Merge pull request #534 from quantified-uncertainty/add-logistic

Add Logistic Distribution

packages/squiggle-lang/__tests__/ReducerInterface/ReducerInterface_Distribution_test.res

@@ -33,6 +33,7 @@ describe("eval on distribution functions", () => {
     testEval("mean(gamma(5,5))", "Ok(25)")
     testEval("mean(bernoulli(0.2))", "Ok(0.2)")
     testEval("mean(bernoulli(0.8))", "Ok(0.8)")
+    testEval("mean(logistic(5,1))", "Ok(5)")
   })
   describe("toString", () => {
     testEval("toString(normal(5,2))", "Ok('Normal(5,2)')")

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

@@ -216,6 +216,24 @@ module Uniform = {
   }
 }
 
+module Logistic = {
+  type t = logistic
+  let make = (location, scale) =>
+    scale > 0.0
+      ? Ok(#Logistic({location: location, scale: scale}))
+      : Error("Scale must be positive")
+
+  let pdf = (x, t: t) => Stdlib.Logistic.pdf(x, t.location, t.scale)
+  let cdf = (x, t: t) => Stdlib.Logistic.cdf(x, t.location, t.scale)
+  let inv = (p, t: t) => Stdlib.Logistic.quantile(p, t.location, t.scale)
+  let sample = (t: t) => {
+    let s = Uniform.sample({low: 0.0, high: 1.0})
+    inv(s, t)
+  }
+  let mean = (t: t) => Ok(Stdlib.Logistic.mean(t.location, t.scale))
+  let toString = ({location, scale}: t) => j`Logistic($location,$scale)`
+}
+
 module Bernoulli = {
   type t = bernoulli
   let make = p =>
@@ -304,6 +322,7 @@ module T = {
     | #Cauchy(n) => Cauchy.pdf(x, n)
     | #Gamma(n) => Gamma.pdf(x, n)
     | #Lognormal(n) => Lognormal.pdf(x, n)
+    | #Logistic(n) => Logistic.pdf(x, n)
     | #Uniform(n) => Uniform.pdf(x, n)
     | #Beta(n) => Beta.pdf(x, n)
     | #Float(n) => Float.pdf(x, n)
@@ -317,6 +336,7 @@ module T = {
     | #Exponential(n) => Exponential.cdf(x, n)
     | #Cauchy(n) => Cauchy.cdf(x, n)
     | #Gamma(n) => Gamma.cdf(x, n)
+    | #Logistic(n) => Logistic.cdf(x, n)
     | #Lognormal(n) => Lognormal.cdf(x, n)
     | #Uniform(n) => Uniform.cdf(x, n)
     | #Beta(n) => Beta.cdf(x, n)
@@ -331,6 +351,7 @@ module T = {
     | #Exponential(n) => Exponential.inv(x, n)
     | #Cauchy(n) => Cauchy.inv(x, n)
     | #Gamma(n) => Gamma.inv(x, n)
+    | #Logistic(n) => Logistic.inv(x, n)
     | #Lognormal(n) => Lognormal.inv(x, n)
     | #Uniform(n) => Uniform.inv(x, n)
     | #Beta(n) => Beta.inv(x, n)
@@ -345,6 +366,7 @@ module T = {
     | #Exponential(n) => Exponential.sample(n)
     | #Cauchy(n) => Cauchy.sample(n)
     | #Gamma(n) => Gamma.sample(n)
+    | #Logistic(n) => Logistic.sample(n)
     | #Lognormal(n) => Lognormal.sample(n)
     | #Uniform(n) => Uniform.sample(n)
     | #Beta(n) => Beta.sample(n)
@@ -369,6 +391,7 @@ module T = {
     | #Cauchy(n) => Cauchy.toString(n)
     | #Normal(n) => Normal.toString(n)
     | #Gamma(n) => Gamma.toString(n)
+    | #Logistic(n) => Logistic.toString(n)
     | #Lognormal(n) => Lognormal.toString(n)
     | #Uniform(n) => Uniform.toString(n)
     | #Beta(n) => Beta.toString(n)
@@ -383,6 +406,7 @@ module T = {
     | #Cauchy(n) => Cauchy.inv(minCdfValue, n)
     | #Normal(n) => Normal.inv(minCdfValue, n)
     | #Lognormal(n) => Lognormal.inv(minCdfValue, n)
+    | #Logistic(n) => Logistic.inv(minCdfValue, n)
     | #Gamma(n) => Gamma.inv(minCdfValue, n)
     | #Uniform({low}) => low
     | #Bernoulli(n) => Bernoulli.min(n)
@@ -398,6 +422,7 @@ module T = {
     | #Normal(n) => Normal.inv(maxCdfValue, n)
     | #Gamma(n) => Gamma.inv(maxCdfValue, n)
     | #Lognormal(n) => Lognormal.inv(maxCdfValue, n)
+    | #Logistic(n) => Logistic.inv(maxCdfValue, n)
     | #Beta(n) => Beta.inv(maxCdfValue, n)
     | #Bernoulli(n) => Bernoulli.max(n)
     | #Uniform({high}) => high
@@ -412,6 +437,7 @@ module T = {
     | #Normal(n) => Normal.mean(n)
     | #Lognormal(n) => Lognormal.mean(n)
     | #Beta(n) => Beta.mean(n)
+    | #Logistic(n) => Logistic.mean(n)
     | #Uniform(n) => Uniform.mean(n)
     | #Gamma(n) => Gamma.mean(n)
     | #Bernoulli(n) => Bernoulli.mean(n)

