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move LinearAlgebra in an extension #7

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6 changes: 4 additions & 2 deletions Project.toml
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Expand Up @@ -5,14 +5,15 @@ authors = ["Éric Thiébaut <eric.thiebaut@univ-lyon1.fr> and contributors"]

[deps]
InverseFunctions = "3587e190-3f89-42d0-90ee-14403ec27112"
LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
Requires = "ae029012-a4dd-5104-9daa-d747884805df"

[weakdeps]
LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
OffsetArrays = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"

[extensions]
TypeUtilsLinearAlgebraExt = "LinearAlgebra"
TypeUtilsOffsetArraysExt = "OffsetArrays"
TypeUtilsUnitfulExt = "Unitful"

Expand All @@ -28,9 +29,10 @@ julia = "1"

[extras]
Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
OffsetArrays = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"

[targets]
test = ["Aqua", "Test", "OffsetArrays", "Unitful"]
test = ["Aqua", "LinearAlgebra", "Test", "OffsetArrays", "Unitful"]
42 changes: 42 additions & 0 deletions ext/TypeUtilsLinearAlgebraExt.jl
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@@ -0,0 +1,42 @@
module TypeUtilsLinearAlgebraExt

if isdefined(Base, :get_extension)
using TypeUtils, LinearAlgebra
else
using ..TypeUtils, ..LinearAlgebra
end

# Convert element type for LinearAlgebra factorizations.
# `LinearAlgebra.Factorization{T}(A)` can be used to convert element type of `A` for QR,
# LinearAlgebra.QRCompactWY, QRPivoted, LQ, Cholesky, CholeskyPivoted, LU, LDLt,
# BunchKaufman, SVD, etc.
TypeUtils.convert_eltype(::Type{T}, A::Factorization{T}) where {T} = A
TypeUtils.convert_eltype(::Type{T}, A::Factorization) where {T} = Factorization{T}(A)
if VERSION < v"1.7.0-beta1"
# For old Julia versions, the above is not sufficient for SVD.
TypeUtils.convert_eltype(::Type{T}, A::SVD{T}) where {T} = A
TypeUtils.convert_eltype(::Type{T}, A::SVD) where {T} =
SVD(TypeUtils.convert_eltype(T, A.U), TypeUtils.convert_eltype(real(T), A.S), TypeUtils.convert_eltype(T, A.Vt))
end
TypeUtils.convert_eltype(::Type{T}, A::Hessenberg{T}) where {T} = A
TypeUtils.convert_eltype(::Type{T}, A::Hessenberg) where {T} = throw(
ArgumentError(
"changing element type of Hessenberg decomposition is not supported, consider re-computing the decomposition"
)
)

# For `Adjoint` and `Transpose`, we want to preserve this structure.
for S in (:Adjoint, :Transpose)
@eval begin
TypeUtils.convert_eltype(::Type{T}, A::$S{T}) where {T} = A
TypeUtils.convert_eltype(::Type{T}, A::$S) where {T} = $S(TypeUtils.convert_eltype(T, parent(A)))
end
end

# Get and adapt precision for LinearAlgebra factorizations.
TypeUtils.get_precision(::Type{<:Factorization{T}}) where {T} = TypeUtils.get_precision(T)
TypeUtils.adapt_precision(::Type{T}, A::Factorization{T}) where {T <: TypeUtils.Precision} = A
TypeUtils.adapt_precision(::Type{T}, A::Factorization{S}) where {T <: TypeUtils.Precision, S} =
TypeUtils.convert_eltype(TypeUtils.adapt_precision(T, S), A)

end # module
3 changes: 2 additions & 1 deletion src/TypeUtils.jl
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Expand Up @@ -55,7 +55,6 @@ include("macros.jl")
default_precision

