lognormal

packages/squiggle-lang/src/rescript/Distributions/SymbolicDist/SymbolicDist2.res

@@ -5,7 +5,7 @@ module type ValidNormal = {
   let distribution: validated<symbolicDist>
 }
 
-let from90PercentCI = (low, high) => {
+let normalFrom90PercentCI = (low, high) => {
   let mean = E.A.Floats.mean([low, high])
   let stdev = (high -. low) /. (2.0 *. 1.644854)
   (mean, stdev)
@@ -16,8 +16,7 @@ module Normal = (Validated: ValidNormal) => {
   let cdf = x => Jstat.Normal.cdf(x, Validated.params.mean, Validated.params.stdev)
 
   let from90PercentCI = (low, high) => {
-      let mean = E.A.Floats.mean([low, high])
-      let stdev = (high -. low) /. (2.0 *. 1.644854)
+      let (mean, stdev) = normalFrom90PercentCI(low, high)
       normalConstr({mean: mean, stdev: stdev})
   }
 
@@ -49,9 +48,67 @@ module NormalBinOps = (N1: ValidNormal, N2: ValidNormal) => {
   }
 }
 
+module type ValidLognormal = {
+    let params: lognormal
+    let distribution: validated<symbolicDist>
+}
+
+let lognormalFrom90PercentCI = (low, high) => {
+    let logLow = log(low)
+    let logHigh = log(high)
+    let mu = E.A.Floats.mean([logLow, logHigh])
+    let sigma = (logHigh -. logLow) /. (2.0 *. 1.645)
+    (mu, sigma)
+}
+
+let lognormalFromMeanAndStdev = (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)
+    (mu, sigma)
+} 
+
+module Lognormal = (Validated: ValidLognormal) => {
+    let pdf = x => Jstat.Lognormal.pdf(x, Validated.params.mu, Validated.params.sigma)
+    let cdf = x => Jstat.Lognormal.cdf(x, Validated.params.mu, Validated.params.sigma)
+    let inv = p => Jstat.Lognormal.inv(p, Validated.params.mu, Validated.params.sigma)
+    let mean = Jstat.Lognormal.mean(Validated.params.mu, Validated.params.sigma)
+    let sample = Jstat.Lognormal.sample(Validated.params.mu, Validated.params.sigma)
+    let toString = j`Lognormal(${Js.Float.toString(Validated.params.sigma)},${Js.Float.toString(Validated.params.sigma)})`
+    let from90PercentCI = (low, high) => {
+        let (mu, sigma) = lognormalFrom90PercentCI(low, high)  
+        lognormalConstr({mu: mu, sigma: sigma})
+    }
+    let fromMeanAndStdev = (mean, stdev) => {
+        let (mu, sigma) = lognormalFromMeanAndStdev(mean, stdev)
+        lognormalConstr({mu: mu, sigma: sigma})
+    }
+}
+
+module LognormalBinOp = (LN1: ValidLognormal, LN2: ValidLognormal) => {
+    let multiply = {
+        let mu = LN1.params.mu +. LN2.params.mu 
+        let sigma = LN1.params.sigma +. LN2.params.sigma 
+        lognormalConstr({mu: mu, sigma: sigma})
+    }
+    let divide = {
+        let mu = LN1.params.mu -. LN2.params.mu 
+        let sigma = LN1.params.sigma +. LN2.params.sigma 
+        lognormalConstr({mu: mu, sigma: sigma})
+    }
+    let operate = (operation: Operation.Algebraic.t) => {
+        switch operation {
+            | #Multiply => Some(multiply)
+            | #Divide => Some(divide)
+            | _ => None
+        }
+    }
+}
+
 module From90thPercentile = {
-  let constr: (float, float) => validated<symbolicDist> = (low, high) => {
-    let (mean, stdev) = from90PercentCI(low, high)
+  let make: (float, float) => validated<symbolicDist> = (low, high) => {
+    let (mean, stdev) = normalFrom90PercentCI(low, high)
     module NormalValueValidated: ValidNormal = {
       let params = {mean: mean, stdev: stdev}
       let distribution = normalConstr(params)
@@ -75,7 +132,18 @@ module T = {
           module NormalValue = Normal(NormalValueValidated)
           switch NormalValueValidated.distribution {
             | Ok(symbdist) => NormalValue.pdf(x)
-            | Error(invalidNormal) => 0.0
+            | Error(invalidNormal) => -1e0  // dummy value till we decide if results are gonna propagate through everything. 
+          }
+      }
+      | #Lognormal(_params) => {
+          module LognormalValueValidated: ValidLognormal = {
+              let params = _params
+              let distribution = lognormalConstr(params)
+          }
+          module LognormalValue = Lognormal(LognormalValueValidated)
+          switch LognormalValueValidated.distribution {
+              | Ok(symbdist) => LognormalValue.pdf(x)
+              | Error(invalidLognormal) => -1e0  // dummy value till we decide how results propagate up 
           }
       }
     }