DifferentialEquations.jl
slimv
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DifferentialEquations.jl | slimv | |
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6 | 14 | |
2,754 | 448 | |
1.5% | - | |
7.3 | 3.2 | |
18 days ago | 10 months ago | |
Julia | Common Lisp | |
GNU General Public License v3.0 or later | - |
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DifferentialEquations.jl
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Startups are building with the Julia Programming Language
This lists some of its unique abilities:
https://docs.sciml.ai/DiffEqDocs/stable/
The routines are sufficiently generic, with regard to Julia’s type system, to allow the solvers to automatically compose with other packages and to seamlessly use types other than Numbers. For example, instead of handling just functions Number→Number, you can define your ODE in terms of quantities with physical dimensions, uncertainties, quaternions, etc., and it will just work (for example, propagating uncertainties correctly to the solution¹). Recent developments involve research into the automated selection of solution routines based on the properties of the ODE, something that seems really next-level to me.
[1] https://lwn.net/Articles/834571/
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From Common Lisp to Julia
https://github.com/SciML/DifferentialEquations.jl/issues/786. As you could see from the tweet, it's now at 0.1 seconds. That has been within one year.
Also, if you take a look at a tutorial, say the tutorial video from 2018,
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When is julia getting proper precompilation?
It's not faith, and it's not all from Julia itself. https://github.com/SciML/DifferentialEquations.jl/issues/785 should reduce compile times of what OP mentioned for example.
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Julia 1.7 has been released
Let's even put raw numbers to it. DifferentialEquations.jl usage has seen compile times drop from 22 seconds to 3 seconds over the last few months.
https://github.com/SciML/DifferentialEquations.jl/issues/786
- Suggest me a Good library for scientific computing in Julia with good support for multi-core CPUs and GPUs.
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DifferentialEquations compilation issue in Julia 1.6
https://github.com/SciML/DifferentialEquations.jl/issues/737 double posted, with the answer here. Please don't do that.
slimv
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Does anyone use vim for lisp dev?
I use Vim with slimv, and have for years.
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Portacle - Does it have auto indent?
Maybe you should stick to one new thing at a time. Vim is more than capable of handling Common Lisp. Look at Slimv and Vlime for vim-style SLIME. Focus on CL first. You can come back to Doom / Emacs later.
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What is to go-to environment on Windows for Common LISP development?
Neovim works just fine. I use Neoterm to send-to-repl, here's what my config looks like. Your other options include vlime and slimv. I switched to neoterm because it's simple, explicit, and doesn't create unpredictable windows. Works for any other language just as well.
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From Common Lisp to Julia
https://GitHub.com/jpalardy/vim-slime is a terrible SLIME to be honest! It is not even a SLIME. It just This does not look like SLIME. It just copies text from one text buffer and paste it to another Vim buffer which is probably running a REPL. "Probably" because who knows what the target buffer is running. vim-slime does not care. This is not Superior Lisp Interaction Mode for $EDITOR (SLIME) in any way.
vim-slime does not connect to any Swank server. It does not understanding Lisp s-expressions. It would happily copy any random text into any random REPL and call it job done! Lisp interaction mode is much much more than just copying and pasting text around. A superior lisp interaction mode gives you live debugging, handling conditions, inspecting variables, navigating the stack frames, ... Vim-slime cannot do anything like this because, well, it just copy-pastes stuff around. Vim-slime is a disingenious and misleading name for a project that is not SLIME.
If you really want to use Vim, do yourself a favor and use https://github.com/kovisoft/slimv and experience a true Lisp interaction mode.
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Common Lisp vs Racket
Join me vim brother and don't settle for forcing yourself to use emacs while developing in CL when you don't have to! You even have two vim options! https://github.com/kovisoft/slimv and https://github.com/vlime/vlime with a great comparison of the two: https://susam.net/blog/lisp-in-vim.html
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Is SLIME setup possible for Vim?
I've seen SLIMV recommended as a SLIME alternative for Vim. Like SLIME, SLIMV is a SWANK client.
- Slimv – Superior Lisp Interaction Mode for Vim (“Slime for Vim”)
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What would you consider a modern lisp workflow/toolchain?
I found Vlime to be more updated than slimv and give a smoother experience. With time I've switched to bare neoterm which I highly recommend. CL and lisps in general are designed with a text repl in mind, so this is the method that is guaranteed to work on every obscure CL distribution, and also transfer well to any other REPL-based languages.
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Opening and running functions in Portacle
If you are already familiar with vim you may want to use slimv
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Is anyone programming in lisp?
You need Parinfer. Several versions are available for Vim. It's easier to learn than Paredit and works better with Vim-style editing anyway. Lisp emphasizes interactivity with the REPL. It helps if you can send forms you're editing to the REPL for testing. Try something like slimv.
What are some alternatives?
ModelingToolkit.jl - An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
vlime - A Common Lisp dev environment for Vim (and Neovim)
diffeqpy - Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization
w3m.vim - w3m plugin for vim
Gridap.jl - Grid-based approximation of partial differential equations in Julia
paredit.vim - Paredit Mode: Structured Editing of Lisp S-expressions
ApproxFun.jl - Julia package for function approximation
vim-sexp-mappings-for-regular-people - vim-sexp mappings for regular people
DiffEqBase.jl - The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
doom-emacs - An Emacs framework for the stubborn martian hacker [Moved to: https://github.com/doomemacs/doomemacs]
FFTW.jl - Julia bindings to the FFTW library for fast Fourier transforms
awesome-cl - A curated list of awesome Common Lisp frameworks, libraries and other shiny stuff.