![]() For high accuracy but with the range of Float64 ( ~1e-8-1e-12), we recommend Vern6, Vern7, or Vern8 as efficient choices. ![]() For fast solving at higher tolerances, we recommend BS3 (or OwrenZen3 if the interpolation error is important). ![]() If at moderate tolerances and the interpolation error is very important, consider the OwrenZen5 method. When more robust error control is required, BS5 is a good choice. For most non-stiff problems, we recommend Tsit5. Non-Stiff Problemsįor non-stiff problems, the native OrdinaryDiffEq.jl algorithms are vastly more efficient than the other choices. For very large systems ( >1000 ODEs?), consider using lsoda. For lower tolerances, using AutoVern7 or AutoVern9 with Rodas4, KenCarp4, or Rodas5P can all be good choices depending on the problem. They are a good go-to method when applicable.įor default tolerances, AutoTsit5(Rosenbrock23()) is a good choice. The cost for auto-switching is very minimal, but the choices are restrained. These methods are multi-paradigm and allow for efficient solution of both stiff and non-stiff problems. When the stiffness of the problem is unknown, it is recommended you use a stiffness detection and auto-switching algorithm. This guide is to help you choose the right algorithm. However, in some cases you may want something specific, or you may just be curious. It is suggested that you try choosing an algorithm using the alg_hints keyword argument. If no algorithm is given, a default algorithm will be chosen. Solves the ODE defined by prob using the algorithm alg.
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