Merge pull request #2165 from cwittens/ROS2

added ROS2 method and added ROS2, ROS23 and ROS34PW methods to iipvsoop_test.jl

src/OrdinaryDiffEq.jl

@@ -392,7 +392,7 @@ export Rosenbrock23, Rosenbrock32, RosShamp4, Veldd4, Velds4, GRK4T, GRK4A,
        Rodas5, Rodas5P,
        RosenbrockW6S4OS, ROS34PW1a, ROS34PW1b, ROS34PW2, ROS34PW3, ROS34PRw, ROS3PRL,
        ROS3PRL2,
-       ROS2PR, ROS2S, ROS3, ROS3PR, Scholz4_7
+       ROS2, ROS2PR, ROS2S, ROS3, ROS3PR, Scholz4_7
 
 export LawsonEuler, NorsettEuler, ETD1, ETDRK2, ETDRK3, ETDRK4, HochOst4, Exp4, EPIRK4s3A,
        EPIRK4s3B,

src/alg_utils.jl

@@ -632,6 +632,7 @@ alg_order(alg::Feagin12) = 12
 alg_order(alg::Feagin14) = 14
 alg_order(alg::PFRK87) = 8
 
+alg_order(alg::ROS2) = 2
 alg_order(alg::ROS2PR) = 2
 alg_order(alg::ROS2S) = 2
 alg_order(alg::ROS3) = 3

src/algorithms.jl

@@ -2898,6 +2898,11 @@ end
 - Shampine L.F. and Reichelt M., (1997) The MATLAB ODE Suite, SIAM Journal of
 Scientific Computing, 18 (1), pp. 1-22.
 
+#### ROS2
+
+- J. G. Verwer et al. (1999): A second-order Rosenbrock method applied to photochemical dispersion problems
+  https://doi.org/10.1137/S1064827597326651
+
 #### ROS3P
 
 - Lang, J. & Verwer, ROS3P—An Accurate Third-Order Rosenbrock Solver Designed for
@@ -2967,6 +2972,7 @@ University of Geneva, Switzerland.
 for Alg in [
     :Rosenbrock23,
     :Rosenbrock32,
+    :ROS2,
     :ROS2PR,
     :ROS2S,
     :ROS3,

src/caches/rosenbrock_caches.jl

@@ -407,6 +407,12 @@ end
 
 ################################################################################
 
+### ROS2 methods
+
+@ROS2(:cache)
+
+################################################################################
+
 ### ROS23 methods
 
 @ROS23(:cache)

src/generic_rosenbrock.jl

@@ -805,7 +805,7 @@ macro Rosenbrock4(part)
     end
 end
 
-#ROS23 and ROS34PW methods (Rang and Angermann, 2005)
+#ROS2, ROS23 and ROS34PW methods (Rang and Angermann, 2005)
 
 """
     Ros34dummyTableau()
@@ -849,6 +849,25 @@ function Ros23dummyTableau()
     RosenbrockAdaptiveTableau(a,C,b,btilde,gamma,d,c)
 end
 
+"""
+    Ros2dummyTableau()
+
+Generate a dummy tableau for ROS2 methods. This type of methods has 2 steps.
+"""
+function Ros2dummyTableau()
+    a=[false false;
+       true  false]
+    C=[false false;
+       true  false]
+    b=[true,true]
+    btilde=[true,true]
+    gamma=true
+    c=[false,true]
+    d=[true,true]
+    RosenbrockAdaptiveTableau(a,C,b,btilde,gamma,d,c)
+end
+
+
 """
     _transformtab(Alpha,Gamma,B,Bhat)
 
@@ -872,6 +891,78 @@ end
 
 
 
