More overloads for ambiguity (#41)

* More overloads for ambiguity

* Fix #40

* Update runtests.jl

* Update runtests.jl

* Update ldiv.jl

Author: dlfivefifty

Project.toml

@@ -1,7 +1,7 @@
 name = "ArrayLayouts"
 uuid = "4c555306-a7a7-4459-81d9-ec55ddd5c99a"
 authors = ["Sheehan Olver <[email protected]>"]
-version = "0.4.6"
+version = "0.4.7"
 
 [deps]
 FillArrays = "1a297f60-69ca-5386-bcde-b61e274b549b"

src/ArrayLayouts.jl

@@ -158,6 +158,7 @@ for Typ in (:LayoutArray, :(Transpose{<:Any,<:LayoutMatrix}), :(Adjoint{<:Any,<:
 end
 
 getindex(A::LayoutVector, kr::AbstractVector) = layout_getindex(A, kr)
+getindex(A::LayoutVector, kr::Colon) = layout_getindex(A, kr)
 
 _copyto!(_, _, dest::AbstractArray{T,N}, src::AbstractArray{V,N}) where {T,V,N} =
     Base.invoke(copyto!, Tuple{AbstractArray{T,N},AbstractArray{V,N}}, dest, src)
@@ -177,6 +178,7 @@ copyto!(dest::AbstractArray{<:Any,N}, src::SubArray{<:Any,N,<:LayoutArray}) wher
 copyto!(dest::LayoutMatrix, src::AdjOrTrans{<:Any,<:LayoutArray}) = _copyto!(dest, src)
 copyto!(dest::LayoutMatrix, src::SubArray{<:Any,2,<:AdjOrTrans{<:Any,<:LayoutArray}}) = _copyto!(dest, src)
 copyto!(dest::AbstractMatrix, src::AdjOrTrans{<:Any,<:LayoutArray}) = _copyto!(dest, src)
+copyto!(dest::SubArray{<:Any,2,<:LayoutMatrix}, src::SubArray{<:Any,2,<:AdjOrTrans{<:Any,<:LayoutArray}}) = _copyto!(dest, src)
 copyto!(dest::AbstractMatrix, src::SubArray{<:Any,2,<:AdjOrTrans{<:Any,<:LayoutArray}}) = _copyto!(dest, src)
 # ambiguity from sparsematrix.jl
 if VERSION ≥ v"1.5"

src/ldiv.jl

@@ -50,7 +50,8 @@ getindex(L::Ldiv, k...) = _getindex(indextype(L), L, k)
 concretize(L::AbstractArray) = convert(Array,L)
 concretize(L::Ldiv) = ldiv(concretize(L.A), concretize(L.B))
 _getindex(::Type{Tuple{I}}, L::Ldiv, (k,)::Tuple{I}) where I = concretize(L)[k]
-_getindex(::Type{Tuple{I,J}}, L::Ldiv, (k,j)::Tuple{I,J}) where {I,J} = Ldiv(L.A, L.B[:,j])[k]
+_getindex(::Type{Tuple{I,J}}, L::Ldiv, (k,j)::Tuple{Colon,J}) where {I,J} = Ldiv(L.A, L.B[:,j])
+_getindex(::Type{Tuple{I,J}}, L::Ldiv, (k,j)::Tuple{I,J}) where {I,J} = L[:,j][k]
 
 check_ldiv_axes(A, B) =
     axes(A,1) == axes(B,1) || throw(DimensionMismatch("First axis of A, $(axes(A,1)), and first axis of B, $(axes(B,1)) must match"))

src/mul.jl

@@ -197,6 +197,8 @@ macro layoutmul(Typ)
             Base.:*(A::$Mod{<:Any,<:$Typ}, B::$Mod{<:Any,<:$Typ}) = ArrayLayouts.mul(A,B)
             Base.:*(A::$Mod{<:Any,<:$Typ}, B::AbstractMatrix) = ArrayLayouts.mul(A,B)
             Base.:*(A::AbstractMatrix, B::$Mod{<:Any,<:$Typ}) = ArrayLayouts.mul(A,B)
+            Base.:*(A::LinearAlgebra.AdjointAbsVec, B::$Mod{<:Any,<:$Typ}) = ArrayLayouts.mul(A,B)
+            Base.:*(A::LinearAlgebra.TransposeAbsVec, B::$Mod{<:Any,<:$Typ}) = ArrayLayouts.mul(A,B)
             Base.:*(A::$Mod{<:Any,<:$Typ}, B::AbstractVector) = ArrayLayouts.mul(A,B)
             Base.:*(A::$Mod{<:Any,<:$Typ}, B::ArrayLayouts.LayoutVector) = ArrayLayouts.mul(A,B)
 