using Base: OneTo
using LinearAlgebra
if !isdefined(Base, :get_extension)
using Requires
end
Expand All @@ -73,6 +72,8 @@ import .LazyMaps: LazyMap, lazymap
function __init__()
@static if !isdefined(Base, :get_extension)
# Extend methods when other packages are loaded.
@require LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e" include(
"../ext/TypeUtilsLinearAlgebraExt.jl")
@require Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d" include(
"../ext/TypeUtilsUnitfulExt.jl")
@require OffsetArrays = "6fe1bfb0-de20-5000-8ca7-80f57d26f881" include(
Expand Down
23 changes: 0 additions & 23 deletions src/arrays.jl
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Expand Up @@ -165,29 +165,6 @@ convert_eltype(::Type{T}, A::AbstractArray) where {T} = AbstractArray{T}(A)
convert_eltype(::Type{T}, ::Type{<:Array{<:Any,N}}) where {T,N} = Array{T,N}
convert_eltype(::Type{T}, ::Type{<:AbstractArray{<:Any,N}}) where {T,N} = AbstractArray{T,N}

# `LinearAlgebra.Factorization{T}(A)` can be used to convert element type of `A` for QR,
# LinearAlgebra.QRCompactWY, QRPivoted, LQ, Cholesky, CholeskyPivoted, LU, LDLt,
# BunchKaufman, SVD, etc.
convert_eltype(::Type{T}, A::Factorization{T}) where {T} = A
convert_eltype(::Type{T}, A::Factorization) where {T} = Factorization{T}(A)
if VERSION < v"1.7.0-beta1"
# For old Julia versions, the above is not sufficient for SVD.
convert_eltype(::Type{T}, A::SVD{T}) where {T} = A
convert_eltype(::Type{T}, A::SVD) where {T} =
SVD(convert_eltype(T, A.U), convert_eltype(real(T), A.S), convert_eltype(T, A.Vt))
end
convert_eltype(::Type{T}, A::Hessenberg{T}) where {T} = A
convert_eltype(::Type{T}, A::Hessenberg) where {T} = throw(ArgumentError(
"changing element type of Hessenberg decomposition is not supported, consider re-computing the decomposition"))

# For `Adjoint` and `Transpose`, we want to preserve this structure.
for S in (:Adjoint, :Transpose)
@eval begin
convert_eltype(::Type{T}, A::$S{T}) where {T} = A
convert_eltype(::Type{T}, A::$S) where {T} = $S(convert_eltype(T, parent(A)))
end
end

# Convert element type for numbers.
convert_eltype(::Type{T}, ::Type{<:Number}) where {T} = T

Expand Down
6 changes: 0 additions & 6 deletions src/precision.jl
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Expand Up @@ -26,7 +26,6 @@ get_precision(::Type) = AbstractFloat # pass-through
get_precision(::Type{T}) where {T<:Precision} = T
get_precision(::Type{<:Complex{T}}) where {T} = get_precision(T)
get_precision(::Type{<:AbstractArray{T}}) where {T} = get_precision(T)
get_precision(::Type{<:Factorization{T}}) where {T} = get_precision(T)

# Second type parameter of a named tuple is a tuple of types.
get_precision(::Type{NamedTuple{S,T}}) where {S,T} = get_precision(T)
Expand Down Expand Up @@ -118,11 +117,6 @@ adapt_precision(::Type{T}, A::AbstractArray{T}) where {T<:Precision} = A
adapt_precision(::Type{T}, A::AbstractArray{S}) where {T<:Precision,S} =
convert_eltype(adapt_precision(T, S), A)

# Adapt precision of factorizations.
adapt_precision(::Type{T}, A::Factorization{T}) where {T<:Precision} = A
adapt_precision(::Type{T}, A::Factorization{S}) where {T<:Precision,S} =
convert_eltype(adapt_precision(T, S), A)

# Set precision for tuples.
adapt_precision(::Type{T}, x::Union{Tuple,NamedTuple}) where {T<:Precision} =
map(adapt_precision(T), x)
Expand Down