# Objective
- Add gizmos integration for the new `Curve` things in the math lib
## Solution
- Add the following methods
- `curve_2d(curve, sample_times, color)`
- `curve_3d(curve, sample_times, color)`
- `curve_gradient_2d(curve, sample_times_with_colors)`
- `curve_gradient_3d(curve, sample_times_with_colors)`
## Testing
- I added examples of the 2D and 3D variants of the gradient curve
gizmos to the gizmos examples.
## Showcase
### 2D
```rust
let domain = Interval::EVERYWHERE;
let curve = function_curve(domain, |t| Vec2::new(t, (t / 25.0).sin() * 100.0));
let resolution = ((time.elapsed_seconds().sin() + 1.0) * 50.0) as usize;
let times_and_colors = (0..=resolution)
.map(|n| n as f32 / resolution as f32)
.map(|t| (t - 0.5) * 600.0)
.map(|t| (t, TEAL.mix(&HOT_PINK, (t + 300.0) / 600.0)));
gizmos.curve_gradient_2d(curve, times_and_colors);
```
### 3D
```rust
let domain = Interval::EVERYWHERE;
let curve = function_curve(domain, |t| {
(Vec2::from((t * 10.0).sin_cos())).extend(t - 6.0)
});
let resolution = ((time.elapsed_seconds().sin() + 1.0) * 100.0) as usize;
let times_and_colors = (0..=resolution)
.map(|n| n as f32 / resolution as f32)
.map(|t| t * 5.0)
.map(|t| (t, TEAL.mix(&HOT_PINK, t / 5.0)));
gizmos.curve_gradient_3d(curve, times_and_colors);
```
# Objective
- `Curve<T>` was meant to be object safe, but one of the latest commits
made it not object safe.
- When trying to use `Curve<T>` as `&dyn Curve<T>` this compile error is
raised:
```
error[E0038]: the trait `curve::Curve` cannot be made into an object
--> crates/bevy_math/src/curve/mod.rs:1025:20
note: for a trait to be "object safe" it needs to allow building a vtable to allow the call to be resolvable dynamically; for more information visit <https://doc.rust-lang.org/reference/items/traits.html#object-safety>
--> crates/bevy_math/src/curve/mod.rs:60:8
|
23 | pub trait Curve<T> {
| ----- this trait cannot be made into an object...
...
60 | fn sample_iter(&self, iter: impl IntoIterator<Item = f32>) -> impl Iterator<Item = Option<T>> {
| ^^^^^^^^^^^ ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ ...because method `sample_iter` references an `impl Trait` type in its return type
| |
| ...because method `sample_iter` has generic type parameters
...
```
## Solution
- Making `Curve<T>` object safe again by adding `Self: Sized` to newly
added methods.
## Testing
- Added new test that ensures the `Curve<T>` trait can be made into an
objet.
# Objective
This is a value that is and will be used as a domain of curves pretty
often. By adding it as a dedicated constant we can get rid of some
`unwraps` and function calls.
## Solution
added `Interval::UNIT`
## Testing
I replaced all occurrences of `interval(0.0, 1.0).unwrap()` with the new
`Interval::UNIT` constant in tests and doc tests.
# Objective
Citing @mweatherley
> As mentioned before, a multi-sampling function in the API which takes
an iterator is probably something we want (e.g. `sample_iter(iter: impl
IntoIterator<Item = f32>) -> impl IntoIterator<Item = T> { //... }`, but
there are some design choices to be made on the details (e.g. does this
filter out points that aren't in the domain? does it do sorting? etc.)
## Solution
I think the most flexible solution for end users is to expose all the
`sample_...` functions with an `iter` equivalent, so we'll have
- `sample_iter`
- `sample_iter_unchecked`
- `sample_iter_clamped`
Answering some questions from the original idea:
> does this filter out points that aren't in the domain?
With the methods the user has the choice to just sample or if they want
to filter out invalid types us `sample_iter` and then apply `filter_map`
to the iterator returned themselves.
> does it do sorting?
I think it's the same thing. If the user wants it, they need to do it
themselves by either collecting and sorting a `Vec` or using
`itertools`. I think there is a legit use case for "please sample me
this collection of points that are unordered" and we would destroy it if
we take away to much agency from users by sorting for them
## Testing
- Added a test which covers all three methods
# Objective
`arc_2d` wasn't actually doing what the docs were saying. The arc wasn't
offset by what was previously `direction_angle` but by `direction_angle
- arc_angle / 2.0`. This meant that the arcs center was laying on the
`Vec2::Y` axis and then it was offset. This was probably done to fit the
behavior of the `Arc2D` primitive. I would argue that this isn't
desirable for the plain `arc_2d` gizmo method since
- a) the docs get longer to explain the weird centering
- b) the mental model the user has to know gets bigger with more
implicit assumptions
given the code
```rust
my_gizmos.arc_2d(Vec2::ZERO, 0.0, FRAC_PI_2, 75.0, ORANGE_RED);
```
we get
where after the fix with
```rust
my_gizmos.arc_2d(Isometry2d::IDENTITY, FRAC_PI_2, 75.0, ORANGE_RED);
```
we get
To get the same result with the previous implementation you would have
to randomly add `arc_angle / 2.0` to the `direction_angle`.
```rust
my_gizmos.arc_2d(Vec2::ZERO, FRAC_PI_4, FRAC_PI_2, 75.0, ORANGE_RED);
```
This makes constructing similar helping functions as they already exist
in 3D like
- `long_arc_2d_between`
- `short_arc_2d_between`
much harder.
