Merge branch 'master' into head

Author: Shreyas-Ekanathan

src/OrdinaryDiffEq.jl

@@ -428,7 +428,7 @@ export FunctionMap, Euler, Heun, Ralston, Midpoint, RK4, ExplicitRK, OwrenZen3,
        FRK65, PFRK87,
        RKM, MSRK5, MSRK6, Stepanov5, SIR54, QPRK98, PSRK4p7q6, PSRK3p6q5, PSRK3p5q4
 
-export RadauIIA3, RadauIIA5, RadauIIA7
+export RadauIIA3, RadauIIA5, RadauIIA9
 
 export MagnusMidpoint, LinearExponential, MagnusLeapfrog, LieEuler, CayleyEuler,
        MagnusGauss4, MagnusNC6, MagnusGL6, MagnusGL8, MagnusNC8, MagnusGL4,

src/alg_utils.jl

@@ -175,7 +175,7 @@ qmin_default(alg::DP8) = 1 // 3
 qmax_default(alg::Union{OrdinaryDiffEqAlgorithm, DAEAlgorithm}) = 10
 qmax_default(alg::CompositeAlgorithm) = minimum(qmax_default.(alg.algs))
 qmax_default(alg::DP8) = 6
-qmax_default(alg::Union{RadauIIA3, RadauIIA5, RadauIIA7}) = 8
+qmax_default(alg::Union{RadauIIA3, RadauIIA5, RadauIIA9}) = 8
 
 function has_chunksize(alg::OrdinaryDiffEqAlgorithm)
     return alg isa Union{OrdinaryDiffEqExponentialAlgorithm,
@@ -430,7 +430,8 @@ alg_order(alg::TanYam7) = 7
 alg_order(alg::TsitPap8) = 8
 alg_order(alg::RadauIIA3) = 3
 alg_order(alg::RadauIIA5) = 5
-alg_order(alg::RadauIIA7) = 7
+alg_order(alg::RadauIIA9) = 9
+alg_order(alg::ImplicitEuler) = 1
 alg_order(alg::RKMK2) = 2
 alg_order(alg::RKMK4) = 4
 alg_order(alg::LieRK4) = 4
@@ -530,6 +531,7 @@ alg_adaptive_order(alg::Rosenbrock32) = 2
 
 alg_adaptive_order(alg::RadauIIA3) = 1
 alg_adaptive_order(alg::RadauIIA5) = 3
+alg_adaptive_order(alg::RadauIIA9) = 7
 
 # this is actually incorrect and is purposefully decreased as this tends
 # to track the real error much better

src/algorithms.jl

@@ -673,10 +673,10 @@ year={1999},
 publisher={Elsevier}
 }
 
-RadauIIA7: Fully-Implicit Runge-Kutta Method
+RadauII97: Fully-Implicit Runge-Kutta Method
 An A-B-L stable fully implicit Runge-Kutta method with internal tableau complex basis transform for efficiency.
 """
-struct RadauIIA7{CS, AD, F, P, FDT, ST, CJ, Tol, C1, C2, StepLimiter} <:
+struct RadauIIA9{CS, AD, F, P, FDT, ST, CJ, Tol, C1, C2, StepLimiter} <:
        OrdinaryDiffEqNewtonAdaptiveAlgorithm{CS, AD, FDT, ST, CJ}
     linsolve::F
     precs::P
@@ -690,15 +690,15 @@ struct RadauIIA7{CS, AD, F, P, FDT, ST, CJ, Tol, C1, C2, StepLimiter} <:
     step_limiter!::StepLimiter
 end
 
-function RadauIIA7(; chunk_size = Val{0}(), autodiff = Val{true}(),
+function RadauIIA9(; chunk_size = Val{0}(), autodiff = Val{true}(),
         standardtag = Val{true}(), concrete_jac = nothing,
         diff_type = Val{:forward},
         linsolve = nothing, precs = DEFAULT_PRECS,
         extrapolant = :dense, fast_convergence_cutoff = 1 // 5,
         new_W_γdt_cutoff = 1 // 5,
         controller = :Predictive, κ = nothing, maxiters = 10, smooth_est = true,
         step_limiter! = trivial_limiter!)
-    RadauIIA7{_unwrap_val(chunk_size), _unwrap_val(autodiff), typeof(linsolve),
+    RadauIIA9{_unwrap_val(chunk_size), _unwrap_val(autodiff), typeof(linsolve),
         typeof(precs), diff_type, _unwrap_val(standardtag), _unwrap_val(concrete_jac),
         typeof(κ), typeof(fast_convergence_cutoff),
         typeof(new_W_γdt_cutoff), typeof(step_limiter!)}(linsolve,
@@ -712,7 +712,7 @@ function RadauIIA7(; chunk_size = Val{0}(), autodiff = Val{true}(),
         controller,
         step_limiter!)
 end
-TruncatedStacktraces.@truncate_stacktrace RadauIIA7
+TruncatedStacktraces.@truncate_stacktrace RadauIIA9
 
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