Merge NamedTuple transforms by merging the underlying NamedTuples

docs/src/index.md

@@ -85,6 +85,19 @@ See `methods(as)` for all the constructors, `?as` for their documentation.
 as
 ```
 
+Transforms which produce `NamedTuple`s can be `merge`d, which internally calls `Base.merge`; name collisions will thus follow `Base` behavior, which is that the right-most instance will be kept.
+When using e.g. [`ConstructionBase.setproperties`](https://juliaobjects.github.io/ConstructionBase.jl/stable/#ConstructionBase.setproperties) to map a vector onto a subset of parameters stored in a struct, this functionality allows transforms for different parameter subsets to be constructed for use separately or together:
+
+```julia
+t_a = as((;a = asℝ₊))
+t_b = as((;b = as𝕀))
+t_c = as((;c = TVShift(5) ∘ TVExp()))
+t_ab = merge(t_a, t_b)
+t_abc = merge(t_ab, t_c)
+t_abc = merge(t_a, t_b, t_c)
+t_collision = merge(t_a, as((;a = asℝ₋))) # Will have a = asℝ₋, from rightmost
+```
+
 ## Scalar transforms
 
 The symbol `∞` is a placeholder for infinity. It does not correspond to `Inf`, but acts as a placeholder for the correct dispatch. `-∞` is valid.

src/aggregation.jl

@@ -286,6 +286,15 @@ Base.getindex(t::TransformTuple, i::Int) = getindex(_inner(t), i)
 Base.propertynames(t::TransformTuple) = propertynames(_inner(t))
 Base.getproperty(t::TransformTuple, i::Int) = getproperty(_inner(t), i)
 Base.getproperty(t::TransformTuple{<:NamedTuple}, i::Symbol) = getproperty(_inner(t), i)
+"""
+$(SIGNATURES)
+
+Merge multiple `TransformTuple{<:NamedTuple}` by merging the underlying `NamedTuple`s.
+"""
+function Base.merge(t1::TransformTuple{<:NamedTuple}, 
+                    ts::Vararg{TransformTuple{<:NamedTuple}})
+    TransformTuple(merge(_inner(t1), map(_inner, ts)...))
+end
 
 function _summary_rows(transformation::TransformTuple, mime)
     inner = _inner(transformation)

test/runtests.jl

@@ -506,6 +506,31 @@ end
     @test_throws ArgumentError("Property :b not in (:a, :c).") inverse(t, (a = 1.0, c = 2.0))
 end
 
+@testset "merging NamedTuple" begin
+    t1 = as((a = asℝ, b = as𝕀))
+    t2 = as((c = CorrCholeskyFactor(3), d = unit_vector_norm(4)))
+    t3 = as((e = asℝ₊, f = as𝕀))
+    tm = @inferred(merge(t1))
+    @test tm == t1
+    tm = @inferred(merge(t1, t2))
+    @test tm == as((a = asℝ, b = as𝕀, c = CorrCholeskyFactor(3), d = unit_vector_norm(4)))
+    tm = @inferred(merge(t1, t2, t3))
+    @test tm == as((a = asℝ, b = as𝕀, c = CorrCholeskyFactor(3), d = unit_vector_norm(4),
+                    e = asℝ₊, f = as𝕀))
+    x = randn(dimension(tm))
+    y = transform(tm, x)
+    x′ = inverse(tm, y)
+    @test x ≈ x′
+    # Check merge collision behavior: rightmost gets kept
+    t4 = as((b = asℝ₋, c = TVScale(2.0)))
+    tm = @inferred(merge(t1, t4))
+    @test tm == as((a = asℝ, b = asℝ₋, c = TVScale(2.0)))
+    @test tm != as((a = asℝ, b = as𝕀, c = TVScale(2.0)))
+    tm = @inferred(merge(t1, t4, t2))
+    @test tm == as((a = asℝ, b = asℝ₋, c = CorrCholeskyFactor(3), d = unit_vector_norm(4)))
+
+end
+
 ####
 #### log density correctness checks
 ####