Merge pull request #44 from JuliaAI/dev

For a 0.3.2 release

Author: ablaom

Project.toml

@@ -1,7 +1,7 @@
 name = "MLJMultivariateStatsInterface"
 uuid = "1b6a4a23-ba22-4f51-9698-8599985d3728"
 authors = ["Anthony D. Blaom <[email protected]>", "Thibaut Lienart <[email protected]>", "Okon Samuel <[email protected]>"]
-version = "0.3.1"
+version = "0.3.2"
 
 [deps]
 Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"

src/models/decomposition_models.jl

@@ -340,8 +340,13 @@ model_types = [
 ]
 
 for (M, MFitResultType) in model_types
-    @eval function MMI.fitted_params(::$M, fr)
-        return (projection=copy(MS.projection(fr)),)
+
+    if M !== ICA # special cased below
+        quote
+            function MMI.fitted_params(::$M, fr)
+                return (projection=copy(MS.projection(fr)),)
+            end
+        end |> eval
     end
 
     @eval function MMI.transform(::$M, fr::$MFitResultType, X)
@@ -360,3 +365,5 @@ for (M, MFitResultType) in model_types
         end
     end
 end
+
+MMI.fitted_params(::ICA, fr) = (projection=copy(fr.W), mean = copy(MS.mean(fr)))

test/models/decomposition_models.jl

@@ -75,7 +75,6 @@ end
     test_composition_model(ica_ms, ica_mlj, X, X_array, test_inverse=false)
 end
 
-
 @testset "PPCA" begin
     X_array = matrix(X)
     tolerance = 5.0

test/testutils.jl

@@ -39,4 +39,8 @@ function test_composition_model(ms_model, mlj_model, X, X_array ; test_inverse=t
         Xinv_mlj = matrix(Xinv_mlj_table)
         @test Xinv_ms ≈ Xinv_mlj
     end
+
+    # smoke test for issue #42
+    fp = MLJBase.fitted_params(mlj_model, fitresult)
+    :projection in keys(fp)
 end