Oceananigans.jl
erfa
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Oceananigans.jl | erfa | |
---|---|---|
4 | 2 | |
875 | 125 | |
1.6% | 0.0% | |
9.5 | 4.4 | |
5 days ago | about 2 months ago | |
Julia | C | |
MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Oceananigans.jl
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Julia 1.10 Released
I think it’s also the design philosophy. JuMP and ForwardDiff are great success stories and are packages very light on dependencies. I like those.
The DiffEq library seems to pull you towards the SciML ecosystem and that might not be agreeable to everyone.
For instance a known Julia project that simulates diff equations seems to have implemented their own solver
https://github.com/CliMA/Oceananigans.jl
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GPU vendor-agnostic fluid dynamics solver in Julia
I‘m currently playing around with Oceananigans.jl (https://github.com/CliMA/Oceananigans.jl). Do you know how both are similar or different?
Oceananigans.jl has really intuitive step-by-step examples and a great discussion page on GitHub.
- Supercharged high-resolution ocean simulation with Jax
erfa
- Julia 1.10 Released
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License Adherence Help
I'm working on a pure Rust approximation of astropy. Up til now, I was able to recreate the intent by looking at an external API, but I'm moving on to functionality that I don't understand enough to implement without basically copying the code. Astropy uses the BSD-3 license, and it wraps the ERFA library which uses a custom license. My project currently uses the MIT license. My PR is here - my question is have I attributed everything correctly, or is there anything I need to change for everything to be above-board?
What are some alternatives?
MATDaemon.jl
astro-rs - Astronomy utils written in Rust
FiniteDiff.jl - Fast non-allocating calculations of gradients, Jacobians, and Hessians with sparsity support
astropy - Astronomy and astrophysics core library
MITgcm - M.I.T General Circulation Model master code and documentation repository
Torch.jl - Sensible extensions for exposing torch in Julia.
Metal.jl - Metal programming in Julia
assist - ASSIST is a software package for ephemeris-quality integrations of test particles.
opendylan - Open Dylan compiler and IDE
PyCallChainRules.jl - Differentiate python calls from Julia
julia-ml-from-scratch - Machine learning from scratch in Julia
threads - Threads for Lua and LuaJIT. Transparent exchange of data between threads is allowed thanks to torch serialization.