## Solution
- Make the arc really start at `Vec2::Y * radius` in counter-clockwise
direction + offset by an angle as the docs state it
- Use `Isometry2d` instead of `position : Vec2` and `direction_angle :
f32` to reduce the chance of messing up rotation/translation
- Adjust the docs for the changes above
- Adjust the gizmo rendering of some primitives
## Testing
- check `2d_gizmos.rs` and `render_primitives.rs` examples
## Migration Guide
- users have to adjust their usages of `arc_2d`:
- before:
```rust
arc_2d(
pos,
angle,
arc_angle,
radius,
color
)
```
- after:
```rust
arc_2d(
// this `+ arc_angle * 0.5` quirk is only if you want to preserve the
previous behavior
// with the new API.
// feel free to try to fix this though since your current calls to this
function most likely
// involve some computations to counter-act that quirk in the first
place
Isometry2d::new(pos, Rot2::radians(angle + arc_angle * 0.5),
arc_angle,
radius,
color
)
```
# Objective
- Fixes#14796
## Solution
- Copy docs for wrapper methods, make sure they are consistent with the
original docs except for the section on precision.
# Objective
Fixes#14782
## Solution
Enable the lint and fix all upcoming hints (`--fix`). Also tried to
figure out the false-positive (see review comment). Maybe split this PR
up into multiple parts where only the last one enables the lint, so some
can already be merged resulting in less many files touched / less
potential for merge conflicts?
Currently, there are some cases where it might be easier to read the
code with the qualifier, so perhaps remove the import of it and adapt
its cases? In the current stage it's just a plain adoption of the
suggestions in order to have a base to discuss.
## Testing
`cargo clippy` and `cargo run -p ci` are happy.
# Objective
Some algorithms don't really work well or are not efficient in 3D space.
When we know we have points on an `InfinitePlane3d` it would be helpful
to have some utility methods to reversibly transform points on the plane
to 2D space to apply some algorithms there.
## Solution
This PR adds a few of methods to project 3D points on a plane to 2D
points and inject them back. Additionally there are some other small
common helper methods.
## Testing
- added some tests that cover the new methods
---------
Co-authored-by: Matty <weatherleymatthew@gmail.com>
# Objective
Finish what we started in #14630. The Curve RFC is
[here](https://github.com/bevyengine/rfcs/blob/main/rfcs/80-curve-trait.md).
## Solution
This contains the rest of the library from my branch. The main things
added here are:
- Bulk sampling / resampling methods on `Curve` itself
- Data structures supporting the above
- The `cores` submodule that those data structures use to encapsulate
sample interpolation
The weirdest thing in here is probably `ChunkedUnevenCore` in `cores`,
which is not used by anything in the Curve library itself but which is
required for efficient storage of glTF animation curves. (See #13105.)
We can move it into a different PR if we want to; I don't have strong
feelings either way.
## Testing
New tests related to resampling are included. As I write this, I realize
we could use some tests in `cores` itself, so I will add some on this
branch before too long.
---------
Co-authored-by: Alice Cecile <alice.i.cecile@gmail.com>
Co-authored-by: Robert Walter <26892280+RobWalt@users.noreply.github.com>
# 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
This PR implements part of the [Curve
RFC](https://github.com/bevyengine/rfcs/blob/main/rfcs/80-curve-trait.md).
See that document for motivation, objectives, etc.
## Solution
For purposes of reviewability, this PR excludes the entire part of the
RFC related to taking multiple samples, resampling, and interpolation
generally. (This means the entire `cores` submodule is also excluded.)
On the other hand, the entire `Interval` type and all of the functional
`Curve` adaptors are included.
## Testing
Test modules are included and can be run locally (but they are also
included in CI).
---------
Co-authored-by: Alice Cecile <alice.i.cecile@gmail.com>
Basically it's https://github.com/bevyengine/bevy/pull/13792 with the
bumped versions of `encase` and `hexasphere`.
---------
Co-authored-by: Robert Swain <robert.swain@gmail.com>
Co-authored-by: Alice Cecile <alice.i.cecile@gmail.com>
# Objective
Bevy's direction types have `new` and `new_unchecked` constructors, but
no unchecked variant for the `Dir2::from_xy` and `Dir3::from_xyz`
methods.
For me, this has several times lead to constructing directions like
this, in cases where the components of the direction are already known
to be normalized:
```rust
let normal = Dir2::new_unchecked(Vec2::new(-ray.direction.x.signum(), 0.0));
```
```rust
segment.direction =
Dir2::new_unchecked(Vec2::new(-segment.direction.x, segment.direction.y));
```
For consistency and ergonomics, it would be nice to have unchecked
variants of `Dir2::from_xy` and `Dir3::from_xyz`:
```rust
let normal = Dir2::from_xy_unchecked(-ray.direction.x.signum(), 0.0);
```
```rust
segment.direction = Dir2::from_xy_unchecked(-segment.direction.x, segment.direction.y);
```
## Solution
Add `Dir2::from_xy_unchecked` and `Dir3::from_xyz_unchecked`.
# Objective
Previously, this area of bevy_math used raw translation and rotations to
encode isometries, which did not exist earlier. The goal of this PR is
to make the codebase of bevy_math more harmonious by using actual
isometries (`Isometry2d`/`Isometry3d`) in these places instead — this
will hopefully make the interfaces more digestible for end-users, in
addition to facilitating conversions.
For instance, together with the addition of #14478, this means that a
bounding box for a collider with an isometric `Transform` can be
computed as
```rust
collider.aabb_3d(collider_transform.to_isometry())
```
instead of using manual destructuring.
