Merge pull request #73 from QURIresearch/fix-graphs

Fix exponential, beta, triangular distributions and function rendering

packages/components/src/SquiggleChart.tsx

@@ -163,7 +163,7 @@ export const SquiggleChart: React.FC<SquiggleChartProps> = (props) => {
         // We are looking at a function. In this case, we draw a Percentiles chart
         let start = props.diagramStart ? props.diagramStart : 0;
         let stop = props.diagramStop ? props.diagramStop : 10;
-        let count = props.diagramCount ? props.diagramCount : 0.1;
+        let count = props.diagramCount ? props.diagramCount : 100;
         let step = (stop - start) / count;
         let data = _.range(start, stop, step).map((x) => {
           if (chartResult.NAME == "Function") {
@@ -192,10 +192,10 @@ export const SquiggleChart: React.FC<SquiggleChartProps> = (props) => {
                 p99: percentiles[12],
               };
             }
+            return null;
           }
-          return 0;
         });
-        return <SquigglePercentilesChart data={{ facet: data }} />;
+        return <SquigglePercentilesChart data={{ facet: data.filter(x => x !== null) }} />;
       }
     });
     return <>{chartResults}</>;

packages/squiggle-lang/src/rescript/interpreter/typeSystem/HardcodedFunctions.res

@@ -22,7 +22,7 @@ let makeSymbolicFromTwoFloats = (name, fn) =>
     ~inputTypes=[#Float, #Float],
     ~run=x =>
       switch x {
-      | [#Float(a), #Float(b)] => Ok(#SymbolicDist(fn(a, b)))
+      | [#Float(a), #Float(b)] => fn(a, b) |> E.R.fmap(r => (#SymbolicDist(r)))
       | e => wrongInputsError(e)
       },
     (),
@@ -35,7 +35,7 @@ let makeSymbolicFromOneFloat = (name, fn) =>
     ~inputTypes=[#Float],
     ~run=x =>
       switch x {
-      | [#Float(a)] => Ok(#SymbolicDist(fn(a)))
+      | [#Float(a)] => fn(a) |> E.R.fmap(r => #SymbolicDist(r))
       | e => wrongInputsError(e)
       },
     (),

packages/squiggle-lang/src/rescript/symbolicDist/SymbolicDist.res

@@ -2,7 +2,10 @@ open SymbolicDistTypes
 
 module Normal = {
   type t = normal
-  let make = (mean, stdev): symbolicDist => #Normal({mean: mean, stdev: stdev})
+  let make = (mean: float, stdev: float): result<symbolicDist,string> => 
+    stdev > 0.0
+      ? Ok(#Normal({mean: mean, stdev: stdev}))
+      : Error("Standard deviation of normal distribution must be larger than 0")
   let pdf = (x, t: t) => Jstat.Normal.pdf(x, t.mean, t.stdev)
   let cdf = (x, t: t) => Jstat.Normal.cdf(x, t.mean, t.stdev)
 
@@ -45,10 +48,12 @@ module Normal = {
 
 module Exponential = {
   type t = exponential
-  let make = (rate: float): symbolicDist =>
-    #Exponential({
-      rate: rate,
-    })
+  let make = (rate: float): result<symbolicDist,string> =>
+    rate > 0.0
+      ? Ok(#Exponential({
+          rate: rate,
+        }))
+      : Error("Exponential distributions mean must be larger than 0")
   let pdf = (x, t: t) => Jstat.Exponential.pdf(x, t.rate)
   let cdf = (x, t: t) => Jstat.Exponential.cdf(x, t.rate)
   let inv = (p, t: t) => Jstat.Exponential.inv(p, t.rate)
@@ -84,7 +89,10 @@ module Triangular = {
 
 module Beta = {
   type t = beta
-  let make = (alpha, beta) => #Beta({alpha: alpha, beta: beta})
+  let make = (alpha, beta) => 
+    alpha > 0.0 && beta > 0.0
+      ? Ok(#Beta({alpha: alpha, beta: beta}))
+      : Error("Beta distribution parameters must be positive")
   let pdf = (x, t: t) => Jstat.Beta.pdf(x, t.alpha, t.beta)
   let cdf = (x, t: t) => Jstat.Beta.cdf(x, t.alpha, t.beta)
   let inv = (p, t: t) => Jstat.Beta.inv(p, t.alpha, t.beta)
@@ -95,7 +103,10 @@ module Beta = {
 
