nsi
OffsetArrays.jl
| nsi | OffsetArrays.jl | |
|---|---|---|
| 1 | 7 | |
| 15 | 192 | |
| - | 1.0% | |
| 7.0 | 6.0 | |
| 6 months ago | 18 days ago | |
| Rust | Julia | |
| BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
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nsi
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Evcxr: A Rust REPL and Jupyter Kernel
I added jupyter notebook support to my nsi[1] crate via evxcr.
It allows you to do a 3D (offline) render with 3Delight (on AWS, if you want) directly into a notebook.
Here is an example notebook[2].
I haven't managed to update the image dynamically while it's rendering (there's no support for that in evxcr). If anyone knows how to do this, I'd be keen to add that too.
[1] https://crates.io/crates/nsi
[2] https://github.com/virtualritz/nsi/blob/master/examples/jupy...
OffsetArrays.jl
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Why I am switching my programming language to 1-based array indexing.
Well, there is OffsetArrays in Julia, but it has acquired a reputation as a poison pill because most code assumes the 1-based indexing and it's easy to forget to convert the indexing and screw up the code.
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The Julia language has a number of correctness flaws
Similar correctness issues are a big part of the reason that, several years ago, I submitted a series of pull requests to Julia so that its entire test suite would run without memory errors under Valgrind, save for a few that either (i) we understood and wrote suppressions for, or (ii) we did not understand and had open issues for. Unfortunately, no one ever integrated Valgrind into the CI system, so the test suite no longer fully runs under it, last time I checked. (The test suite took nearly a day to run under Valgrind on a fast desktop machine when it worked, so is infeasible for every pull request, but could be done periodically, e.g. once every few days.)
Even a revived effort on getting core Julia tests to pass under Valgrind would not do much to help catch correctness bugs due to composing different packages in the ecosystem. For that, running in testing with `--check-bounds=yes` is probably a better solution, and much quicker to execute as well. (see e.g. https://github.com/JuliaArrays/OffsetArrays.jl/issues/282)
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-🎄- 2021 Day 6 Solutions -🎄-
You might be interested in OffsetArrays.jl.
- PyTorch: Where we are headed and why it looks a lot like Julia (but not exactly)
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Why does Julia adopt 1-based index?
Counting starts at one, as do most vector/matrix/tensor indices. If it bothers you too much, see OffsetArrays.jl and Arrays with custom indices.
- some may hate it, some may love it
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Evcxr: A Rust REPL and Jupyter Kernel
No need for another version, Julia supports custom indices by default. Check out https://docs.julialang.org/en/v1/devdocs/offset-arrays/ and https://github.com/JuliaArrays/OffsetArrays.jl
What are some alternatives?
evcxr
StarWarsArrays.jl - Arrays indexed as the order of Star Wars movies
ipython - Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
TwoBasedIndexing.jl - Two-based indexing
vim-slime - A vim plugin to give you some slime. (Emacs)
Optimization.jl - Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.
TailRec.jl - A tail recursion optimization macro for julia.
julia - The Julia Programming Language
StatsBase.jl - Basic statistics for Julia
wenyan - 文言文編程語言 A programming language for the ancient Chinese.