Minor cleanup of mean and variance

__tests__/Distributions__Test.re

@@ -194,10 +194,10 @@ describe("Shape", () => {
       0.9,
     );
     makeTest("integralEndY", T.Integral.sum(~cache=None, discrete), 1.0);
-    makeTest("mean", T.getMean(discrete), 3.9);
+    makeTest("mean", T.mean(discrete), 3.9);
     makeTestCloseEquality(
       "variance",
-      T.getVariance(discrete),
+      T.variance(discrete),
       5.89,
       ~digits=7,
     );
@@ -393,25 +393,25 @@ describe("Shape", () => {
 
     makeTestCloseEquality(
       "Mean of a normal",
-      T.getMean(normalShape),
+      T.mean(normalShape),
       mean,
       ~digits=2,
     );
     makeTestCloseEquality(
       "Variance of a normal",
-      T.getVariance(normalShape),
+      T.variance(normalShape),
       variance,
       ~digits=1,
     );
     makeTestCloseEquality(
       "Mean of a lognormal",
-      T.getMean(lognormalShape),
+      T.mean(lognormalShape),
       mean,
       ~digits=2,
     );
     makeTestCloseEquality(
       "Variance of a lognormal",
-      T.getVariance(lognormalShape),
+      T.variance(lognormalShape),
       variance,
       ~digits=0,
     );

src/components/charts/DistPlusPlot.re

@@ -124,6 +124,7 @@ let table = (distPlus, x) => {
   </div>;
 };
 let percentiles = distPlus => {
+  <div>
     <table className="table-auto text-sm">
       <thead>
         <tr>
@@ -134,6 +135,7 @@ let percentiles = distPlus => {
           <td className="px-4 py-2"> {"75" |> ReasonReact.string} </td>
           <td className="px-4 py-2"> {"95" |> ReasonReact.string} </td>
           <td className="px-4 py-2"> {"99" |> ReasonReact.string} </td>
+          <td className="px-4 py-2"> {"99.999" |> ReasonReact.string} </td>
         </tr>
       </thead>
       <tbody>
@@ -173,16 +175,6 @@ let percentiles = distPlus => {
              |> Distributions.DistPlus.T.Integral.yToX(~cache=None, 0.99)
              |> showFloat}
           </td>
-        <td className="px-4 py-2 border">
-          {distPlus
-           |> Distributions.DistPlus.T.Integral.yToX(~cache=None, 0.999)
-           |> showFloat}
-        </td>
-        <td className="px-4 py-2 border">
-          {distPlus
-           |> Distributions.DistPlus.T.Integral.yToX(~cache=None, 0.9999)
-           |> showFloat}
-        </td>
           <td className="px-4 py-2 border">
             {distPlus
              |> Distributions.DistPlus.T.Integral.yToX(~cache=None, 0.99999)
@@ -190,7 +182,29 @@ let percentiles = distPlus => {
           </td>
         </tr>
       </tbody>
-  </table>;
+    </table>
+    <table className="table-auto text-sm">
+      <thead>
+        <tr>
+          <td className="px-4 py-2"> {"mean" |> ReasonReact.string} </td>
+          <td className="px-4 py-2">
+            {"standard deviation" |> ReasonReact.string}
+          </td>
+          <td className="px-4 py-2"> {"variance" |> ReasonReact.string} </td>
+        </tr>
+      </thead>
+      <tbody>
+        <tr>
+          <td className="px-4 py-2 border">
+            {distPlus |> Distributions.DistPlus.T.mean |> showFloat}
+          </td>
+          <td className="px-4 py-2 border">
+            {distPlus |> Distributions.DistPlus.T.variance |> showFloat}
+          </td>
+        </tr>
+      </tbody>
+    </table>
+  </div>;
 };
 
 let adjustBoth = discreteProbabilityMass => {

src/distPlus/distribution/Distributions.re

@@ -18,8 +18,8 @@ module type dist = {
   let integralXtoY: (~cache: option(integral), float, t) => float;
   let integralYtoX: (~cache: option(integral), float, t) => float;
 
-  let getMean: t => float;
-  let getVariance: t => float;
+  let mean: t => float;
+  let variance: t => float;
 };
 
 module Dist = (T: dist) => {
@@ -38,8 +38,8 @@ module Dist = (T: dist) => {
   let toDiscrete = T.toDiscrete;
   let toScaledContinuous = T.toScaledContinuous;
   let toScaledDiscrete = T.toScaledDiscrete;
-  let getMean = T.getMean;
-  let getVariance = T.getVariance;
+  let mean = T.mean;
+  let variance = T.variance;
 
   // TODO: Move this to each class, have use integral to produce integral in DistPlus class.
   let scaleBy = (~scale=1.0, t: t) => t |> mapY((r: float) => r *. scale);
@@ -141,7 +141,7 @@ module Continuous = {
       let toScaledContinuous = t => Some(t);
       let toScaledDiscrete = _ => None;
 
-      let getMean = (t: t) => {
+      let mean = (t: t) => {
         let indefiniteIntegralStepwise = (p, h1) => h1 *. p ** 2.0 /. 2.0;
         let indefiniteIntegralLinear = (p, a, b) =>
           a *. p ** 2.0 /. 2.0 +. b *. p ** 3.0 /. 3.0;
@@ -151,10 +151,10 @@ module Continuous = {
           t,
         );
       };
-      let getVariance = (t: t): float =>
+      let variance = (t: t): float =>
         XYShape.Analysis.getVarianceDangerously(
           t,
-          getMean,
+          mean,
           XYShape.Analysis.getMeanOfSquaresContinuousShape,
         );
     });
@@ -229,12 +229,12 @@ module Discrete = {
         |> Continuous.getShape
         |> XYShape.YtoX.linear(f);
 
