Merge pull request #121 from tpapp/tp/remove-unpack

Remove SimpleUnpack.@unpack, depend on Julia 1.10

.github/workflows/CI.yml

@@ -17,7 +17,7 @@ jobs:
       fail-fast: false
       matrix:
         version:
-          - '1.6' # Replace this with the minimum Julia version that your package supports. E.g. if your package requires Julia 1.5 or higher, change this to '1.5'.
+          - '1.10' # Replace this with the minimum Julia version that your package supports. E.g. if your package requires Julia 1.5 or higher, change this to '1.5'.
           - '1' # Leave this line unchanged. '1' will automatically expand to the latest stable 1.x release of Julia.
         os:
           - ubuntu-latest

Project.toml

@@ -1,7 +1,7 @@
 name = "TransformVariables"
 uuid = "84d833dd-6860-57f9-a1a7-6da5db126cff"
 authors = ["Tamas K. Papp <[email protected]>"]
-version = "0.8.11"
+version = "0.9.0"
 
 [deps]
 ArgCheck = "dce04be8-c92d-5529-be00-80e4d2c0e197"
@@ -12,7 +12,6 @@ InverseFunctions = "3587e190-3f89-42d0-90ee-14403ec27112"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 LogExpFunctions = "2ab3a3ac-af41-5b50-aa03-7779005ae688"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
-SimpleUnPack = "ce78b400-467f-4804-87d8-8f486da07d0a"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 
 [compat]
@@ -24,6 +23,5 @@ InverseFunctions = "0.1"
 LinearAlgebra = "1.6"
 LogExpFunctions = "0.3"
 Random = "1.6"
-SimpleUnPack = "1"
 StaticArrays = "1"
-julia = "1.6"
+julia = "1.10"

src/TransformVariables.jl

@@ -7,7 +7,6 @@ using LogExpFunctions
 using LinearAlgebra: UpperTriangular, logabsdet
 using Random: AbstractRNG, GLOBAL_RNG
 using StaticArrays: MMatrix, SMatrix, SArray, SVector, pushfirst
-using SimpleUnPack: @unpack
 
 import ChangesOfVariables
 import InverseFunctions

src/aggregation.jl

@@ -15,7 +15,7 @@ struct ArrayTransformation{T <: AbstractTransform,M} <: VectorTransform
 end
 
 function _summary_rows(transformation::ArrayTransformation, mime)
-    @unpack inner_transformation, dims = transformation
+    (; inner_transformation, dims) = transformation
     _dims = foldr((a,b) -> "$(string(a))×$(string(b))", dims, init = "")
     rows = _summary_row(transformation, _dims)
     for row in _summary_rows(inner_transformation, mime)
@@ -71,7 +71,7 @@ function as(::Type{Matrix}, args...)
 end
 
 function transform_with(flag::LogJacFlag, transformation::ArrayTransformation, x, index::T) where {T}
-    @unpack inner_transformation, dims = transformation
+    (; inner_transformation, dims) = transformation
     # NOTE not using index increments as that somehow breaks type inference
     d = dimension(inner_transformation) # length of an element transformation
     len = prod(dims)              # number of elements
@@ -102,7 +102,7 @@ function _array_domain_label(inner_transformation, dims, index::Int)
 end
 
 function _domain_label(transformation::ArrayTransformation, index::Int)
-    @unpack inner_transformation, dims = transformation
+    (; inner_transformation, dims) = transformation
     _array_domain_label(inner_transformation, dims, index)
 end
 
@@ -139,7 +139,7 @@ function transform_with(flag::LogJacFlag, t::ViewTransformation, x, index)
 end
 
 function _domain_label(transformation::ViewTransformation, index::Int)
-    @unpack dims = transformation
+    (; dims) = transformation
     _array_domain_label(asℝ, dims, index)
 end
 
@@ -193,7 +193,7 @@ result_size(::StaticArrayTransformation{D,S}) where {D,S} = fieldtypes(S)
 
 function transform_with(flag::LogJacFlag, transformation::StaticArrayTransformation{D,S},
                         x::AbstractVector{T}, index::Int) where {D,S,T}
-    @unpack inner_transformation = transformation
+    (; inner_transformation) = transformation
     # NOTE this is a fix for #112, enforcing types taken from the transformation of the
     # first element.
     y1, ℓ1, index1 = transform_with(flag, inner_transformation, x, index)
@@ -219,7 +219,7 @@ end
 function inverse_at!(x::AbstractVector, index,
                      transformation::Union{ArrayTransformation,StaticArrayTransformation},
                      y::AbstractArray)
-    @unpack inner_transformation = transformation
+    (; inner_transformation) = transformation
     dims = result_size(transformation)
     @argcheck size(y) == dims
     for elt in vec(y)
@@ -267,7 +267,7 @@ struct TransformTuple{T} <: VectorTransform
 end
 