 module Lognormal = {
   type t = lognormal
-  let make = (mu, sigma) => #Lognormal({mu: mu, sigma: sigma})
+  let make = (mu, sigma) => 
+      sigma > 0.0
+        ? Ok(#Lognormal({mu: mu, sigma: sigma}))
+        : Error("Lognormal standard deviation must be larger than 0")
   let pdf = (x, t: t) => Jstat.Lognormal.pdf(x, t.mu, t.sigma)
   let cdf = (x, t: t) => Jstat.Lognormal.cdf(x, t.mu, t.sigma)
   let inv = (p, t: t) => Jstat.Lognormal.inv(p, t.mu, t.sigma)
@@ -110,11 +121,16 @@ module Lognormal = {
     #Lognormal({mu: mu, sigma: sigma})
   }
   let fromMeanAndStdev = (mean, stdev) => {
-    let variance = Js.Math.pow_float(~base=stdev, ~exp=2.0)
-    let meanSquared = Js.Math.pow_float(~base=mean, ~exp=2.0)
-    let mu = Js.Math.log(mean) -. 0.5 *. Js.Math.log(variance /. meanSquared +. 1.0)
-    let sigma = Js.Math.pow_float(~base=Js.Math.log(variance /. meanSquared +. 1.0), ~exp=0.5)
-    #Lognormal({mu: mu, sigma: sigma})
+    if stdev > 0.0 {
+      let variance = Js.Math.pow_float(~base=stdev, ~exp=2.0)
+      let meanSquared = Js.Math.pow_float(~base=mean, ~exp=2.0)
+      let mu = Js.Math.log(mean) -. 0.5 *. Js.Math.log(variance /. meanSquared +. 1.0)
+      let sigma = Js.Math.pow_float(~base=Js.Math.log(variance /. meanSquared +. 1.0), ~exp=0.5)
+      Ok(#Lognormal({mu: mu, sigma: sigma}))
+    }
+    else {
+      Error("Lognormal standard deviation must be larger than 0")
+    }
   }
 
   let multiply = (l1, l2) => {
@@ -137,7 +153,11 @@ module Lognormal = {
 
 module Uniform = {
   type t = uniform
-  let make = (low, high) => #Uniform({low: low, high: high})
+  let make = (low, high) =>
+     high > low 
+       ? Ok(#Uniform({low: low, high: high}))
+       : Error("High must be larger than low")
+
   let pdf = (x, t: t) => Jstat.Uniform.pdf(x, t.low, t.high)
   let cdf = (x, t: t) => Jstat.Uniform.cdf(x, t.low, t.high)
   let inv = (p, t: t) => Jstat.Uniform.inv(p, t.low, t.high)

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

@@ -25,61 +25,61 @@ module Uniform = {
 
 type beta
 module Beta = {
-  @module("jstat") @scope("uniform") external pdf: (float, float, float) => float = "pdf"
-  @module("jstat") @scope("uniform") external cdf: (float, float, float) => float = "cdf"
-  @module("jstat") @scope("uniform") external inv: (float, float, float) => float = "inv"
-  @module("jstat") @scope("uniform") external sample: (float, float) => float = "sample"
-  @module("jstat") @scope("uniform") external mean: (float, float) => float = "mean"
+  @module("jstat") @scope("beta") external pdf: (float, float, float) => float = "pdf"
+  @module("jstat") @scope("beta") external cdf: (float, float, float) => float = "cdf"
+  @module("jstat") @scope("beta") external inv: (float, float, float) => float = "inv"
+  @module("jstat") @scope("beta") external sample: (float, float) => float = "sample"
+  @module("jstat") @scope("beta") external mean: (float, float) => float = "mean"
 }
 
 module Exponential = {
-  @module("jstat") @scope("uniform") external pdf: (float, float) => float = "pdf"
-  @module("jstat") @scope("uniform") external cdf: (float, float) => float = "cdf"
-  @module("jstat") @scope("uniform") external inv: (float, float) => float = "inv"
-  @module("jstat") @scope("uniform") external sample: (float) => float = "sample"
-  @module("jstat") @scope("uniform") external mean: (float) => float = "mean"
+  @module("jstat") @scope("exponential") external pdf: (float, float) => float = "pdf"
+  @module("jstat") @scope("exponential") external cdf: (float, float) => float = "cdf"
+  @module("jstat") @scope("exponential") external inv: (float, float) => float = "inv"
+  @module("jstat") @scope("exponential") external sample: (float) => float = "sample"
+  @module("jstat") @scope("exponential") external mean: (float) => float = "mean"
 }
 
