switch to symbol API (#28)

Author: vchuravy

examples/bratu.jl

@@ -59,7 +59,7 @@ fig
 uₖ, _ = newton_krylov!(
     bratu!,
     copy(u₀), (dx, λ), similar(u₀);
-    Workspace = CgWorkspace,
+    algo = :cg,
 )
 
 ϵ = abs2.(uₖ .- reference)
@@ -85,15 +85,15 @@ end
 _, stats = newton_krylov(
     bratu,
     copy(u₀), (dx, λ);
-    Workspace = CgWorkspace
+    algo = :cg
 )
 stats
 
 # ## Solving with a fixed forcing
 _, stats = newton_krylov!(
     bratu!,
     copy(u₀), (dx, λ), similar(u₀);
-    Workspace = CgWorkspace,
+    algo = :cg,
     forcing = NewtonKrylov.Fixed(0.1)
 )
 stats
@@ -102,7 +102,7 @@ stats
 _, stats = newton_krylov!(
     bratu!,
     copy(u₀), (dx, λ), similar(u₀);
-    Workspace = CgWorkspace,
+    algo = :cg,
     forcing = nothing
 )
 stats
@@ -112,7 +112,7 @@ stats
 # _, stats = newton_krylov!(
 #     bratu!,
 #     copy(u₀), (dx, λ), similar(u₀);
-#     Workspace = GmresWorkspace,
+#     algo = :gmres,
 # )
 # stats
 # ```
@@ -121,7 +121,7 @@ stats
 _, stats = newton_krylov!(
     bratu!,
     copy(u₀), (dx, λ), similar(u₀);
-    Workspace = GmresWorkspace,
+    algo = :gmres,
     N = (J) -> ilu(collect(J)), # Assembles the full Jacobian
     krylov_kwargs = (; ldiv = true)
 )
@@ -131,7 +131,7 @@ stats
 _, stats = newton_krylov!(
     bratu!,
     copy(u₀), (dx, λ), similar(u₀);
-    Workspace = FgmresWorkspace,
+    algo = :fgmres,
     N = (J) -> ilu(collect(J)), # Assembles the full Jacobian
     krylov_kwargs = (; ldiv = true)
 )
@@ -151,7 +151,7 @@ end
 _, stats = newton_krylov!(
     bratu!,
     copy(u₀), (dx, λ), similar(u₀);
-    Workspace = FgmresWorkspace,
+    algo = :fgmres,
     N = (J) -> GmresPreconditioner(J, 5),
 )
 stats
@@ -161,7 +161,7 @@ stats
 # newton_krylov!(
 # 	bratu!,
 # 	copy(u₀), (dx, λ), similar(u₀);
-# 	Workspace = CglsWorkspace, # CgneWorkspace
+# 	algo = :cgls, # Cgne
 #   krylov_kwargs = (; verbose=1)
 # )
 # ```
@@ -171,7 +171,7 @@ stats
 # 	bratu!,
 # 	copy(u₀), (dx, λ), similar(u₀);
 # 	verbose = 1,
-# 	Workspace = BicgstabWorkspace, # L=2
+# 	algo = :bicgstab, # L=2
 # 	η_max = nothing
 # )
 # ```

examples/bratu_ka.jl

@@ -63,7 +63,7 @@ fig
 uₖ, _ = newton_krylov!(
     bratu!,
     copy(u₀), (dx, λ), similar(u₀);
-    Workspace = CgWorkspace,
+    algo = :cg,
 )
 
 ϵ = abs2.(uₖ .- reference)

examples/bvp.jl

@@ -53,7 +53,7 @@ function BVP_solve(n = 801, T = Float64)
 
     bvpout, stats = newton_krylov!(
         Fbvp!, U0, (force, tv, tvdag, h, n), res,
-        Workspace = FgmresWorkspace,
+        algo = :fgmres,
         N = (J) -> GmresPreconditioner(J, 30),
     )
     return (; bvpout, tv, stats)

examples/implicit.jl

@@ -51,11 +51,9 @@ end
 
 # ## Non-adaptive time stepping
 
-import Krylov
-
 function solve(
         G!, f!, uₙ, p, Δt, ts; callback = _ -> nothing,
-        verbose = 0, Workspace = Krylov.GmresWorkspace, krylov_kwargs = (;)
+        verbose = 0, algo = :gmres, krylov_kwargs = (;)
     )
     u = copy(uₙ)
     du = zero(uₙ)
@@ -68,7 +66,7 @@ function solve(
         end
         _, stats = newton_krylov!(
             F!, u, (uₙ, Δt, du, p, t), res;
-            verbose, Workspace, tol_abs = 6.0e-6, krylov_kwargs
+            verbose, algo, tol_abs = 6.0e-6, krylov_kwargs
         )
         if !stats.solved
             @warn "non linear solve failed marching on" t stats

src/NewtonKrylov.jl

@@ -292,7 +292,7 @@ function newton_krylov!(
         max_niter = 50,
         forcing::Union{Forcing, Nothing} = EisenstatWalker(),
         verbose = 0,
-        Workspace = GmresWorkspace,
+        algo = :gmres,
         M = nothing,
         N = nothing,
         krylov_kwargs = (;),
@@ -309,12 +309,13 @@ function newton_krylov!(
         η = inital(forcing)
     end
 
-    verbose > 0 && @info "Jacobian-Free Newton-Krylov" Workspace res₀ = n_res tol tol_rel tol_abs η
+    verbose > 0 && @info "Jacobian-Free Newton-Krylov" algo res₀ = n_res tol tol_rel tol_abs η
 
     J = JacobianOperator(F!, res, u, p)
 
+    # TODO: Refactor to provide method that re-uses the cache here.
     kc = KrylovConstructor(res)
-    workspace = Workspace(kc)
+    workspace = krylov_workspace(algo, kc)
 
     stats = Stats(0, 0, n_res)
     while n_res > tol && stats.outer_iterations <= max_niter