## Solution
- The traits `Bounded2d` and `Bounded3d` now use `Isometry2d` and
`Isometry3d` (respectively) instead of `translation` and `rotation`
parameters; e.g.:
```rust
/// A trait with methods that return 3D bounding volumes for a shape.
pub trait Bounded3d {
/// Get an axis-aligned bounding box for the shape translated and
rotated by the given isometry.
fn aabb_3d(&self, isometry: Isometry3d) -> Aabb3d;
/// Get a bounding sphere for the shape translated and rotated by the
given isometry.
fn bounding_sphere(&self, isometry: Isometry3d) -> BoundingSphere;
}
```
- Similarly, the `from_point_cloud` constructors for axis-aligned
bounding boxes and bounding circles/spheres now take isometries instead
of separate `translation` and `rotation`; e.g.:
```rust
/// Computes the smallest [`Aabb3d`] containing the given set of points,
/// transformed by the rotation and translation of the given isometry.
///
/// # Panics
///
/// Panics if the given set of points is empty.
#[inline(always)]
pub fn from_point_cloud(
isometry: Isometry3d,
points: impl Iterator<Item = impl Into<Vec3A>>,
) -> Aabb3d { //... }
```
This has a couple additional results:
1. The end-user no longer interacts directly with `Into<Vec3A>` or
`Into<Rot2>` parameters; these conversions all happen earlier now,
inside the isometry types.
2. Similarly, almost all intermediate `Vec3 -> Vec3A` conversions have
been eliminated from the `Bounded3d` implementations for primitives.
This probably has some performance benefit, but I have not measured it
as of now.
## Testing
Existing unit tests help ensure that nothing has been broken in the
refactor.
---
## Migration Guide
The `Bounded2d` and `Bounded3d` traits now take `Isometry2d` and
`Isometry3d` parameters (respectively) instead of separate translation
and rotation arguments. Existing calls to `aabb_2d`, `bounding_circle`,
`aabb_3d`, and `bounding_sphere` will have to be changed to use
isometries instead. A straightforward conversion is to refactor just by
calling `Isometry2d/3d::new`, as follows:
```rust
// Old:
let aabb = my_shape.aabb_2d(my_translation, my_rotation);
// New:
let aabb = my_shape.aabb_2d(Isometry2d::new(my_translation, my_rotation));
```
However, if the old translation and rotation are 3d
translation/rotations originating from a `Transform` or
`GlobalTransform`, then `to_isometry` may be used instead. For example:
```rust
// Old:
let bounding_sphere = my_shape.bounding_sphere(shape_transform.translation, shape_transform.rotation);
// New:
let bounding_sphere = my_shape.bounding_sphere(shape_transform.to_isometry());
```
This discussion also applies to the `from_point_cloud` construction
method of `Aabb2d`/`BoundingCircle`/`Aabb3d`/`BoundingSphere`, which has
similarly been altered to use isometries.
# Objective
Previously, our cubic spline constructors would produce
`CubicCurve`/`RationalCurve` output with no data when they themselves
didn't hold enough control points to produce a well-formed curve.
Attempting to sample the resulting empty "curves" (e.g. by calling
`CubicCurve::position`) would crash the program (😓).
The objectives of this PR are:
1. Ensure that the curve output of `bevy_math`'s spline constructions
are never invalid as data.
2. Provide a type-level guarantee that `CubicCurve` and `RationalCurve`
actually function as curves.
## Solution
This has a few pieces. Firstly, the curve generator traits
`CubicGenerator`, `CyclicCubicGenerator`, and `RationalGenerator` are
now fallible — they have associated error types, and the
curve-generation functions are allowed to fail:
```rust
/// Implement this on cubic splines that can generate a cubic curve from their spline parameters.
pub trait CubicGenerator<P: VectorSpace> {
/// An error type indicating why construction might fail.
type Error;
/// Build a [`CubicCurve`] by computing the interpolation coefficients for each curve segment.
fn to_curve(&self) -> Result<CubicCurve<P>, Self::Error>;
}
```
All existing spline constructions use this together with errors that
indicate when they didn't have the right control data and provide curves
which have at least one segment whenever they return an `Ok` variant.
Next, `CubicCurve` and `RationalCurve` have been blessed with a
guarantee that their internal array of segments (`segments`) is never
empty. In particular, this field is no longer public, so that invalid
curves cannot be built using struct instantiation syntax. To compensate
for this shortfall for users (in particular library authors who might
want to implement their own generators), there is a new method
`from_segments` on these for constructing a curve from a list of
segments, failing if the list is empty:
```rust
/// Create a new curve from a collection of segments. If the collection of segments is empty,
/// a curve cannot be built and `None` will be returned instead.
pub fn from_segments(segments: impl Into<Vec<CubicSegment<P>>>) -> Option<Self> { //... }
```
All existing methods on `CyclicCurve` and `CubicCurve` maintain the
invariant, so the direct construction of invalid values by users is
impossible.
## Testing
Run unit tests from `bevy_math::cubic_splines`. Additionally, run the
`cubic_splines` example and try to get it to crash using small numbers
of control points: it uses the fallible constructors directly, so if
invalid data is ever constructed, it is basically guaranteed to crash.
---
## Migration Guide
The `to_curve` method on Bevy's cubic splines is now fallible (returning
a `Result`), meaning that any existing calls will need to be updated by
handling the possibility of an error variant.
Similarly, any custom implementation of `CubicGenerator` or
`RationalGenerator` will need to be amended to include an `Error` type
and be made fallible itself.
Finally, the fields of `CubicCurve` and `RationalCurve` are now private,
so any direct constructions of these structs from segments will need to
be replaced with the new `CubicCurve::from_segments` and
`RationalCurve::from_segments` methods.
---
## Design
The main thing to justify here is the choice for the curve internals to
remain the same. After all, if they were able to cause crashes in the
first place, it's worth wondering why safeguards weren't put in place on
the types themselves to prevent that.
