# Objective Previously, the `Point` trait, which abstracts all of the operations of a real vector space, was sitting in the submodule of `bevy_math` for cubic splines. However, the trait has broader applications than merely cubic splines, and we should use it when possible to avoid code duplication when performing vector operations. ## Solution `Point` has been moved into a new submodule in `bevy_math` named `common_traits`. Furthermore, it has been renamed to `VectorSpace`, which is more descriptive, and an additional trait `NormedVectorSpace` has been introduced to expand the API to cover situations involving geometry in addition to algebra. Additionally, `VectorSpace` itself now requires a `ZERO` constant and `Neg`. It also supports a `lerp` function as an automatic trait method. Here is what that looks like: ```rust /// A type that supports the mathematical operations of a real vector space, irrespective of dimension. /// In particular, this means that the implementing type supports: /// - Scalar multiplication and division on the right by elements of `f32` /// - Negation /// - Addition and subtraction /// - Zero /// /// Within the limitations of floating point arithmetic, all the following are required to hold: /// - (Associativity of addition) For all `u, v, w: Self`, `(u + v) + w == u + (v + w)`. /// - (Commutativity of addition) For all `u, v: Self`, `u + v == v + u`. /// - (Additive identity) For all `v: Self`, `v + Self::ZERO == v`. /// - (Additive inverse) For all `v: Self`, `v - v == v + (-v) == Self::ZERO`. /// - (Compatibility of multiplication) For all `a, b: f32`, `v: Self`, `v * (a * b) == (v * a) * b`. /// - (Multiplicative identity) For all `v: Self`, `v * 1.0 == v`. /// - (Distributivity for vector addition) For all `a: f32`, `u, v: Self`, `(u + v) * a == u * a + v * a`. /// - (Distributivity for scalar addition) For all `a, b: f32`, `v: Self`, `v * (a + b) == v * a + v * b`. /// /// Note that, because implementing types use floating point arithmetic, they are not required to actually /// implement `PartialEq` or `Eq`. pub trait VectorSpace: Mul<f32, Output = Self> + Div<f32, Output = Self> + Add<Self, Output = Self> + Sub<Self, Output = Self> + Neg + Default + Debug + Clone + Copy { /// The zero vector, which is the identity of addition for the vector space type. const ZERO: Self; /// Perform vector space linear interpolation between this element and another, based /// on the parameter `t`. When `t` is `0`, `self` is recovered. When `t` is `1`, `rhs` /// is recovered. /// /// Note that the value of `t` is not clamped by this function, so interpolating outside /// of the interval `[0,1]` is allowed. #[inline] fn lerp(&self, rhs: Self, t: f32) -> Self { *self * (1. - t) + rhs * t } } ``` ```rust /// A type that supports the operations of a normed vector space; i.e. a norm operation in addition /// to those of [`VectorSpace`]. Specifically, the implementor must guarantee that the following /// relationships hold, within the limitations of floating point arithmetic: /// - (Nonnegativity) For all `v: Self`, `v.norm() >= 0.0`. /// - (Positive definiteness) For all `v: Self`, `v.norm() == 0.0` implies `v == Self::ZERO`. /// - (Absolute homogeneity) For all `c: f32`, `v: Self`, `(v * c).norm() == v.norm() * c.abs()`. /// - (Triangle inequality) For all `v, w: Self`, `(v + w).norm() <= v.norm() + w.norm()`. /// /// Note that, because implementing types use floating point arithmetic, they are not required to actually /// implement `PartialEq` or `Eq`. pub trait NormedVectorSpace: VectorSpace { /// The size of this element. The return value should always be nonnegative. fn norm(self) -> f32; /// The squared norm of this element. Computing this is often faster than computing /// [`NormedVectorSpace::norm`]. #[inline] fn norm_squared(self) -> f32 { self.norm() * self.norm() } /// The distance between this element and another, as determined by the norm. #[inline] fn distance(self, rhs: Self) -> f32 { (rhs - self).norm() } /// The squared distance between this element and another, as determined by the norm. Note that /// this is often faster to compute in practice than [`NormedVectorSpace::distance`]. #[inline] fn distance_squared(self, rhs: Self) -> f32 { (rhs - self).norm_squared() } } ``` Furthermore, this PR also demonstrates the use of the `NormedVectorSpace` combined API to implement `ShapeSample` for `Triangle2d` and `Triangle3d` simultaneously. Such deduplication is one of the drivers for developing these APIs. --- ## Changelog - `Point` from `cubic_splines` becomes `VectorSpace`, exported as `bevy::math::VectorSpace`. - `VectorSpace` requires `Neg` and `VectorSpace::ZERO` in addition to its existing prerequisites. - Introduced public traits `bevy::math::NormedVectorSpace` for generic geometry tasks involving vectors. - Implemented `ShapeSample` for `Triangle2d` and `Triangle3d`. ## Migration Guide Since `Point` no longer exists, any projects using it must switch to `bevy::math::VectorSpace`. Additionally, third-party implementations of this trait now require the `Neg` trait; the constant `VectorSpace::ZERO` must be provided as well. --- ## Discussion ### Design considerations Originally, the `NormedVectorSpace::norm` method was part of a separate trait `Normed`. However, I think that was probably too broad and, more importantly, the semantics of having it in `NormedVectorSpace` are much clearer. As it currently stands, the API exposed here is pretty minimal, and there is definitely a lot more that we could do, but there are more questions to answer along the way. As a silly example, we could implement `NormedVectorSpace::length` as an alias for `NormedVectorSpace::norm`, but this overlaps with methods in all of the glam types, so we would want to make sure that the implementations are effectively identical (for what it's worth, I think they are already). ### Future directions One example of something that could belong in the `NormedVectorSpace` API is normalization. Actually, such a thing previously existed on this branch before I decided to shelve it because of concerns with namespace collision. It looked like this: ```rust /// This element, but normalized to norm 1 if possible. Returns an error when the reciprocal of /// the element's norm is not finite. #[inline] #[must_use] fn normalize(&self) -> Result<Self, NonNormalizableError> { let reciprocal = 1.0 / self.norm(); if reciprocal.is_finite() { Ok(*self * reciprocal) } else { Err(NonNormalizableError { reciprocal }) } } /// An error indicating that an element of a [`NormedVectorSpace`] was non-normalizable due to having /// non-finite norm-reciprocal. #[derive(Debug, Error)] #[error("Element with norm reciprocal {reciprocal} cannot be normalized")] pub struct NonNormalizableError { reciprocal: f32 } ``` With this kind of thing in hand, it might be worth considering eventually making the passage from vectors to directions fully generic by employing a wrapper type. (Of course, for our concrete types, we would leave the existing names in place as aliases.) That is, something like: ```rust pub struct NormOne<T> where T: NormedVectorSpace { //... } ``` Utterly separately, the reason that I implemented `ShapeSample` for `Triangle2d`/`Triangle3d` was to prototype uniform sampling of abstract meshes, so that's also a future direction. --------- Co-authored-by: Zachary Harrold <zac@harrold.com.au> |
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What is Bevy?
