remove Ops AutoOpen

#333

src/FSharp.Stats/Array.fs

@@ -40,7 +40,7 @@ module Array =
         let random = Random.rndgen
         let pivotIndex = left + random.NextInt() % (right - left + 1)
         let pivot = items.[pivotIndex]
-        if isNan pivot then
+        if Ops.isNan pivot then
             ~~~pivotIndex
         else
             swapInPlace pivotIndex right items // swap random pivot to right.
@@ -55,7 +55,7 @@ module Array =
             let rec loop i j =
                 if j <  right then 
                     let v = items.[j]
-                    if isNan v then   // true if nan
+                    if Ops.isNan v then   // true if nan
                         loop (~~~j) right // break beacause nan                    
                     else
                         if (v <= pivot) then

src/FSharp.Stats/DistanceMetrics.fs

@@ -116,7 +116,7 @@ module DistanceMetrics =
             let mutable dist = 0.
             for i in 0 .. (dim - 1) do
                 let x = v1.[i] - v2.[i]
-                if not (isNan x) then
+                if not (Ops.isNan x) then
                     dist <- dist + abs x
             dist
 
@@ -186,7 +186,7 @@ module DistanceMetrics =
                     let diff = abs (v1.[i] - v2.[i])
                     let d = diff ** p
 
-                    if not (isNan d) then
+                    if not (Ops.isNan d) then
                         dist <- dist + d
 
                 if p >= 1.0 then
@@ -273,7 +273,7 @@ module DistanceMetrics =
             let mutable dist = 0.0
             for i in 0 .. (dim - 1) do
                 let x = a1.[i] - a2.[i]
-                if not (isNan x) then
+                if not (Ops.isNan x) then
                     dist <- dist + (x * x)
             float dist
 
@@ -311,7 +311,7 @@ module DistanceMetrics =
             let mutable dist = 0.0
             for i in 0 .. (dim - 1) do 
                 let x = a1.[i] - a2.[i]
-                if not (isNan x) then
+                if not (Ops.isNan x) then
                     dist <- dist + System.Math.Abs x
             dist
 
@@ -381,7 +381,7 @@ module DistanceMetrics =
                     let diff = abs (a1.[i] - a2.[i])
                     let d = diff ** p
 
-                    if not (isNan d) then
+                    if not (Ops.isNan d) then
                         dist <- dist + d
 
                 if p >= 1.0 then

src/FSharp.Stats/Distributions/Bandwidth.fs

@@ -43,7 +43,7 @@ module Bandwidth =
         /// </code>
         /// </example>
         let sturges ndataLength =
-            ceil (1. + log2 ndataLength)
+            ceil (1. + Ops.log2 ndataLength)
 
 
         /// <summary>The Rice Rule is presented as a simple alternative to Sturges's rule.</summary>
@@ -88,8 +88,8 @@ module Bandwidth =
     let forHistogram data =
         let data' =
             data
-            |> Seq.filter (fun v -> not (isNan v))
-            |> Seq.filter (fun v -> not (isInf v))
+            |> Seq.filter (fun v -> not (Ops.isNan v))
+            |> Seq.filter (fun v -> not (Ops.isInf v))
 
         let interval = Seq.range data' 
         let dmin,dmax = Interval.values interval

src/FSharp.Stats/Distributions/Continuous/Gamma.fs

@@ -148,7 +148,7 @@ type Gamma =
         Gamma.CheckParam alpha beta
         match alpha,beta with
         | 0., 0. -> infNeg
-        | a , b when isPosInf(b) -> if a = x then infinity else 0. 
+        | a , b when Ops.isPosInf(b) -> if a = x then infinity else 0. 
         | 1., _ -> beta * exp(-beta*x)
         | _ -> Gamma.PDFLn alpha beta x |> exp
 
@@ -167,7 +167,7 @@ type Gamma =
         //shape rate
         match alpha,beta with
         | 0., 0. -> 0.
-        | a , b when isPosInf(b) -> if a = x then infinity else infNeg 
+        | a , b when Ops.isPosInf(b) -> if a = x then infinity else infNeg 
         | 1., _ -> log(beta) * (-beta*x)
         | _     -> (alpha - 1.) * log(x) - x / beta - (alpha * log(beta)
                     + SpecialFunctions.Gamma.gammaLn(alpha)) 

src/FSharp.Stats/Distributions/Discrete/Binomial.fs

@@ -21,7 +21,7 @@ type Binomial =
 
     // Binomial distribution helper functions.
     static member CheckParam p n = 
-        if n < 0 || p < 0. || p > 1. || isNan(p) then 
+        if n < 0 || p < 0. || p > 1. || Ops.isNan(p) then 
             failwith "Binomial distribution should be parametrized by n > 0.0 and 0 ≤ p ≤ 1."
 
