diff --git a/ocaml/out/samples b/ocaml/out/samples
index 8894eb80..68868270 100755
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diff --git a/ocaml/out/samples.cmi b/ocaml/out/samples.cmi
index 206bf915..484674c5 100644
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diff --git a/ocaml/out/samples.cmx b/ocaml/out/samples.cmx
index ac1d98bb..afdc5d87 100644
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diff --git a/ocaml/out/samples.o b/ocaml/out/samples.o
index e25be8e9..61a5f516 100644
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diff --git a/ocaml/samples.ml b/ocaml/samples.ml
index 11939124..15eef8ee 100644
--- a/ocaml/samples.ml
+++ b/ocaml/samples.ml
@@ -3,12 +3,12 @@ let pi = acos (-1.)
 let normal_95_ci_length = 1.6448536269514722
 
 (* Array manipulation helpers *)
-let sumFloats xs = List.fold_left(fun acc x -> acc +. x) 0.0 xs
+let sumFloats xs = Array.fold_left(fun acc x -> acc +. x) 0.0 xs
 let normalizeXs xs = 
   let sum_xs = sumFloats xs in 
-  List.map(fun x -> x /. sum_xs) xs
+  Array.map(fun x -> x /. sum_xs) xs
 let cumsumXs xs = 
-  let _, cum_sum = List.fold_left(fun (sum, ys) x -> 
+  let _, cum_sum = Array.fold_left(fun (sum, ys) x -> 
     let new_sum = sum +. x in
     new_sum, ys @ [new_sum]
   ) (0.0, []) xs in
@@ -16,27 +16,32 @@ let cumsumXs xs =
 
 (* Basic samplers *)
 let sampleZeroToOne () : float = Random.float 1.0
+
 let sampleStandardNormal (): float = 
   let u1 = sampleZeroToOne () in 
   let u2 = sampleZeroToOne () in 
   let z = sqrt(-2.0 *. log(u1)) *. sin(2.0 *. pi *. u2) in 
   z
+
 let sampleNormal mean std = mean +. std *. (sampleStandardNormal ())
+
 let sampleLognormal logmean logstd = exp(sampleNormal logmean logstd)
+
 let sampleTo low high = 
   let loglow = log(low) in
   let loghigh = log(high) in
   let logmean = (loglow +. loghigh) /. 2.0 in
   let logstd = (loghigh -. loglow) /. (2.0 -. normal_95_ci_length ) in
   sampleLognormal logmean logstd
-let mixture (samplers: (unit -> float) list) (weights: float list) = 
-  match (List.length samplers == List.length weights) with
+
+let mixture (samplers: (unit -> float) array) (weights: float array) = 
+  match (Array.length samplers == Array.length weights) with
     | false -> None
     | true -> 
         let normalized_weights = normalizeXs weights in
         let cumsummed_normalized_weights = cumsumXs normalized_weights in
+        let answer = 1.1 in
         Some(1.0)
-      
 
 let () =
   Random.init 1;