changed Scholz47 to Scholz4_7 as recommended in #2126 (comment)

src/OrdinaryDiffEq.jl

@@ -387,7 +387,7 @@ export MagnusMidpoint, LinearExponential, MagnusLeapfrog, LieEuler, CayleyEuler,
 export Rosenbrock23, Rosenbrock32, RosShamp4, Veldd4, Velds4, GRK4T, GRK4A,
     Ros4LStab, ROS3P, Rodas3, Rodas23W, Rodas3P, Rodas4, Rodas42, Rodas4P, Rodas4P2, Rodas5, Rodas5P,
     RosenbrockW6S4OS, ROS34PW1a, ROS34PW1b, ROS34PW2, ROS34PW3, ROS34PRw, ROS3PRL, ROS3PRL2,
-    ROS2PR, ROS2S, ROS3PR, Scholz47
+    ROS2PR, ROS2S, ROS3PR, Scholz4_7
 
 export LawsonEuler, NorsettEuler, ETD1, ETDRK2, ETDRK3, ETDRK4, HochOst4, Exp4, EPIRK4s3A,
     EPIRK4s3B,

src/alg_utils.jl

@@ -624,7 +624,7 @@ alg_order(alg::PFRK87) = 8
 alg_order(alg::ROS2PR) = 2
 alg_order(alg::ROS2S) = 2
 alg_order(alg::ROS3PR) = 3
-alg_order(alg::Scholz47) = 3
+alg_order(alg::Scholz4_7) = 3
 alg_order(alg::Rosenbrock23) = 2
 alg_order(alg::Rodas23W) = 3
 alg_order(alg::Rosenbrock32) = 3

src/algorithms.jl

@@ -2895,7 +2895,7 @@ Scientific Computing, 18 (1), pp. 1-22.
 - E. Hairer, G. Wanner, Solving ordinary differential equations II, stiff and
   differential-algebraic problems. Computational mathematics (2nd revised ed.), Springer (1996)
 
-#### ROS2PR, ROS2S, ROS3PR, Scholz47
+#### ROS2PR, ROS2S, ROS3PR, Scholz4_7
 -Rang, Joachim (2014): The Prothero and Robinson example: 
  Convergence studies for Runge-Kutta and Rosenbrock-Wanner methods.
  https://doi.org/10.24355/dbbs.084-201408121139-0
@@ -2957,7 +2957,7 @@ for Alg in [
     :ROS2PR,
     :ROS2S,
     :ROS3PR,
-    :Scholz47,
+    :Scholz4_7,
     :ROS3P,
     :Rodas3,
     :ROS34PW1a,

src/generic_rosenbrock.jl

@@ -963,15 +963,15 @@ More Information at https://doi.org/10.24355/dbbs.084-201408121139-0
 """ ROS3PR
 
 """
-    Scholz47Tableau()
+    Scholz4_7Tableau()
 
 3nd order stiffly accurate Rosenbrock-Wanner method with 3 internal stages with B_PR consistent of order 3, which is strongly A-stable with Rinf~=-0.73
 Convergence with order 4 for the stiff case, but has a poor accuracy.
 
 Rang, Joachim (2014): The Prothero and Robinson example: 
 Convergence studies for Runge-Kutta and Rosenbrock-Wanner methods. https://doi.org/10.24355/dbbs.084-201408121139-0
 """
-function Scholz47Tableau() # 3rd order
+function Scholz4_7Tableau() # 3rd order
     gamma=7.88675134594813e-01
     Alpha=[0                       0                      0;
            2.36602540378444e+00    0                      0;
@@ -989,13 +989,13 @@ end
 3nd order stiffly accurate Rosenbrock-Wanner method with 3 internal stages with B_PR consistent of order 3, which is strongly A-stable with Rinf~=-0.73
 Convergence with order 4 for the stiff case, but has a poor accuracy.
 More Information at https://doi.org/10.24355/dbbs.084-201408121139-0
-""" Scholz47
+""" Scholz4_7
 
 
 """
     @ROS23(part)
 