My view on this is that the problem was really that the internals of
these methods implicitly relied on the assumption that the value they
were operating on was *actually a curve*, when this wasn't actually
guaranteed. Now, it's possible to make a bunch of small changes inside
the curve struct methods to account for that, but I think that's worse
than just guaranteeing that the data is valid upstream — sampling is
about as hot a code path as we're going to get in this area, and hitting
an additional branch every time it happens just to check that the struct
contains valid data is probably a waste of resources.
Another way of phrasing this is that even if we're only interested in
solving the crashes, the curve's validity needs to be checked at some
point, and it's almost certainly better to do this once at the point of
construction than every time the curve is sampled.
In cases where the control data is supplied dynamically, users would
already have to deal with empty curve outputs basically not working.
Anecdotally, I ran into this while writing the `cubic_splines` example,
and I think the diff illustrates the improvement pretty nicely — the
code no longer has to anticipate whether the output will be good or not;
it just has to handle the `Result`.
The cost of all this, of course, is that we have to guarantee that the
new invariant is actually maintained whenever we extend the API.
However, for the most part, I don't expect users to want to do much
surgery on the internals of their curves anyway.
# Objective
- Fix issue #2611
## Solution
- Add `--generate-link-to-definition` to all the `rustdoc-args` arrays
in the `Cargo.toml`s (for docs.rs)
- Add `--generate-link-to-definition` to the `RUSTDOCFLAGS` environment
variable in the docs workflow (for dev-docs.bevyengine.org)
- Document all the workspace crates in the docs workflow (needed because
otherwise only the source code of the `bevy` package will be included,
making the argument useless)
- I think this also fixes#3662, since it fixes the bug on
dev-docs.bevyengine.org, while on docs.rs it has been fixed for a while
on their side.
---
## Changelog
- The source code viewer on docs.rs now includes links to the
definitions.
# Objective
Fill a gap in the functionality of our curve constructions by allowing
users to easily build cyclic curves from control data.
## Solution
Here I opted for something lightweight and discoverable. There is a new
`CyclicCubicGenerator` trait with a method `to_curve_cyclic` which uses
splines' control data to create curves that are cyclic. For now, its
signature is exactly like that of `CubicGenerator` — `to_curve_cyclic`
just yields a `CubicCurve`:
```rust
/// Implement this on cubic splines that can generate a cyclic cubic curve from their spline parameters.
///
/// This makes sense only when the control data can be interpreted cyclically.
pub trait CyclicCubicGenerator<P: VectorSpace> {
/// Build a cyclic [`CubicCurve`] by computing the interpolation coefficients for each curve segment.
fn to_curve_cyclic(&self) -> CubicCurve<P>;
}
```
This trait has been implemented for `CubicHermite`,
`CubicCardinalSpline`, `CubicBSpline`, and `LinearSpline`:
<img width="753" alt="Screenshot 2024-07-01 at 8 58 27 PM"
src="https://github.com/bevyengine/bevy/assets/2975848/69ae0802-3b78-4fb9-b73a-6f842cf3b33c">
<img width="628" alt="Screenshot 2024-07-01 at 9 00 14 PM"
src="https://github.com/bevyengine/bevy/assets/2975848/2992175a-a96c-40fc-b1a1-5206c3572cde">
<img width="606" alt="Screenshot 2024-07-01 at 8 59 36 PM"
src="https://github.com/bevyengine/bevy/assets/2975848/9e99eb3a-dbe6-42da-886c-3d3e00410d03">
<img width="603" alt="Screenshot 2024-07-01 at 8 59 01 PM"
src="https://github.com/bevyengine/bevy/assets/2975848/d037bc0c-396a-43af-ab5c-fad9a29417ef">
(Each type pictured respectively with the control points rendered as
green spheres; tangents not pictured in the case of the Hermite spline.)
These curves are all parametrized so that the output of `to_curve` and
the output of `to_curve_cyclic` are similar. For instance, in
`CubicCardinalSpline`, the first output segment is a curve segment
joining the first and second control points in each, although it is
constructed differently. In the other cases, the segments from
`to_curve` are a subset of those in `to_curve_cyclic`, with the new
segments appearing at the end.
## Testing
I rendered cyclic splines from control data and made sure they looked
reasonable. Existing tests are intact for splines where previous code
was modified. (Note that the coefficient computation for cyclic spline
segments is almost verbatim identical to that of their non-cyclic
counterparts.)
The Bezier benchmarks also look fine.
---
## Changelog
- Added `CyclicCubicGenerator` trait to `bevy_math::cubic_splines` for
creating cyclic curves from control data.
- Implemented `CyclicCubicGenerator` for `CubicHermite`,
`CubicCardinalSpline`, `CubicBSpline`, and `LinearSpline`.
- `bevy_math` now depends on `itertools`.
---
## Discussion
### Design decisions
The biggest thing here is just the approach taken in the first place:
namely, the cyclic constructions use new methods on the same old
structs. This choice was made to reduce friction and increase
discoverability but also because creating new ones just seemed
unnecessary: the underlying data would have been the same, so creating
something like "`CyclicCubicBSpline`" whose internally-held control data
is regarded as cyclic in nature doesn't really accomplish much — the end
result for the user is basically the same either way.
Similarly, I don't presently see a pressing need for `to_curve_cyclic`
to output something other than a `CubicCurve`, although changing this in
the future may be useful. See below.
A notable omission here is that `CyclicCubicGenerator` is not
implemented for `CubicBezier`. This is not a gap waiting to be filled —
`CubicBezier` just doesn't have enough data to join its start with its
end without just making up the requisite control points wholesale. In
all the cases where `CyclicCubicGenerator` has been implemented here,
the fashion in which the ends are connected is quite natural and follows
the semantics of the associated spline construction.