 module Cauchy = {
-  @module("jstat") @scope("uniform") external pdf: (float, float, float) => float = "pdf"
-  @module("jstat") @scope("uniform") external cdf: (float, float, float) => float = "cdf"
-  @module("jstat") @scope("uniform") external inv: (float, float, float) => float = "inv"
-  @module("jstat") @scope("uniform") external sample: (float, float) => float = "sample"
-  @module("jstat") @scope("uniform") external mean: (float, float) => float = "mean"
+  @module("jstat") @scope("cauchy") external pdf: (float, float, float) => float = "pdf"
+  @module("jstat") @scope("cauchy") external cdf: (float, float, float) => float = "cdf"
+  @module("jstat") @scope("cauchy") external inv: (float, float, float) => float = "inv"
+  @module("jstat") @scope("cauchy") external sample: (float, float) => float = "sample"
+  @module("jstat") @scope("cauchy") external mean: (float, float) => float = "mean"
 }
 
 module Triangular = {
-  @module("jstat") @scope("uniform") external pdf: (float, float, float, float) => float = "pdf"
-  @module("jstat") @scope("uniform") external cdf: (float, float, float, float) => float = "cdf"
-  @module("jstat") @scope("uniform") external inv: (float, float, float, float) => float = "inv"
-  @module("jstat") @scope("uniform") external sample: (float, float, float) => float = "sample"
-  @module("jstat") @scope("uniform") external mean: (float, float, float) => float = "mean"
+  @module("jstat") @scope("triangular") external pdf: (float, float, float, float) => float = "pdf"
+  @module("jstat") @scope("triangular") external cdf: (float, float, float, float) => float = "cdf"
+  @module("jstat") @scope("triangular") external inv: (float, float, float, float) => float = "inv"
+  @module("jstat") @scope("triangular") external sample: (float, float, float) => float = "sample"
+  @module("jstat") @scope("triangular") external mean: (float, float, float) => float = "mean"
 }
 
 
 module Pareto = {
-  @module("jstat") @scope("uniform") external pdf: (float, float, float) => float = "pdf"
-  @module("jstat") @scope("uniform") external cdf: (float, float, float) => float = "cdf"
-  @module("jstat") @scope("uniform") external inv: (float, float, float) => float = "inv"
+  @module("jstat") @scope("pareto") external pdf: (float, float, float) => float = "pdf"
+  @module("jstat") @scope("pareto") external cdf: (float, float, float) => float = "cdf"
+  @module("jstat") @scope("pareto") external inv: (float, float, float) => float = "inv"
 }
 
 module Poisson = {
-  @module("jstat") @scope("uniform") external pdf: (float, float) => float = "pdf"
-  @module("jstat") @scope("uniform") external cdf: (float, float) => float = "cdf"
-  @module("jstat") @scope("uniform") external sample: (float) => float = "sample"
-  @module("jstat") @scope("uniform") external mean: (float) => float = "mean"
+  @module("jstat") @scope("poisson") external pdf: (float, float) => float = "pdf"
+  @module("jstat") @scope("poisson") external cdf: (float, float) => float = "cdf"
+  @module("jstat") @scope("poisson") external sample: (float) => float = "sample"
+  @module("jstat") @scope("poisson") external mean: (float) => float = "mean"
 }
 
 module Weibull = {
-  @module("jstat") @scope("uniform") external pdf: (float, float, float) => float = "pdf"
-  @module("jstat") @scope("uniform") external cdf: (float, float,float ) => float = "cdf"
-  @module("jstat") @scope("uniform") external sample: (float,float) => float = "sample"
-  @module("jstat") @scope("uniform") external mean: (float,float) => float = "mean"
+  @module("jstat") @scope("weibull") external pdf: (float, float, float) => float = "pdf"
+  @module("jstat") @scope("weibull") external cdf: (float, float,float ) => float = "cdf"
+  @module("jstat") @scope("weibull") external sample: (float,float) => float = "sample"
+  @module("jstat") @scope("weibull") external mean: (float,float) => float = "mean"
 }
 
 module Binomial = {
-  @module("jstat") @scope("uniform") external pdf: (float, float, float) => float = "pdf"
-  @module("jstat") @scope("uniform") external cdf: (float, float,float ) => float = "cdf"
+  @module("jstat") @scope("binomial") external pdf: (float, float, float) => float = "pdf"
+  @module("jstat") @scope("binomial") external cdf: (float, float,float ) => float = "cdf"
 }
 
 @module("jstat") external sum: array<float> => float = "sum"