Merge pull request #124 from QURIresearch/sparklines

sparklines (issue 70)

CONTRIBUTING.md

@@ -36,6 +36,15 @@ You need `yarn`.
 
 TODO: fill this out based on all the different packages scripts once they cool down. 
 
+## If you're on NixOS
+
+You'll need to run a command like this in order to get `yarn build` to run, especially in `packages/squiggle-lang`. 
+```sh
+patchelf --set-interpreter $(patchelf --print-interpreter $(which mkdir)) ./node_modules/gentype/gentype.exe 
+```
+
+See [here](https://github.com/NixOS/nixpkgs/issues/107375)
+
 # Pull request protocol
 
 Please work against `staging` branch. **Do not** work against `master`. Please do not merge without approval from some subset of Quinn, Sam, and Ozzie; they will be auto-pinged. 

flake.nix

@@ -44,6 +44,7 @@
               yarn2nix
               nodePackages.npm
               nodejs
+              patchelf
               (pkgs.vscode-with-extensions.override {
                   vscode = pkgs.vscodium;
                   vscodeExtensions = pkgs.vscode-utils.extensionsFromVscodeMarketplace [

packages/squiggle-lang/__tests__/Symbolic_test.res

@@ -0,0 +1,33 @@
+open Jest
+open Expect
+open Js.Array
+open SymbolicDist
+
+let makeTest = (~only=false, str, item1, item2) =>
+  only
+    ? Only.test(str, () => expect(item1) -> toEqual(item2))
+    : test(str, () => expect(item1) -> toEqual(item2))
+
+let pdfImage = (thePdf, inps) => map(thePdf, inps)
+
+let parameterWiseAdditionHelper = (n1: SymbolicDistTypes.normal, n2: SymbolicDistTypes.normal) => {
+  let normalDistAtSumMeanConstr = Normal.add(n1, n2)
+  let normalDistAtSumMean: SymbolicDistTypes.normal = switch normalDistAtSumMeanConstr {
+    | #Normal(params) => params
+  }
+  x => Normal.pdf(x, normalDistAtSumMean)
+}
+
+describe("Normal distribution with sparklines", () => {
+
+  let normalDistAtMean5: SymbolicDistTypes.normal = {mean: 5.0, stdev: 2.0}
+  let normalDistAtMean10: SymbolicDistTypes.normal = {mean: 10.0, stdev: 2.0}
+  let range20Float = E.A.rangeFloat(0, 20) // [0.0,1.0,2.0,3.0,4.0,...19.0,]
+
+  let pdfNormalDistAtMean5 = x => Normal.pdf(x, normalDistAtMean5)
+  let sparklineMean5 = pdfImage(pdfNormalDistAtMean5, range20Float)
+  makeTest("mean=5", Sparklines.create(sparklineMean5, ()), `▁▂▃▅███▅▃▂▁▁▁▁▁▁▁▁▁▁▁`)
+
+  let sparklineMean15 = normalDistAtMean5 -> parameterWiseAdditionHelper(normalDistAtMean10) -> pdfImage(range20Float)
+  makeTest("parameter-wise addition of two normal distributions", Sparklines.create(sparklineMean15, ()), `▁▁▁▁▁▁▁▁▁▁▂▃▅▇███▇▅▃▂`)
+})

packages/squiggle-lang/src/rescript/utility/E.res

@@ -1,5 +1,4 @@
 open Rationale.Function.Infix
-
 module FloatFloatMap = {
   module Id = Belt.Id.MakeComparable({
     type t = float
@@ -87,6 +86,11 @@ module O = {
   let max = compare(\">")
 }
 
+module O2 = {
+  let default = (a, b) => O.default(b, a)
+  let toExn = (a, b) => O.toExn(b, a)
+}
+
 /* Functions */
 module F = {
   let apply = (a, e) => a |> e
@@ -269,6 +273,8 @@ module A = {
       ))
       |> Rationale.Result.return
     }
+  let rangeFloat = (~step=1, start, stop) =>
+    Belt.Array.rangeBy(start, stop, ~step) |> fmap(Belt.Int.toFloat)
 
   // This zips while taking the longest elements of each array.
   let zipMaxLength = (array1, array2) => {
@@ -322,7 +328,8 @@ module A = {
         | r => Some(r)
         }
     )
-  let filter = (o, e) => Js.Array.filter(o, e)
+  let filter = Js.Array.filter
+  let joinWith = Js.Array.joinWith
 
   module O = {
     let concatSomes = (optionals: array<option<'a>>): array<'a> =>
@@ -405,6 +412,7 @@ module A = {
             : {
                 let _ = Js.Array.push(element, continuous)
               }
+
           ()
         })
 
@@ -434,6 +442,11 @@ module A = {
   }
 }
 
+module A2 = {
+  let fmap = (a, b) => Array.map(b, a)
+  let joinWith = (a, b) => A.joinWith(b, a)
+}
+
 module JsArray = {
   let concatSomes = (optionals: Js.Array.t<option<'a>>): Js.Array.t<'a> =>
     optionals

packages/squiggle-lang/src/rescript/utility/Sparklines.res

@@ -0,0 +1,26 @@
+// Port of Sindre Sorhus' Sparkly to Rescript
+// reference implementation: https://github.com/sindresorhus/sparkly
+// Omitting rgb "fire" style, so no `chalk` dependency
+// Omitting: NaN handling, special consideration for constant data.
+
+let ticks = [`▁`, `▂`, `▃`, `▄`, `▅`, `▆`, `▇`, `█`]
+
+let _ticksLength = E.A.length(ticks)
+
+let _heightToTickIndex = (maximum: float, v: float) => {
+  let suggestedTickIndex = Js.Math.ceil_int(v /. maximum *. Belt.Int.toFloat(_ticksLength)) - 1
+  max(suggestedTickIndex, 0)
+}
+
+let create = (relativeHeights: array<float>, ~maximum=?, ()) => {
+  if E.A.length(relativeHeights) === 0 {
+    ""
+  } else {
+    let maximum = maximum->E.O2.default(E.A.max(relativeHeights)->E.O2.toExn(""))
+
+    relativeHeights
+    ->E.A2.fmap(_heightToTickIndex(maximum))
+    ->E.A2.fmap(r => E.A.get(ticks, r)->E.O2.toExn(""))
+    ->E.A2.joinWith("")
+  }
+}