### Future direction
There are two main things here:
1. We should investigate whether we should do something similar for
NURBS. I just don't know that much about NURBS at the moment, so I
regarded this as out of scope for the PR.
2. We may eventually want to change the output type of
`CyclicCubicGenerator::to_curve_cyclic` to a type which reifies the
cyclic nature of the curve output. This wasn't done in this PR because
I'm unsure how much value a type-level guarantee of cyclicity actually
has, but if some useful features make sense only in the case of cyclic
curves, this might be worth pursuing.
Reference to #14299.
# Objective
- Ensuring consistent practice of instantiating 3D primitive shapes in
Bevy.
## Solution
- Add `new` method, containing `radius` and `height` arguments, to Cone
3D primitive shape.
## Testing
- Instantiated cone using same values (radius is `2.` and height is
`5.`), using the current method and the added `new` method.
- Basic setup of Bevy Default Plugins and `3DCameraBundle`.
---
## Showcase
<details>
<summary>Click to view showcase</summary>
```rust
use bevy::prelude::*;
fn main() {
App::new()
.add_plugins(DefaultPlugins)
.add_systems(Startup, setup)
.run();
}
fn setup(
mut commands: Commands,
mut meshes: ResMut<Assets<Mesh>>,
mut materials: ResMut<Assets<StandardMaterial>>,
) {
let new_cone = meshes.add(Cone::new(2., 5.));
commands.spawn(PbrBundle {
mesh: new_cone,
..default()
});
let old_cone = meshes.add(Cone {
radius: 2.,
height: 5.,
});
commands.spawn(PbrBundle {
mesh: old_cone,
material: materials.add(Color::WHITE),
transform: Transform::from_xyz(10., 0., 0.),
..default()
});
commands.spawn(Camera3dBundle {
transform: Transform::from_xyz(20., 20., 20.).looking_at(Vec3::ZERO, Dir3::Y),
..default()
});
}
```
</details>
- Pink Cone is created using the `new` method.
- Black Cone is created using the existing method.
## Migration Guide
- Addition of `new` method to the 3D primitive Cone struct.
# Objective
`Annulus` is missing `Bounded2d` even though the implementation is
trivial.
## Solution
Implement `Bounded2d` for `Annulus`.
## Testing
There is a basic test to verify that the produced bounding volumes are
correct.
# Objective
Fixes#14308.
#14269 added the `Isometry2d` and `Isometry3d` types, but they don't
have usage examples or much documentation on what the types actually
represent or what they may be useful for.
In addition, their module is public and the types are not re-exported at
the crate root, unlike all the other core math types like Glam's types,
direction types, and `Rot2`.
## Solution
Improve the documentation of `Isometry2d` and `Isometry3d`, explaining
what they represent and can be useful for, along with doc examples on
common high-level usage. I also made the way the types are exported
consistent with other core math types.
This does add some duplication, but I personally think having good docs
for this is valuable, and people are also less likely to look at the
module-level docs than type-level docs.
# Objective
The isometry types added in #14269 support transforming other isometries
and points, as well as computing the inverse of an isometry using
`inverse`.
However, transformations like `iso1.inverse() * iso2` and `iso.inverse()
* point` can be optimized for single-shot cases using custom methods
that avoid an extra rotation operation.
## Solution
Add `inverse_mul` and `inverse_transform_point` for `Isometry2d` and
`Isometry3d`. Note that these methods are only faster when the isometry
can't be reused for multiple transformations.
## Testing
All of the methods have a test, similarly to the existing transformation
operations.
# Objective
Creating isometry types with just a translation is a bit more verbose
than it needs to be for cases where you don't have an existing vector to
pass in.
```rust
let iso = Isometry3d::from_translation(Vec3::new(2.0, 1.0, -1.0));
```
This could be made more ergonomic with a method similar to
`Dir2::from_xy`, `Dir3::from_xyz`, and `Transform::from_xyz`:
```rust
let iso = Isometry3d::from_xyz(2.0, 1.0, -1.0);
```
## Solution
Add `Isometry2d::from_xy` and `Isometry3d::from_xyz`.
# Objective
Introduce isometry types for describing relative and absolute position
in mathematical contexts.
## Solution
For the time being, this is a very minimal implementation. This
implements the following faculties for two- and three-dimensional
isometry types:
- Identity transformations
- Creation from translations and/or rotations
- Inverses
- Multiplication (composition) of isometries with each other
- Application of isometries to points (as vectors)
- Conversion of isometries to affine transformations
There is obviously a lot more that could be added, so I erred on the
side of adding things that I knew would be useful, with the idea of
expanding this in the near future as needed.
(I also fixed some random doc problems in `bevy_math`.)
---
## Design
One point of interest here is the matter of if/when to use aligned
types. In the implementation of 3d isometries, I used `Vec3A` rather
than `Vec3` because it has no impact on size/alignment, but I'm still
not sure about that decision (although it is easily changed).
For 2d isometries — which are encoded by four floats — the idea of
shoving them into a single 128-bit buffer (`__m128` or whatever) sounds
kind of enticing, but it's more involved and would involve writing
unsafe code, so I didn't do that for now.
## Future work
- Expand the API to include shortcuts like `inverse_mul` and
`inverse_transform` for efficiency reasons.
- Include more convenience constructors and methods (e.g. `from_xy`,
`from_xyz`).
- Refactor `bevy_math::bounding` to use the isometry types.
- Add conversions to/from isometries for `Transform`/`GlobalTransform`
in `bevy_transform`.
