1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354
/*!
# glam
`glam` is a simple and fast linear algebra library for games and graphics.
## Features
* [`f32`](mod@f32) types
* vectors: [`Vec2`], [`Vec3`], [`Vec3A`] and [`Vec4`]
* square matrices: [`Mat2`], [`Mat3`], [`Mat3A`] and [`Mat4`]
* a quaternion type: [`Quat`]
* affine transformation types: [`Affine2`] and [`Affine3A`]
* [`f64`](mod@f64) types
* vectors: [`DVec2`], [`DVec3`] and [`DVec4`]
* square matrices: [`DMat2`], [`DMat3`] and [`DMat4`]
* a quaternion type: [`DQuat`]
* affine transformation types: [`DAffine2`] and [`DAffine3`]
* [`i16`](mod@i16) types
* vectors: [`I16Vec2`], [`I16Vec3`] and [`I16Vec4`]
* [`u16`](mod@u16) types
* vectors: [`U16Vec2`], [`U16Vec3`] and [`U16Vec4`]
* [`i32`](mod@i32) types
* vectors: [`IVec2`], [`IVec3`] and [`IVec4`]
* [`u32`](mod@u32) types
* vectors: [`UVec2`], [`UVec3`] and [`UVec4`]
* [`i64`](mod@i64) types
* vectors: [`I64Vec2`], [`I64Vec3`] and [`I64Vec4`]
* [`u64`](mod@u64) types
* vectors: [`U64Vec2`], [`U64Vec3`] and [`U64Vec4`]
* [`bool`](mod@bool) types
* vectors: [`BVec2`], [`BVec3`] and [`BVec4`]
## SIMD
`glam` is built with SIMD in mind. Many `f32` types use 128-bit SIMD vector types for storage
and/or implementation. The use of SIMD generally enables better performance than using primitive
numeric types such as `f32`.
Some `glam` types use SIMD for storage meaning they are 16 byte aligned, these types include
`Mat2`, `Mat3A`, `Mat4`, `Quat`, `Vec3A`, `Vec4`, `Affine2` an `Affine3A`. Types
with an `A` suffix are a SIMD alternative to a scalar type, e.g. `Vec3` uses `f32` storage and
`Vec3A` uses SIMD storage.
When SIMD is not available on the target the types will maintain 16 byte alignment and internal
padding so that object sizes and layouts will not change between architectures. There are scalar
math fallback implementations exist when SIMD is not available. It is intended to add support for
other SIMD architectures once they appear in stable Rust.
Currently only SSE2 on x86/x86_64 is supported as this is what stable Rust supports.
## Vec3A and Mat3A
`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. `Mat3A` is composed
of three `Vec3A` columns.
| Type | `f32` bytes | Align bytes | Size bytes | Padding |
|:-----------|------------:|------------:|-----------:|--------:|
|[`Vec3`] | 12| 4| 12| 0|
|[`Vec3A`] | 12| 16| 16| 4|
|[`Mat3`] | 36| 4| 36| 0|
|[`Mat3A`] | 36| 16| 48| 12|
Despite this wasted space the SIMD implementations tend to outperform `f32` implementations in
[**mathbench**](https://github.com/bitshifter/mathbench-rs) benchmarks.
`glam` treats [`Vec3`] as the default 3D vector type and [`Vec3A`] a special case for optimization.
When methods need to return a 3D vector 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.
// We use an explicit method here instead of a From impl as data is lost in the conversion.
let v3a = Vec3A::from_vec4(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);
```
## Affine2 and Affine3A
`Affine2` and `Affine3A` are composed of a linear transform matrix and a vector translation. The
represent 2D and 3D affine transformations which are commonly used in games.
The table below shows the performance advantage of `Affine2` over `Mat3A` and `Mat3A` over `Mat3`.
| operation | `Mat3` | `Mat3A` | `Affine2` |
|--------------------|-------------|------------|------------|
| inverse | 11.4±0.09ns | 7.1±0.09ns | 5.4±0.06ns |
| mul self | 10.5±0.04ns | 5.2±0.05ns | 4.0±0.05ns |
| transform point2 | 2.7±0.02ns | 2.7±0.03ns | 2.8±0.04ns |
| transform vector2 | 2.6±0.01ns | 2.6±0.03ns | 2.3±0.02ns |
Performance is much closer between `Mat4` and `Affine3A` with the affine type being faster to
invert.
| operation | `Mat4` | `Affine3A` |
|--------------------|-------------|-------------|
| inverse | 15.9±0.11ns | 10.8±0.06ns |
| mul self | 7.3±0.05ns | 7.0±0.06ns |
| transform point3 | 3.6±0.02ns | 4.3±0.04ns |
| transform point3a | 3.0±0.02ns | 3.0±0.04ns |
| transform vector3 | 4.1±0.02ns | 3.9±0.04ns |
| transform vector3a | 2.8±0.02ns | 2.8±0.02ns |
Benchmarks were taken on an Intel Core i7-4710HQ.
