cgmath-rs
NumPy
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cgmath-rs | NumPy | |
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4 | 272 | |
1,101 | 26,360 | |
1.9% | 1.9% | |
0.0 | 10.0 | |
over 1 year ago | 5 days ago | |
Rust | Python | |
Apache License 2.0 | 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.
cgmath-rs
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Hey Rustaceans! Got a question? Ask here! (31/2022)!
Take a look into math libraries, like glam, nalgebra, and cgmath. I've only used these through game engines, though, so I can't offer per-basis reviews/advice.
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Any plans for built-in support of Vec2/Vec3/Vec4 in Rust?
But I am writing a Vulkan-based game engine and I use https://crates.io/crates/cgmath extensively. It has vector classes, all the math functions I need, and it even supports a version of swizzling if you activate the feature. Maybe this crate can do what you need?
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I want to change my point of view by key input in glium.
There's also a good crate which you can use to quickly create the required matrices called cgmath: https://crates.io/crates/cgmath
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Rendering large 3D tilemaps with a single draw call at 3000 FPS
One great thing about Rust is that the library ecosystem is surprisingly mature, especially considering how young the language is (1.0 was released in 2015). C# also has good libraries, but from my experience it's kinda fiddly to use most open source libraries with Unity, at least without modifications. Rust's ecosystem has some excellent libraries that help with game development, such as noise for procedural generation and cgmath for linear algebra.
NumPy
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In NumPy with @, dot() or matmul():
- NumPy 2.0.0 Beta1
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Element-wise vs Matrix vs Dot multiplication
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication.
- JSON dans les projets data science : Trucs & Astuces
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JSON in data science projects: tips & tricks
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:
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Introducing Flama for Robust Machine Learning APIs
numpy: A library for scientific computing in Python
- help with installing numpy, please
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A Comprehensive Guide to NumPy Arrays
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy.
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Why do all the popular projects use relative imports in __init__ files if PEP 8 recommends absolute?
I was looking at all the big projects like numpy, pytorch, flask, etc.
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NumPy 2.0 development status & announcements: major C-API and Python API cleanup
I wish the NumPy devs would more thoroughly consider adding full fluent API support, e.g. x.sqrt().ceil(). [Issue #24081]
What are some alternatives?
nalgebra - Linear algebra library for Rust.
SymPy - A computer algebra system written in pure Python
glam-rs - A simple and fast linear algebra library for games and graphics
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
rust-gmp
blaze - NumPy and Pandas interface to Big Data
Ruma - A set of Rust crates for interacting with the Matrix chat network.
SciPy - SciPy library main repository
rust-GSL - A GSL (the GNU Scientific Library) binding for Rust
Numba - NumPy aware dynamic Python compiler using LLVM
blas - Wrappers for BLAS (Fortran)
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).