Revert "Add DiffResult for MArray (#18)" (#32)

This reverts commit f80602e.

Author: gdalle

Project.toml

@@ -1,6 +1,6 @@
 name = "DiffResults"
 uuid = "163ba53b-c6d8-5494-b064-1a9d43ac40c5"
-version = "1.2.0"
+version = "1.1.0"
 
 [deps]
 StaticArraysCore = "1e83bf80-4336-4d27-bf5d-d5a4f845583c"

src/DiffResults.jl

@@ -1,6 +1,6 @@
 module DiffResults
 
-using StaticArraysCore: StaticArray, similar_type, Size, SArray
+using StaticArraysCore: StaticArray, similar_type, Size
 
 #########
 # Types #
@@ -36,7 +36,7 @@ Return `r::DiffResult`, with output value storage provided by `value` and output
 storage provided by `derivs`.
 
 In reality, `DiffResult` is an abstract supertype of two concrete types, `MutableDiffResult`
-and `ImmutableDiffResult`. If all `value`/`derivs` are all `Number`s or `StaticArrays.SArray`s,
+and `ImmutableDiffResult`. If all `value`/`derivs` are all `Number`s or `StaticArray`s,
 then `r` will be immutable (i.e. `r::ImmutableDiffResult`). Otherwise, `r` will be mutable
 (i.e. `r::MutableDiffResult`).
 
@@ -45,8 +45,8 @@ Note that `derivs` can be provide in splatted form, i.e. `DiffResult(value, deri
 DiffResult
 
 DiffResult(value::Number, derivs::Tuple{Vararg{Number}}) = ImmutableDiffResult(value, derivs)
-DiffResult(value::Number, derivs::Tuple{Vararg{SArray}}) = ImmutableDiffResult(value, derivs)
-DiffResult(value::SArray, derivs::Tuple{Vararg{SArray}}) = ImmutableDiffResult(value, derivs)
+DiffResult(value::Number, derivs::Tuple{Vararg{StaticArray}}) = ImmutableDiffResult(value, derivs)
+DiffResult(value::StaticArray, derivs::Tuple{Vararg{StaticArray}}) = ImmutableDiffResult(value, derivs)
 DiffResult(value::Number, derivs::Tuple{Vararg{AbstractArray}}) = MutableDiffResult(value, derivs)
 DiffResult(value::AbstractArray, derivs::Tuple{Vararg{AbstractArray}}) = MutableDiffResult(value, derivs)
 DiffResult(value::Union{Number,AbstractArray}, derivs::Union{Number,AbstractArray}...) = DiffResult(value, derivs)

test/runtests.jl

@@ -10,12 +10,9 @@ using DiffResults: DiffResult, GradientResult, JacobianResult, HessianResult,
     n0, n1, n2 = rand(), rand(), rand()
     x0, x1, x2 = rand(k), rand(k, k), rand(k, k, k)
     s0, s1, s2 = SVector{k}(rand(k)), SMatrix{k,k}(rand(k, k)), SArray{Tuple{k,k,k}}(rand(k, k, k))
-    m0, m1, m2 = MVector{k}(rand(k)), MMatrix{k,k}(rand(k, k)), MArray{Tuple{k,k,k}}(rand(k, k, k))
-
     rn = DiffResult(n0, n1, n2)
     rx = DiffResult(x0, x1, x2)
     rs = DiffResult(s0, s1, s2)
-    rm = DiffResult(m0, m1, m2)
     rsmix = DiffResult(n0, s0, s1)
 
     issimilar(x, y) = typeof(x) == typeof(y) && size(x) == size(y)
@@ -25,7 +22,6 @@ using DiffResults: DiffResult, GradientResult, JacobianResult, HessianResult,
     @test rn === DiffResult(n0, n1, n2)
     @test rx == DiffResult(x0, x1, x2)
     @test rs === DiffResult(s0, s1, s2)
-    @test rm == DiffResult(m0, m1, m2)
     @test rsmix === DiffResult(n0, s0, s1)
 
     @test issimilar(GradientResult(x0), DiffResult(first(x0), x0))
@@ -38,15 +34,9 @@ using DiffResults: DiffResult, GradientResult, JacobianResult, HessianResult,
     @test JacobianResult(SVector{k+1}(vcat(s0, 0.0)), s0) === DiffResult(SVector{k+1}(vcat(s0, 0.0)), zeros(SMatrix{k+1,k,Float64}))
     @test HessianResult(s0) === DiffResult(first(s0), s0, zeros(SMatrix{k,k,Float64}))
 
