glam/lib.rs
1/*!
2# glam
3
4`glam` is a simple and fast linear algebra library for games and graphics.
5
6## Features
7
8* [`f32`](mod@f32) types
9 * vectors: [`Vec2`], [`Vec3`], [`Vec3A`] and [`Vec4`]
10 * square matrices: [`Mat2`], [`Mat3`], [`Mat3A`] and [`Mat4`]
11 * a quaternion type: [`Quat`]
12 * affine transformation types: [`Affine2`] and [`Affine3A`]
13* [`f64`](mod@f64) types
14 * vectors: [`DVec2`], [`DVec3`] and [`DVec4`]
15 * square matrices: [`DMat2`], [`DMat3`] and [`DMat4`]
16 * a quaternion type: [`DQuat`]
17 * affine transformation types: [`DAffine2`] and [`DAffine3`]
18* [`i8`](mod@i8) types
19 * vectors: [`I8Vec2`], [`I8Vec3`] and [`I8Vec4`]
20* [`u8`](mod@u8) types
21 * vectors: [`U8Vec2`], [`U8Vec3`] and [`U8Vec4`]
22* [`i16`](mod@i16) types
23 * vectors: [`I16Vec2`], [`I16Vec3`] and [`I16Vec4`]
24* [`u16`](mod@u16) types
25 * vectors: [`U16Vec2`], [`U16Vec3`] and [`U16Vec4`]
26* [`i32`](mod@i32) types
27 * vectors: [`IVec2`], [`IVec3`] and [`IVec4`]
28* [`u32`](mod@u32) types
29 * vectors: [`UVec2`], [`UVec3`] and [`UVec4`]
30* [`i64`](mod@i64) types
31 * vectors: [`I64Vec2`], [`I64Vec3`] and [`I64Vec4`]
32* [`u64`](mod@u64) types
33 * vectors: [`U64Vec2`], [`U64Vec3`] and [`U64Vec4`]
34* [`bool`](mod@bool) types
35 * vectors: [`BVec2`], [`BVec3`] and [`BVec4`]
36
37## SIMD
38
39`glam` is built with SIMD in mind. Many `f32` types use 128-bit SIMD vector types for storage
40and/or implementation. The use of SIMD generally enables better performance than using primitive
41numeric types such as `f32`.
42
43Some `glam` types use SIMD for storage meaning they are 16 byte aligned, these types include
44`Mat2`, `Mat3A`, `Mat4`, `Quat`, `Vec3A`, `Vec4`, `Affine2` an `Affine3A`. Types
45with an `A` suffix are a SIMD alternative to a scalar type, e.g. `Vec3` uses `f32` storage and
46`Vec3A` uses SIMD storage.
47
48When SIMD is not available on the target the types will maintain 16 byte alignment and internal
49padding so that object sizes and layouts will not change between architectures. There are scalar
50math fallback implementations exist when SIMD is not available. It is intended to add support for
51other SIMD architectures once they appear in stable Rust.
52
53Currently only SSE2 on x86/x86_64, NEON on Aarch64, and simd128 on WASM are supported.
54
55## Vec3A and Mat3A
56
57`Vec3A` is a SIMD optimized version of the `Vec3` type, which due to 16 byte alignment results
58in `Vec3A` containing 4 bytes of padding making it 16 bytes in size in total. `Mat3A` is composed
59of three `Vec3A` columns.
60
61| Type | `f32` bytes | Align bytes | Size bytes | Padding |
62|:-----------|------------:|------------:|-----------:|--------:|
63|[`Vec3`] | 12| 4| 12| 0|
64|[`Vec3A`] | 12| 16| 16| 4|
65|[`Mat3`] | 36| 4| 36| 0|
66|[`Mat3A`] | 36| 16| 48| 12|
67
68Despite this wasted space the SIMD implementations tend to outperform `f32` implementations in
69[**mathbench**](https://github.com/bitshifter/mathbench-rs) benchmarks.