@@ -242,6 +244,9 @@ dot(a, b) = materialize(Dot(a, b))
 @inline LinearAlgebra.dot(a::LayoutArray, b::LayoutArray) = dot(a,b)
 @inline LinearAlgebra.dot(a::LayoutArray, b::AbstractArray) = dot(a,b)
 @inline LinearAlgebra.dot(a::AbstractArray, b::LayoutArray) = dot(a,b)
+@inline LinearAlgebra.dot(a::LayoutArray{<:Number}, b::SparseArrays.SparseVectorUnion{<:Number}) = dot(a,b)
+@inline LinearAlgebra.dot(a::SparseArrays.SparseVectorUnion{<:Number}, b::LayoutArray{<:Number}) = dot(a,b)
+
 @inline LinearAlgebra.dot(a::SubArray{<:Any,N,<:LayoutArray}, b::AbstractArray) where N = dot(a,b)
 @inline LinearAlgebra.dot(a::SubArray{<:Any,N,<:LayoutArray}, b::LayoutArray) where N = dot(a,b)
 @inline LinearAlgebra.dot(a::AbstractArray, b::SubArray{<:Any,N,<:LayoutArray}) where N = dot(a,b)

test/runtests.jl

@@ -1,4 +1,4 @@
-using ArrayLayouts, Random, FillArrays, Test, Base64
+using ArrayLayouts, Random, FillArrays, Test, SparseArrays, Base64
 import ArrayLayouts: MemoryLayout, @_layoutlmul, triangulardata
 
 Random.seed!(0)
@@ -32,22 +32,26 @@ MemoryLayout(::Type{MyVector}) = DenseColumnMajor()
 # These need to test dispatch reduces to ArrayLayouts.mul, etc.
 @testset "LayoutArray" begin
     @testset "LayoutVector" begin
-        A = MyVector([1.,2,3])
+        a = MyVector([1.,2,3])
         B = randn(3,3)
         b = randn(3)
 
-        @test A == A.A == Vector(A)
-        @test A[1:3] == A.A[1:3]
-        @test stringmime("text/plain", A) == "3-element MyVector:\n 1.0\n 2.0\n 3.0"
-        @test B*A ≈ B*A.A
-        @test B'*A ≈ B'*A.A
-        @test transpose(B)*A ≈ transpose(B)*A.A
-        @test b'A ≈ transpose(b)A ≈ A'b ≈ transpose(A)b ≈ b'A.A
-        @test qr(B).Q*A ≈ qr(B).Q*A.A
-
-        @test A'A == transpose(A)A == dot(A,A) == dot(A,A.A) == dot(A.A,A) == 14
-        v = view(A,1:3)
-        @test dot(v,A) == dot(v,A.A) == dot(A,v) == dot(A.A,v) == dot(v,v) == 14
+        @test a == a.A == Vector(a)
+        @test a[1:3] == a.A[1:3]
+        @test a[:] == a
+        @test stringmime("text/plain", a) == "3-element MyVector:\n 1.0\n 2.0\n 3.0"
+        @test B*a ≈ B*a.A
+        @test B'*a ≈ B'*a.A
+        @test transpose(B)*a ≈ transpose(B)*a.A
+        @test b'a ≈ transpose(b)a ≈ a'b ≈ transpose(a)b ≈ b'a.A
+        @test qr(B).Q*a ≈ qr(B).Q*a.A
+
+        @test a'a == transpose(a)a == dot(a,a) == dot(a,a.A) == dot(a.A,a) == 14
+        v = view(a,1:3)
+        @test dot(v,a) == dot(v,a.A) == dot(a,v) == dot(a.A,v) == dot(v,v) == 14
+
+        s = SparseVector(3, [1], [2])
+        @test a's == s'a == dot(a,s) == dot(s,a) == dot(s,a.A)
     end
 
     @testset "LayoutMatrix" begin
@@ -74,6 +78,8 @@ MemoryLayout(::Type{MyVector}) = DenseColumnMajor()
         @test copyto!(Array{Float64}(undef,5,5), A') == A'
         @test copyto!(Array{Float64}(undef,5,5), view(A',:,:)) == A'
 
+        @test copyto!(view(MyMatrix(Array{Float64}(undef,5,5)),:,:), view(A',:,:)) == A'
+
         @test qr(A).factors ≈ qr(A.A).factors
         @test qr(A,Val(true)).factors ≈ qr(A.A,Val(true)).factors
         @test lu(A).factors ≈ lu(A.A).factors
@@ -136,6 +142,13 @@ MemoryLayout(::Type{MyVector}) = DenseColumnMajor()
             b = randn(5)
             @test dot(b, A, b) ≈ b'*(A*b) ≈ b'A*b
         end
+
+        @testset "dual vector * symmetric (#40)" begin
+            A = randn(3,3)
+            x = rand(3)
+            @test x' * Symmetric(MyMatrix(A)) ≈ x'Symmetric(A)
+            @test transpose(x) * Symmetric(MyMatrix(A)) ≈ transpose(x)Symmetric(A)
+        end
     end
 
     @testset "l/rmul!" begin