Minor fixes

src/components/DistBuilder3.re

@@ -77,7 +77,7 @@ let make = () => {
       ~validationStrategy=OnDemand,
       ~schema,
       ~onSubmit=({state}) => {None},
-      ~initialState={guesstimatorString: "lognormal(6.1, 3)"},
+      ~initialState={guesstimatorString: "mm(1 to 10000)"},
       (),
     );
 

src/components/charts/DistPlusPlot.re

@@ -235,12 +235,6 @@ module DistPlusChart = {
       distPlus |> Distributions.DistPlus.T.Integral.yToX(~cache=None, 0.99);
     };
 
-    Js.log3(
-      distPlus |> Distributions.DistPlus.T.Integral.yToX(~cache=None, 0.0001),
-      minX,
-      distPlus |> Distributions.DistPlus.T.Integral.yToX(~cache=None, 0.98),
-    );
-
     let timeScale = distPlus.unit |> DistTypes.DistributionUnit.toJson;
     let toDiscreteProbabilityMass =
       distPlus |> Distributions.DistPlus.T.toDiscreteProbabilityMass;

src/symbolic/MathJsParser.re

@@ -107,9 +107,11 @@ module MathAdtToDistDst = {
 
   let to_: array(arg) => result(SymbolicDist.bigDist, string) =
     fun
-    | [|Value(low), Value(high)|] => {
+    | [|Value(low), Value(high)|] when low < high => {
         Ok(`Simple(SymbolicDist.Lognormal.from90PercentCI(low, high)));
       }
+    | [|Value(_), Value(_)|] =>
+      Error("Low value must be less than high value.")
     | _ => Error("Wrong number of variables in lognormal distribution");
 
   let uniform: array(arg) => result(SymbolicDist.bigDist, string) =
@@ -122,7 +124,11 @@ module MathAdtToDistDst = {
     | [|Value(alpha), Value(beta)|] => Ok(`Simple(`Beta({alpha, beta})))
     | _ => Error("Wrong number of variables in lognormal distribution");
 
-  let multiModal = (args: array(result(SymbolicDist.bigDist, string))) => {
+  let multiModal =
+      (
+        args: array(result(SymbolicDist.bigDist, string)),
+        weights: array(float),
+      ) => {
     let dists =
       args
       |> E.A.fmap(
@@ -135,7 +141,9 @@ module MathAdtToDistDst = {
     | 0 => Error("Multimodals need at least one input")
     | _ =>
       dists
-      |> E.A.fmap(r => (r, 1.0))
+      |> E.A.fmapi((index, item) =>
+           (item, weights |> E.A.get(_, index) |> E.O.default(1.0))
+         )
       |> (r => Ok(`PointwiseCombination(r)))
     };
   };
@@ -151,9 +159,25 @@ module MathAdtToDistDst = {
       | Fn({name: "to", args}) => to_(args)
       | Fn({name: "mm", args}) => {
           let dists = args |> E.A.fmap(functionParser);
-          multiModal(dists);
+          let weights =
+            args
+            |> E.A.last
+            |> E.O.bind(
+                 _,
+                 fun
+                 | Array(values) => Some(values)
+                 | _ => None,
+               )
+            |> E.A.O.defaultEmpty
+            |> E.A.fmap(
+                 fun
+                 | Value(r) => Some(r)
+                 | _ => None,
+               )
+            |> E.A.O.concatSomes;
+          multiModal(dists, weights);
         }
-      | Fn({name}) => Error(name ++ ": name not found")
+      | Fn({name}) => Error(name ++ ": function not supported")
       | _ => Error("This type not currently supported")
     );
 

src/symbolic/SymbolicDist.re

@@ -132,15 +132,19 @@ module GenericSimple = {
     | `Uniform({high}) => high
     };
 
+  let interpolateXs =
+      (~xSelection: [ | `Linear | `ByWeight]=`Linear, dist: dist, sampleCount) => {
+    switch (xSelection) {
+    | `Linear => Functions.range(min(dist), max(dist), sampleCount)
+    | `ByWeight =>
+      Functions.range(minCdfValue, maxCdfValue, sampleCount)
+      |> E.A.fmap(x => inv(x, dist))
+    };
+  };
+
   let toShape =
       (~xSelection: [ | `Linear | `ByWeight]=`Linear, dist: dist, sampleCount) => {
-    let xs =
-      switch (xSelection) {
-      | `Linear => Functions.range(min(dist), max(dist), sampleCount)
-      | `ByWeight =>
-        Functions.range(minCdfValue, maxCdfValue, sampleCount)
-        |> E.A.fmap(x => inv(x, dist))
-      };
+    let xs = interpolateXs(~xSelection, dist, sampleCount);
     let ys = xs |> E.A.fmap(r => pdf(r, dist));
     XYShape.T.fromArrays(xs, ys);
   };
@@ -166,7 +170,19 @@ module PointwiseAddDistributionsWeighted = {
     dists |> E.A.fmap(d => d |> fst |> GenericSimple.max) |> Functions.max;
 
   let toShape = (dists: t, sampleCount: int) => {
-    let xs = Functions.range(min(dists), max(dists), sampleCount);
+    let xs =
+      dists
+      |> E.A.fmap(r =>
+           r
+           |> fst
+           |> GenericSimple.interpolateXs(
+                ~xSelection=`ByWeight,
+                _,
+                sampleCount / (dists |> E.A.length),
+              )
+         )
+      |> E.A.concatMany;
+    xs |> Array.fast_sort(compare);
     let ys = xs |> E.A.fmap(pdf(dists));
     XYShape.T.fromArrays(xs, ys);
   };
@@ -176,7 +192,13 @@ module PointwiseAddDistributionsWeighted = {
       dists
       |> E.A.fmap(d => GenericSimple.toString(fst(d)))
       |> Js.Array.joinWith(",");
-    {j|multimodal($distString)|j};
+    let weights =
+      dists
+      |> E.A.fmap(d =>
+           snd(d) |> Js.Float.toPrecisionWithPrecision(~digits=2)
+         )
+      |> Js.Array.joinWith(",");
+    {j|multimodal($distString, [$weights])|j};
   };
 };