     /// <summary>Computes the mode.</summary>

src/FSharp.Stats/Distributions/Discrete/Multinomial.fs

@@ -16,7 +16,7 @@ type Multinomial =
         if n < 0 then
             failwith "Multinomial distribution should be parametrized by n >= 0."
         let checkBetween p =
-            p < 0. || p > 1. || isNan(p)
+            p < 0. || p > 1. || Ops.isNan(p)
         if (p |> Seq.map checkBetween |> Seq.exists id) then 
             failwith "Multinomial distribution should be parametrized by 0 ≤ p_i ≤ 1."
 

src/FSharp.Stats/Fitting/GoodnessOfFit.fs

@@ -424,14 +424,14 @@ module GoodnessOfFit =
                                 else 
                                     let rnd = rnd.Next(0,n)
                                     let tmp = zippedData.[rnd]
-                                    if not (isNan(fst tmp)) then
+                                    if not (Ops.isNan(fst tmp)) then
                                         zippedData.[rnd] <- (nan,nan)
                                         loop (i+1) (tmp::acc)
                                     else loop i acc
                             loop 0 []
                             )
                     //generate the kth subset out of the left over values in the original data set
-                    let rest = zippedData |> Array.filter (fun (a,b) -> not (isNan a))
+                    let rest = zippedData |> Array.filter (fun (a,b) -> not (Ops.isNan a))
                     //combine all the subsets
                     let subsequence = Array.append [|rest|] chunks 
 

src/FSharp.Stats/Fitting/LinearRegression.fs

@@ -665,11 +665,11 @@ module LinearRegression =
                     let factor = 
                         //[for l = 0 to (level - 1) do yield i-l] 
                         List.init level (fun l -> i-l)
-                        |> List.filter (not << isNan)
+                        |> List.filter (not << Ops.isNan)
                         |> List.fold (fun acc c -> acc * (float c)) 1.
                     factor * coef.Coefficients.[i] * (pown x (i-level))
                     )
-                |> Array.filter (not << isNan)
+                |> Array.filter (not << Ops.isNan)
                 |> Array.sum
 
             /// <summary>

src/FSharp.Stats/Fitting/NonLinearRegression.fs

@@ -236,7 +236,7 @@ module NonLinearRegression =
         ///
         let private validateBounds (lowerBound: vector) (upperBound: vector) (parameters: vector) =
             try
-                if Vector.map3 (fun l u x -> if l <= x && u >= x then x else nan) lowerBound upperBound parameters |> Vector.exists isNan then 
+                if Vector.map3 (fun l u x -> if l <= x && u >= x then x else nan) lowerBound upperBound parameters |> Vector.exists Ops.isNan then 
                     failwith "initial parameters are not within Bounds"
                 else 
                     ()

src/FSharp.Stats/Interpolation.fs

@@ -2181,7 +2181,7 @@ module Interpolation =
             let xy = 
                 Seq.zip xData yData
                 // Remove nan
-                |> Seq.filter (fun (x,y) -> not (isNan x || isNan y || isInf x || isInf y))
+                |> Seq.filter (fun (x,y) -> not (Ops.isNan x || Ops.isNan y || Ops.isInf x || Ops.isInf y))
                 // sort by x
                 |> Seq.sortBy fst
                 |> Seq.groupBy fst

src/FSharp.Stats/Interval.fs

@@ -205,7 +205,7 @@ type Interval<'a when 'a : comparison> =
                 | true  -> 
                     let current = projection e.Current
                     // fail if collection contains nan
-                    if isfloat && isNan current then 
+                    if isfloat && Ops.isNan current then 
                         //Interval.Empty 
                         invalidOp "Interval cannot be determined if collection contains nan"
                     else

src/FSharp.Stats/List.fs

@@ -55,7 +55,7 @@ module List =
             | [] ->
                 // place pivot in equal pile
                 cont [] 0 [x] 1 [] 0
-            | y::ys when isNan y -> y
+            | y::ys when Ops.isNan y -> y
             | y::ys ->
                 if y < x then
                     // place item in less-than pile
@@ -84,7 +84,7 @@ module List =
         let rec loop before xs after =
             match xs with
             | [] -> failwith "Median of empty list"
-            | x::xs when isNan x -> x
+            | x::xs when Ops.isNan x -> x
             | x::xs ->
                 partition x xs (fun lts numlt eqs numeq gts numgt ->
                     if before + numlt > numeq + numgt + after then

