# Objective
- Fixes#17960
## Solution
- Followed the [edition upgrade
guide](https://doc.rust-lang.org/edition-guide/editions/transitioning-an-existing-project-to-a-new-edition.html)
## Testing
- CI
---
## Summary of Changes
### Documentation Indentation
When using lists in documentation, proper indentation is now linted for.
This means subsequent lines within the same list item must start at the
same indentation level as the item.
```rust
/* Valid */
/// - Item 1
/// Run-on sentence.
/// - Item 2
struct Foo;
/* Invalid */
/// - Item 1
/// Run-on sentence.
/// - Item 2
struct Foo;
```
### Implicit `!` to `()` Conversion
`!` (the never return type, returned by `panic!`, etc.) no longer
implicitly converts to `()`. This is particularly painful for systems
with `todo!` or `panic!` statements, as they will no longer be functions
returning `()` (or `Result<()>`), making them invalid systems for
functions like `add_systems`. The ideal fix would be to accept functions
returning `!` (or rather, _not_ returning), but this is blocked on the
[stabilisation of the `!` type
itself](https://doc.rust-lang.org/std/primitive.never.html), which is
not done.
The "simple" fix would be to add an explicit `-> ()` to system
signatures (e.g., `|| { todo!() }` becomes `|| -> () { todo!() }`).
However, this is _also_ banned, as there is an existing lint which (IMO,
incorrectly) marks this as an unnecessary annotation.
So, the "fix" (read: workaround) is to put these kinds of `|| -> ! { ...
}` closuers into variables and give the variable an explicit type (e.g.,
`fn()`).
```rust
// Valid
let system: fn() = || todo!("Not implemented yet!");
app.add_systems(..., system);
// Invalid
app.add_systems(..., || todo!("Not implemented yet!"));
```
### Temporary Variable Lifetimes
The order in which temporary variables are dropped has changed. The
simple fix here is _usually_ to just assign temporaries to a named
variable before use.
### `gen` is a keyword
We can no longer use the name `gen` as it is reserved for a future
generator syntax. This involved replacing uses of the name `gen` with
`r#gen` (the raw-identifier syntax).
### Formatting has changed
Use statements have had the order of imports changed, causing a
substantial +/-3,000 diff when applied. For now, I have opted-out of
this change by amending `rustfmt.toml`
```toml
style_edition = "2021"
```
This preserves the original formatting for now, reducing the size of
this PR. It would be a simple followup to update this to 2024 and run
`cargo fmt`.
### New `use<>` Opt-Out Syntax
Lifetimes are now implicitly included in RPIT types. There was a handful
of instances where it needed to be added to satisfy the borrow checker,
but there may be more cases where it _should_ be added to avoid
breakages in user code.
### `MyUnitStruct { .. }` is an invalid pattern
Previously, you could match against unit structs (and unit enum
variants) with a `{ .. }` destructuring. This is no longer valid.
### Pretty much every use of `ref` and `mut` are gone
Pattern binding has changed to the point where these terms are largely
unused now. They still serve a purpose, but it is far more niche now.
### `iter::repeat(...).take(...)` is bad
New lint recommends using the more explicit `iter::repeat_n(..., ...)`
instead.
## Migration Guide
The lifetimes of functions using return-position impl-trait (RPIT) are
likely _more_ conservative than they had been previously. If you
encounter lifetime issues with such a function, please create an issue
to investigate the addition of `+ use<...>`.
## Notes
- Check the individual commits for a clearer breakdown for what
_actually_ changed.
---------
Co-authored-by: François Mockers <francois.mockers@vleue.com>
# Objective
Fixes#16104
## Solution
I removed all instances of `:?` and put them back one by one where it
caused an error.
I removed some bevy_utils helper functions that were only used in 2
places and don't add value. See: #11478
## Testing
CI should catch the mistakes
## Migration Guide
`bevy::utils::{dbg,info,warn,error}` were removed. Use
`bevy::utils::tracing::{debug,info,warn,error}` instead.
