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.

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.

Type	`f32` bytes	Align bytes	Padding	Size bytes
`Vec3`	12	4	0	12
`Vec3A`	12	16	4	16

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.