Fix revert for ParallelTableTrasform (#146)

* Fix revert for ParallelTableTrasform

* Update test/metadata.jl

* Add more tests

* Fix tests for VarMeta

* Improve docstring for ParallelTableTransform

Author: juliohm

src/transforms/parallel.jl

@@ -6,13 +6,22 @@
     ParallelTableTransform(transforms)
 
 A transform where `transforms` are applied in parallel.
+It [`isrevertible`](@ref) if any of the constituent
+`transforms` is revertible. In this case, the
+[`revert`](@ref) is performed with the first
+revertible transform in the list.
 
 # Examples
 
 ```julia
 Scale(low=0.3, high=0.6) ⊔ EigenAnalysis(:VDV)
 ZScore() ⊔ EigenAnalysis(:V)
 ```
+
+### Notes
+
+- Metadata is transformed with the first revertible
+  transform in the list of `transforms`.
 """
 struct ParallelTableTransform <: TableTransform
   transforms::Vector{Transform}
@@ -95,19 +104,16 @@ function revert(p::ParallelTableTransform, newtable, cache)
   fcols = Tables.columns(newfeat)
   names = Tables.columnnames(fcols)
 
-  # retrieve subtable to revert
+  # subset of features to revert
   rnames = names[range]
   rcols  = [Tables.getcolumn(fcols, j) for j in range]
   rfeat  = (; zip(rnames, rcols)...) |> Tables.materializer(newfeat)
 
-  # revert transform on subtable
-  feat = revert(rtrans, rfeat, rcache)
-
   # propagate metadata
-  meta = newmeta
+  rtable = attach(rfeat, newmeta)
 
-  # attach features and metadata
-  attach(feat, meta)
+  # revert transform
+  revert(rtrans, rtable, rcache)
 end
 
 function reapply(p::ParallelTableTransform, table, cache)

test/metadata.jl

@@ -32,6 +32,15 @@
     mtₒ = revert(T, mn, mc)
     @test mtₒ.meta == mt.meta
     @test Tables.matrix(mtₒ.table) ≈ Tables.matrix(mt.table)
+
+    T = (Functional(sin) → MinMax()) ⊔ Center()
+    mn, mc = apply(T, mt)
+    tn, tc = apply(T, t)
+    @test mn.meta == m
+    @test mn.table == tn
+    mtₒ = revert(T, mn, mc)
+    @test mtₒ.meta == mt.meta
+    @test Tables.matrix(mtₒ.table) ≈ Tables.matrix(mt.table)
   end
 
   @testset "VarMeta" begin
@@ -67,5 +76,27 @@
     mtₒ = revert(T, mn, mc)
     @test mtₒ.meta == mt.meta
     @test Tables.matrix(mtₒ.table) ≈ Tables.matrix(mt.table)
+
+    # first revertible branch has two transforms,
+    # so metadata is increased by 2 + 2 = 4
+    T = (Functional(sin) → MinMax()) ⊔ Center()
+    mn, mc = apply(T, mt)
+    tn, tc = apply(T, t)
+    @test mn.meta == VarMeta(m.data .+ 4)
+    @test mn.table == tn
+    mtₒ = revert(T, mn, mc)
+    @test mtₒ.meta == mt.meta
+    @test Tables.matrix(mtₒ.table) ≈ Tables.matrix(mt.table)
+
+    # first revertible branch has one transform,
+    # so metadata is increased by 2
+    T = Center() ⊔ (Functional(sin) → MinMax())
+    mn, mc = apply(T, mt)
+    tn, tc = apply(T, t)
+    @test mn.meta == VarMeta(m.data .+ 2)
+    @test mn.table == tn
+    mtₒ = revert(T, mn, mc)
+    @test mtₒ.meta == mt.meta
+    @test Tables.matrix(mtₒ.table) ≈ Tables.matrix(mt.table)
   end
 end