-    @test issimilar(GradientResult(m0), DiffResult(first(m0), m0))
-    @test issimilar(JacobianResult(m0), DiffResult(m0, zeros(MMatrix{k,k,Float64})))
-    @test issimilar(JacobianResult(MVector{k + 1}(vcat(m0, 0.0)), m0), DiffResult(MVector{k + 1}(vcat(m0, 0.0)), zeros(MMatrix{k + 1,k,Float64})))
-    @test issimilar(HessianResult(m0), DiffResult(first(m0), m0, zeros(MMatrix{k,k,Float64})))
-
     @test eltype(rn) === typeof(n0)
     @test eltype(rx) === eltype(x0)
     @test eltype(rs) === eltype(s0)
-    @test eltype(rm) === eltype(m0)
 
     rn_copy = copy(rn)
     @test rn == rn_copy
@@ -60,10 +50,6 @@ using DiffResults: DiffResult, GradientResult, JacobianResult, HessianResult,
     @test rs == rs_copy
     @test rs === rs_copy
 
-    rm_copy = copy(rm)
-    @test rm == rm_copy
-    @test rm !== rm_copy
-
     rsmix_copy = copy(rsmix)
     @test rsmix == rsmix_copy
     @test rsmix === rsmix_copy
@@ -73,7 +59,6 @@ using DiffResults: DiffResult, GradientResult, JacobianResult, HessianResult,
         @test value(rn) === n0
         @test value(rx) === x0
         @test value(rs) === s0
-        @test value(rm) === m0
         @test value(rsmix) === n0
 
         rn = value!(rn, n1)
@@ -91,11 +76,6 @@ using DiffResults: DiffResult, GradientResult, JacobianResult, HessianResult,
         @test typeof(value(rs)) === typeof(s0)
         rs = value!(rs, s0)
 
-        m0_new, m0_copy = rand(k), copy(m0)
-        rm = value!(rm, m0_new)
-        @test value(rm) === m0 == m0_new
-        rm = value!(rm, m0_copy)
-
         rsmix = value!(rsmix, n1)
         @test value(rsmix) === n1
         rsmix = value!(rsmix, n0)
@@ -115,11 +95,6 @@ using DiffResults: DiffResult, GradientResult, JacobianResult, HessianResult,
         @test typeof(value(rs)) === typeof(s0)
         rs = value!(rs, s0)
 
-        m0_new, m0_copy = rand(k), copy(m0)
-        rm = value!(exp, rm, m0_new)
-        @test value(rm) === m0 == exp.(m0_new)
-        rm = value!(rm, m0_copy)
-
         rsmix = value!(exp, rsmix, n1)
         @test value(rsmix) === exp(n1)
         rsmix = value!(rsmix, n0)
@@ -141,9 +116,6 @@ using DiffResults: DiffResult, GradientResult, JacobianResult, HessianResult,
         @test derivative(rs) === s1
         @test derivative(rs, Val{2}) === s2
 
-        @test derivative(rm) === m1
-        @test derivative(rm, Val{2}) === m2
-
         @test derivative(rsmix) === s0
         @test derivative(rsmix, Val{2}) === s1
 
@@ -168,11 +140,6 @@ using DiffResults: DiffResult, GradientResult, JacobianResult, HessianResult,
         @test typeof(derivative(rsmix)) === typeof(s0)
         rsmix = derivative!(rsmix, s0)
 
-        m1_new, m1_copy = rand(k, k), copy(m1)
-        rm = derivative!(rm, m1_new)
-        @test derivative(rm) === m1 == m1_new
-        rm = derivative!(rm, m1_copy)
-
         rn = derivative!(rn, n1, Val{2})
         @test derivative(rn, Val{2}) === n1
         rn = derivative!(rn, n2, Val{2})
@@ -194,11 +161,6 @@ using DiffResults: DiffResult, GradientResult, JacobianResult, HessianResult,
         @test typeof(derivative(rsmix, Val{2})) === typeof(s1)
         rsmix = derivative!(rsmix, s1, Val{2})
 
-        m2_new, m2_copy = rand(k, k, k), copy(m2)
-        rm = derivative!(rm, m2_new, Val{2})
-        @test derivative(rm, Val{2}) === m2 == m2_new
-        rm = derivative!(rm, m2_copy, Val{2})
-
         rn = derivative!(exp, rn, n0)
         @test derivative(rn) === exp(n0)
         rn = derivative!(rn, n1)
@@ -220,11 +182,6 @@ using DiffResults: DiffResult, GradientResult, JacobianResult, HessianResult,
         @test typeof(derivative(rsmix)) === typeof(s0)
         rsmix = derivative!(exp, rsmix, s0)
 