70
71`glam` treats [`Vec3`] as the default 3D vector type and [`Vec3A`] a special case for optimization.
72When methods need to return a 3D vector they will generally return [`Vec3`].
73
74There are [`From`] trait implementations for converting from [`Vec4`] to a [`Vec3A`] and between
75[`Vec3`] and [`Vec3A`] (and vice versa).
76
77```
78use glam::{Vec3, Vec3A, Vec4};
79
80let v4 = Vec4::new(1.0, 2.0, 3.0, 4.0);
81
82// Convert from `Vec4` to `Vec3A`, this is a no-op if SIMD is supported.
83// We use an explicit method here instead of a From impl as data is lost in the conversion.
84let v3a = Vec3A::from_vec4(v4);
85assert_eq!(Vec3A::new(1.0, 2.0, 3.0), v3a);
86
87// Convert from `Vec3A` to `Vec3`.
88let v3 = Vec3::from(v3a);
89assert_eq!(Vec3::new(1.0, 2.0, 3.0), v3);
90
91// Convert from `Vec3` to `Vec3A`.
92let v3a = Vec3A::from(v3);
93assert_eq!(Vec3A::new(1.0, 2.0, 3.0), v3a);
94```
95
96## Affine2 and Affine3A
97
98`Affine2` and `Affine3A` are composed of a linear transform matrix and a vector translation. The
99represent 2D and 3D affine transformations which are commonly used in games.
100
101The table below shows the performance advantage of `Affine2` over `Mat3A` and `Mat3A` over `Mat3`.
102
103| operation | `Mat3` | `Mat3A` | `Affine2` |
104|--------------------|-------------|------------|------------|
105| inverse | 11.4±0.09ns | 7.1±0.09ns | 5.4±0.06ns |
106| mul self | 10.5±0.04ns | 5.2±0.05ns | 4.0±0.05ns |
107| transform point2 | 2.7±0.02ns | 2.7±0.03ns | 2.8±0.04ns |
108| transform vector2 | 2.6±0.01ns | 2.6±0.03ns | 2.3±0.02ns |
109
110Performance is much closer between `Mat4` and `Affine3A` with the affine type being faster to
111invert.
112
113| operation | `Mat4` | `Affine3A` |
114|--------------------|-------------|-------------|
115| inverse | 15.9±0.11ns | 10.8±0.06ns |
116| mul self | 7.3±0.05ns | 7.0±0.06ns |
117| transform point3 | 3.6±0.02ns | 4.3±0.04ns |
118| transform point3a | 3.0±0.02ns | 3.0±0.04ns |
119| transform vector3 | 4.1±0.02ns | 3.9±0.04ns |
120| transform vector3a | 2.8±0.02ns | 2.8±0.02ns |
121
122Benchmarks were taken on an Intel Core i7-4710HQ.
123
124## Linear algebra conventions
125
126`glam` interprets vectors as column matrices (also known as column vectors) meaning when
127transforming a vector with a matrix the matrix goes on the left.
128
129```
130use glam::{Mat3, Vec3};
131let m = Mat3::IDENTITY;
132let x = Vec3::X;
133let v = m * x;
134assert_eq!(v, x);
135```
136
137Matrices are stored in memory in column-major order.
138
139All angles are in radians. Rust provides the `f32::to_radians()` and `f64::to_radians()` methods to
140convert from degrees.
141
142## Direct element access
143
144Because some types may internally be implemented using SIMD types, direct access to vector elements
145is supported by implementing the [`Deref`] and [`DerefMut`] traits.
