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OrdinaryDiffEq.jl Alternatives
Similar projects and alternatives to OrdinaryDiffEq.jl
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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StochasticDiffEq.jl
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NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better OrdinaryDiffEq.jl alternative or higher similarity.
OrdinaryDiffEq.jl reviews and mentions
Posts with mentions or reviews of OrdinaryDiffEq.jl.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-11.
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Modern Numerical Solving methods
There has been a lot of research in Runge Kutta methods in the last couple decades which resulted in all kind of specialized Runge Kutta methods. You have high order ones, RK methods for stiff problems, embedded RK methods which benefit from adaprive step size control, RK-Nystrom methods for second order Problems, symplectic RK methods which preserve energy (eg. hamiltonian) ando so on. If you are interested in the numerics and the use cases I highly recommend checking out the Julia Libary OrdinaryDiffEq (https://github.com/SciML/OrdinaryDiffEq.jl). If you look into the documentation you find A LOT of implemented RK methods for all kind of use cases.
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Why Fortran is a scientific powerhouse
Project.toml or Manifest.toml? Every package has Project.toml which specifies bounds (https://github.com/SciML/OrdinaryDiffEq.jl/blob/master/Proje...). Every fully reproducible project has a Manifest that decrease the complete package state (https://github.com/SciML/SciMLBenchmarks.jl/blob/master/benc...).
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How do the Julia ODE solvers choose/select their initial steps? What formula do they use to estimate the appropriate initial step size?
Yes. If you want to see a robust version of the algorithm you can check out https://github.com/SciML/OrdinaryDiffEq.jl/blob/master/src/initdt.jl
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Basic OrdinaryDiffEq.jl repo stats
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2 days ago
SciML/OrdinaryDiffEq.jl is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.
The primary programming language of OrdinaryDiffEq.jl is Julia.
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