src/FSharp.Stats/ML/Unsupervised/IterativeClustering.fs

@@ -121,7 +121,7 @@ module IterativeClustering =
     /// </code>
     /// </example>
     let private meanNaN (input: float []) = 
-        let isValid f = not (isNan f || isInf f)
+        let isValid f = not (Ops.isNan f || Ops.isInf f)
         let rec loop i sum count = 
             if i < input.Length then 
                 let current = input.[i]

src/FSharp.Stats/ML/Unsupervised/PrincipalComponentAnalysis.fs

@@ -33,7 +33,7 @@ module PCA =
     /// </code>
     /// </example>
     let center m = 
-        if m |> Matrix.exists (fun x -> isNan x || isInf x) then 
+        if m |> Matrix.exists (fun x -> Ops.isNan x || Ops.isInf x) then 
             failwith "Computation not possible. Matrix contains invalid entries. Check for the existence of values equal to nan, infinity or -infinity."
         else
         let columnMeans =
@@ -68,7 +68,7 @@ module PCA =
     /// </code>
     /// </example>
     let compute m =  
-        if m |> Matrix.exists (fun x -> isNan x || isInf x) then 
+        if m |> Matrix.exists (fun x -> Ops.isNan x || Ops.isInf x) then 
             failwith "Computation not possible. Matrix contains invalid entries. Check for the existence of values equal to nan, infinity or -infinity."
         else
         let s,u,v = FSharp.Stats.Algebra.LinearAlgebra.SVD (m) 

src/FSharp.Stats/Ops.fs

@@ -3,8 +3,7 @@ namespace FSharp.Stats
 #nowarn "40"
 #nowarn "42"
 
-/// Operations module (automatically opened)
-[<AutoOpen>]
+/// Operations module
 module Ops =
     open System
     open System

src/FSharp.Stats/Precision.fs

@@ -15,9 +15,9 @@ module Precision =
     /// </code>
     /// </example>
     let almostEqualNormRelative maximumError a b  = 
-        if a |> isInf || b |> isInf then
+        if a |> Ops.isInf || b |> Ops.isInf then
             a = b 
-        elif a |> isNan || b |> isNan then
+        elif a |> Ops.isNan || b |> Ops.isNan then
             false 
         elif ((a - b) |> abs) < maximumError  then 
             true

src/FSharp.Stats/Quantile.fs

@@ -408,11 +408,11 @@ module Quantile =
         if (q < 0. || q > 1. || data.Length = 0) then
             nan
         elif (h' <= 0 || q = 0.) then
-            if Array.exists isNan data then 
+            if Array.exists Ops.isNan data then 
                 nan 
             else Array.min data
         elif (h' >= data.Length || q = 1.) then
-            if Array.exists isNan data then 
+            if Array.exists Ops.isNan data then 
                 nan 
             else Array.max data
         else

src/FSharp.Stats/Random.fs

@@ -72,7 +72,7 @@ module Random =
     /// </remarks>
     let boxMullerTransform() =
         let (u1,u2) = rndgen.NextFloat(),rndgen.NextFloat()
-        let z0 = sqrt(-2. * log u1) * cos (2. * pi * u2)
-        let z1 = sqrt(-2. * log u1) * sin (2. * pi * u2)
+        let z0 = sqrt(-2. * log u1) * cos (2. * Ops.pi * u2)
+        let z1 = sqrt(-2. * log u1) * sin (2. * Ops.pi * u2)
         z0,z1
 

src/FSharp.Stats/Seq.fs

@@ -272,7 +272,7 @@ module Seq =
             let random = Random.rndgen
             let pivotIndex = left + random.NextInt() % (right - left + 1)
             let pivot = items.[pivotIndex]
-            if isNan pivot then
+            if Ops.isNan pivot then
                 ~~~pivotIndex
             else
                 swapInPlace pivotIndex right items // swap random pivot to right.
@@ -287,7 +287,7 @@ module Seq =
                 let rec loop i j =
                     if j <  right then 
                         let v = items.[j]
-                        if isNan v then   // true if nan
+                        if Ops.isNan v then   // true if nan
                             loop (~~~j) right // break beacause nan                    
                         else
                             if (v <= pivot) then        
@@ -1151,7 +1151,7 @@ module Seq =
         /// <returns>sum of squares</returns> 
         let sumOfSquares (xData:seq<float>) (exData:seq<float>) =
             let xX = Seq.zip xData exData 
-            Seq.fold (fun acc (x,ex) -> acc + square (x - ex)) 0. xX
+            Seq.fold (fun acc (x,ex) -> acc + Ops.square (x - ex)) 0. xX
 
