Add missing convert methods for Cholesky

JuliaLang · Nov 14, 2024 · ecdf3a1 · ecdf3a1
1 parent cf36497
commit ecdf3a1
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diff --git a/stdlib/LinearAlgebra/src/cholesky.jl b/stdlib/LinearAlgebra/src/cholesky.jl
@@ -96,6 +96,9 @@ Cholesky(A::AbstractMatrix{T}, uplo::AbstractChar, info::Integer) where {T} =
 Cholesky(U::UpperTriangular{T}) where {T} = Cholesky{T,typeof(U.data)}(U.data, 'U', 0)
 Cholesky(L::LowerTriangular{T}) where {T} = Cholesky{T,typeof(L.data)}(L.data, 'L', 0)
 
+Base.convert(::Type{Cholesky{T,S}}, C::Cholesky{T,S}) where {T,S<:AbstractMatrix} = C
+Base.convert(::Type{Cholesky{T,S}}, C::Cholesky) where {T,S<:AbstractMatrix} = Cholesky{T,S}(C.factors, C.uplo, C.info)
+
 # iteration for destructuring into components
 Base.iterate(C::Cholesky) = (C.L, Val(:U))
 Base.iterate(C::Cholesky, ::Val{:U}) = (C.U, Val(:done))
@@ -170,6 +173,10 @@ CholeskyPivoted(A::AbstractMatrix{T}, uplo::AbstractChar, piv::AbstractVector{<:
 @deprecate(CholeskyPivoted{T,S}(factors, uplo, piv, rank, tol, info) where {T,S<:AbstractMatrix},
            CholeskyPivoted{T,S,typeof(piv)}(factors, uplo, piv, rank, tol, info), false)
 
+Base.convert(::Type{CholeskyPivoted{T,S}}, C::CholeskyPivoted{T,S}) where {T,S<:AbstractMatrix} = C
+Base.convert(::Type{CholeskyPivoted{T,S}}, C::CholeskyPivoted) where {T,S<:AbstractMatrix} = CholeskyPivoted{T,S}(C.factors, C.uplo, C.piv, C.rank, C.tol, C.info)
+Base.convert(::Type{CholeskyPivoted{T,S,P}}, C::CholeskyPivoted{T,S,P}) where {T,S<:AbstractMatrix,P<:AbstractVector{<:Integer}} = C
+Base.convert(::Type{CholeskyPivoted{T,S,P}}, C::CholeskyPivoted) where {T,S<:AbstractMatrix,P<:AbstractVector{<:Integer}} = CholeskyPivoted{T,S,P}(C.factors, C.uplo, C.piv, C.rank, C.tol, C.info)
 
 # iteration for destructuring into components
 Base.iterate(C::CholeskyPivoted) = (C.L, Val(:U))

diff --git a/stdlib/LinearAlgebra/test/cholesky.jl b/stdlib/LinearAlgebra/test/cholesky.jl
@@ -281,6 +281,23 @@ end
             end
         end
     end
+
+    @testset "eltype/matrixtype conversions" begin
+        apd  = Matrix(Hermitian(areal'*areal))
+        capd = cholesky(apd)
+        @test convert(Cholesky{Float64}, capd) === capd
+        @test convert(Cholesky{Float64,Matrix{Float64}}, capd) === convert(typeof(capd), capd) === capd
+        @test eltype(convert(Cholesky{Float32}, capd)) === Float32
+        @test eltype(convert(Cholesky{Float32,Matrix{Float32}}, capd)) === Float32
+
+        capd = cholesky(apd, RowMaximum())
+        @test convert(CholeskyPivoted{Float64}, capd) === capd
+        @test convert(CholeskyPivoted{Float64,Matrix{Float64}}, capd) == capd
+        @test convert(CholeskyPivoted{Float64,Matrix{Float64},Vector{Int}}, capd) === convert(typeof(capd), capd) === capd
+        @test eltype(convert(CholeskyPivoted{Float32}, capd)) === Float32
+        @test eltype(convert(CholeskyPivoted{Float32,Matrix{Float32}}, capd)) === Float32
+        @test eltype(convert(CholeskyPivoted{Float32,Matrix{Float32},Vector{Int}}, capd)) === Float32
+    end
 end
 
 @testset "behavior for non-positive definite matrices" for T in (Float64, ComplexF64, BigFloat)