---------
Co-authored-by: SpecificProtagonist <vincentjunge@posteo.net>
# Objective
Fixes typos in bevy project, following suggestion in
https://github.com/bevyengine/bevy-website/pull/1912#pullrequestreview-2483499337
## Solution
I used https://github.com/crate-ci/typos to find them.
I included only the ones that feel undebatable too me, but I am not in
game engine so maybe some terms are expected.
I left out the following typos:
- `reparametrize` => `reparameterize`: There are a lot of occurences, I
believe this was expected
- `semicircles` => `hemicircles`: 2 occurences, may mean something
specific in geometry
- `invertation` => `inversion`: may mean something specific
- `unparented` => `parentless`: may mean something specific
- `metalness` => `metallicity`: may mean something specific
## Testing
- Did you test these changes? If so, how? I did not test the changes,
most changes are related to raw text. I expect the others to be tested
by the CI.
- Are there any parts that need more testing? I do not think
- How can other people (reviewers) test your changes? Is there anything
specific they need to know? To me there is nothing to test
- If relevant, what platforms did you test these changes on, and are
there any important ones you can't test?
---
## Migration Guide
> This section is optional. If there are no breaking changes, you can
delete this section.
(kept in case I include the `reparameterize` change here)
- If this PR is a breaking change (relative to the last release of
Bevy), describe how a user might need to migrate their code to support
these changes
- Simply adding new functionality is not a breaking change.
- Fixing behavior that was definitely a bug, rather than a questionable
design choice is not a breaking change.
## Questions
- [x] Should I include the above typos? No
(https://github.com/bevyengine/bevy/pull/16702#issuecomment-2525271152)
- [ ] Should I add `typos` to the CI? (I will check how to configure it
properly)
This project looks awesome, I really enjoy reading the progress made,
thanks to everyone involved.
# Objective
- Contributes to #15460
## Solution
- Added two new features, `std` (default) and `alloc`, gating `std` and
`alloc` behind them respectively.
- Added missing `f32` functions to `std_ops` as required. These `f32`
methods have been added to the `clippy.toml` deny list to aid in
`no_std` development.
## Testing
- CI
- `cargo clippy -p bevy_math --no-default-features --features libm
--target "x86_64-unknown-none"`
- `cargo test -p bevy_math --no-default-features --features libm`
- `cargo test -p bevy_math --no-default-features --features "libm,
alloc"`
- `cargo test -p bevy_math --no-default-features --features "libm,
alloc, std"`
- `cargo test -p bevy_math --no-default-features --features "std"`
## Notes
The following items require the `alloc` feature to be enabled:
- `CubicBSpline`
- `CubicBezier`
- `CubicCardinalSpline`
- `CubicCurve`
- `CubicGenerator`
- `CubicHermite`
- `CubicNurbs`
- `CyclicCubicGenerator`
- `RationalCurve`
- `RationalGenerator`
- `BoxedPolygon`
- `BoxedPolyline2d`
- `BoxedPolyline3d`
- `SampleCurve`
- `SampleAutoCurve`
- `UnevenSampleCurve`
- `UnevenSampleAutoCurve`
- `EvenCore`
- `UnevenCore`
- `ChunkedUnevenCore`
This requirement could be relaxed in certain cases, but I had erred on
the side of gating rather than modifying. Since `no_std` is a new set of
platforms we are adding support to, and the `alloc` feature is enabled
by default, this is not a breaking change.
---------
Co-authored-by: Benjamin Brienen <benjamin.brienen@outlook.com>
Co-authored-by: Matty <2975848+mweatherley@users.noreply.github.com>
Co-authored-by: Joona Aalto <jondolf.dev@gmail.com>
# Objective
Bevy seems to want to standardize on "American English" spellings. Not
sure if this is laid out anywhere in writing, but see also #15947.
While perusing the docs for `typos`, I noticed that it has a `locale`
config option and tried it out.
## Solution
Switch to `en-us` locale in the `typos` config and run `typos -w`
## Migration Guide
The following methods or fields have been renamed from `*dependants*` to
`*dependents*`.
