🔧 rewrite code

src/Xicor.jl

@@ -2,9 +2,39 @@ module Xicor
 
 using Distributions, Random, StatsBase
 
+"""
+ xicor(X, Y; rank=tiedrank, noties=false)
+
+Computes the asymmetric ξ correlation coefficient sbetween two vectors `X` and `Y`.
+`rank` species how the rank is computed, default uses `tiedrank`. If there
+are no ties in `Y`, `noties` can be set to `true`, which speeds up computation.
+
+`ξ` is an alias for this function.
+"""
+function xicor(X::AbstractVector, Y::AbstractVector; rank=denserank, noties=false)
+ @assert length(X) == length(Y) "length `X` and `Y` missmatch"
+ n = length(Y)
+ xsortperm = sortperm(X)
+ # todo: carfully check the rank function
+ r = rank(xsortperm, by=i->Y[i])
+ if !noties
+ l = rank(xsortperm, by=i->Y[i], rev=true)
+ end
+ ξn = 0.0
+ for i in 1:n-1
+ ξn += abs(r[i+1] - r[i])
+ end
+ ξn *= noties ? 3 / (n^2 - 1) : n / 2sum(li->li*(n-li), l)
+ ξn = 1 - ξn
+ return ξn
+end
+
+ξ = xicor
+
+
 include("correlation.jl")
 include("rank.jl")
 
-export xicor
+export xicor, ξ
 
 end

src/rank.jl

@@ -2,29 +2,33 @@ using Random, StatsBase
 
 
 """
+ maxrank(x)
+
 A function that returns the sample ranks using maximum ranks 
 for equal values.
  - x : A Vector of Floats, Integers, or Bools
 """
-function maxrank(x)
+function maxrank(x::AbstractVector)
  sorted_x = sort(x)
  ranks = zeros(Int, length(x))
- for (idx,i) in enumerate(x)
+ for (idx, i) in enumerate(x)
  ranks[idx] = findlast(isequal(i), sorted_x)
  end
  return ranks
 end
 
 
 """
+ minrank(x)
+
 A function that returns the sample ranks using minimum ranks 
 for equal values.
  - x : A Vector of Floats, Integers, or Bools
 """
 function minrank(x)
  sorted_x = sort(x)
  ranks = zeros(Int, length(x))
- for (idx,i) in enumerate(x)
+ for (idx, i) in enumerate(x)
  ranks[idx] = findfirst(isequal(i), sorted_x)
  end
  return ranks
@@ -38,11 +42,8 @@ of equal values.
  - seed : either an Integer to seed the random number 
  generator or `missing` to use the default seed.
 """
-function randrank(x; seed=missing)
- @assert typeof(seed) <: Integer || typeof(seed) <: Missing
- if !ismissing(seed)
- Random.seed!(seed)
- end
+function randrank(x; seed::Union{Nothing,Integer}=nothing)
+ @assert seed isa Integer || isnothing(seed)
  sorted_x = sort(x)
  ranks = zeros(Int, length(x))
  for (idx,i) in enumerate(x)
@@ -62,9 +63,8 @@ A function that returns the sample ranks of the values in a vector.
 TO DO: the original R `rank` function has an argument that let's you choose the
  placement of the missing values.
 """
-function rank(x; ties_method::String="average", seed=missing)
+function rank(x; ties_method::String="average", seed::Union{Nothing,Integer}=missing)
  @assert ties_method ∈ ["average", "random", "max", "min"]
- @assert typeof(seed) <: Integer || typeof(seed) <: Missing
 
  # get NA/missing
  missing_values = ismissing.(x)

test/runtests.jl

@@ -2,5 +2,9 @@ using Xicor
 using Test
 
 @testset "Xicor.jl" begin
- # Write your tests here.
+ X = [1, 2, 3, 5]
+ Y = [1.0, 3.0, 8.0, 10.0]
+
+ @test ξ(X, Y) > 0 
+ @test ξ(X, Y, rank=denserank) ≈ ξ(X, Y, rank=denserank, noties=true)
 end