Crate glam[][src]

glam

glam is a simple and fast linear algebra library for games and graphics.

Features

glam is built with SIMD in mind. Currently only SSE2 on x86/x86_64 is supported as this is what stable Rust supports.

  • Vector, quaternion and matrix types support for f32 and f64
  • Vector types supported for i32, u32 and bool
  • SSE2 storage and optimization for many f32 types, including Mat2, Mat4, Quat, Vec3A and Vec4
  • Scalar math fallback implementations exist when SSE2 is not available
  • Most functionality includes unit tests and benchmarks

Linear algebra conventions

glam interprets vectors as column matrices (also known as “column vectors”) meaning when transforming a vector with a matrix the matrix goes on the left.

use glam::{Mat3, Vec3};
let m = Mat3::IDENTITY;
let x = Vec3::X;
let v = m * x;
assert_eq!(v, x);

Matrices are stored in memory in column-major order.

All angles are in radians. Rust provides the to_radians() method which can be used to convert from degrees.

Direct element access

Because some types may internally be implemeted using SIMD types, direct access to vector elements is supported by implementing the Deref and DerefMut traits.

use glam::Vec3A;
let mut v = Vec3A::new(1.0, 2.0, 3.0);
assert_eq!(3.0, v.z);
v.z += 1.0;
assert_eq!(4.0, v.z);

Size and alignment of types

Some glam types use SIMD for storage meaning they are 16 byte aligned, these types include Mat2, Mat4, Quat, Vec3A and Vec4.

When SSE2 is not available on the target architecture this type will still be 16 byte aligned so that object sizes and layouts will not change between architectures.

SIMD support can be disabled entirely using the scalar-math feature. This feature will also disable SIMD alignment meaning most types will use native f32 alignment of 4 bytes.

All the main glam types are #[repr(C)], so they are possible to expose as struct members to C interfaces if desired. Be mindful of Vec3A’s extra padding though.

Vec3A

Vec3A is a SIMD optimized version of the Vec3 type, which due to 16 byte alignment results in Vec3A containing 4 bytes of padding making it 16 bytes in size in total.

Typef32 bytesAlign bytesPaddingSize bytes
Vec3124012
Vec3A1216416

Despite this wasted space the SIMD version tends to outperform the f32 implementation in mathbench benchmarks.

glam treats Vec3 as the default vector 3 type and Vec3A a special case for optimization. When methods need to return a vector 3 type they will generally return Vec3.

There are From trait implementations for converting from Vec4 to a Vec3A and between Vec3 and Vec3A (and vice versa).

use glam::{Vec3, Vec3A, Vec4};

let v4 = Vec4::new(1.0, 2.0, 3.0, 4.0);

// Convert from `Vec4` to `Vec3A`, this is a no-op if SIMD is supported.
let v3a = Vec3A::from(v4);
assert_eq!(Vec3A::new(1.0, 2.0, 3.0), v3a);

// Convert from `Vec3A` to `Vec3`.
let v3 = Vec3::from(v3a);
assert_eq!(Vec3::new(1.0, 2.0, 3.0), v3);

// Convert from `Vec3` to `Vec3A`.
let v3a = Vec3A::from(v3);
assert_eq!(Vec3A::new(1.0, 2.0, 3.0), v3a);

Vector swizzles

glam vector types have functions allowing elements of vectors to be reordered, this includes creating a vector of a different size from the vectors elements.

The swizzle functions are implemented using traits to add them to each vector type. This is primarily because there are a lot of swizzle functions which can obfuscate the other vector functions in documentation and so on. The traits are Vec2Swizzles, Vec3Swizzles and Vec4Swizzles.