- `ProcessorAssetInfo::dependants`
- `ProcessorAssetInfos::add_dependant`
- `ProcessorAssetInfos::non_existent_dependants`
- `AssetInfo::dependants_waiting_on_load`
- `AssetInfo::dependants_waiting_on_recursive_dep_load`
- `AssetInfos::loader_dependants`
- `AssetInfos::remove_dependants_and_labels`
# Objective
Unlike `Capsule3d` which has the `.to_cylinder` method, `Capsule2d`
doesn't have an equivalent `.to_inner_rectangle` method and as shown by
#15191 this is surprisingly easy to get wrong
## Solution
Implemented a `Capsule2d::to_inner_rectangle` method as it is
implemented in the fixed `Capsule2d` shape sampling, and as I was adding
tests I noticed `Capsule2d` didn't implement `Measure2d` so I did this
as well.
## Changelog
### Added
- `Capsule2d::to_inner_rectangle`, `Capsule2d::area` and
`Capsule2d::perimeter`
---------
Co-authored-by: Joona Aalto <jondolf.dev@gmail.com>
Co-authored-by: James Liu <contact@jamessliu.com>
Co-authored-by: Alice Cecile <alice.i.cecile@gmail.com>
# Objective
- Fixes#6370
- Closes#6581
## Solution
- Added the following lints to the workspace:
- `std_instead_of_core`
- `std_instead_of_alloc`
- `alloc_instead_of_core`
- Used `cargo +nightly fmt` with [item level use
formatting](https://rust-lang.github.io/rustfmt/?version=v1.6.0&search=#Item%5C%3A)
to split all `use` statements into single items.
- Used `cargo clippy --workspace --all-targets --all-features --fix
--allow-dirty` to _attempt_ to resolve the new linting issues, and
intervened where the lint was unable to resolve the issue automatically
(usually due to needing an `extern crate alloc;` statement in a crate
root).
- Manually removed certain uses of `std` where negative feature gating
prevented `--all-features` from finding the offending uses.
- Used `cargo +nightly fmt` with [crate level use
formatting](https://rust-lang.github.io/rustfmt/?version=v1.6.0&search=#Crate%5C%3A)
to re-merge all `use` statements matching Bevy's previous styling.
- Manually fixed cases where the `fmt` tool could not re-merge `use`
statements due to conditional compilation attributes.
## Testing
- Ran CI locally
## Migration Guide
The MSRV is now 1.81. Please update to this version or higher.
## Notes
- This is a _massive_ change to try and push through, which is why I've
outlined the semi-automatic steps I used to create this PR, in case this
fails and someone else tries again in the future.
- Making this change has no impact on user code, but does mean Bevy
contributors will be warned to use `core` and `alloc` instead of `std`
where possible.
- This lint is a critical first step towards investigating `no_std`
options for Bevy.
---------
Co-authored-by: François Mockers <francois.mockers@vleue.com>
# Objective
`Capsule2d::sample_interior` uses the radius of the capsule for the
width of its rectangular section. It should be using two times the
radius for the full width!
I noticed this as I was getting incorrect results for angular inertia
approximated from a point cloud of points sampled on the capsule. This
hinted that something was wrong with the sampling.
## Solution
Multiply the radius by two to get the full width of the rectangular
section. With this, the sampling produces the correct result in my
tests.
# Objective
Closes#14474
Previously, the `libm` feature of bevy_math would just pass the same
feature flag down to glam. However, bevy_math itself had many uses of
floating-point arithmetic with unspecified precision. For example,
`f32::sin_cos` and `f32::powi` have unspecified precision, which means
that the exact details of their output are not guaranteed to be stable
across different systems and/or versions of Rust. This means that users
of bevy_math could observe slightly different behavior on different
systems if these methods were used.
The goal of this PR is to make it so that the `libm` feature flag
actually guarantees some degree of determinacy within bevy_math itself
by switching to the libm versions of these functions when the `libm`
feature is enabled.
