61 lines
2.5 KiB
Markdown
61 lines
2.5 KiB
Markdown
[](https://travis-ci.org/sebcrozet/nalgebra)
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nalgebra
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========
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**nalgebra** is a low-dimensional linear algebra library written for Rust targeting:
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* General-purpose linear algebra (still lacks a lot of features…)
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* Real time computer graphics.
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* Real time computer physics.
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An on-line version of this documentation is available [here](http://nalgebra.org/doc/nalgebra).
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## Using **nalgebra**
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All the functionality of **nalgebra** is grouped in one place: the root module `nalgebra::`. This
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module re-exports everything and includes free functions for all traits methods performing
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out-of-place operations.
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Thus, you can import the whole prelude using:
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```.ignore
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use nalgebra::*;
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```
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However, the recommended way to use **nalgebra** is to import types and traits
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explicitly, and call free-functions using the `na::` prefix:
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```.rust
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extern crate nalgebra as na;
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use na::{Vector3, Rotation3, Rotation};
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fn main() {
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let a = Vector3::new(1.0f64, 1.0, 1.0);
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let mut b = Rotation3::new(na::zero());
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b.append_rotation_mut(&a);
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assert!(na::approx_eq(&na::rotation(&b), &a));
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}
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```
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## Features
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**nalgebra** is meant to be a general-purpose, low-dimensional, linear algebra library, with
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an optimized set of tools for computer graphics and physics. Those features include:
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* Vectors with predefined static sizes: `Vector1`, `Vector2`, `Vector3`, `Vector4`, `Vector5`, `Vector6`.
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* Vector with a user-defined static size: `VectorN` (available only with the `generic_sizes` feature).
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* Points with static sizes: `Point1`, `Point2`, `Point3`, `Point4`, `Point5`, `Point6`.
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* Square matrices with static sizes: `Matrix1`, `Matrix2`, `Matrix3`, `Matrix4`, `Matrix5`, `Matrix6 `.
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* Rotation matrices: `Rotation2`, `Rotation3`
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* Quaternions: `Quaternion`, `UnitQuaternion`.
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* Isometries (translation ⨯ rotation): `Isometry2`, `Isometry3`
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* Similarity transformations (translation ⨯ rotation ⨯ uniform scale): `Similarity2`, `Similarity3`.
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* 3D projections for computer graphics: `Persp3`, `PerspMatrix3`, `Ortho3`, `OrthoMatrix3`.
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* Dynamically sized heap-allocated vector: `DVector`.
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* Dynamically sized stack-allocated vectors with a maximum size: `DVector1` to `DVector6`.
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* Dynamically sized heap-allocated (square or rectangular) matrix: `DMatrix`.
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* Linear algebra and data analysis operators: `Covariance`, `Mean`, `qr`, `cholesky`.
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* Almost one trait per functionality: useful for generic programming.
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