Minor cleanup in nonlinear solvers.

JuliaGNI · Jul 12, 2024 · 660b656 · 660b656
1 parent 081ec3b
commit 660b656
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Showing 3 changed files with 11 additions and 9 deletions.
diff --git a/src/nonlinear/abstract_newton_solver.jl b/src/nonlinear/abstract_newton_solver.jl
@@ -71,6 +71,8 @@ cache(solver::AbstractNewtonSolver) = solver.cache
 config(solver::AbstractNewtonSolver) = solver.config
 status(solver::AbstractNewtonSolver) = solver.status
 jacobian(solver::AbstractNewtonSolver) = solver.jacobian
+linearsolver(solver::AbstractNewtonSolver) = solver.linear
+linesearch(solver::AbstractNewtonSolver) = solver.linesearch
 
 compute_jacobian!(s::AbstractNewtonSolver, x, f::Callable) = compute_jacobian!(s, x, f, missing)
 compute_jacobian!(s::AbstractNewtonSolver, x, f::Callable, ::Missing) = s.jacobian(s.cache.J, x, f)

diff --git a/src/nonlinear/newton_solver.jl b/src/nonlinear/newton_solver.jl
@@ -20,8 +20,8 @@ end
 
 function solver_step!(x, f, forj, s::NewtonSolver)
     # shortcuts
-    rhs = s.cache.rhs
-    δ = s.cache.δx
+    rhs = cache(s).rhs
+    δ = cache(s).δx
 
     # update Newton solver cache
     update!(s, x)
@@ -30,14 +30,14 @@ function solver_step!(x, f, forj, s::NewtonSolver)
     compute_jacobian!(s, x, forj)
 
     # factorize linear solver
-    factorize!(s.linear, s.cache.J)
+    factorize!(linearsolver(s), cache(s).J)
 
     # compute RHS
     f(rhs, x)
     rmul!(rhs, -1)
 
     # solve J δx = -f(x)
-    ldiv!(δ, s.linear, rhs)
+    ldiv!(δ, linearsolver(s), rhs)
 
     # apply line search
     α = s.linesearch(linesearch_objective(f, jacobian(s), cache(s)))

diff --git a/src/nonlinear/quasi_newton_solver.jl b/src/nonlinear/quasi_newton_solver.jl
@@ -22,24 +22,24 @@ end
 
 function solver_step!(x, f, forj, s::QuasiNewtonSolver)
     # shortcuts
-    rhs = s.cache.rhs
-    δ = s.cache.δx
+    rhs = cache(s).rhs
+    δ = cache(s).δx
 
     # update Newton solver cache
     update!(s, x)
 
     # compute Jacobian and factorize
-    if mod(s.status.i-1, s.refactorize) == 0
+    if mod(status(s).i-1, s.refactorize) == 0
         compute_jacobian!(s, x, forj)
-        factorize!(s.linear, s.cache.J)
+        factorize!(linearsolver(s), cache(s).J)
     end
 
     # compute RHS
     f(rhs, x)
     rmul!(rhs, -1)
 
     # solve J δx = -f(x)
-    ldiv!(δ, s.linear, rhs)
+    ldiv!(δ, linearsolver(s), rhs)
 
     # apply line search
     α = s.linesearch(linesearch_objective(f, jacobian(s), cache(s)))