# Objective
- Bevy currently has lot of invalid intra-doc links, let's fix them!
- Also make CI test them, to avoid future regressions.
- Helps with #1983 (but doesn't fix it, as there could still be explicit
links to docs.rs that are broken)
## Solution
- Make `cargo r -p ci -- doc-check` check fail on warnings (could also
be changed to just some specific lints)
- Manually fix all the warnings (note that in some cases it was unclear
to me what the fix should have been, I'll try to highlight them in a
self-review)
# Objective
With an unlucky denormalised quaternion (or just a regular very
denormalised quaternion), it's possible to obtain NaN values for AABB's
in shapes which rely on an AABB for a disk.
## Solution
Add an additional `.max(Vec3::ZERO)` clamp to get rid of negative values
arising due to numerical errors.
Fixup some unnecessary calculations and improve variable names in
relevant code, aiming for consistency.
## Discussion
These two (nontrivial) lines of code are repeated at least 5 times,
maybe they could be their own method.
Bump version after release
This PR has been auto-generated
Co-authored-by: Bevy Auto Releaser <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: François Mockers <mockersf@gmail.com>
# Objective
Allow random sampling from the surfaces of triangle meshes.
## Solution
This has two parts.
Firstly, rendering meshes can now yield their collections of triangles
through a method `Mesh::triangles`. This has signature
```rust
pub fn triangles(&self) -> Result<Vec<Triangle3d>, MeshTrianglesError> { //... }
```
and fails in a variety of cases — the most obvious of these is that the
mesh must have either the `TriangleList` or `TriangleStrip` topology,
and the others correspond to malformed vertex or triangle-index data.
With that in hand, we have the second piece, which is
`UniformMeshSampler`, which is a `Vec3`-valued
[distribution](https://docs.rs/rand/latest/rand/distributions/trait.Distribution.html)
that samples uniformly from collections of triangles. It caches the
triangles' distribution of areas so that after its initial setup,
sampling is allocation-free. It is constructed via
`UniformMeshSampler::try_new`, which looks like this:
```rust
pub fn try_new<T: Into<Vec<Triangle3d>>>(triangles: T) -> Result<Self, ZeroAreaMeshError> { //... }
```
It fails if the collection of triangles has zero area.
The sum of these parts means that you can sample random points from a
mesh as follows:
```rust
let triangles = my_mesh.triangles().unwrap();
let mut rng = StdRng::seed_from_u64(8765309);
let distribution = UniformMeshSampler::try_new(triangles).unwrap();
// 10000 random points from the surface of my_mesh:
let sample_points: Vec<Vec3> = distribution.sample_iter(&mut rng).take(10000).collect();
```
## Testing
Tested by instantiating meshes and sampling as demonstrated above.
---
## Changelog
- Added `Mesh::triangles` method to get a collection of triangles from a
mesh.
- Added `UniformMeshSampler` to `bevy_math::sampling`. This is a
distribution which allows random sampling over collections of triangles
(such as those provided through meshes).
---
## Discussion
### Design decisions
The main thing here was making sure to have a good separation between
the parts of this in `bevy_render` and in `bevy_math`. Getting the
triangles from a mesh seems like a reasonable step after adding
`Triangle3d` to `bevy_math`, so I decided to make all of the random
sampling operate at that level, with the fallible conversion to
triangles doing most of the work.
Notably, the sampler could be called something else that reflects that
its input is a collection of triangles, but if/when we add other kinds
of meshes to `bevy_math` (e.g. half-edge meshes), the fact that
`try_new` takes an `impl Into<Vec<Triangle3d>>` means that those meshes
just need to satisfy that trait bound in order to work immediately with
this sampling functionality. In that case, the result would just be
something like this:
```rust
let dist = UniformMeshSampler::try_new(mesh).unwrap();
```
I think this highlights that most of the friction is really just from
extracting data from `Mesh`.
It's maybe worth mentioning also that "collection of triangles"
(`Vec<Triangle3d>`) sits downstream of any other kind of triangle mesh,
since the topology connecting the triangles has been effectively erased,
which makes an `Into<Vec<Triangle3d>>` trait bound seem all the more
natural to me.
---------
Co-authored-by: Alice Cecile <alice.i.cecile@gmail.com>
This is an attempt to address issue #13725, which was about the
geometric primitives in the bevy_math crate lacking some detail in the
docs.
# Objective
Fixes#13725
## Solution
Added details to the docstrings. Mostly this consisted of specifying
that the primitives are centered on the origin, or describing how
they're defined (e.g., a circle is the set of all points some distance
from the origin).
## Testing
No testing, since the only changes were to docs.
# Objective
- Primitives should not use poorly defined types like `usize`,
especially since they are serializable
## Solution
- Use `u32` instead of `usize`
- The generic array types do not need to be changed because this size is
not actually stored or serialized anywhere
---
## Migration Guide
- `RegularPolygon` now uses `u32` instead of `usize` for the number of
sides
i based the design on @mgi388 in the discussion about the issue.
i added the illustration in such a way that it shows up when you hover
your mouse over the type, i hope this is what was meant by the issue
no unit tests were added bc obviously
Fixes#13664
# Objective
Partially address #13408
Rework of #13613
Unify the very nice forms of interpolation specifically present in
`bevy_math` under a shared trait upon which further behavior can be
based.
The ideas in this PR were prompted by [Lerp smoothing is broken by Freya
Holmer](https://www.youtube.com/watch?v=LSNQuFEDOyQ).
## Solution
There is a new trait `StableInterpolate` in `bevy_math::common_traits`
which enshrines a quite-specific notion of interpolation with a lot of
guarantees:
```rust
/// A type with a natural interpolation that provides strong subdivision guarantees.
