Change LDLFactorizations to be a weakdep (#326)

* Move LDLFactorizations to weak deps

* fix weak deps

Project.toml

@@ -4,7 +4,6 @@ version = "2.7.0"
 
 [deps]
 FastClosures = "9aa1b823-49e4-5ca5-8b0f-3971ec8bab6a"
-LDLFactorizations = "40e66cde-538c-5869-a4ad-c39174c6795b"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
 Requires = "ae029012-a4dd-5104-9daa-d747884805df"
@@ -14,10 +13,12 @@ TimerOutputs = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
 [weakdeps]
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
+LDLFactorizations = "40e66cde-538c-5869-a4ad-c39174c6795b"
 
 [extensions]
 LinearOperatorsChainRulesCoreExt = "ChainRulesCore"
 LinearOperatorsCUDAExt = "CUDA"
+LinearOperatorsLDLFactorizationsExt = "LDLFactorizations"
 
 [compat]
 ChainRulesCore = "1"
@@ -34,4 +35,4 @@ julia = "^1.6.0"
 [extras]
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
-
+LDLFactorizations = "40e66cde-538c-5869-a4ad-c39174c6795b"

ext/LinearOperatorsLDLFactorizationsExt.jl

@@ -0,0 +1,34 @@
+module LinearOperatorsLDLFactorizationsExt
+
+using FastClosures, LDLFactorizations, LinearAlgebra, LinearOperators, SparseArrays
+
+function LinearOperators.opLDL(M::AbstractMatrix; check::Bool = false)
+  (m, n) = size(M)
+  m == n || throw(LinearOperatorException("shape mismatch"))
+  if check
+    check_hermitian(M) || throw(LinearOperatorException("matrix is not Hermitian"))
+  end
+  LDL = ldlt(M)
+  prod! = @closure (res, v, α, β) -> LinearOperators.mulFact!(res, LDL, v, α, β)
+  tprod! = @closure (res, u, α, β) -> LinearOperators.tmulFact!(res, LDL, u, α, β)  # M.' = conj(M)
+  ctprod! = @closure (res, w, α, β) -> LinearOperators.mulFact!(res, LDL, w, α, β)
+  S = eltype(LDL)
+  return LinearOperator{S}(m, m, isreal(M), true, prod!, tprod!, ctprod!)
+  #TODO: use iterative refinement.
+end
+
+function LinearOperators.opLDL(M::Symmetric{T, SparseMatrixCSC{T, Int}}; check::Bool = false) where {T <: Real}
+  (m, n) = size(M)
+  m == n || throw(LinearOperatorException("shape mismatch"))
+  if check
+    check_hermitian(M) || throw(LinearOperatorException("matrix is not Hermitian"))
+  end
+  LDL = ldl(M)
+  prod! = @closure (res, v) -> ldiv!(res, LDL, v)
+  tprod! = @closure (res, u) -> ldiv!(res, LDL, u)  # M.' = conj(M)
+  ctprod! = @closure (res, w) -> ldiv!(res, LDL, w)
+  S = eltype(LDL)
+  return LinearOperator{S}(m, m, isreal(M), true, prod!, tprod!, ctprod!)
+end
+
+end # module

src/LinearOperators.jl

@@ -1,7 +1,6 @@
 module LinearOperators
 
 using FastClosures, LinearAlgebra, Printf, SparseArrays
-using LDLFactorizations
 
 # Basic defitions
 include("abstract.jl")
@@ -41,6 +40,9 @@ end
     Requires.@require CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba" begin
       include("../ext/LinearOperatorsCUDAExt.jl")
     end
+    Requires.@require LDLFactorizations = "40e66cde-538c-5869-a4ad-c39174c6795b" begin
+      include("../ext/LinearOperatorsLDLFactorizationsExt.jl")
+    end
   end
 end
 

src/linalg.jl

@@ -1,4 +1,4 @@
-export opInverse, opCholesky, opLDL, opHouseholder, opHermitian
+export opInverse, opCholesky, opHouseholder, opLDL, opHermitian
 
 function mulFact!(res, F, v, α, β::T) where {T}
   if β == zero(T)
@@ -67,38 +67,12 @@ argument will perform a cheap hermicity check.
 If M is sparse and real, then only the upper triangle should be stored in order to use 
 [`LDLFactorizations.jl`](https://github.com/JuliaSmoothOptimizers/LDLFactorizations.jl):
 
+    using LDLFactorizations
     triu!(M)
     opLDL(Symmetric(M, :U))
 
 """
-function opLDL(M::AbstractMatrix; check::Bool = false)
-  (m, n) = size(M)
-  m == n || throw(LinearOperatorException("shape mismatch"))
-  if check
-    check_hermitian(M) || throw(LinearOperatorException("matrix is not Hermitian"))
-  end
-  LDL = ldlt(M)
-  prod! = @closure (res, v, α, β) -> mulFact!(res, LDL, v, α, β)
-  tprod! = @closure (res, u, α, β) -> tmulFact!(res, LDL, u, α, β)  # M.' = conj(M)
-  ctprod! = @closure (res, w, α, β) -> mulFact!(res, LDL, w, α, β)
-  S = eltype(LDL)
-  return LinearOperator{S}(m, m, isreal(M), true, prod!, tprod!, ctprod!)
-  #TODO: use iterative refinement.
-end
-
-function opLDL(M::Symmetric{T, SparseMatrixCSC{T, Int}}; check::Bool = false) where {T <: Real}
-  (m, n) = size(M)
-  m == n || throw(LinearOperatorException("shape mismatch"))
-  if check
-    check_hermitian(M) || throw(LinearOperatorException("matrix is not Hermitian"))
-  end
-  LDL = ldl(M)
-  prod! = @closure (res, v) -> ldiv!(res, LDL, v)
-  tprod! = @closure (res, u) -> ldiv!(res, LDL, u)  # M.' = conj(M)
-  ctprod! = @closure (res, w) -> ldiv!(res, LDL, w)
-  S = eltype(LDL)
-  return LinearOperator{S}(m, m, isreal(M), true, prod!, tprod!, ctprod!)
-end
+function opLDL end
 
 function mulHouseholder!(res, h, v, α, β::T) where {T}
   if β == zero(T)

test/runtests.jl

@@ -1,5 +1,5 @@
 using Arpack, Test, TestSetExtensions, LinearOperators
-using LinearAlgebra, SparseArrays
+using LinearAlgebra, LDLFactorizations, SparseArrays
 using Zygote
 include("test_aux.jl")