StabalizedIRK docs

docs/src/implicit/StabalizedIRK.md

@@ -0,0 +1,20 @@
+# OrdinaryDiffEqStabalizedIRK
+
+Explicit stabilized methods utilize an upper bound on the spectral radius of the Jacobian.
+Users can supply an upper bound by specifying the keyword argument `eigen_est`, for example
+
+```julia
+`eigen_est = (integrator) -> integrator.eigen_est = upper_bound`
+```
+
+```@eval
+first_steps = evalfile("./common_first_steps.jl")
+first_steps("OrdinaryDiffEqStabalizedIRK", "IRKC")
+```
+
+## Full list of solvers
+
+```@docs
+IRKC
+```
+

lib/OrdinaryDiffEqStabilizedIRK/src/OrdinaryDiffEqStabilizedIRK.jl

@@ -10,7 +10,8 @@ import OrdinaryDiffEqCore: alg_order, alg_maximum_order,
                            OrdinaryDiffEqAdaptiveAlgorithm,
                            OrdinaryDiffEqAdaptiveImplicitAlgorithm,
                            alg_cache, _unwrap_val, DEFAULT_PRECS, @cache,
-                           _reshape, _vec, full_cache, get_fsalfirstlast
+                           _reshape, _vec, full_cache, get_fsalfirstlast,
+                           generic_solver_docstring
 
 using OrdinaryDiffEqDifferentiation: dolinsolve, update_W!
 using OrdinaryDiffEqNonlinearSolve: NLNewton, nlsolve!, isnewton, build_nlsolver,

lib/OrdinaryDiffEqStabilizedIRK/src/algorithms.jl

@@ -1,3 +1,12 @@
+@doc generic_solver_docstring("Description TBD",
+    "IRKC",
+    "Stabalized Implicit Runge Kutta method.",
+    "REF TBD",
+    "- `eigen_est`: function of the form
+    `(integrator) -> integrator.eigen_est = upper_bound`,
+    where `upper_bound` is an estimated upper bound on the spectral radius of the Jacobian matrix.
+    If `eigen_est` is not provided, `upper_bound` will be estimated using the power iteration.",
+    "eigen_est = nothing,")
 struct IRKC{CS, AD, F, F2, P, FDT, ST, CJ, K, T, E} <:
        OrdinaryDiffEqNewtonAdaptiveAlgorithm{CS, AD, FDT, ST, CJ}
     linsolve::F