Note that the Vec3Swizzles implementation for Vec3A will return a Vec3A for 3 element swizzles, all other implementations will return Vec3.

use glam::{swizzles::*, Vec2, Vec3, Vec3A, Vec4};

let v = Vec4::new(1.0, 2.0, 3.0, 4.0);

// Reverse elements of `v`, if SIMD is supported this will use a vector shuffle.
let wzyx = v.wzyx();
assert_eq!(Vec4::new(4.0, 3.0, 2.0, 1.0), wzyx);

// Swizzle the yzw elements of `v` into a `Vec3`
let yzw = v.yzw();
assert_eq!(Vec3::new(2.0, 3.0, 4.0), yzw);

// To swizzle a `Vec4` into a `Vec3A` swizzle the `Vec4` first then convert to
// `Vec3A`. If SIMD is supported this will use a vector shuffle. The last
// element of the shuffled `Vec4` is ignored by the `Vec3A`.
let yzw = Vec3A::from(v.yzwx());
assert_eq!(Vec3A::new(2.0, 3.0, 4.0), yzw);

// You can swizzle from a `Vec4` to a `Vec2`
let xy = v.xy();
assert_eq!(Vec2::new(1.0, 2.0), xy);

// And back again
let yyxx = xy.yyxx();
assert_eq!(Vec4::new(2.0, 2.0, 1.0, 1.0), yyxx);

SIMD and scalar consistency

glam types implement serde Serialize and Deserialize traits to ensure that they will serialize and deserialize exactly the same whether or not SIMD support is being used.

The SIMD versions implement the core::fmt::Debug and core::fmt::Display traits so they print the same as the scalar version.

use glam::Vec4;
let a = Vec4::new(1.0, 2.0, 3.0, 4.0);
assert_eq!(format!("{}", a), "[1, 2, 3, 4]");

Feature gates

All glam dependencies are optional, however some are required for tests and benchmarks.

  • std - the default feature, has no dependencies.
  • rand - used to generate random values. Used in benchmarks.
  • serde - used for serialization and deserialization of types.
  • mint - used for interoperating with other linear algebra libraries.
  • scalar-math - disables SIMD support and uses native alignment for all types.
  • debug-glam-assert - adds assertions in debug builds which check the validity of parameters passed to glam to help catch runtime errors.
  • glam-assert - adds assertions to all builds which check the validity of parameters passed to glam to help catch runtime errors.

Minimum Supported Version or Rust (MSVR)

The minimum supported version of Rust for glam is 1.36.0.

Re-exports

pub use self::bool::*;
pub use self::f32::*;
pub use self::f64::*;
pub use self::i32::*;
pub use self::u32::*;

Modules

bool

bool vector mask types.

f32

f32 vector, quaternion and matrix types.

f64

f64 vector, quaternion and matrix types.

i32

i32 vector types.

swizzles

Traits adding swizzle methods to all vector types.

u32

u32 vector types.

Macros

const_dmat2

Creates a DMat2 from two column vectors that can be used to initialize a constant value.

const_dmat3

Creates a DMat3 from three column vectors that can be used to initialize a constant value.

const_dmat4

Creates a DMat4 from four column vectors that can be used to initialize a constant value.

const_dquat

Creates a DQuat from x, y, z and w values that can be used to initialize a constant value.

const_dvec2

Creates a DVec2 that can be used to initialize a constant value.

const_dvec3

Creates a DVec3 that can be used to initialize a constant value.

const_dvec4

Creates a DVec4 that can be used to initialize a constant value.

const_ivec2

Creates a IVec2 that can be used to initialize a constant value.

const_ivec3

Creates a IVec3 that can be used to initialize a constant value.

const_ivec4

Creates a IVec4 that can be used to initialize a constant value.

const_m128
const_mat2

Creates a Mat2 from two column vectors that can be used to initialize a constant value.

const_mat3

Creates a Mat3 from three column vectors that can be used to initialize a constant value.

const_mat4

Creates a Mat4 from four column vectors that can be used to initialize a constant value.

const_quat

Creates a Quat from x, y, z and w values that can be used to initialize a constant value.

const_uvec2

Creates a UVec2 that can be used to initialize a constant value.

const_uvec3

Creates a UVec3 that can be used to initialize a constant value.

const_uvec4

Creates a UVec4 that can be used to initialize a constant value.

const_vec2

Creates a Vec2 that can be used to initialize a constant value.

const_vec3

Creates a Vec3 that can be used to initialize a constant value.

const_vec3a

Creates a Vec3A that can be used to initialize a constant value.

const_vec4

Creates a Vec4 that can be used to initialize a constant value.

Traits

Vec2Swizzles

Swizzle methods for 2-dimensional vector types.

Vec3Swizzles

Swizzle methods for 3-dimensional vector types.

Vec4Swizzles

Swizzle methods for 3-dimensional vector types.