+# 2 step ROS Methods
+"""
+    ROS2Tableau()
+2nd order stiffly accurate Rosenbrock-Wanner method with 2 internal stages with (Rinf=0).
+The embedded method is taken from Kinetic PreProcessor (KPP).
+J. G. Verwer et al. (1999): A second-order Rosenbrock method applied to photochemical dispersion problems
+https://doi.org/10.1137/S1064827597326651
+"""
+function ROS2Tableau() # 2nd order
+    gamma=1.7071067811865475 # 1+1/sqrt(2)
+    Alpha=[0     0;
+           1.    0]
+    Gamma=[gamma                   0;
+           -3.414213562373095   gamma]
+    B=[0.5, 0.5]
+    Bhat=[1, 0]
+    a,C,b,btilde,d,c=_transformtab(Alpha,Gamma,B,Bhat)
+    RosenbrockAdaptiveTableau(a,C,b,btilde,gamma,d,c)
+end
+
+@doc """
+    ROS2()
+
+2nd order stiffly accurate Rosenbrock-Wanner method with 2 internal stages with (Rinf=0).
+The embedded method is taken from Kinetic PreProcessor (KPP).
+J. G. Verwer et al. (1999): A second-order Rosenbrock method applied to photochemical dispersion problems
+More Information at https://doi.org/10.1137/S1064827597326651
+""" ROS2
+
+
+
+"""
+    @ROS2(part)
+
+Generate code for the 2 step ROS methods: ROS2
+`part` should be one of `:tableau`, `:cache`, `:init`, `:performstep`.
+`@ROS2(:tableau)` should be placed in `tableaus/rosenbrock_tableaus.jl`.
+`@ROS2(:cache)` should be placed in `caches/rosenbrock_caches.jl`.
+`@ROS2(:init)` and `@ROS2(:performstep)` should be placed in
+`perform_step/rosenbrock_perform_step.jl`.
+"""
+macro ROS2(part)
+    tabmask=Ros2dummyTableau()
+    cachename=:ROS2Cache
+    constcachename=:ROS2ConstantCache
+    ROS2tabname=:ROS2Tableau
+    n_normalstep=length(tabmask.b)-1
+    if part.value==:tableau
+        tabstructexpr=gen_tableau_struct(tabmask,:Ros2Tableau)
+        tabexprs=Array{Expr,1}([tabstructexpr])
+        push!(tabexprs,gen_tableau(ROS2Tableau(),tabstructexpr,ROS2tabname))
+        return esc(quote $(tabexprs...) end)
+    elseif part.value==:cache
+        constcacheexpr,cacheexpr=gen_cache_struct(tabmask,cachename,constcachename)
+        cacheexprs=Array{Expr,1}([constcacheexpr,cacheexpr])
+        push!(cacheexprs,gen_algcache(cacheexpr,constcachename,:ROS2,ROS2tabname))
+        return esc(quote $(cacheexprs...) end)
+    elseif part.value==:init
+        return esc(gen_initialize(cachename,constcachename))
+    elseif part.value==:performstep
+        performstepexprs=Array{Expr,1}()
+        push!(performstepexprs,gen_constant_perform_step(tabmask,constcachename,n_normalstep))
+        push!(performstepexprs,gen_perform_step(tabmask,cachename,n_normalstep))
+        return esc(quote $(performstepexprs...) end)
+    else
+        throw(ArgumentError("Unknown parameter!"))
+        nothing
+    end
+end
+
+
+
 # 3 step ROS Methods
 """
     ROS2PRTableau()

src/perform_step/rosenbrock_perform_step.jl

@@ -933,6 +933,13 @@ end
 
 ################################################################################
 
+#### ROS2 type method
+
+@ROS2(:init)
+@ROS2(:performstep)
+
+################################################################################
+
 #### ROS23 type method
 
 @ROS23(:init)

src/tableaus/rosenbrock_tableaus.jl

@@ -214,6 +214,8 @@ function Rodas3PTableau(T, T2)
         h21, h22, h23, h24, h25, h31, h32, h33, h34, h35, h2_21, h2_22, h2_23, h2_24, h2_25)
 end
 
+@ROS2(:tableau)
+
 @ROS23(:tableau)
 
 @ROS34PW(:tableau)

test/algconvergence/ode_rosenbrock_tests.jl

@@ -90,6 +90,23 @@ import LinearSolve
     sol = solve(prob, Rodas3())
     @test length(sol) < 20
 
+    ### ROS2
+    prob = prob_ode_linear
+
+    sim = test_convergence(dts, prob, ROS2())
+    @test sim.𝒪est[:final]≈2 atol=testTol
+
+    sol = solve(prob, ROS2())
+    @test length(sol) < 61
+
+    prob = prob_ode_2Dlinear
+
+    sim = test_convergence(dts, prob, ROS2())
+    @test sim.𝒪est[:final]≈2 atol=testTol
+
+    sol = solve(prob, ROS2PR())
+    @test length(sol) < 60
+
     ### ROS2PR
     prob = prob_ode_linear
 

test/interface/mass_matrix_tests.jl

@@ -107,6 +107,7 @@ dependent_M2 = MatrixOperator(ones(3, 3), update_func = update_func2,
         @test _norm_dsol(Rosenbrock32(), prob, prob2)≈0 atol=1e-11
         @test _norm_dsol(ROS3P(), prob, prob2)≈0 atol=1e-11
         @test _norm_dsol(Rodas3(), prob, prob2)≈0 atol=1e-11
+        @test _norm_dsol(ROS2(), prob, prob2)≈0 atol=1e-11
         @test _norm_dsol(ROS2PR(), prob, prob2)≈0 atol=1e-11
         @test _norm_dsol(ROS2S(), prob, prob2)≈0 atol=1e-11
         @test _norm_dsol(ROS3(), prob, prob2)≈0 atol=1e-11

test/regression/iipvsoop_tests.jl

@@ -115,7 +115,10 @@ end
 
 working_rosenbrock_algs = [Rosenbrock23(), ROS3P(), Rodas3(),
     RosShamp4(), Veldd4(), Velds4(), GRK4T(), GRK4A(),
-    Ros4LStab(), Rodas4(), Rodas42(), Rodas4P(), Rodas5()]
+    Ros4LStab(), Rodas4(), Rodas42(), Rodas4P(), Rodas5(),
+    ROS2(), ROS2PR(), ROS2S(), ROS3(), ROS3PR(), Scholz4_7(),
+    ROS34PW1a(), ROS34PW1b(), ROS34PW2(), ROS34PW3(), 
+    ROS34PRw(), ROS3PRL(), ROS3PRL2()] 
 
 rosenbrock_algs = [Rosenbrock32()
 ]