## Solution
bevy_math now has an internal module `bevy_math::ops`, which re-exports
either the standard versions of the operations or the libm versions
depending on whether the `libm` feature is enabled. For example,
`ops::sin` compiles to `f32::sin` without the `libm` feature and to
`libm::sinf` with it.
This approach has a small shortfall, which is that `f32::powi` (integer
powers of floating point numbers) does not have an equivalent in `libm`.
On the other hand, this method is only used for squaring and cubing
numbers in bevy_math. Accordingly, this deficit is covered by the
introduction of a trait `ops::FloatPow`:
```rust
pub(crate) trait FloatPow {
fn squared(self) -> Self;
fn cubed(self) -> Self;
}
```
Next, each current usage of the unspecified-precision methods has been
replaced by its equivalent in `ops`, so that when `libm` is enabled, the
libm version is used instead. The exception, of course, is that
`.powi(2)`/`.powi(3)` have been replaced with `.squared()`/`.cubed()`.
Finally, the usage of the plain `f32` methods with unspecified precision
is now linted out of bevy_math (and hence disallowed in CI). For
example, using `f32::sin` within bevy_math produces a warning that tells
the user to use the `ops::sin` version instead.
## Testing
Ran existing tests. It would be nice to check some benchmarks on NURBS
things once #14677 merges. I'm happy to wait until then if the rest of
this PR is fine.
---
## Discussion
In the future, it might make sense to actually expose `bevy_math::ops`
as public if any downstream Bevy crates want to provide similar
determinacy guarantees. For now, it's all just `pub(crate)`.
This PR also only covers `f32`. If we find ourselves using `f64`
internally in parts of bevy_math for better robustness, we could extend
the module and lints to cover the `f64` versions easily enough.
I don't know how feasible it is, but it would also be nice if we could
standardize the bevy_math tests with the `libm` feature in CI, since
their success is currently platform-dependent (e.g. 8 of them fail on my
machine when run locally).
---------
Co-authored-by: IQuick 143 <IQuick143cz@gmail.com>
# Objective
Add random sampling for the `Annulus` primitive. This is part of ongoing
work to bring the various `bevy_math` primitives to feature parity.
## Solution
`Annulus` implements `ShapeSample`. Boundary sampling is implemented in
the obvious way, and interior sampling works exactly as in the
implementation for `Circle`, using the fact that the square of the
radius should be taken uniformly from between r^2 and R^2, where r and R
are the inner and outer radii respectively.
## Testing
I generated a bunch of random points and rendered them. Here's 1000
points on the interior of the default annulus:
<img width="1440" alt="Screenshot 2024-05-22 at 8 01 34 AM"
src="https://github.com/bevyengine/bevy/assets/2975848/19c31bb0-edba-477f-b247-2b12d854afae">
This looks kind of weird around the edges, but I verified that they're
all actually inside the annulus, so I assume it has to do with the fact
that the rendered circles have some radius.
Stolen from #12835.
# Objective
Sometimes you want to sample a whole bunch of points from a shape
instead of just one. You can write your own loop to do this, but it's
really more idiomatic to use a `rand`
[`Distribution`](https://docs.rs/rand/latest/rand/distributions/trait.Distribution.html)
with the `sample_iter` method. Distributions also support other useful
things like mapping, and they are suitable as generic items for
consumption by other APIs.
## Solution
`ShapeSample` has been given two new automatic trait methods,
`interior_dist` and `boundary_dist`. They both have similar signatures
(recall that `Output` is the output type for `ShapeSample`):
```rust
fn interior_dist(self) -> impl Distribution<Self::Output>
where Self: Sized { //... }
```
These have default implementations which are powered by wrapper structs
`InteriorOf` and `BoundaryOf` that actually implement `Distribution` —
the implementations effectively just call `ShapeSample::sample_interior`
and `ShapeSample::sample_boundary` on the contained type.
