Formatted AlgebraicShapeCombination and added |> ignore statements
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@ -80,7 +80,6 @@ let toDiscretePointMassesFromTriangulars =
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{n: n - 2, masses, means, variances};
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} else {
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for (i in 1 to n - 2) {
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// area of triangle = width * height / 2
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let _ =
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Belt.Array.set(
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@ -115,7 +114,11 @@ let toDiscretePointMassesFromTriangulars =
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};
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let combineShapesContinuousContinuous =
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(op: ExpressionTypes.algebraicOperation, s1: DistTypes.xyShape, s2: DistTypes.xyShape)
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(
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op: ExpressionTypes.algebraicOperation,
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s1: DistTypes.xyShape,
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s2: DistTypes.xyShape,
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)
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: DistTypes.xyShape => {
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let t1n = s1 |> XYShape.T.length;
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let t2n = s2 |> XYShape.T.length;
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@ -123,10 +126,11 @@ let combineShapesContinuousContinuous =
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// if we add the two distributions, we should probably use normal filters.
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// if we multiply the two distributions, we should probably use lognormal filters.
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let t1m = toDiscretePointMassesFromTriangulars(s1);
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let t2m = switch (op) {
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let t2m =
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switch (op) {
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| `Divide => toDiscretePointMassesFromTriangulars(~inverse=true, s2)
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| _ => toDiscretePointMassesFromTriangulars(~inverse=false, s2)
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};
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};
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let combineMeansFn =
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switch (op) {
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@ -190,27 +194,30 @@ let combineShapesContinuousContinuous =
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// we now want to create a set of target points. For now, let's just evenly distribute 200 points between
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// between the outputMinX and outputMaxX
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let nOut = 300;
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let outputXs: array(float) = E.A.Floats.range(outputMinX^, outputMaxX^, nOut);
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let outputXs: array(float) =
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E.A.Floats.range(outputMinX^, outputMaxX^, nOut);
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let outputYs: array(float) = Belt.Array.make(nOut, 0.0);
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// now, for each of the outputYs, accumulate from a Gaussian kernel over each input point.
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for (j in 0 to E.A.length(masses) - 1) { // go through all of the result points
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let _ = if (variances[j] > 0. && masses[j] > 0.) {
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for (i in 0 to E.A.length(outputXs) - 1) { // go through all of the target points
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for (j in 0 to E.A.length(masses) - 1) {
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// go through all of the result points
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if (variances[j] > 0. && masses[j] > 0.) {
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for (i in 0 to E.A.length(outputXs) - 1) {
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// go through all of the target points
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let dx = outputXs[i] -. means[j];
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let contribution = masses[j] *. exp(-. (dx ** 2.) /. (2. *. variances[j])) /. (sqrt(2. *. 3.14159276 *. variances[j]));
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let _ = Belt.Array.set(outputYs, i, outputYs[i] +. contribution);
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();
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let contribution =
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masses[j]
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*. exp(-. (dx ** 2.) /. (2. *. variances[j]))
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/. sqrt(2. *. 3.14159276 *. variances[j]);
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Belt.Array.set(outputYs, i, outputYs[i] +. contribution) |> ignore;
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};
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();
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};
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();
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};
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{xs: outputXs, ys: outputYs};
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};
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let toDiscretePointMassesFromDiscrete = (s: DistTypes.xyShape): pointMassesWithMoments => {
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let n = s |> XYShape.T.length;
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let toDiscretePointMassesFromDiscrete =
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(s: DistTypes.xyShape): pointMassesWithMoments => {
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let {xs, ys}: XYShape.T.t = s;
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let n = E.A.length(xs);
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@ -219,36 +226,21 @@ let toDiscretePointMassesFromDiscrete = (s: DistTypes.xyShape): pointMassesWithM
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let variances: array(float) = Belt.Array.makeUninitializedUnsafe(n);
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for (i in 0 to n - 1) {
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let _ =
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Belt.Array.set(
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masses,
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i,
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ys[i]
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);
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let _ =
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Belt.Array.set(
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means,
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i,
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xs[i]
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);
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let _ =
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Belt.Array.set(
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variances,
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i,
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0.0
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);
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();
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Belt.Array.set(masses, i, ys[i]) |> ignore;
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Belt.Array.set(means, i, xs[i]) |> ignore;
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Belt.Array.set(variances, i, 0.0) |> ignore;
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};
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{n, masses, means, variances};
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};
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let combineShapesContinuousDiscrete =
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(op: ExpressionTypes.algebraicOperation, s1: DistTypes.xyShape, s2: DistTypes.xyShape)
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(
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op: ExpressionTypes.algebraicOperation,
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s1: DistTypes.xyShape,
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s2: DistTypes.xyShape,
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)
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: array(DistTypes.xyShape) => {
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let t1n = s1 |> XYShape.T.length;
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let t2n = s2 |> XYShape.T.length;
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@ -260,7 +252,7 @@ let combineShapesContinuousDiscrete =
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switch (op) {
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| `Add
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| `Subtract => {
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| `Subtract =>
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for (j in 0 to t2n - 1) {
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// for each one of the discrete points
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// create a new distribution, as long as the original continuous one
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@ -268,40 +260,33 @@ let combineShapesContinuousDiscrete =
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Belt.Array.makeUninitializedUnsafe(t1n);
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for (i in 0 to t1n - 1) {
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let _ =
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Belt.Array.set(
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dxyShape,
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i,
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(fn(s1.xs[i], s2.xs[j]), s1.ys[i] *. s2.ys[j]),
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);
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();
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Belt.Array.set(
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dxyShape,
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i,
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(fn(s1.xs[i], s2.xs[j]), s1.ys[i] *. s2.ys[j]),
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)
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|> ignore;
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};
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let _ = Belt.Array.set(outXYShapes, j, dxyShape);
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();
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Belt.Array.set(outXYShapes, j, dxyShape) |> ignore;
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}
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}
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| `Multiply
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| `Divide => {
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| `Multiply
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| `Divide =>
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for (j in 0 to t2n - 1) {
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// for each one of the discrete points
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// create a new distribution, as long as the original continuous one
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let dxyShape: array((float, float)) =
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Belt.Array.makeUninitializedUnsafe(t1n);
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for (i in 0 to t1n - 1) {
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let _ =
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Belt.Array.set(
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dxyShape,
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i,
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(fn(s1.xs[i], s2.xs[j]), s1.ys[i] *. s2.ys[j] /. s2.xs[j]),
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);
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();
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Belt.Array.set(
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dxyShape,
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i,
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(fn(s1.xs[i], s2.xs[j]), s1.ys[i] *. s2.ys[j] /. s2.xs[j]),
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)
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|> ignore;
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};
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let _ = Belt.Array.set(outXYShapes, j, dxyShape);
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();
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}
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Belt.Array.set(outXYShapes, j, dxyShape) |> ignore;
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}
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};
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outXYShapes
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|> E.A.fmap(XYShape.T.fromZippedArray);
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outXYShapes |> E.A.fmap(XYShape.T.fromZippedArray);
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};
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