 function _summary_rows(transformation::TransformTuple, mime)
-    @unpack transformations = transformation
+    (; transformations) = transformation
     repr1 = (transformations isa NamedTuple ? "NamedTuple" : "Tuple" ) * " of transformations"
     rows = _summary_row(transformation, repr1)
     _index = 0
@@ -369,13 +369,13 @@ function transform_with(flag::LogJacFlag, tt::TransformTuple{<:Tuple}, x, index)
 end
 
 function inverse_eltype(tt::TransformTuple{<:Tuple}, y::Tuple)
-    @unpack transformations = tt
+    (; transformations) = tt
     @argcheck length(transformations) == length(y)
     _inverse_eltype_tuple(transformations, y)
 end
 
 function inverse_at!(x::AbstractVector, index, tt::TransformTuple{<:Tuple}, y::Tuple)
-    @unpack transformations = tt
+    (; transformations) = tt
     @argcheck length(transformations) == length(y)
     _inverse!_tuple(x, index, tt.transformations, y)
 end
@@ -384,19 +384,19 @@ as(transformations::NamedTuple{N,<:NTransforms}) where N =
     TransformTuple(transformations)
 
 function transform_with(flag::LogJacFlag, tt::TransformTuple{<:NamedTuple}, x, index)
-    @unpack transformations = tt
+    (; transformations) = tt
     y, ℓ, index′ = transform_tuple(flag, values(transformations), x, index)
     NamedTuple{keys(transformations)}(y), ℓ, index′
 end
 
 function inverse_eltype(tt::TransformTuple{<:NamedTuple}, y::NamedTuple)
-    @unpack transformations = tt
+    (; transformations) = tt
     @argcheck _same_set_of_names(transformations, y)
     _inverse_eltype_tuple(values(transformations), values(NamedTuple{keys(transformations)}(y)))
 end
 
 function inverse_at!(x::AbstractVector, index, tt::TransformTuple{<:NamedTuple}, y::NamedTuple)
-    @unpack transformations = tt
+    (; transformations) = tt
     @argcheck _same_set_of_names(transformations, y)
     _inverse!_tuple(x, index, values(transformations), values(NamedTuple{keys(transformations)}(y)))
 end

src/custom.jl

@@ -75,12 +75,12 @@ CustomTransform(n::Integer, f, flatten; kwargs...) =
 dimension(t::CustomTransform) = dimension(t.g)
 
 function transform_with(flag::NoLogJac, t::CustomTransform, x::AbstractVector, index)
-    @unpack g, f = t
+    (; g, f) = t
     f(first(transform_with(flag, g, x, index))), flag, index + dimension(t)
 end
 
 function transform_with(flag::LogJac, t::CustomTransform, x::AbstractVector, index)
-    @unpack g, f, flatten, cfg = t
+    (; g, f, flatten, cfg) = t
     index = firstindex(x)
     index′ = index + dimension(g)
     y, ℓ = value_and_logjac_forwarddiff(_custom_f(g, f), x[index:(index′ - 1)];

src/generic.jl

@@ -341,7 +341,7 @@ function Base.show(io::IO,  mime::MIME"text/plain", transformation::AbstractTran
         print(io, only(rows).repr, " (dimension $(dimension(transformation)))")
     else
         for (i, row) in enumerate(rows)
-            @unpack level, indices, repr = row
+            (; level, indices, repr) = row
             i > 1 && println(io)
             print(io, ' '^(2 * (level - 1)))
             indices ≢ nothing && print(io, '[', indices, "] ")

src/scalar.jl

@@ -73,7 +73,7 @@ transform(t::ShiftedExp{D}, x::Real) where D =
 transform_and_logjac(t::ShiftedExp, x::Real) = transform(t, x), x
 
 function inverse(t::ShiftedExp{D}, x::Real) where D
-    @unpack shift = t
+    (; shift) = t
     if D
         @argcheck x > shift DomainError
         log(x - shift)