///
/// Although the only required method is `interpolate_stable`, many things are expected of it:
///
/// 1. The notion of interpolation should follow naturally from the semantics of the type, so
/// that inferring the interpolation mode from the type alone is sensible.
///
/// 2. The interpolation recovers something equivalent to the starting value at `t = 0.0`
/// and likewise with the ending value at `t = 1.0`.
///
/// 3. Importantly, the interpolation must be *subdivision-stable*: for any interpolation curve
/// between two (unnamed) values and any parameter-value pairs `(t0, p)` and `(t1, q)`, the
/// interpolation curve between `p` and `q` must be the *linear* reparametrization of the original
/// interpolation curve restricted to the interval `[t0, t1]`.
///
/// The last of these conditions is very strong and indicates something like constant speed. It
/// is called "subdivision stability" because it guarantees that breaking up the interpolation
/// into segments and joining them back together has no effect.
///
/// Here is a diagram depicting it:
/// ```text
/// top curve = u.interpolate_stable(v, t)
///
/// t0 => p t1 => q
/// |-------------|---------|-------------|
/// 0 => u / \ 1 => v
/// / \
/// / \
/// / linear \
/// / reparametrization \
/// / t = t0 * (1 - s) + t1 * s \
/// / \
/// |-------------------------------------|
/// 0 => p 1 => q
///
/// bottom curve = p.interpolate_stable(q, s)
/// ```
///
/// Note that some common forms of interpolation do not satisfy this criterion. For example,
/// [`Quat::lerp`] and [`Rot2::nlerp`] are not subdivision-stable.
///
/// Furthermore, this is not to be used as a general trait for abstract interpolation.
/// Consumers rely on the strong guarantees in order for behavior based on this trait to be
/// well-behaved.
///
/// [`Quat::lerp`]: crate::Quat::lerp
/// [`Rot2::nlerp`]: crate::Rot2::nlerp
pub trait StableInterpolate: Clone {
/// Interpolate between this value and the `other` given value using the parameter `t`.
/// Note that the parameter `t` is not necessarily clamped to lie between `0` and `1`.
/// When `t = 0.0`, `self` is recovered, while `other` is recovered at `t = 1.0`,
/// with intermediate values lying between the two.
fn interpolate_stable(&self, other: &Self, t: f32) -> Self;
}
```
This trait has a blanket implementation over `NormedVectorSpace`, where
`lerp` is used, along with implementations for `Rot2`, `Quat`, and the
direction types using variants of `slerp`. Other areas may choose to
implement this trait in order to hook into its functionality, but the
stringent requirements must actually be met.
This trait bears no direct relationship with `bevy_animation`'s
`Animatable` trait, although they may choose to use `interpolate_stable`
in their trait implementations if they wish, as both traits involve
type-inferred interpolations of the same kind. `StableInterpolate` is
not a supertrait of `Animatable` for a couple reasons:
1. Notions of interpolation in animation are generally going to be much
more general than those allowed under these constraints.
2. Laying out these generalized interpolation notions is the domain of
`bevy_animation` rather than of `bevy_math`. (Consider also that
inferring interpolation from types is not universally desirable.)
Similarly, this is not implemented on `bevy_color`'s color types,
although their current mixing behavior does meet the conditions of the
trait.
As an aside, the subdivision-stability condition is of interest
specifically for the [Curve
RFC](https://github.com/bevyengine/rfcs/pull/80), where it also ensures
a kind of stability for subsampling.
Importantly, this trait ensures that the "smooth following" behavior
defined in this PR behaves predictably:
```rust
/// Smoothly nudge this value towards the `target` at a given decay rate. The `decay_rate`
/// parameter controls how fast the distance between `self` and `target` decays relative to
/// the units of `delta`; the intended usage is for `decay_rate` to generally remain fixed,
/// while `delta` is something like `delta_time` from an updating system. This produces a
/// smooth following of the target that is independent of framerate.
///
/// More specifically, when this is called repeatedly, the result is that the distance between
/// `self` and a fixed `target` attenuates exponentially, with the rate of this exponential
/// decay given by `decay_rate`.
///
/// For example, at `decay_rate = 0.0`, this has no effect.
/// At `decay_rate = f32::INFINITY`, `self` immediately snaps to `target`.
/// In general, higher rates mean that `self` moves more quickly towards `target`.
///
/// # Example
/// ```
/// # use bevy_math::{Vec3, StableInterpolate};
/// # let delta_time: f32 = 1.0 / 60.0;
/// let mut object_position: Vec3 = Vec3::ZERO;
/// let target_position: Vec3 = Vec3::new(2.0, 3.0, 5.0);
/// // Decay rate of ln(10) => after 1 second, remaining distance is 1/10th
/// let decay_rate = f32::ln(10.0);
/// // Calling this repeatedly will move `object_position` towards `target_position`:
/// object_position.smooth_nudge(&target_position, decay_rate, delta_time);
/// ```
fn smooth_nudge(&mut self, target: &Self, decay_rate: f32, delta: f32) {
self.interpolate_stable_assign(target, 1.0 - f32::exp(-decay_rate * delta));
}
```
As the documentation indicates, the intention is for this to be called
in game update systems, and `delta` would be something like
`Time::delta_seconds` in Bevy, allowing positions, orientations, and so
on to smoothly follow a target. A new example, `smooth_follow`,
demonstrates a basic implementation of this, with a sphere smoothly
following a sharply moving target:
https://github.com/bevyengine/bevy/assets/2975848/7124b28b-6361-47e3-acf7-d1578ebd0347
## Testing
Tested by running the example with various parameters.
# Objective
- `Rotation2d` is a very long name for a commonly used type.