Bevy is a refreshingly simple data-driven game engine built in Rust. It is free and open-source forever!
WARNING
Bevy is still in the early stages of development. Important features are missing. Documentation is sparse. A new version of Bevy containing breaking changes to the API is released approximately once every 3 months. We provide migration guides, but we can't guarantee migrations will always be easy. Use only if you are willing to work in this environment.
MSRV: Bevy relies heavily on improvements in the Rust language and compiler. As a result, the Minimum Supported Rust Version (MSRV) is generally close to "the latest stable release" of Rust.
Design Goals
- Capable: Offer a complete 2D and 3D feature set
- Simple: Easy for newbies to pick up, but infinitely flexible for power users
- Data Focused: Data-oriented architecture using the Entity Component System paradigm
- Modular: Use only what you need. Replace what you don't like
- Fast: App logic should run quickly, and when possible, in parallel
- Productive: Changes should compile quickly ... waiting isn't fun
About
- Features: A quick overview of Bevy's features.
- News: A development blog that covers our progress, plans and shiny new features.
Docs
- Quick Start Guide: Bevy's official Quick Start Guide. The best place to start learning Bevy.
- Bevy Rust API Docs: Bevy's Rust API docs, which are automatically generated from the doc comments in this repo.
- Official Examples: Bevy's dedicated, runnable examples, which are great for digging into specific concepts.
- Community-Made Learning Resources: More tutorials, documentation, and examples made by the Bevy community.
Community
Before contributing or participating in discussions with the community, you should familiarize yourself with our Code of Conduct.
- Discord: Bevy's official discord server.
- Reddit: Bevy's official subreddit.
- GitHub Discussions: The best place for questions about Bevy, answered right here!
- Bevy Assets: A collection of awesome Bevy projects, tools, plugins and learning materials.
Contributing
If you'd like to help build Bevy, check out the Contributor's Guide. For simple problems, feel free to open an issue or PR and tackle it yourself!
For more complex architecture decisions and experimental mad science, please open an RFC (Request For Comments) so we can brainstorm together effectively!
Getting Started
We recommend checking out the Quick Start Guide for a brief introduction.
Follow the Setup guide to ensure your development environment is set up correctly. Once set up, you can quickly try out the examples by cloning this repo and running the following commands:
# Switch to the correct version (latest release, default is main development branch)
git checkout latest
# Runs the "breakout" example
cargo run --example breakout
To draw a window with standard functionality enabled, use:
use bevy::prelude::*;
fn main(){
App::new()
.add_plugins(DefaultPlugins)
.run();
}
Fast Compiles
Bevy can be built just fine using default configuration on stable Rust. However for really fast iterative compiles, you should enable the "fast compiles" setup by following the instructions here.
Bevy Cargo Features
This list outlines the different cargo features supported by Bevy. These allow you to customize the Bevy feature set for your use-case.
Thanks
Bevy is the result of the hard work of many people. A huge thanks to all Bevy contributors, the many open source projects that have come before us, the Rust gamedev ecosystem, and the many libraries we build on.
A huge thanks to Bevy's generous sponsors. Bevy will always be free and open source, but it isn't free to make. Please consider sponsoring our work if you like what we're building.
This project is tested with BrowserStack.
License
Bevy is free, open source and permissively licensed! Except where noted (below and/or in individual files), all code in this repository is dual-licensed under either:
- MIT License (LICENSE-MIT or http://opensource.org/licenses/MIT)
- Apache License, Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
at your option. This means you can select the license you prefer! This dual-licensing approach is the de-facto standard in the Rust ecosystem and there are very good reasons to include both.
Some of the engine's code carries additional copyright notices and license terms due to their external origins.
These are generally BSD-like, but exact details vary by crate:
If the README of a crate contains a 'License' header (or similar), the additional copyright notices and license terms applicable to that crate will be listed.
The above licensing requirement still applies to contributions to those crates, and sections of those crates will carry those license terms.
The license field of each crate will also reflect this.
For example, bevy_mikktspace
has code under the Zlib license (as well as a copyright notice when choosing the MIT license).
The assets included in this repository (for our examples) typically fall under different open licenses. These will not be included in your game (unless copied in by you), and they are not distributed in the published bevy crates. See CREDITS.md for the details of the licenses of those files.
Your contributions
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.