Use SciMLBase over OrdinaryDiffEq where possible

[charleskawczynski]

This PR is an attempt to remove our dependency on OrdinaryDiffEq, in favor of using the lighter weight package, SciMLBase.

Unfortunately, we can't remove the dependency because, for example, ODE.Tsit5() is an ODE algorithm that is (I think) first defined in OrdinaryDiffEq. Same goes for a bunch of methods defined in type_getters.jl:

is_explicit_CTS_algo_type(alg_or_tableau) =
    alg_or_tableau <: CTS.ERKAlgorithmName

is_imex_CTS_algo_type(alg_or_tableau) =
    alg_or_tableau <: CTS.IMEXARKAlgorithmName

is_implicit_type(::typeof(ODE.IMEXEuler)) = true
is_implicit_type(alg_or_tableau) =
    alg_or_tableau <: Union{
        ODE.OrdinaryDiffEqImplicitAlgorithm,
        ODE.OrdinaryDiffEqAdaptiveImplicitAlgorithm,
    } || is_imex_CTS_algo_type(alg_or_tableau)

is_ordinary_diffeq_newton(::typeof(ODE.IMEXEuler)) = true
is_ordinary_diffeq_newton(alg_or_tableau) =
    alg_or_tableau <: Union{
        ODE.OrdinaryDiffEqNewtonAlgorithm,
        ODE.OrdinaryDiffEqNewtonAdaptiveAlgorithm,
    }

is_imex_CTS_algo(::CTS.IMEXAlgorithm) = true
is_imex_CTS_algo(::SciMLBase.AbstractODEAlgorithm) = false

is_implicit(::ODE.OrdinaryDiffEqImplicitAlgorithm) = true
is_implicit(::ODE.OrdinaryDiffEqAdaptiveImplicitAlgorithm) = true
is_implicit(ode_algo) = is_imex_CTS_algo(ode_algo)

is_rosenbrock(::ODE.Rosenbrock23) = true
is_rosenbrock(::ODE.Rosenbrock32) = true
is_rosenbrock(::SciMLBase.AbstractODEAlgorithm) = false
use_transform(ode_algo) =
    !(is_imex_CTS_algo(ode_algo) || is_rosenbrock(ode_algo))

additional_integrator_kwargs(::SciMLBase.AbstractODEAlgorithm) = (;
    adaptive = false,
    progress = isinteractive(),
    progress_steps = isinteractive() ? 1 : 1000,
)
additional_integrator_kwargs(::CTS.DistributedODEAlgorithm) = (;
    kwargshandle = ODE.KeywordArgSilent, # allow custom kwargs
    adjustfinal = true,
    # TODO: enable progress bars in ClimaTimeSteppers
)

is_cts_algo(::SciMLBase.AbstractODEAlgorithm) = false
is_cts_algo(::CTS.DistributedODEAlgorithm) = true

A bunch of these ODE. types are (I think) first defined in OrdinaryDiffEq.jl.

[charleskawczynski]

Increasing the jet failures is kind of a bummer, I'm going to see if I can break this down a bit to avoid that, or at least see where it's happening.

[charleskawczynski]

Actually, it looks like load times have improved quite a bit. Maybe it's a fluke, but I think this is generally headed in the right direction if we eventually remove OrdinaryDiffEq in favor of SciMLBase (which we can get away with once we convert the indefinite integrals that we currently depend on: search for ODE.solve( to find).

[charleskawczynski]

bors r+

[bors]

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