#linear-algebra #linear #matrix #vector #algebra #matrix-operations #vector-math

nightly aljabar

A super generic, super experimental linear algebra library

19 releases (3 stable)

1.0.2 Oct 27, 2020
1.0.1 Jul 19, 2020
1.0.0 May 29, 2020
0.5.0 Apr 26, 2020
0.3.1 Jul 30, 2019

#847 in Math

MIT/Apache

135KB
3.5K SLoC

aljabar

Build Status Documentation Version Downloads

An experimental n-dimensional linear algebra and mathematics library for computer graphics, designed to be roughly compatible with cgmath.

The library provides:

  • vectors: Vector2, Vector3, Vector4 and Vector<T, const N: usize>
  • points: Point2, Point3, Point4 and Point<T, const N: usize>
  • matrices: Matrix2, Matrix3, Matrix4 and Matrix<T, const N: usize, const M: usize>
  • a quaternion type: Quaternion
  • orthonormal (rotation) matrices: Orthonormal

aljabar supports Vectors and Matrices of any size and will provide implementations for any mathematic operations that are supported by their scalars. Additionally, aljabar can leverage Rust's type system to ensure that operations are only applied to values that are the correct size. aljabar can do this while remaining no-std compatible.

aljabar relies heavily on unstable Rust features such as const generics and thus requires nightly to build.

For more information and a guide on getting started, check out the documentation.

Cargo Features

  • The mint feature (off by default) adds a dependency to the mint crate and provides support for converting between aljabar types and mint types.
  • The serde feature (off by default) adds serialization/deserialization support from the serde crate.
  • The rand feature (off by default) allows you to create random points, vectors, and matrices by sampling from a random number source.
  • The swizzle feature (off by default) enables swizzle functions for vectors.

Contributions

Pull request of any nature are welcome, especially regaring performance improvements. Although a aljabar is generic with respect to dimensionality, algorithms specialized for certain dimensions are straightforward to add and are intended to replace the generic algorithms along the most common code paths in the future.

Support

Contact the author at map@maplant.com or file an issue on github.

Dependencies

~125–540KB
~10K SLoC