Rename invalidOperationError
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4544268429
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@ -11,7 +11,7 @@ type error =
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| DistributionVerticalShiftIsInvalid
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| TooFewSamples
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| ArgumentError(string)
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| OperationError(Operation.Error.invalidOperationError)
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| OperationError(Operation.Error.t)
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| PointSetConversionError(SampleSetDist.pointsetConversionError)
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| SparklineError(PointSetTypes.sparklineError) // This type of error is for when we find a sparkline of a discrete distribution. This should probably at some point be actually implemented
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| OtherError(string)
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@ -30,7 +30,7 @@ module Error = {
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| DistributionVerticalShiftIsInvalid => "Distribution Vertical Shift is Invalid"
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| ArgumentError(s) => `Argument Error ${s}`
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| TooFewSamples => "Too Few Samples"
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| OperationError(err) => Operation.Error.invalidOperationErrorToString(err)
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| OperationError(err) => Operation.Error.toString(err)
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| PointSetConversionError(err) => SampleSetDist.pointsetConversionErrorToString(err)
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| SparklineError(err) => PointSetTypes.sparklineErrorToString(err)
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| OtherError(s) => s
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@ -151,7 +151,7 @@ module AlgebraicCombination = {
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arithmeticOperation: Operation.algebraicOperation,
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t1: t,
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t2: t,
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): option<result<SymbolicDistTypes.symbolicDist, Operation.Error.invalidOperationError>> =>
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): option<result<SymbolicDistTypes.symbolicDist, Operation.Error.t>> =>
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switch (arithmeticOperation, t1, t2) {
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| (arithmeticOperation, Symbolic(d1), Symbolic(d2)) =>
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switch SymbolicDist.T.tryAnalyticalSimplification(d1, d2, arithmeticOperation) {
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@ -88,7 +88,7 @@ let stepwiseToLinear = (t: t): t =>
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let combinePointwise = (
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~integralSumCachesFn=(_, _) => None,
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~distributionType: PointSetTypes.distributionType=#PDF,
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fn: (float, float) => result<float, Operation.Error.invalidOperationError>,
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fn: (float, float) => result<float, Operation.Error.t>,
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t1: PointSetTypes.continuousShape,
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t2: PointSetTypes.continuousShape,
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): result<PointSetTypes.continuousShape, 'e> => {
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@ -60,10 +60,10 @@ let combinePointwise = (
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PointSetTypes.continuousShape,
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PointSetTypes.continuousShape,
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) => option<PointSetTypes.continuousShape>=(_, _) => None,
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fn: (float, float) => result<float, Operation.Error.invalidOperationError>,
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fn: (float, float) => result<float, Operation.Error.t>,
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t1: t,
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t2: t,
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): result<PointSetTypes.pointSetDist, Operation.Error.invalidOperationError> =>
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): result<PointSetTypes.pointSetDist, Operation.Error.t> =>
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switch (t1, t2) {
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| (Continuous(m1), Continuous(m2)) =>
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Continuous.combinePointwise(
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@ -83,11 +83,10 @@ let sampleN = (t: t, n) => {
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}
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//TODO: Figure out what to do if distributions are different lengths. ``zip`` is kind of inelegant for this.
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let map2 = (
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~fn: (float, float) => result<float, Operation.Error.invalidOperationError>,
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~t1: t,
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~t2: t,
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): result<t, Operation.Error.invalidOperationError> => {
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let map2 = (~fn: (float, float) => result<float, Operation.Error.t>, ~t1: t, ~t2: t): result<
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t,
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Operation.Error.t,
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> => {
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let samples = Belt.Array.zip(get(t1), get(t2))->E.A2.fmap(((a, b)) => fn(a, b))
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// This assertion should never be reached. In order for it to be reached, one
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@ -45,6 +45,6 @@ type symbolicDist = [
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type analyticalSimplificationResult = [
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| #AnalyticalSolution(symbolicDist)
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| #Error(Operation.Error.invalidOperationError)
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| #Error(Operation.Error.t)
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| #NoSolution
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]
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@ -37,35 +37,37 @@ module Convolution = {
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}
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}
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type operationError =
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| DivisionByZeroError
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| ComplexNumberError
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@genType
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module Error = {
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@genType
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type invalidOperationError =
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| DivisionByZeroError
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| ComplexNumberError
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type t = operationError
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let invalidOperationErrorToString = (err: invalidOperationError): string =>
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let toString = (err: t): string =>
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switch err {
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| DivisionByZeroError => "Cannot divide by zero"
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| ComplexNumberError => "Operation returned complex result"
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}
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}
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let power = (a: float, b: float): result<float, Error.invalidOperationError> =>
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let power = (a: float, b: float): result<float, Error.t> =>
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if a >= 0.0 {
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Ok(a ** b)
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} else {
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Error(ComplexNumberError)
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}
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let divide = (a: float, b: float): result<float, Error.invalidOperationError> =>
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let divide = (a: float, b: float): result<float, Error.t> =>
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if b != 0.0 {
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Ok(a /. b)
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} else {
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Error(DivisionByZeroError)
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}
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let logarithm = (a: float, b: float): result<float, Error.invalidOperationError> =>
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let logarithm = (a: float, b: float): result<float, Error.t> =>
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if b == 1. {
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Error(DivisionByZeroError)
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} else if b == 0. {
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@ -80,7 +82,7 @@ let logarithm = (a: float, b: float): result<float, Error.invalidOperationError>
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module Algebraic = {
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@genType
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type t = algebraicOperation
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let toFn: (t, float, float) => result<float, Error.invalidOperationError> = (x, a, b) =>
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let toFn: (t, float, float) => result<float, Error.t> = (x, a, b) =>
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switch x {
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| #Add => Ok(a +. b)
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| #Subtract => Ok(a -. b)
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@ -131,7 +133,7 @@ module DistToFloat = {
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// Note that different logarithms don't really do anything.
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module Scale = {
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type t = scaleOperation
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let toFn = (x: t, a: float, b: float): result<float, Error.invalidOperationError> =>
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let toFn = (x: t, a: float, b: float): result<float, Error.t> =>
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switch x {
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| #Multiply => Ok(a *. b)
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| #Divide => divide(a, b)
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@ -234,11 +234,11 @@ module Zipped = {
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module PointwiseCombination = {
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// t1Interpolator and t2Interpolator are functions from XYShape.XtoY, e.g. linearBetweenPointsExtrapolateFlat.
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let combine: (
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(float, float) => result<float, Operation.Error.invalidOperationError>,
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(float, float) => result<float, Operation.Error.t>,
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interpolator,
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T.t,
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T.t,
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) => result<T.t, Operation.Error.invalidOperationError> = %raw(`
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) => result<T.t, Operation.Error.t> = %raw(`
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// This function combines two xyShapes by looping through both of them simultaneously.
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// It always moves on to the next smallest x, whether that's in the first or second input's xs,
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// and interpolates the value on the other side, thus accumulating xs and ys.
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