## 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 `f32::to_radians()` and `f64::to_radians()` methods to
convert from degrees.
## Direct element access
Because some types may internally be implemented 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);
```
[`Deref`]: https://doc.rust-lang.org/std/ops/trait.Deref.html
[`DerefMut`]: https://doc.rust-lang.org/std/ops/trait.DerefMut.html
## glam assertions
`glam` does not enforce validity checks on method parameters at runtime. For example methods that
require normalized vectors as input such as `Quat::from_axis_angle(axis, angle)` will not check
that axis is a valid normalized vector. To help catch unintended misuse of `glam` the
`debug-glam-assert` or `glam-assert` features can be enabled to add checks ensure that inputs to
are valid.
## 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_vec4(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.
* `approx` - traits and macros for approximate float comparisons
* `bytemuck` - for casting into slices of bytes
* `libm` - uses `libm` math functions instead of `std`, required to compile with `no_std`
* `mint` - for interoperating with other 3D math libraries
* `rand` - implementations of `Distribution` trait for all `glam` types.
* `rkyv` - implementations of `Archive`, `Serialize` and `Deserialize` for all
`glam` types. Note that serialization is not interoperable with and without the
`scalar-math` feature. It should work between all other builds of `glam`.
Endian conversion is currently not supported
* `bytecheck` - to perform archive validation when using the `rkyv` feature
* `serde` - implementations of `Serialize` and `Deserialize` for all `glam`
types. Note that serialization should work between builds of `glam` with and without SIMD enabled
* `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.
* `cuda` - forces `glam` types to match expected cuda alignment
* `fast-math` - By default, glam attempts to provide bit-for-bit identical
results on all platforms. Using this feature will enable platform specific
optimizations that may not be identical to other platforms. **Intermediate
libraries should not use this feature and defer the decision to the final
binary build**.
* `core-simd` - enables SIMD support via the portable simd module. This is an
unstable feature which requires a nightly Rust toolchain and `std` support.
## Minimum Supported Rust Version (MSRV)
The minimum supported Rust version is `1.68.2`.
*/
#![doc(html_root_url = "https://docs.rs/glam/0.28.0")]
#![cfg_attr(not(feature = "std"), no_std)]
#![cfg_attr(target_arch = "spirv", feature(repr_simd))]
#![deny(
rust_2018_compatibility,
rust_2018_idioms,
future_incompatible,
nonstandard_style
)]
// clippy doesn't like `to_array(&self)`
#![allow(clippy::wrong_self_convention)]
#![cfg_attr(
all(feature = "core-simd", not(feature = "scalar-math")),
feature(portable_simd)
)]
#[macro_use]
mod macros;
mod align16;
mod deref;
mod euler;
mod features;
#[cfg(all(
target_arch = "aarch64",
not(any(feature = "core-simd", feature = "scalar-math"))
))]
mod neon;
#[cfg(target_arch = "spirv")]
mod spirv;
#[cfg(all(
target_feature = "sse2",
not(any(feature = "core-simd", feature = "scalar-math"))
))]
mod sse2;
#[cfg(all(
target_feature = "simd128",
not(any(feature = "core-simd", feature = "scalar-math"))
))]
mod wasm32;
#[cfg(all(feature = "core-simd", not(feature = "scalar-math")))]
mod coresimd;
#[cfg(all(
target_feature = "sse2",
not(any(feature = "core-simd", feature = "scalar-math"))
))]
use align16::Align16;
/** `bool` vector mask types. */
pub mod bool;
pub use self::bool::*;
/** `f32` vector, quaternion and matrix types. */
pub mod f32;
pub use self::f32::*;
/** `f64` vector, quaternion and matrix types. */
pub mod f64;
pub use self::f64::*;
/** `i16` vector types. */
pub mod i16;
pub use self::i16::*;
/** `u16` vector types. */
pub mod u16;
pub use self::u16::*;
/** `i32` vector types. */
pub mod i32;
pub use self::i32::*;
/** `u32` vector types. */
pub mod u32;
pub use self::u32::*;
/** `i64` vector types. */
pub mod i64;
pub use self::i64::*;
/** `u64` vector types. */
pub mod u64;
pub use self::u64::*;
/** Traits adding swizzle methods to all vector types. */
pub mod swizzles;
pub use self::swizzles::{Vec2Swizzles, Vec3Swizzles, Vec4Swizzles};
/** Rotation Helper */
pub use euler::EulerRot;
/** A trait for extending [`prim@f32`] and [`prim@f64`] with extra methods. */
mod float;
pub use float::FloatExt;