The upshot is that this allows iteration as follows:
```rust
// Get an iterator over boundary points of a rectangle:
let rectangle = Rectangle::new(1.0, 2.0);
let boundary_iter = rectangle.boundary_dist().sample_iter(rng);
// Collect a bunch of boundary points at once:
let boundary_pts: Vec<Vec2> = boundary_iter.take(1000).collect();
```
Alternatively, you can use `InteriorOf`/`BoundaryOf` explicitly to
similar effect:
```rust
let boundary_pts: Vec<Vec2> = BoundaryOf(rectangle).sample_iter(rng).take(1000).collect();
```
---
## Changelog
- Added `InteriorOf` and `BoundaryOf` distribution wrapper structs in
`bevy_math::sampling::shape_sampling`.
- Added `interior_dist` and `boundary_dist` automatic trait methods to
`ShapeSample`.
- Made `shape_sampling` module public with explanatory documentation.
---
## Discussion
### Design choices
The main point of interest here is just the choice of `impl
Distribution` instead of explicitly using `InteriorOf`/`BoundaryOf`
return types for `interior_dist` and `boundary_dist`. The reason for
this choice is that it allows future optimizations for repeated sampling
— for example, instead of just wrapping the base type,
`interior_dist`/`boundary_dist` could construct auxiliary data that is
held over between sampling operations.
# Objective
Add interior and boundary sampling for the `Tetrahedron` primitive. This
is part of ongoing work to bring the primitives to parity with each
other in terms of their capabilities.
## Solution
`Tetrahedron` implements the `ShapeSample` trait. To support this, there
is a new public method `Tetrahedron::faces` which gets the faces of a
tetrahedron as `Triangle3d`s. There are more sophisticated ideas for
getting the faces we might want to consider in the future (e.g.
adjusting according to the orientation), but this method gives the most
mathematically straightforward answer, giving the faces the orientation
induced by the tetrahedron itself.
# Objective
Augment Bevy's random sampling capabilities by providing good tools for
producing random directions and rotations.
## Solution
The `rand` crate has a natural tool for providing `Distribution`s whose
output is a type that doesn't require any additional data to sample
values — namely,
[`Standard`](https://docs.rs/rand/latest/rand/distributions/struct.Standard.html).
Here, our existing `ShapeSample` implementations have been put to good
use in providing these, resulting in patterns like the following:
```rust
// Using thread-local rng
let random_direction1: Dir3 = random();
// Using an explicit rng
let random_direction2: Dir3 = rng.gen();
// Using an explicit rng coupled explicitly with Standard
let random_directions: Vec<Dir3> = rng.sample_iter(Standard).take(5).collect();
```
Furthermore, we have introduced a trait `FromRng` which provides sugar
for `rng.gen()` that is more namespace-friendly (in this author's
opinion):
```rust
let random_direction = Dir3::from_rng(rng);
```
The types this has been implemented for are `Dir2`, `Dir3`, `Dir3A`, and
`Quat`. Notably, `Quat` uses `glam`'s implementation rather than an
in-house one, and as a result, `bevy_math`'s "rand" feature now enables
that of `glam`.
---
## Changelog
- Created `standard` submodule in `sampling` to hold implementations and
other items related to the `Standard` distribution.
- "rand" feature of `bevy_math` now enables that of `glam`.
---
## Discussion
From a quick glance at `Quat`'s distribution implementation in `glam`, I
am a bit suspicious, since it is simple and doesn't match any algorithm
that I came across in my research. I will do a little more digging as a
follow-up to this and see if it's actually uniform (maybe even using
those tools I wrote — what a thrill).
As an aside, I'd also like to say that I think
[`Distribution`](https://docs.rs/rand/latest/rand/distributions/trait.Distribution.html)
is really, really good. It integrates with distributions provided
externally (e.g. in `rand` itself and its extensions) along with doing a
good job of isolating the source of randomness, so that output can be
reliably reproduced if need be. Finally, `Distribution::sample_iter` is
quite good for ergonomically acquiring lots of random values. At one
point I found myself writing traits to describe random sampling and
essentially reinvented this one. I just think it's good, and I think
it's worth centralizing around to a significant extent.