146
147```
148use glam::Vec3A;
149let mut v = Vec3A::new(1.0, 2.0, 3.0);
150assert_eq!(3.0, v.z);
151v.z += 1.0;
152assert_eq!(4.0, v.z);
153```
154
155[`Deref`]: https://doc.rust-lang.org/std/ops/trait.Deref.html
156[`DerefMut`]: https://doc.rust-lang.org/std/ops/trait.DerefMut.html
157
158## glam assertions
159
160`glam` does not enforce validity checks on method parameters at runtime. For example methods that
161require normalized vectors as input such as `Quat::from_axis_angle(axis, angle)` will not check
162that axis is a valid normalized vector. To help catch unintended misuse of `glam` the
163`debug-glam-assert` or `glam-assert` features can be enabled to add checks ensure that inputs to
164are valid.
165
166## Vector swizzles
167
168`glam` vector types have functions allowing elements of vectors to be reordered, this includes
169creating a vector of a different size from the vectors elements.
170
171The swizzle functions are implemented using traits to add them to each vector type. This is
172primarily because there are a lot of swizzle functions which can obfuscate the other vector
173functions in documentation and so on. The traits are [`Vec2Swizzles`], [`Vec3Swizzles`] and
174[`Vec4Swizzles`].
175
176Note that the [`Vec3Swizzles`] implementation for [`Vec3A`] will return a [`Vec3A`] for 3 element
177swizzles, all other implementations will return [`Vec3`].
178
179```
180use glam::{swizzles::*, Vec2, Vec3, Vec3A, Vec4};
181
182let v = Vec4::new(1.0, 2.0, 3.0, 4.0);
183
184// Reverse elements of `v`, if SIMD is supported this will use a vector shuffle.
185let wzyx = v.wzyx();
186assert_eq!(Vec4::new(4.0, 3.0, 2.0, 1.0), wzyx);
187
188// Swizzle the yzw elements of `v` into a `Vec3`
189let yzw = v.yzw();
190assert_eq!(Vec3::new(2.0, 3.0, 4.0), yzw);
191
192// To swizzle a `Vec4` into a `Vec3A` swizzle the `Vec4` first then convert to
193// `Vec3A`. If SIMD is supported this will use a vector shuffle. The last
194// element of the shuffled `Vec4` is ignored by the `Vec3A`.
195let yzw = Vec3A::from_vec4(v.yzwx());
196assert_eq!(Vec3A::new(2.0, 3.0, 4.0), yzw);
197
198// You can swizzle from a `Vec4` to a `Vec2`
199let xy = v.xy();
200assert_eq!(Vec2::new(1.0, 2.0), xy);
201
202// And back again
203let yyxx = xy.yyxx();
204assert_eq!(Vec4::new(2.0, 2.0, 1.0, 1.0), yyxx);
205```
206
207## SIMD and scalar consistency
208
209`glam` types implement `serde` `Serialize` and `Deserialize` traits to ensure
210that they will serialize and deserialize exactly the same whether or not
211SIMD support is being used.
212
213The SIMD versions implement the `core::fmt::Debug` and `core::fmt::Display`
214traits so they print the same as the scalar version.
215
216```
217use glam::Vec4;
218let a = Vec4::new(1.0, 2.0, 3.0, 4.0);
219assert_eq!(format!("{}", a), "[1, 2, 3, 4]");
220```
221
222## Feature gates
223
224All `glam` dependencies are optional, however some are required for tests
225and benchmarks.
226
227* `std` - the default feature, has no dependencies.
228* `approx` - traits and macros for approximate float comparisons
229* `bytemuck` - for casting into slices of bytes
230* `libm` - uses `libm` math functions instead of `std`, required to compile with `no_std`
231* `mint` - for interoperating with other 3D math libraries
232* `rand` - implementations of `Distribution` trait for all `glam` types.
233* `rkyv` - implementations of `Archive`, `Serialize` and `Deserialize` for all
234 `glam` types. Note that serialization is not interoperable with and without the
235 `scalar-math` feature. It should work between all other builds of `glam`.
236 Endian conversion is currently not supported
237* `bytecheck` - to perform archive validation when using the `rkyv` feature
238* `serde` - implementations of `Serialize` and `Deserialize` for all `glam`
239 types. Note that serialization should work between builds of `glam` with and without SIMD enabled
240* `scalar-math` - disables SIMD support and uses native alignment for all types.
