Linear algebra library for Rust.
Go to file
Sébastien Crozet eb7600adf6 Release v0.2.22.
2015-08-28 08:39:11 +02:00
benches Use the Zero and One traits from the num crate. 2015-04-18 14:38:34 +02:00
src Fix wrong allocated vector length in RowSlice 2015-08-27 16:55:20 +02:00
tests Add RowSlice and ColSlice test cases for DMat 2015-08-27 16:53:20 +02:00
.gitignore Add points. 2014-10-10 11:45:20 +02:00
.travis.yml Don't run benchmarks on travis. 2015-06-19 23:48:27 +02:00
Cargo.toml Release v0.2.22. 2015-08-28 08:39:11 +02:00
LICENSE Initial commit. 2013-05-14 11:34:28 +00:00
Makefile Remove implementations of Rotation, Translation and Transformation for the Identity type. 2015-07-07 22:40:14 +02:00
README.md Add Travis badge to the README. 2015-07-12 09:35:10 +02:00

Build Status

nalgebra

nalgebra is a low-dimensional linear algebra library written for Rust targeting:

  • general-purpose linear algebra (still lacks a lot of features…).
  • real time computer graphics.
  • real time computer physics.

An on-line version of this documentation is available here.

Using nalgebra

All the functionality of nalgebra is grouped in one place: the root module nalgebra::. This module re-exports everything and includes free functions for all traits methods doing out-of-place modifications.

  • You can import the whole prelude using:
use nalgebra::*;

The preferred way to use nalgebra is to import types and traits explicitly, and call free-functions using the na:: prefix:

extern crate nalgebra as na;
use na::{Vec3, Rot3, Rotation};

fn main() {
    let     a = Vec3::new(1.0f64, 1.0, 1.0);
    let mut b = Rot3::new(na::zero());

    b.append_rotation_mut(&a);

    assert!(na::approx_eq(&na::rotation(&b), &a));
}

Features

nalgebra is meant to be a general-purpose, low-dimensional, linear algebra library, with an optimized set of tools for computer graphics and physics. Those features include:

  • Vectors with static sizes: Vec0, Vec1, Vec2, Vec3, Vec4, Vec5, Vec6.
  • Points with static sizes: Pnt0, Pnt1, Pnt2, Pnt3, Pnt4, Pnt5, Pnt6.
  • Square matrices with static sizes: Mat1, Mat2, Mat3, Mat4, Mat5, Mat6 .
  • Rotation matrices: Rot2, Rot3, Rot4.
  • Quaternions: Quat, UnitQuat.
  • Isometries: Iso2, Iso3, Iso4.
  • 3D projections for computer graphics: Persp3, PerspMat3, Ortho3, OrthoMat3.
  • Dynamically sized vector: DVec.
  • Dynamically sized (square or rectangular) matrix: DMat.
  • A few methods for data analysis: Cov, Mean.
  • Almost one trait per functionality: useful for generic programming.
  • Operator overloading using multidispatch.