Add CategoricalArrays.jl extension (#4)

Project.toml

@@ -4,16 +4,19 @@ authors = ["Elias Carvalho <eliascarvdev@gmail.com> and contributors"]
 version = "0.1.0"
 
 [weakdeps]
+CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"
 CoDa = "5900dafe-f573-5c72-b367-76665857777b"
-Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"
 DynamicQuantities = "06fc5a27-2a28-4c7c-a15d-362465fb6821"
+Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"
 
 [extensions]
+SciTypesCategoricalArraysExt = "CategoricalArrays"
 SciTypesCoDaExt = "CoDa"
-SciTypesUnitfulExt = "Unitful"
 SciTypesDynamicQuantitiesExt = "DynamicQuantities"
+SciTypesUnitfulExt = "Unitful"
 
 [compat]
+CategoricalArrays = "0.10"
 CoDa = "1.0"
 DynamicQuantities = "0.7"
 Unitful = "1.17"

ext/SciTypesCategoricalArraysExt.jl

@@ -0,0 +1,11 @@
+module SciTypesCategoricalArraysExt
+
+using SciTypes
+using CategoricalArrays
+
+SciTypes.scitype(::Type{<:CategoricalValue}) = SciTypes.Categorical
+SciTypes.elscitype(::Type{<:CategoricalArray}) = SciTypes.Categorical
+
+SciTypes.isordered(array::CategoricalArray) = isordered(array)
+
+end

src/SciTypes.jl

@@ -108,6 +108,18 @@ Convert the scientific type of elements of the iterable `itr` to `S`.
 """
 coerce(::Type{S}, itr) where {S<:SciType} = map(x -> sciconvert(S, x), itr)
 
+"""
+    isordered(itr)
+
+Checks whether the categorical variables of the iterable `itr` are ordered.
+"""
+function isordered(itr)
+  if !(elscitype(itr) <: Categorical)
+    throw(ArgumentError("iterable elements are not categorical"))
+  end
+  false
+end
+
 #---------
 # EXPORTS
 #---------

test/Project.toml

@@ -1,4 +1,5 @@
 [deps]
+CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"
 CoDa = "5900dafe-f573-5c72-b367-76665857777b"
 DynamicQuantities = "06fc5a27-2a28-4c7c-a15d-362465fb6821"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

test/runtests.jl

@@ -1,4 +1,5 @@
 using SciTypes
+using CategoricalArrays
 import DynamicQuantities
 import Unitful
 using CoDa
@@ -92,6 +93,16 @@ using Test
     @test elscitype(coerce(SciTypes.Continuous, (1, 2, 3))) <: SciTypes.Continuous
   end
 
+  @testset "isordered" begin
+    @test !SciTypes.isordered([1, 2, 3])
+    @test !SciTypes.isordered((:a, :b, :c))
+    @test !SciTypes.isordered(['a', 'b', 'c'])
+    @test !SciTypes.isordered(("a", "b", "c"))
+
+    # throws
+    @test_throws ArgumentError SciTypes.isordered([1.0, 2.0, 3.0])
+  end
+
   @testset "missing values" begin
     @test scitype(Missing) <: SciTypes.Unknown
     @test scitype(Union{Float64,Missing}) <: SciTypes.Continuous
@@ -105,9 +116,9 @@ using Test
   @testset "CoDa" begin
     c1 = Composition(a=0.2, b=0.8)
     c2 = Composition(a=0.5, b=0.5)
-    @test scitype(Composition{2, (:a, :b)}) <: SciTypes.Compositional
+    @test scitype(Composition{2,(:a, :b)}) <: SciTypes.Compositional
     @test scitype(c1) <: SciTypes.Compositional
-    @test elscitype(Vector{Composition{2, (:a, :b)}}) <: SciTypes.Compositional
+    @test elscitype(Vector{Composition{2,(:a, :b)}}) <: SciTypes.Compositional
     @test elscitype([c1, c2]) <: SciTypes.Compositional
     @test elscitype([c1, missing, c2]) <: SciTypes.Compositional
   end
@@ -160,4 +171,19 @@ using Test
     @test isequal(coerce(SciTypes.Continuous, [1 * ui, missing, 3 * ui]), [1.0 * uf, missing, 3.0 * uf])
     @test elscitype(coerce(SciTypes.Continuous, [1 * ui, missing, 3 * ui])) <: SciTypes.Continuous
   end
+
+  @testset "CategoricalArrays" begin
+    carr = categorical([1, 2, 3])
+    cval = first(carr)
+    CV = typeof(cval)
+    CA = typeof(carr)
+    @test scitype(CV) <: SciTypes.Categorical
+    @test scitype(cval) <: SciTypes.Categorical
+    @test elscitype(CA) <: SciTypes.Categorical
+    @test elscitype(carr) <: SciTypes.Categorical
+    @test elscitype(categorical([1, missing, 3])) <: SciTypes.Categorical
+    @test !SciTypes.isordered(carr)
+    carr = categorical([1, 3, 2], ordered=true)
+    @test SciTypes.isordered(carr)
+  end
 end