}
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// worked example in comments below, assuming min=0, max = 10
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// Variables are punctiliously defined because it's otherwise easy to make off-by one errors.
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let numTotalPoints = Belt.Float.toInt(numIntegrationPoints) // superflous declaration, but useful to keep track that we are interpreting "numIntegrationPoints" as the total number on which we evaluate the function, not e.g., as the inner integration points.
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let numInnerPoints = numTotalPoints - 2
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let numOuterPoints = 2
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@ -123,7 +123,6 @@ module Integration = {
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Js.Console.log2("ysOptions", ysOptions)
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}
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//This is pretty hacky. It should use a result type instead of checking that length matches.
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let result = switch E.A.R.firstErrorOrOpen(ysOptions) {
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| Ok(ys) => {
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let innerPointsSum = ys->E.A.reduce(0.0, (a, b) => a +. b)
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@ -159,7 +158,9 @@ module Integration = {
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~output=EvtNumber,
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~requiresNamespace=false,
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~examples=[`Danger.integrateFunctionBetweenWithNumIntegrationPoints({|x| x+1}, 1, 10, 10)`],
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// should be [x^2/2 + x]1_10 = (100/2 + 10) - (1/2 + 1) = 60 - 1.5 = 58.5
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// For the example of integrating x => x+1 between 1 and 10,
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// result should be close to 58.5
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// [x^2/2 + x]1_10 = (100/2 + 10) - (1/2 + 1) = 60 - 1.5 = 58.5
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// https://www.wolframalpha.com/input?i=integrate+x%2B1+from+1+to+10
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~definitions=[
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FnDefinition.make(
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@ -217,8 +218,8 @@ module Integration = {
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(max -. min) /. epsilon,
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env,
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reducer,
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)->E.R2.errMap(_ =>
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"Integration error 7 in Danger.integrate. Something went wrong along the way"
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)->E.R2.errMap(b =>
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"Integration error 7 in Danger.integrate. Something went wrong along the way: " ++ b
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)
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| _ =>
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Error(
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@ -262,6 +263,12 @@ module DiminishingReturns = {
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- Value of marginal spending for each function
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- How much has been assigned to each function.
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*/
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/*
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Two possible algorithms (n=funds/increment, m=num lambdas)
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1. O(n): Iterate through value on next n dollars. At each step, only compute the new marginal return of the function which is spent. (This is what we are doing.)
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2. O(n*(m-1)): Iterate through all possible spending combinations. The advantage of this option is that it wouldn't assume that the returns of marginal spending are diminishing.
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*/
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let optimalAllocationGivenDiminishingMarginalReturnsForManyFunctions = (
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lambdas,
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funds,
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@ -269,11 +276,7 @@ module DiminishingReturns = {
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environment,
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reducer,
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) => {
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/*
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Two possible algorithms (n=funds/increment, m=num lambdas)
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1. O(n): Iterate through value on next n dollars. At each step, only compute the new marginal return of the function which is spent
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2. O(n*m): Iterate through all possible spending combinations. The advantage of this option is that it wouldn't assume that the returns of marginal spending are diminishing.
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*/
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switch (
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E.A.length(lambdas) > 1,
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funds > 0.0,
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@ -322,6 +325,8 @@ module DiminishingReturns = {
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let numDivisions = Js.Math.round(funds /. approximateIncrement)
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let increment = funds /. numDivisions
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let arrayOfIncrements = Belt.Array.make(Belt.Float.toInt(numDivisions), increment)
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// ^ make the increment cleanly divide the amount of funds
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// nicely simplifies the calculations.
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let initAccumulator: diminishingReturnsAccumulator = Ok({
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optimalAllocations: Belt.Array.make(E.A.length(lambdas), 0.0),
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@ -385,6 +390,8 @@ module DiminishingReturns = {
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}
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}
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module Lib = {
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// many nigh-identical functions because of this bug: <https://github.com/quantified-uncertainty/squiggle/issues/1090>
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// discussed further below
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let optimalAllocationGivenDiminishingMarginalReturnsFunctions2 = Function.make(
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~name="optimalAllocationGivenDiminishingMarginalReturnsFunctions2",
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~nameSpace,
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