DifferentialEquations.jl
emmet
DifferentialEquations.jl | emmet | |
---|---|---|
6 | 30 | |
2,761 | 4,435 | |
0.9% | 0.1% | |
7.2 | 6.0 | |
8 days ago | about 2 months ago | |
Julia | TypeScript | |
GNU General Public License v3.0 or later | MIT License |
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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.
emmet
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Emmet is a content/code assist tool to write code faster and more efficiently. It comes standard with VS Code so there is no need for any plugin. The concept is simple: you start typing an Emmet abbreviation, press TAB or 'ENTER', and a full Emmet snippet for that abbreviation will come out.
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Writing HTML by Hand
Not equivalent, but arguably more useful for manual authoring: Emmet [0] was all the range a while back, and I still use it to write HTML. It comes naturally if you're used to writing CSS-like selectors, and mostly gets out of the way.
DSL-wise, I've rather enjoyed Clojure's Hiccup [1].
[0] https://emmet.io/
[1] https://github.com/weavejester/hiccup
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HTML/JSX Emmetl completion in React files not working
local lspconfig = require('lspconfig') local configs = require('lspconfig/configs') local capabilities = vim.lsp.protocol.make_client_capabilities() capabilities.textDocument.completion.completionItem.snippetSupport = true lspconfig.emmet_ls.setup({ -- on_attach = on_attach, capabilities = capabilities, filetypes = { 'html', 'typescriptreact', 'javascriptreact', 'css', 'sass', 'scss', 'less', 'javascript' }, init_options = { html = { options = { -- For possible options, see: https://github.com/emmetio/emmet/blob/master/src/config.ts#L79-L267 ["bem.enabled"] = true, }, }, } })
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Supercharge Your Web Dev Workflow With Emmet
Emmet is a tool that allows you to quickly generate HTML and CSS code by using abbreviations and expanding them into full code.
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Type HTML faster in React with Emmet and VS Code
One interesting plugin from that list is an amazing tool called Emmet, which helps you write HTML and CSS faster by using simple abbreviations that are then converted into code blocks. However, there is one minor drawback; by default, Emmet is not enabled for React in VS Code.
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I feel so stupid. I can’t even make a simple navbar without copying code.
You might also consider adding snippets or Emmet support to your IDE. This will let you reuse existing templates that you use frequently so you don't have to waste time with the initial development.
- Tell HN: Emmet, the HTML editing plugin, gets $100k/yr in donations from casinos
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
lazy.nvim - 💤 A modern plugin manager for Neovim
diffeqpy - Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization
ESLint - Find and fix problems in your JavaScript code.
Gridap.jl - Grid-based approximation of partial differential equations in Julia
TRex - Copy any text on your screen, stop retyping.
ApproxFun.jl - Julia package for function approximation
paper.js - The Swiss Army Knife of Vector Graphics Scripting – Scriptographer ported to JavaScript and the browser, using HTML5 Canvas. Created by @lehni & @puckey
DiffEqBase.jl - The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
starter - Starter template for LazyVim
FFTW.jl - Julia bindings to the FFTW library for fast Fourier transforms
vim-mark - Highlight several words in different colors simultaneously.