Merge pull request #19 from JuliaAI/classes

Make classes(v) work for views of categorical arrays

Author: ablaom

src/utilities.jl

@@ -21,7 +21,8 @@ always true.
 
 Not to be confused with `levels(x.pool)`. See the example below.
 
-Also, overloaded for `x` a `CategoricalArray` or `CategoricalPool`.
+Also, overloaded for `x` a `CategoricalArray`, `CategoricalPool`, and
+for views of `CategoricalArray`.
 
 **Private method.*
 
@@ -57,7 +58,7 @@ Also, overloaded for `x` a `CategoricalArray` or `CategoricalPool`.
 classes(p::CategoricalPool) = [p[i] for i in 1:length(p)]
 classes(x::CategoricalValue) = classes(CategoricalArrays.pool(x))
 classes(v::CategoricalArray) = classes(CategoricalArrays.pool(v))
-
+classes(v::SubArray{<:Any, <:Any, <:CategoricalArray}) = classes(parent(v))
 
 # # CATEGORICAL VALUES TO INTEGERS
 

test/types.jl

@@ -36,7 +36,7 @@ end
     UnivariateFinite(supp, probs, pool=missing, augment=true);
 
     # dimension mismatches:
-    badprobs = rand(40, 3)
+    badprobs = rand(rng, 40, 3)
     @test_throws(CategoricalDistributions.err_dim(supp, badprobs),
                  UnivariateFinite(supp, badprobs, pool=missing))
 
@@ -60,7 +60,7 @@ end
     probs = probs ./ sum(probs)
     u = UnivariateFinite(probs, pool=missing);
     @test u isa UnivariateFinite
-    probs = rand(10, 2)
+    probs = rand(rng, 10, 2)
     probs = probs ./ sum(probs, dims=2)
     u = UnivariateFinite(probs, pool=missing);
     @test u.scitype == Multiclass{2}
@@ -73,9 +73,11 @@ end
 
     v = categorical(1:3)
     @test_logs((:warn, r"Ignoring"),
-               UnivariateFinite(v[1:2], rand(3), augment=true, pool=missing));
+               UnivariateFinite(v[1:2], rand(rng, 3),
+                                augment=true, pool=missing));
     @test_logs((:warn, r"Ignoring"),
-               UnivariateFinite(v[1:2], rand(3), augment=true, ordered=true));
+               UnivariateFinite(v[1:2], rand(rng, 3),
+                                augment=true, ordered=true));
 
     # using `UnivariateFiniteArray` as a constructor just falls back
     # to `UnivariateFinite` constructor:

test/utilities.jl

@@ -17,6 +17,8 @@ import CategoricalDistributions: classes, transform, decoder, int
     levels!(v, reverse(levels(v)))
     @test classes(v[1]) == levels(v)
     @test classes(v) == levels(v)
+    vsub = view(v, 1:2)
+    @test classes(vsub) == classes(v)
 end
 
 @testset "int, classes, decoder" begin