bevy/crates/bevy_math/src/cubic_splines.rs

603 lines
20 KiB
Rust
Raw Normal View History

Add generic cubic splines to `bevy_math` (#7683) # Objective - Make cubic splines more flexible and more performant - Remove the existing spline implementation that is generic over many degrees - This is a potential performance footgun and adds type complexity for negligible gain. - Add implementations of: - Bezier splines - Cardinal splines (inc. Catmull-Rom) - B-Splines - Hermite splines https://user-images.githubusercontent.com/2632925/221780519-495d1b20-ab46-45b4-92a3-32c46da66034.mp4 https://user-images.githubusercontent.com/2632925/221780524-2b154016-699f-404f-9c18-02092f589b04.mp4 https://user-images.githubusercontent.com/2632925/221780525-f934f99d-9ad4-4999-bae2-75d675f5644f.mp4 ## Solution - Implements the concept that splines are curve generators (e.g. https://youtu.be/jvPPXbo87ds?t=3488) via the `CubicGenerator` trait. - Common splines are bespoke data types that implement this trait. This gives us flexibility to add custom spline-specific methods on these types, while ultimately all generating a `CubicCurve`. - All splines generate `CubicCurve`s, which are a chain of precomputed polynomial coefficients. This means that all splines have the same evaluation cost, as the calculations for determining position, velocity, and acceleration are all identical. In addition, `CubicCurve`s are simply a list of `CubicSegment`s, which are evaluated from t=0 to t=1. This also means cubic splines of different type can be chained together, as ultimately they all are simply a collection of `CubicSegment`s. - Because easing is an operation on a singe segment of a Bezier curve, we can simply implement easing on `Beziers` that use the `Vec2` type for points. Higher level crates such as `bevy_ui` can wrap this in a more ergonomic interface as needed. ### Performance Measured on a desktop i5 8600K (6-year-old CPU): - easing: 2.7x faster (19ns) - cubic vec2 position sample: 1.5x faster (1.8ns) - cubic vec3 position sample: 1.5x faster (2.6ns) - cubic vec3a position sample: 1.9x faster (1.4ns) On a laptop i7 11800H: - easing: 16ns - cubic vec2 position sample: 1.6ns - cubic vec3 position sample: 2.3ns - cubic vec3a position sample: 1.2ns --- ## Changelog - Added a generic cubic curve trait, and implementation for Cardinal splines (including Catmull-Rom), B-Splines, Beziers, and Hermite Splines. 2D cubic curve segments also implement easing functionality for animation.
2023-03-03 22:06:42 +00:00
//! Provides types for building cubic splines for rendering curves and use with animation easing.
use glam::{Vec2, Vec3, Vec3A};
use std::{
fmt::Debug,
iter::Sum,
ops::{Add, Mul, Sub},
};
/// A point in space of any dimension that supports the math ops needed for cubic spline
/// interpolation.
pub trait Point:
Mul<f32, Output = Self>
+ Add<Self, Output = Self>
+ Sub<Self, Output = Self>
+ Add<f32, Output = Self>
+ Sum
+ Default
+ Debug
+ Clone
+ PartialEq
+ Copy
{
}
impl Point for Vec3 {}
impl Point for Vec3A {}
impl Point for Vec2 {}
impl Point for f32 {}
/// A spline composed of a series of cubic Bezier curves.
///
/// Useful for user-drawn curves with local control, or animation easing. See
/// [`CubicSegment::new_bezier`] for use in easing.
///
/// ### Interpolation
/// The curve only passes through the first and last control point in each set of four points.
///
/// ### Tangency
/// Manually defined by the two intermediate control points within each set of four points.
///
/// ### Continuity
/// At minimum C0 continuous, up to C2. Continuity greater than C0 can result in a loss of local
/// control over the spline due to the curvature constraints.
///
/// ### Usage
///
/// ```
/// # use bevy_math::{*, prelude::*};
/// let points = [[
/// vec2(-1.0, -20.0),
/// vec2(3.0, 2.0),
/// vec2(5.0, 3.0),
/// vec2(9.0, 8.0),
/// ]];
/// let bezier = Bezier::new(points).to_curve();
/// let positions: Vec<_> = bezier.iter_positions(100).collect();
/// ```
pub struct Bezier<P: Point> {
control_points: Vec<[P; 4]>,
}
impl<P: Point> Bezier<P> {
/// Create a new Bezier curve from sets of control points.
pub fn new(control_points: impl Into<Vec<[P; 4]>>) -> Self {
Self {
control_points: control_points.into(),
}
}
}
impl<P: Point> CubicGenerator<P> for Bezier<P> {
#[inline]
fn to_curve(&self) -> CubicCurve<P> {
let char_matrix = [
[1., 0., 0., 0.],
[-3., 3., 0., 0.],
[3., -6., 3., 0.],
[-1., 3., -3., 1.],
];
let segments = self
.control_points
.iter()
.map(|p| CubicCurve::coefficients(*p, 1.0, char_matrix))
.collect();
CubicCurve { segments }
}
}
/// A spline interpolated continuously between the nearest two control points, with the position and
/// velocity of the curve specified at both control points. This curve passes through all control
/// points, with the specified velocity which includes direction and parametric speed.
///
/// Useful for smooth interpolation when you know the position and velocity at two points in time,
/// such as network prediction.
///
/// ### Interpolation
/// The curve passes through every control point.
///
/// ### Tangency
/// Explicitly defined at each control point.
///
/// ### Continuity
/// At minimum C0 continuous, up to C1.