src/special_arrays.jl

@@ -37,7 +37,7 @@ but use `log(r)` for actual calculations so that large `y`s still give nonsingul
 `ℓ` is the log Jacobian (whether it is evaluated depends on `flag`).
 """
 @inline function l2_remainder_transform(flag::LogJacFlag, x, log_r)
-    @unpack logjac, log_l2_rem = tanh_helpers(x)
+    (; logjac, log_l2_rem) = tanh_helpers(x)
     # note that 1-tanh(x)^2 = sech(x)^2
     (tanh(x) * exp(log_r / 2),
      log_r + log_l2_rem,
@@ -80,7 +80,7 @@ function _summary_rows(transformation::UnitVector, mime)
 end
 
 function transform_with(flag::LogJacFlag, t::UnitVector, x::AbstractVector, index)
-    @unpack n = t
+    (; n) = t
     T = robust_eltype(x)
     log_r = zero(T)
     y = Vector{T}(undef, n)
@@ -98,7 +98,7 @@ end
 inverse_eltype(t::UnitVector, y::AbstractVector) = robust_eltype(y)
 
 function inverse_at!(x::AbstractVector, index, t::UnitVector, y::AbstractVector)
-    @unpack n = t
+    (; n) = t
     @argcheck length(y) == n
     log_r = zero(eltype(y))
     @inbounds for yi in axes(y, 1)[1:(end-1)]
@@ -133,7 +133,7 @@ end
 dimension(t::UnitSimplex) = t.n - 1
 
 function transform_with(flag::LogJacFlag, t::UnitSimplex, x::AbstractVector, index)
-    @unpack n = t
+    (; n) = t
     T = robust_eltype(x)
 
     ℓ = logjac_zero(flag, T)
@@ -160,7 +160,7 @@ end
 inverse_eltype(t::UnitSimplex, y::AbstractVector) = robust_eltype(y)
 
 function inverse_at!(x::AbstractVector, index, t::UnitSimplex, y::AbstractVector)
-    @unpack n = t
+    (; n) = t
     @argcheck length(y) == n
 
     stick = one(eltype(y))
@@ -210,7 +210,7 @@ struct CorrCholeskyFactor <: VectorTransform
 end
 
 function _summary_rows(transformation::CorrCholeskyFactor, mime)
-    @unpack n = transformation
+    (; n) = transformation
     _summary_row(transformation, "$(n)×$(n) correlation cholesky factor")
 end
 

test/Project.toml

@@ -10,7 +10,6 @@ LogDensityProblemsAD = "996a588d-648d-4e1f-a8f0-a84b347e47b1"
 OffsetArrays = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
-SimpleUnPack = "ce78b400-467f-4804-87d8-8f486da07d0a"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 TransformedLogDensities = "f9bc47f6-f3f8-4f3b-ab21-f8bc73906f26"

test/runtests.jl

@@ -1,6 +1,5 @@
-using DocStringExtensions, LinearAlgebra, LogDensityProblems, OffsetArrays, SimpleUnPack,
-    Random, Test, TransformVariables, StaticArrays, TransformedLogDensities,
-    LogDensityProblemsAD
+using DocStringExtensions, LinearAlgebra, LogDensityProblems, OffsetArrays, Random, Test,
+    TransformVariables, StaticArrays, TransformedLogDensities, LogDensityProblemsAD
 import ForwardDiff
 using LogDensityProblems: logdensity, logdensity_and_gradient
 using LogDensityProblemsAD
@@ -140,7 +139,7 @@ end
 @testset "tanh helpers" begin
     for _ in 1:10000
         x = (rand() - 0.5) * 100
-        @unpack log_l2_rem, logjac =  TransformVariables.tanh_helpers(x)
+        (; log_l2_rem, logjac) =  TransformVariables.tanh_helpers(x)
         @test Float64(AD_logjac(tanh, BigFloat(x))) ≈ logjac atol = 1e-4
         @test Float64(log(sech(BigFloat(x))^2)) ≈ log_l2_rem atol = 1e-4
     end
@@ -405,7 +404,7 @@ end
             u = UnitVector(3), L = CorrCholeskyFactor(4),
             δ = as((asℝ₋, as𝕀))))
     function f(θ)
-        @unpack μ, σ, β, α, δ = θ
+        (; μ, σ, β, α, δ) = θ
         -(abs2(μ) + abs2(σ) + abs2(β) + α + δ[1] + δ[2])
     end
     P = TransformedLogDensities.TransformedLogDensity(t, f)
@@ -452,7 +451,7 @@ end
 #         # NOTE tests simplified disabled as they currently fail
 #         t = as((μ = asℝ, ))
 #         function f(θ)
-#             @unpack μ = θ
+#             (; μ) = θ
 #             -(abs2(μ))
 #         end
 #         P = TransformedLogDensity(t, f)