 
         /// <summary>

src/FSharp.Stats/Signal/FFT.fs

@@ -52,7 +52,7 @@ module FFT =
     // FFT Helper function
     let private fftAux (a : Complex array) n j sign m = 
         let w = 
-            let t = pi * float (sign * m) / float j 
+            let t = Ops.pi * float (sign * m) / float j 
             Complex(cos t, sin t)
         let mutable i = m 
         while i < n do 
@@ -90,7 +90,7 @@ module FFT =
     let private bluestein a = 
 
         let bluesteinSequence n = 
-            let s = pi / float n 
+            let s = Ops.pi / float n 
             Array.init n ( fun k -> 
                 let t = s * float(k * k) 
                 Complex (cos t, sin t)

src/FSharp.Stats/SpecialFunctions/Beta.fs

@@ -135,7 +135,7 @@ module Beta =
         let ai = 1.0 / a
         let ui = (1.0 - b) * x 
         let t1 = ui / (a + 1.0)
-        let z  = epsilon * ai
+        let z  = Ops.epsilon * ai
 
         let rec loop u t v s n =
             if (abs v > z) then 
@@ -149,12 +149,12 @@ module Beta =
         let s = loop ui ui t1 0. 2.  
         let u = a * log x
 
-        if ((a + b) < Gamma.maximum && abs u < logMax) then
+        if ((a + b) < Gamma.maximum && abs u < Ops.logMax) then
             let t = Gamma.gamma (a + b) / (Gamma.gamma a * Gamma.gamma b)
             s * t * System.Math.Pow(x, a)
         else
             let t = Gamma.gammaLn (a + b) - Gamma.gammaLn a - Gamma.gammaLn b + u + log s
-            if (t < logMin) then
+            if (t < Ops.logMin) then
                 0.0
             else
                 exp t

src/FSharp.Stats/SpecialFunctions/Gamma.fs

@@ -186,7 +186,7 @@ module Gamma =
         match x with
         | x when x = 0. -> 0.
         | x when (x < 0.0 || a <= 0.0) -> nan
-        | x when (isPosInf x) -> 1.
+        | x when (Ops.isPosInf x) -> 1.
         | _ -> 
             if (x= 0.0) then 0.0
             elif (a >= ASWITCH) then
@@ -205,7 +205,7 @@ module Gamma =
         match x with
         | x when x = 0. -> 1.
         | x when (x < 0.0 || a <= 0.0) -> nan
-        | x when (isPosInf x) -> 0.
+        | x when (Ops.isPosInf x) -> 0.
         | _ -> 
             if (x= 0.0) then 1.0
             elif (a >= ASWITCH) then

src/FSharp.Stats/Testing/MultipleTesting.fs

@@ -155,12 +155,12 @@ module MultipleTesting =
             let pvaluesExtValid =
                 pvaluesExt 
                 |> Array.indexed   
-                |> Array.filter (fun (i,p) -> not (isNan p))
+                |> Array.filter (fun (i,p) -> not (Ops.isNan p))
 
             let pvaluesExtInValid = 
                 pvaluesExt 
                 |> Array.indexed   
-                |> Array.filter (fun (i,p) -> (isNan p))
+                |> Array.filter (fun (i,p) -> (Ops.isNan p))
 
             // if all pvalues are none, just return the nans
             if pvaluesExtValid.Length = 0 then 
@@ -252,12 +252,12 @@ module MultipleTesting =
             let pvaluesExtValid =
                 pvaluesExt 
                 |> Array.indexed   
-                |> Array.filter (fun (i,p) -> not (isNan p))
+                |> Array.filter (fun (i,p) -> not (Ops.isNan p))
 
             let pvaluesExtInValid = 
                 pvaluesExt 
                 |> Array.indexed   
-                |> Array.filter (fun (i,p) -> (isNan p))
+                |> Array.filter (fun (i,p) -> (Ops.isNan p))
 
             // if all pvalues are none, just return the nans
             if pvaluesExtValid.Length = 0 then