[![Build Status](https://travis-ci.org/sebcrozet/nalgebra.svg?branch=master)](https://travis-ci.org/sebcrozet/nalgebra) 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](http://nalgebra.org/doc/nalgebra). ## 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 performing out-of-place operations. * You can import the whole prelude using: ```.ignore use nalgebra::*; ``` The preferred way to use **nalgebra** is to import types and traits explicitly, and call free-functions using the `na::` prefix: ```.rust 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 predefined static sizes: `Vec1`, `Vec2`, `Vec3`, `Vec4`, `Vec5`, `Vec6`. * Vector with a user-defined static size: `VecN`. * Points with static sizes: `Pnt1`, `Pnt2`, `Pnt3`, `Pnt4`, `Pnt5`, `Pnt6`. * Square matrices with static sizes: `Mat1`, `Mat2`, `Mat3`, `Mat4`, `Mat5`, `Mat6 `. * Rotation matrices: `Rot2`, `Rot3` * Quaternions: `Quat`, `UnitQuat`. * Isometries (translation ⨯ rotation): `Iso2`, `Iso3` * Similarity transformations (translation ⨯ rotation ⨯ uniform scale): `Sim2`, `Sim3`. * 3D projections for computer graphics: `Persp3`, `PerspMat3`, `Ortho3`, `OrthoMat3`. * Dynamically sized heap-allocated vector: `DVec`. * Dynamically sized stack-allocated vectors with a maximum size: `DVec1` to `DVec6`. * Dynamically sized heap-allocated (square or rectangular) matrix: `DMat`. * Linear algebra and data analysis operators: `Cov`, `Mean`, `qr`, `cholesky`. * Almost one trait per functionality: useful for generic programming.