241* `debug-glam-assert` - adds assertions in debug builds which check the validity of parameters
242 passed to `glam` to help catch runtime errors.
243* `glam-assert` - adds assertions to all builds which check the validity of parameters passed to
244 `glam` to help catch runtime errors.
245* `cuda` - forces `glam` types to match expected cuda alignment
246* `fast-math` - By default, glam attempts to provide bit-for-bit identical
247 results on all platforms. Using this feature will enable platform specific
248 optimizations that may not be identical to other platforms. **Intermediate
249 libraries should not use this feature and defer the decision to the final
250 binary build**.
251* `core-simd` - enables SIMD support via the portable simd module. This is an
252 unstable feature which requires a nightly Rust toolchain and `std` support.
253
254## Minimum Supported Rust Version (MSRV)
255
256The minimum supported Rust version is `1.68.2`.
257
258*/
259#![doc(html_root_url = "https://docs.rs/glam/0.29.2")]
260#![cfg_attr(not(feature = "std"), no_std)]
261#![cfg_attr(target_arch = "spirv", feature(repr_simd))]
262#![deny(
263 rust_2018_compatibility,
264 rust_2018_idioms,
265 future_incompatible,
266 nonstandard_style
267)]
268// clippy doesn't like `to_array(&self)`
269#![allow(clippy::wrong_self_convention)]
270#![cfg_attr(
271 all(feature = "core-simd", not(feature = "scalar-math")),
272 feature(portable_simd)
273)]
274
275#[macro_use]
276mod macros;
277
278mod align16;
279mod deref;
280mod euler;
281mod features;
282
283#[cfg(all(
284 target_arch = "aarch64",
285 not(any(feature = "core-simd", feature = "scalar-math"))
286))]
287mod neon;
288
289#[cfg(target_arch = "spirv")]
290mod spirv;
291
292#[cfg(all(
293 target_feature = "sse2",
294 not(any(feature = "core-simd", feature = "scalar-math"))
295))]
296mod sse2;
297
298#[cfg(all(
299 target_feature = "simd128",
300 not(any(feature = "core-simd", feature = "scalar-math"))
301))]
302mod wasm32;
303
304#[cfg(all(feature = "core-simd", not(feature = "scalar-math")))]
305mod coresimd;
306
307#[cfg(all(
308 target_feature = "sse2",
309 not(any(feature = "core-simd", feature = "scalar-math"))
310))]
311use align16::Align16;
312
313/** `bool` vector mask types. */
314pub mod bool;
315pub use self::bool::*;
316
317/** `f32` vector, quaternion and matrix types. */
318pub mod f32;
319pub use self::f32::*;
320
321/** `f64` vector, quaternion and matrix types. */
322pub mod f64;
323pub use self::f64::*;
324
325/** `i8` vector types. */
326pub mod i8;
327pub use self::i8::*;
328
329/** `u8` vector types. */
330pub mod u8;
331pub use self::u8::*;
332
333/** `i16` vector types. */
334pub mod i16;
335pub use self::i16::*;
336
337/** `u16` vector types. */
338pub mod u16;
339pub use self::u16::*;
340
341/** `i32` vector types. */
342pub mod i32;
343pub use self::i32::*;
344
345/** `u32` vector types. */
346pub mod u32;
347pub use self::u32::*;
348
349/** `i64` vector types. */
350pub mod i64;
351pub use self::i64::*;
352
353/** `u64` vector types. */
354pub mod u64;
355pub use self::u64::*;
356
357/** Traits adding swizzle methods to all vector types. */
358pub mod swizzles;
359pub use self::swizzles::{Vec2Swizzles, Vec3Swizzles, Vec4Swizzles};
360
361/** Rotation Helper */
362pub use euler::EulerRot;
363
364/** A trait for extending [`prim@f32`] and [`prim@f64`] with extra methods. */
365mod float;
366pub use float::FloatExt;