## Solution
- Rename it to `Rot2` to match `glam`'s naming convention (e.g. `Vec2`)
I ran a poll, and `Rot2` was the favorite of the candidate names.
This is not actually a breaking change, since `Rotation2d` has not been
shipped yet.
---------
Co-authored-by: Alice Cecile <alice.i.cecil@gmail.com>
# Objective
- Due to coherency, it was previously not possible to implement
`Bounded3d` for `Extrusion<MyCustomPrimitive>`. This PR fixes that.
## Solution
- Added a new trait `BoundedExtrusion: Primitive2d + Bounded2d` which
provides functions for bounding boxes and spheres of extrusions of 2D
primitives.
- Changed all implementations of `Bounded3d for Extrusion<T>` to
`BoundedExtrusion for T`
- Implemented `Bounded3d for Extrusion<T: BoundedExtrusion>`
- Removed the `extrusion_bounding_box` and `extrusion_bounding_sphere`
functions and used them as default implementations in `BoundedExtrusion`
## Testing
- This PR does not change any implementations
---------
Co-authored-by: Lynn Büttgenbach <62256001+solis-lumine-vorago@users.noreply.github.com>
Co-authored-by: Matty <weatherleymatthew@gmail.com>
# Objective
Fill the gap in this functionality by implementing it for `Rotation2d`.
We have this already for `Quat` in addition to the direction types.
## Solution
`bevy_math::sampling` now contains an implementation of
`Distribution<Rotation2d>` for `Standard`, along with the associated
convenience implementation `Rotation2d: FromRng`, which allows syntax
like this for creating a random rotation:
```rust
// With `FromRng`:
let rotation = Rotation2d::from_rng(rng);
// With `rand::random`:
let another_rotation: Rotation2d = random();
// With `Rng::gen`:
let yet_another_rotation: Rotation2d = rng.gen();
```
I also cleaned up the documentation a little bit, seeding the `Rng`s
instead of building them from entropy, along with adding a handful of
inline directives.
# Objective
- Implement `Bounded3d` for some `Extrusion<T>`
- Provide methods to calculate `Aabb3d`s and `BoundingSphere`s for any
extrusion with a `Bounded2d` base shape
## Solution
- Implemented `Bounded3d` for all 2D `bevy_math` primitives with the
exception of `Plane2d`. As far as I can see, `Plane2d` is pretty much a
line? and I think it is very unintuitive to extrude a plane and get a
plane as a result.
- Add `extrusion_bounding_box` and `extrusion_bounding_sphere`. These
are not always used internally since there are faster methods for
specific extrusions. Both of them produce the optimal result within
precision limits though.
## Testing
- Bounds for extrusions are tested within the same module. All unique
implementations are tested.
- The correctness was validated visually aswell.
---------
Co-authored-by: Raphael Büttgenbach <62256001+solis-lumine-vorago@users.noreply.github.com>
Co-authored-by: IQuick 143 <IQuick143cz@gmail.com>
# Objective
Filling a hole in the API: Previously, there was no particularly
ergonomic way to go from, e.g., a pair of directions to the rotation
that links them.
## Solution
We introduce a small suite of API methods to `Dir2` to address this:
```rust
/// Get the rotation that rotates this direction to `other`.
pub fn rotation_to(self, other: Self) -> Rotation2d { //... }
/// Get the rotation that rotates `other` to this direction.
pub fn rotation_from(self, other: Self) -> Rotation2d { //... }
/// Get the rotation that rotates the X-axis to this direction.
pub fn rotation_from_x(self) -> Rotation2d { //... }
/// Get the rotation that rotates this direction to the X-axis.
pub fn rotation_to_x(self) -> Rotation2d { //... }
/// Get the rotation that rotates this direction to the Y-axis.
pub fn rotation_from_y(self) -> Rotation2d { //... }
/// Get the rotation that rotates the Y-axis to this direction.
pub fn rotation_to_y(self) -> Rotation2d { //... }
```
I also removed some language from the `Rotation2d` docs that is
misleading: the radian and angle conversion functions are already clear
about which angles they spit out, and `Rotation2d` itself doesn't have
any bounds on angles or anything.
# Objective
Implements #13647
## Solution
Created two enums, CompassQuadrant and CompassOctant inside compass.rs
with impls To and From Dir2. Used dir.to_angle().to_degrees() and
matched against the resulting value. I could have skipped to_degrees()
and matched against the radian value, but I thought this was more
readable. I'm probably wrong lol.
## Testing
Tested various dirs to compass variations.
---
---------
Co-authored-by: Alice Cecile <alice.i.cecile@gmail.com>
# Objective
When working on `leafwing-input-manager` and in my games, I've found
these compass directions to be both clear and useful when attempting to
describe angles in 2 dimensions.
This was directly used when mapping gamepad inputs into 4-way movement
as a virtual dpad, and I expect other uses are common in games.
## Solution
- Add constants corresponding to the 4 cardinal and 4 semi-cardinal
directions.
## Testing
- I've validated the quadrants of each of the directions through
self-review.
---------
Co-authored-by: Alice Cecile <alice.i.cecil@gmail.com>
# Objective
Fixes#13535.
## Solution
I implemented `Reflect` for close to all math types now, except for some
types that it would cause issues (like some boxed types).
## Testing
- Everything seems to still build, will await CI though.
---
## Changelog
- Made close to all math types implement `Reflect`.
# Objective
Fixes#13456
## Solution
Moved `bevy_math`'s `Reflect` impls from `bevy_reflect` to `bevy_math`.
### Quick note
I accidentally used the same commit message while resolving a merge
conflict (first time I had to resolve a conflict). Sorry about that.
