fixes

Author: Shreyas-Ekanathan

lib/OrdinaryDiffEqFIRK/src/algorithms.jl

@@ -163,13 +163,13 @@ struct AdaptiveRadau{CS, AD, F, P, FDT, ST, CJ, Tol, C1, C2, StepLimiter} <:
  new_W_γdt_cutoff::C2
  controller::Symbol
  step_limiter!::StepLimiter
- min_num_stages::Int
- max_num_stages::Int
+ min_stages::Int
+ max_stages::Int
 end
 
 function AdaptiveRadau(; chunk_size = Val{0}(), autodiff = Val{true}(),
      standardtag = Val{true}(), concrete_jac = nothing,
-     diff_type = Val{:forward}, min_num_stages = 3, max_num_stages = 7, 
+     diff_type = Val{:forward}, min_stages = 3, max_stages = 7, 
      linsolve = nothing, precs = DEFAULT_PRECS,
      extrapolant = :dense, fast_convergence_cutoff = 1 // 5,
      new_W_γdt_cutoff = 1 // 5,
@@ -187,6 +187,6 @@ function AdaptiveRadau(; chunk_size = Val{0}(), autodiff = Val{true}(),
      fast_convergence_cutoff,
      new_W_γdt_cutoff,
      controller,
-     step_limiter!, min_num_stages, max_num_stages)
+     step_limiter!, min_stages, max_stages)
 end
 

lib/OrdinaryDiffEqFIRK/src/controllers.jl

@@ -24,7 +24,7 @@
     q
 end
 
-function step_accept_controller!(integrator, controller::PredictiveController, alg::Union{RadauIIA3, RadauIIA5, RadauIIA9}, q)
+function step_accept_controller!(integrator, controller::PredictiveController, alg, q)
     @unpack qmin, qmax, gamma, qsteady_min, qsteady_max = integrator.opts
 
     EEst = DiffEqBase.value(integrator.EEst)
@@ -74,9 +74,9 @@ function step_accept_controller!(integrator, controller::PredictiveController, a
     @show cache.num_stages
     if (step > 10)
         Ψ = θ * θprev
-        if (Ψ <= 0.001 && num_stages < alg.max_num_stages)
+        if (Ψ <= 0.001 && num_stages < alg.max_stages)
             cache.num_stages += 2
-        elseif ((Ψ >= 0.1 || cache.status == VerySlowConvergence || cache.status == Divergence) && num_stages > alg.min_num_stages)
+        elseif ((Ψ >= 0.1 || cache.status == VerySlowConvergence || cache.status == Divergence) && num_stages > alg.min_stages)
             cache.num_stages -= 2 
             cache.step = 1
         end

lib/OrdinaryDiffEqFIRK/src/firk_caches.jl

@@ -498,12 +498,12 @@ function alg_cache(alg::AdaptiveRadau, u, rate_prototype, ::Type{uEltypeNoUnits}
         ::Val{false}) where {uEltypeNoUnits, uBottomEltypeNoUnits, tTypeNoUnits}
     uf = UDerivativeWrapper(f, t, p)
     uToltype = constvalue(uBottomEltypeNoUnits)
-    num_stages = alg.min_num_stages
-    max = alg.max_num_stages
+    num_stages = alg.min_stages
+    max = alg.max_stages
     tabs = [BigRadauIIA5Tableau(uToltype, constvalue(tTypeNoUnits)), BigRadauIIA9Tableau(uToltype, constvalue(tTypeNoUnits)), BigRadauIIA13Tableau(uToltype, constvalue(tTypeNoUnits))]
 
     i = 9
-    while i <= alg.max_num_stages
+    while i <= alg.max_stages
         push!(tabs, adaptiveRadauTableau(uToltype, constvalue(tTypeNoUnits), i))
         i += 2
     end
@@ -570,8 +570,8 @@ function alg_cache(alg::AdaptiveRadau, u, rate_prototype, ::Type{uEltypeNoUnits}
     uf = UJacobianWrapper(f, t, p)
     uToltype = constvalue(uBottomEltypeNoUnits)
 
-    min = alg.min_num_stages
-    max = alg.max_num_stages
+    min = alg.min_stages
+    max = alg.max_stages
 
     num_stages = min
 

lib/OrdinaryDiffEqFIRK/test/ode_firk_tests.jl

@@ -19,7 +19,7 @@ prob_ode_2Dlinear_big = remake(prob_ode_2Dlinear, u0 = big.(prob_ode_2Dlinear.u0
 
 for i in [3, 5, 7, 9], prob in [prob_ode_linear_big, prob_ode_2Dlinear_big]
     dts = 1 ./ 2 .^ (4.25:-1:0.25)
-    sim21 = test_convergence(dts, prob, AdaptiveRadau(min_num_stages = i, max_num_stages = i))
+    sim21 = test_convergence(dts, prob, AdaptiveRadau(min_stages = i, max_stages = i))
     @test sim21.𝒪est[:final]≈ (2 * i - 1) atol=testTol
 end