OffsetArrays.jl
TwoBasedIndexing.jl
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OffsetArrays.jl | TwoBasedIndexing.jl | |
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7 | 11 | |
192 | 57 | |
1.6% | - | |
6.0 | 0.0 | |
12 days ago | almost 7 years ago | |
Julia | Julia | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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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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-π- 2021 Day 6 Solutions -π-
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
TwoBasedIndexing.jl
- PyCharm is the worst IDE I have used. /s
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Obviously European elevators are designed by C programmers!
We need to evolve 2 based indexing is the superior choice
- I promise it wonβt hurt you
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The counter-intuitive rise of Python in scientific computing
There are other choices like https://github.com/simonster/TwoBasedIndexing.jl and https://github.com/giordano/StarWarsArrays.jl if you do not like 1-based indexing.
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what a wonderful world
Not a problem, there are packages that let you have two-based indexing.
- Kill it bevor it lays eggs
- How to start a war
- Why does Julia adopt 1-based index?
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some may hate it, some may love it
The one and only indexing is https://github.com/simonster/TwoBasedIndexing.jl
- Why not Julia?
What are some alternatives?
StarWarsArrays.jl - Arrays indexed as the order of Star Wars movies
DataFramesMeta.jl - Metaprogramming tools for DataFrames
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.
julia - The Julia Programming Language
TailRec.jl - A tail recursion optimization macro for julia.
FromFile.jl - Julia enhancement proposal (Julep) for implicit per file module in Julia
StatsBase.jl - Basic statistics for Julia
HTTP.jl - HTTP for Julia
evcxr
Bigsimr.jl - Simulate multivariate distributions with arbitrary marginals.