small changes

Author: vpuri3

src/LinearSolve.jl

@@ -3,7 +3,6 @@ module LinearSolve
 using ArrayInterface: lu_instance
 using Base: cache_dependencies, Bool
 using LinearAlgebra
-using Reexport
 using SciMLBase: AbstractDiffEqOperator, AbstractLinearAlgorithm
 using Setfield
 using UnPack
@@ -13,6 +12,7 @@ import Krylov
 import KrylovKit
 import IterativeSolvers
 
+using Reexport
 @reexport using SciMLBase
 
 abstract type SciMLLinearSolveAlgorithm <: SciMLBase.AbstractLinearAlgorithm end
@@ -22,6 +22,6 @@ include("factorization.jl")
 include("krylov.jl")
 
 export LUFactorization, SVDFactorization, QRFactorization
-export KrylovJL
+export KrylovJL, IterativeSolversJL, KrylovKitJL 
 
 end

src/default.jl

@@ -0,0 +1,18 @@
+#
+mutable struct DefaultLinSolve
+    iterable
+end
+
+DefaultLinSolve() = DefaultLinSolve(nothing, nothing, nothing)
+
+function SciMLBase.solve(cache::LinearCache,
+                         alg::DefaultLinSolve,
+                         args...;kwargs...)
+    @unpack iterable = alg
+    @unpack A, b, u, cacheval = cache
+
+    return A \ u
+end
+
+
+function

src/factorization.jl

@@ -52,7 +52,7 @@ SVDFactorization() = SVDFactorization(false, LinearAlgebra.DivideAndConquer())
 
 function SciMLBase.solve(cache::LinearCache, alg::SVDFactorization)
     cache.A isa Union{AbstractMatrix,AbstractDiffEqOperator} ||
-        error("SVD is not defined for $(typeof(prob.A))")
+        error("SVD is not defined for $(typeof(cache.A))")
     cache = set_cacheval(cache, svd!(cache.A; full = alg.full, alg = alg.alg))
     ldiv!(cache.u,cache.cacheval, cache.b)
 end

src/krylov.jl

@@ -2,8 +2,8 @@
 
 # place Krylov.CGsolver in LinearCache.cacheval, and resule
 
-struct KrylovJL{A,K} <: SciMLLinearSolveAlgorithm
-    solver::Function
+struct KrylovJL{F,A,K} <: SciMLLinearSolveAlgorithm
+    solver::F
     args::A
     kwargs::K
 end
@@ -17,16 +17,33 @@ function SciMLBase.solve(cache::LinearCache, alg::KrylovJL,args...;kwargs...)
     u, stats = alg.solver(A, b, args...; M=Pl, N=Pr, kwargs...)
     resid = A * u - b
     retcode = stats.solved ? :Success : :Failure
-    return u #SciMLBase.build_solution(prob, alg, x, resid; retcode = retcode)
+    return u
 end
 
 ## IterativeSolvers.jl
 
-struct IterativeSolversJL{A,K} <: SciMLLinearSolveAlgorithm
-    solver::Function
+struct IterativeSolversJL{F,A,K} <: SciMLLinearSolveAlgorithm
+    solver::F
     args::A
     kwargs::K
 end
 
 ## KrylovKit.jl
 
+struct KrylovKitJL{F,A,K} <: SciMLLinearSolveAlgorithm
+    solver::F
+    args::A
+    kwargs::K
+end
+
+function KrylovKitJL(args...; solver = KrylovKit.CG(), kwargs...)
+    return KrylovKitJL(solver, args, kwargs)
+end
+
+function SciMLBase.solve(cache::LinearCache, alg::KrylovKitJL,args...;kwargs...)
+    @unpack A, b, u = cache
+    @unpack solver = alg
+    u = KrylovKit.linsolve(A, b, u, solver, args...; kwargs...)[1] #no precond?!
+    return u
+end
+