Add accessor functions (#10)

Author: eliascarv

src/interface.jl

@@ -50,3 +50,24 @@ function Base.show(io::IO, model::StatsLearnModel{M}) where {M}
   println(io, "├─ input: $(model.input)")
   print(io, "└─ output: $(model.output)")
 end
+
+"""
+    StatsLearnModels.model(lmodel::StatsLearnModel)
+  
+Returns the model of the `lmodel`.
+"""
+model(lmodel::StatsLearnModel) = lmodel.model
+
+"""
+    StatsLearnModels.input(lmodel::StatsLearnModel)
+  
+Returns the input column selection of the `lmodel`.
+"""
+input(lmodel::StatsLearnModel) = lmodel.input
+
+"""
+    StatsLearnModels.output(lmodel::StatsLearnModel)
+  
+Returns the output column selection of the `lmodel`.
+"""
+output(lmodel::StatsLearnModel) = lmodel.output

test/Project.toml

@@ -1,4 +1,5 @@
 [deps]
+ColumnSelectors = "9cc86067-7e36-4c61-b350-1ac9833d277f"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 GLM = "38e38edf-8417-5370-95a0-9cbb8c7f171a"

test/runtests.jl

@@ -6,6 +6,7 @@ using Test
 
 using GLM: ProbitLink
 using Distributions: Binomial
+using ColumnSelectors: selector
 
 import MLJ, MLJDecisionTreeInterface
 
@@ -24,8 +25,17 @@ const SLM = StatsLearnModels
   end
 
   @testset "StatsLearnModel" begin
-    model = SLM.StatsLearnModel(DecisionTreeClassifier(), [:a, :b], :c)
-    @test sprint(show, model) == """
+    # accessor functions
+    model = DecisionTreeClassifier()
+    incols = selector([:a, :b])
+    outcols = selector(:c)
+    lmodel = SLM.StatsLearnModel(model, incols, outcols)
+    @test SLM.model(lmodel) === model
+    @test SLM.input(lmodel) === incols
+    @test SLM.output(lmodel) === outcols
+    # show
+    lmodel = SLM.StatsLearnModel(DecisionTreeClassifier(), [:a, :b], :c)
+    @test sprint(show, lmodel) == """
     StatsLearnModel{DecisionTreeClassifier}
     ├─ input: [:a, :b]
     └─ output: :c"""