packages/squiggle-lang/src/rescript/Distributions/SymbolicDist/SymbolicDistTypes.res

@@ -36,6 +36,11 @@ type gamma = {
   scale: float,
 }
 
+type logistic = {
+  location: float,
+  scale: float,
+}
+
 type bernoulli = {p: float}
 
 @genType
@@ -50,6 +55,7 @@ type symbolicDist = [
   | #Gamma(gamma)
   | #Float(float)
   | #Bernoulli(bernoulli)
+  | #Logistic(logistic)
 ]
 
 type analyticalSimplificationResult = [

packages/squiggle-lang/src/rescript/ReducerInterface/ReducerInterface_GenericDistribution.res

@@ -178,6 +178,7 @@ module SymbolicConstructors = {
     | "uniform" => Ok(SymbolicDist.Uniform.make)
     | "beta" => Ok(SymbolicDist.Beta.make)
     | "lognormal" => Ok(SymbolicDist.Lognormal.make)
+    | "logistic" => Ok(SymbolicDist.Logistic.make)
     | "cauchy" => Ok(SymbolicDist.Cauchy.make)
     | "gamma" => Ok(SymbolicDist.Gamma.make)
     | "to" => Ok(SymbolicDist.From90thPercentile.make)
@@ -212,7 +213,14 @@ let dispatchToGenericOutput = (
   | ("delta", [EvNumber(f)]) =>
     SymbolicDist.Float.makeSafe(f)->SymbolicConstructors.symbolicResultToOutput
   | (
-      ("normal" | "uniform" | "beta" | "lognormal" | "cauchy" | "gamma" | "to") as fnName,
+      ("normal"
+      | "uniform"
+      | "beta"
+      | "lognormal"
+      | "cauchy"
+      | "gamma"
+      | "to"
+      | "logistic") as fnName,
       [EvNumber(f1), EvNumber(f2)],
     ) =>
     SymbolicConstructors.twoFloat(fnName)

packages/squiggle-lang/src/rescript/Utility/Stdlib.res

@@ -10,4 +10,31 @@ module Bernoulli = {
 
   @module external mean: float => float = "@stdlib/stats/base/dists/bernoulli/mean"
   let mean = mean
+
+  @module external stdev: float => float = "@stdlib/stats/base/dists/bernoulli/stdev"
+  let stdev = stdev
+
+  @module external variance: float => float = "@stdlib/stats/base/dists/bernoulli/variance"
+  let variance = variance
+}
+
+module Logistic = {
+  @module external cdf: (float, float, float) => float = "@stdlib/stats/base/dists/logistic/cdf"
+  let cdf = cdf
+
+  @module external pdf: (float, float, float) => float = "@stdlib/stats/base/dists/logistic/pdf"
+  let pdf = pdf
+
+  @module
+  external quantile: (float, float, float) => float = "@stdlib/stats/base/dists/logistic/quantile"
+  let quantile = quantile
+
+  @module external mean: (float, float) => float = "@stdlib/stats/base/dists/logistic/mean"
+  let mean = mean
+
+  @module external stdev: (float, float) => float = "@stdlib/stats/base/dists/logistic/stdev"
+  let stdev = stdev
+
+  @module external variance: (float, float) => float = "@stdlib/stats/base/dists/logistic/variance"
+  let variance = variance
 }