-        m1_new, m1_copy = rand(k, k), copy(m1)
-        rm = derivative!(exp, rm, m1_new)
-        @test derivative(rm) === m1 == exp.(m1_new)
-        rm = derivative!(exp, rm, m1_copy)
-
         rn = derivative!(exp, rn, n1, Val{2})
         @test derivative(rn, Val{2}) === exp(n1)
         rn = derivative!(rn, n2, Val{2})
@@ -245,11 +202,6 @@ using DiffResults: DiffResult, GradientResult, JacobianResult, HessianResult,
         @test derivative(rsmix, Val{2}) == exp.(s1_new)
         @test typeof(derivative(rsmix, Val{2})) === typeof(s1)
         rsmix = derivative!(exp, rsmix, s1, Val{2})
-
-        m2_new, m2_copy = rand(k, k, k), copy(m2)
-        rm = derivative!(exp, rm, m2_new, Val{2})
-        @test derivative(rm, Val{2}) === m2 == exp.(m2_new)
-        rm = derivative!(exp, rm, m2_copy, Val{2})
     end
 
     @testset "gradient/gradient!" begin
@@ -265,11 +217,6 @@ using DiffResults: DiffResult, GradientResult, JacobianResult, HessianResult,
         @test typeof(gradient(rs)) === typeof(s1)
         rs = gradient!(rs, s1)
 
-        m1_new, m1_copy = rand(k, k), copy(m1)
-        rm = gradient!(rm, m1_new)
-        @test gradient(rm) === m1 == m1_new
-        rm = gradient!(rm, m1_copy)
-
         x1_new, x1_copy = rand(k, k), copy(x1)
         rx = gradient!(exp, rx, x1_new)
         @test gradient(rx) === x1 == exp.(x1_new)
@@ -281,11 +228,6 @@ using DiffResults: DiffResult, GradientResult, JacobianResult, HessianResult,
         @test typeof(gradient(rsmix)) === typeof(s0)
         rsmix = gradient!(exp, rsmix, s0)
 
-        m1_new, m1_copy = rand(k, k), copy(m1)
-        rm = gradient!(exp, rm, m1_new)
-        @test gradient(rm) === m1 == exp.(m1_new)
-        rm = gradient!(exp, rm, m1_copy)
-
         T = typeof(SVector{k*k}(rand(k*k)))
         rs_new = gradient!(rs, convert(T, gradient(rs)))
         @test rs_new === rs
@@ -304,11 +246,6 @@ using DiffResults: DiffResult, GradientResult, JacobianResult, HessianResult,
         @test typeof(jacobian(rs)) === typeof(s1)
         rs = jacobian!(rs, s1)
 
-        m1_new, m1_copy = rand(k, k), copy(m1)
-        rm = jacobian!(rm, m1_new)
-        @test jacobian(rm) === m1 == m1_new
-        rm = jacobian!(rm, m1_copy)
-
         x1_new, x1_copy = rand(k, k), copy(x1)
         rx = jacobian!(exp, rx, x1_new)
         @test jacobian(rx) === x1 == exp.(x1_new)
@@ -320,11 +257,6 @@ using DiffResults: DiffResult, GradientResult, JacobianResult, HessianResult,
         @test typeof(jacobian(rsmix)) === typeof(s0)
         rsmix = jacobian!(exp, rsmix, s0)
 
-        m1_new, m1_copy = rand(k, k), copy(m1)
-        rm = jacobian!(exp, rm, m1_new)
-        @test jacobian(rm) === m1 == exp.(m1_new)
-        rm = jacobian!(exp, rm, m1_copy)
-
         T = typeof(SVector{k*k}(rand(k*k)))
         rs_new = jacobian!(rs, convert(T, jacobian(rs)))
         @test rs_new === rs
@@ -343,11 +275,6 @@ using DiffResults: DiffResult, GradientResult, JacobianResult, HessianResult,
         @test typeof(hessian(rs)) === typeof(s2)
         rs = hessian!(rs, s2)
 
-        m2_new, m2_copy = rand(k, k, k), copy(m2)
-        rm = hessian!(rm, m2_new)
-        @test hessian(rm) === m2 == m2_new
-        rm = hessian!(rm, m2_copy)
-
         x2_new, x2_copy = rand(k, k, k), copy(x2)
         rx = hessian!(exp, rx, x2_new)
         @test hessian(rx) === x2 == exp.(x2_new)
@@ -359,11 +286,6 @@ using DiffResults: DiffResult, GradientResult, JacobianResult, HessianResult,
         @test typeof(hessian(rsmix)) === typeof(s1)
         rsmix = hessian!(exp, rsmix, s1)
 
-        m2_new, m2_copy = rand(k, k, k), copy(m2)
-        rm = hessian!(exp, rm, m2_new)
-        @test hessian(rm) === m2 == exp.(m2_new)
-        rm = hessian!(exp, rm, m2_copy)
-
         T = typeof(SVector{k*k*k}(rand(k*k*k)))
         rs_new = hessian!(rs, convert(T, hessian(rs)))
         @test rs_new === rs