9e739676a7
Fix #184. |
||
---|---|---|
benches | ||
src | ||
tests | ||
.gitignore | ||
.travis.yml | ||
CHANGELOG.md | ||
Cargo.toml | ||
LICENSE | ||
Makefile | ||
README.md |
README.md
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 performing
out-of-place operations.
- 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 predefined static sizes:
Vec1
,Vec2
,Vec3
,Vec4
,Vec5
,Vec6
. - Vector with a user-defined static size:
VecN
(available only with thegeneric_sizes
feature). - 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
toDVec6
. - 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.