-      let getMean = (t: t): float =>
+      let mean = (t: t): float =>
         E.A.reducei(t.xs, 0.0, (acc, x, i) => acc +. x *. t.ys[i]);
-      let getVariance = (t: t): float => {
+      let variance = (t: t): float => {
         let getMeanOfSquares = t =>
-          getMean(XYShape.Analysis.squareXYShape(t));
-        XYShape.Analysis.getVarianceDangerously(t, getMean, getMeanOfSquares);
+          mean(XYShape.Analysis.squareXYShape(t));
+        XYShape.Analysis.getVarianceDangerously(t, mean, getMeanOfSquares);
       };
     });
 };
@@ -408,36 +408,36 @@ module Mixed = {
         };
       };
 
-      let getMean = (t: t): float => {
+      let mean = (t: t): float => {
         let discreteProbabilityMassFraction =
           t.discreteProbabilityMassFraction;
         switch (discreteProbabilityMassFraction) {
-        | 1.0 => Discrete.T.getMean(t.discrete)
-        | 0.0 => Continuous.T.getMean(t.continuous)
+        | 1.0 => Discrete.T.mean(t.discrete)
+        | 0.0 => Continuous.T.mean(t.continuous)
         | _ =>
-          Discrete.T.getMean(t.discrete)
+          Discrete.T.mean(t.discrete)
           *. discreteProbabilityMassFraction
-          +. Continuous.T.getMean(t.continuous)
+          +. Continuous.T.mean(t.continuous)
           *. (1.0 -. discreteProbabilityMassFraction)
         };
       };
 
-      let getVariance = (t: t): float => {
+      let variance = (t: t): float => {
         let discreteProbabilityMassFraction =
           t.discreteProbabilityMassFraction;
         let getMeanOfSquares = (t: t) => {
-          Discrete.T.getMean(XYShape.Analysis.squareXYShape(t.discrete))
+          Discrete.T.mean(XYShape.Analysis.squareXYShape(t.discrete))
           *. t.discreteProbabilityMassFraction
           +. XYShape.Analysis.getMeanOfSquaresContinuousShape(t.continuous)
           *. (1.0 -. t.discreteProbabilityMassFraction);
         };
         switch (discreteProbabilityMassFraction) {
-        | 1.0 => Discrete.T.getVariance(t.discrete)
-        | 0.0 => Continuous.T.getVariance(t.continuous)
+        | 1.0 => Discrete.T.variance(t.discrete)
+        | 0.0 => Continuous.T.variance(t.continuous)
         | _ =>
           XYShape.Analysis.getVarianceDangerously(
             t,
-            getMean,
+            mean,
             getMeanOfSquares,
           )
         };
@@ -547,18 +547,18 @@ module Shape = {
           Continuous.T.mapY(fn),
         ));
 
-      let getMean = (t: t): float =>
+      let mean = (t: t): float =>
         switch (t) {
-        | Mixed(m) => Mixed.T.getMean(m)
-        | Discrete(m) => Discrete.T.getMean(m)
-        | Continuous(m) => Continuous.T.getMean(m)
+        | Mixed(m) => Mixed.T.mean(m)
+        | Discrete(m) => Discrete.T.mean(m)
+        | Continuous(m) => Continuous.T.mean(m)
         };
 
-      let getVariance = (t: t): float =>
+      let variance = (t: t): float =>
         switch (t) {
-        | Mixed(m) => Mixed.T.getVariance(m)
-        | Discrete(m) => Discrete.T.getVariance(m)
-        | Continuous(m) => Continuous.T.getVariance(m)
+        | Mixed(m) => Mixed.T.variance(m)
+        | Discrete(m) => Discrete.T.variance(m)
+        | Continuous(m) => Continuous.T.variance(m)
         };
     });
 };
@@ -674,8 +674,8 @@ module DistPlus = {
       let integralYtoX = (~cache as _, f, t: t) => {
         Shape.T.Integral.yToX(~cache=Some(t.integralCache), f, toShape(t));
       };
-      let getMean = (t: t) => Shape.T.getMean(t.shape);
-      let getVariance = (t: t) => Shape.T.getVariance(t.shape);
+      let mean = (t: t) => Shape.T.mean(t.shape);
+      let variance = (t: t) => Shape.T.variance(t.shape);
     });
 };
 

src/distPlus/distribution/XYShape.re

@@ -347,14 +347,11 @@ module Analysis = {
   };
 
   let getVarianceDangerously =
-      (t: 't, getMean: 't => float, getMeanOfSquares: 't => float): float => {
-    let meanSquared = getMean(t) ** 2.0;
+      (t: 't, mean: 't => float, getMeanOfSquares: 't => float): float => {
+    let meanSquared = mean(t) ** 2.0;
     let meanOfSquares = getMeanOfSquares(t);
     meanOfSquares -. meanSquared;
   };
 
-  let squareXYShape = (t): DistTypes.xyShape => {
-    ...t,
-    xs: E.A.fmap(x => x ** 2.0, t.xs),
-  };
+  let squareXYShape = T.mapX(x => x ** 2.0)
 };