-Generate code for the 3 step ROS methods: ROS2PR, ROS2S, ROS3PR, Scholz47
+Generate code for the 3 step ROS methods: ROS2PR, ROS2S, ROS3PR, Scholz4_7
 `part` should be one of `:tableau`, `:cache`, `:init`, `:performstep`.
 `@ROS23(:tableau)` should be placed in `tableaus/rosenbrock_tableaus.jl`.
 `@ROS23(:cache)` should be placed in `caches/rosenbrock_caches.jl`.
@@ -1009,23 +1009,23 @@ macro ROS23(part)
     ROS2PRtabname=:ROS2PRTableau
     ROS2Stabname=:ROS2STableau
     ROS3PRtabname=:ROS3PRTableau
-    Scholz47tabname=:Scholz47Tableau
+    Scholz4_7tabname=:Scholz4_7Tableau
     n_normalstep=length(tabmask.b)-1
     if part.value==:tableau
         tabstructexpr=gen_tableau_struct(tabmask,:Ros23Tableau)
         tabexprs=Array{Expr,1}([tabstructexpr])
         push!(tabexprs,gen_tableau(ROS2PRTableau(),tabstructexpr,ROS2PRtabname))
         push!(tabexprs,gen_tableau(ROS2STableau(),tabstructexpr,ROS2Stabname))
         push!(tabexprs,gen_tableau(ROS3PRTableau(),tabstructexpr,ROS3PRtabname))
-        push!(tabexprs,gen_tableau(Scholz47Tableau(),tabstructexpr,Scholz47tabname))
+        push!(tabexprs,gen_tableau(Scholz4_7Tableau(),tabstructexpr,Scholz4_7tabname))
         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,:ROS2PR,ROS2PRtabname))
         push!(cacheexprs,gen_algcache(cacheexpr,constcachename,:ROS2S,ROS2Stabname))
         push!(cacheexprs,gen_algcache(cacheexpr,constcachename,:ROS3PR,ROS3PRtabname))
-        push!(cacheexprs,gen_algcache(cacheexpr,constcachename,:Scholz47,Scholz47tabname))
+        push!(cacheexprs,gen_algcache(cacheexpr,constcachename,:Scholz4_7,Scholz4_7tabname))
         return esc(quote $(cacheexprs...) end)
     elseif part.value==:init
         return esc(gen_initialize(cachename,constcachename))

test/algconvergence/ode_rosenbrock_tests.jl

@@ -141,21 +141,21 @@ import LinearSolve
     sol = solve(prob, ROS3PR())
     @test length(sol) < 20 #length(sol) = 4 => Too Small??
 
-    ### Scholz47
+    ### Scholz4_7
     prob = prob_ode_linear
 
-    sim = test_convergence(dts, prob, Scholz47())
+    sim = test_convergence(dts, prob, Scholz4_7())
     @test sim.𝒪est[:final]≈3 atol=testTol
 
-    sol = solve(prob, Scholz47())
+    sol = solve(prob, Scholz4_7())
     @test length(sol) < 30 
 
     prob = prob_ode_2Dlinear
 
-    sim = test_convergence(dts, prob, Scholz47())
+    sim = test_convergence(dts, prob, Scholz4_7())
     @test sim.𝒪est[:final]≈3 atol=testTol
 
-    sol = solve(prob, Scholz47())
+    sol = solve(prob, Scholz4_7())
     @test length(sol) < 30 
 
     println("4th order Rosenbrocks")

test/interface/mass_matrix_tests.jl

@@ -109,7 +109,7 @@ dependent_M2 = MatrixOperator(ones(3, 3), update_func = update_func2,
         @test _norm_dsol(ROS2PR(), prob, prob2)≈0 atol=1e-11
         @test _norm_dsol(ROS2S(), prob, prob2)≈0 atol=1e-11
         @test _norm_dsol(ROS3PR(), prob, prob2)≈0 atol=1e-11
-        @test _norm_dsol(Scholz47(), prob, prob2)≈0 atol=1e-11
+        @test _norm_dsol(Scholz4_7(), prob, prob2)≈0 atol=1e-11
         @test _norm_dsol(RosShamp4(), prob, prob2)≈0 atol=1e-10
         @test _norm_dsol(Veldd4(), prob, prob2)≈0 atol=1e-10
         @test _norm_dsol(Velds4(), prob, prob2)≈0 atol=1e-10