///
/// ### Usage
///
/// ```
/// # use bevy_math::{*, prelude::*};
/// let points = [
/// vec2(-1.0, -20.0),
/// vec2(3.0, 2.0),
/// vec2(5.0, 3.0),
/// vec2(9.0, 8.0),
/// ];
/// let tangents = [
/// vec2(0.0, 1.0),
/// vec2(0.0, 1.0),
/// vec2(0.0, 1.0),
/// vec2(0.0, 1.0),
/// ];
/// let hermite = Hermite::new(points, tangents).to_curve();
/// let positions: Vec<_> = hermite.iter_positions(100).collect();
/// ```
pub struct Hermite<P: Point> {
control_points: Vec<(P, P)>,
}
impl<P: Point> Hermite<P> {
/// Create a new Hermite curve from sets of control points.
pub fn new(
control_points: impl IntoIterator<Item = P>,
tangents: impl IntoIterator<Item = P>,
) -> Self {
Self {
control_points: control_points
.into_iter()
.zip(tangents.into_iter())
.collect(),
}
}
}
impl<P: Point> CubicGenerator<P> for Hermite<P> {
#[inline]
fn to_curve(&self) -> CubicCurve<P> {
let char_matrix = [
[1., 0., 0., 0.],
[0., 1., 0., 0.],
[-3., -2., 3., -1.],
[2., 1., -2., 1.],
];
let segments = self
.control_points
.windows(2)
.map(|p| {
let (p0, v0, p1, v1) = (p[0].0, p[0].1, p[1].0, p[1].1);
CubicCurve::coefficients([p0, v0, p1, v1], 1.0, char_matrix)
})
.collect();
CubicCurve { segments }
}
}
/// A spline interpolated continuously across the nearest four control points, with the position of
/// the curve specified at every control point and the tangents computed automatically.
///
/// **Note** the Catmull-Rom spline is a special case of Cardinal spline where the tension is 0.5.
///
/// ### Interpolation
/// The curve passes through every control point.
///
/// ### Tangency
/// Automatically defined at each control point.
///
/// ### Continuity
/// C1 continuous.
///
/// ### Usage
///
/// ```
/// # use bevy_math::{*, prelude::*};
/// let points = [
/// vec2(-1.0, -20.0),
/// vec2(3.0, 2.0),
/// vec2(5.0, 3.0),
/// vec2(9.0, 8.0),
/// ];
/// let cardinal = CardinalSpline::new(0.3, points).to_curve();
/// let positions: Vec<_> = cardinal.iter_positions(100).collect();
/// ```
pub struct CardinalSpline<P: Point> {
tension: f32,
control_points: Vec<P>,
}
impl<P: Point> CardinalSpline<P> {
/// Build a new Cardinal spline.
pub fn new(tension: f32, control_points: impl Into<Vec<P>>) -> Self {
Self {
tension,
control_points: control_points.into(),
}
}
/// Build a new Catmull-Rom spline, the special case of a Cardinal spline where tension = 1/2.
pub fn new_catmull_rom(control_points: impl Into<Vec<P>>) -> Self {
Self {
tension: 0.5,
control_points: control_points.into(),
}
}
}
impl<P: Point> CubicGenerator<P> for CardinalSpline<P> {
#[inline]
fn to_curve(&self) -> CubicCurve<P> {
let s = self.tension;
let char_matrix = [
[0., 1., 0., 0.],
[-s, 0., s, 0.],
[2. * s, s - 3., 3. - 2. * s, -s],
[-s, 2. - s, s - 2., s],
];
let segments = self
.control_points
.windows(4)
.map(|p| CubicCurve::coefficients([p[0], p[1], p[2], p[3]], 1.0, char_matrix))
.collect();
CubicCurve { segments }
}
}
/// A spline interpolated continuously across the nearest four control points. The curve does not
/// pass through any of the control points.
///
/// ### Interpolation
/// The curve does not pass through control points.
///
/// ### Tangency
/// Automatically computed based on the position of control points.
///
/// ### Continuity
/// C2 continuous! The acceleration continuity of this spline makes it useful for camera paths.
///
/// ### Usage
///
/// ```
/// # use bevy_math::{*, prelude::*};
/// let points = [
/// vec2(-1.0, -20.0),
/// vec2(3.0, 2.0),
/// vec2(5.0, 3.0),
/// vec2(9.0, 8.0),
/// ];
/// let b_spline = BSpline::new(points).to_curve();
/// let positions: Vec<_> = b_spline.iter_positions(100).collect();
/// ```
pub struct BSpline<P: Point> {
control_points: Vec<P>,
}
impl<P: Point> BSpline<P> {
/// Build a new Cardinal spline.
pub fn new(control_points: impl Into<Vec<P>>) -> Self {
Self {
control_points: control_points.into(),
}
}
}
impl<P: Point> CubicGenerator<P> for BSpline<P> {
#[inline]
fn to_curve(&self) -> CubicCurve<P> {
let char_matrix = [
[1., 4., 1., 0.],
[-3., 0., 3., 0.],
[3., -6., 3., 0.],
[-1., 3., -3., 1.],
];
let segments = self
.control_points
.windows(4)
.map(|p| CubicCurve::coefficients([p[0], p[1], p[2], p[3]], 1.0 / 6.0, char_matrix))
.collect();
CubicCurve { segments }
}
}
/// Implement this on cubic splines that can generate a curve from their spline parameters.
pub trait CubicGenerator<P: Point> {
/// Build a [`CubicCurve`] by computing the interpolation coefficients for each curve segment.
fn to_curve(&self) -> CubicCurve<P>;
}
/// A segment of a cubic curve, used to hold precomputed coefficients for fast interpolation.
///
/// Segments can be chained together to form a longer compound curve.
#[derive(Clone, Debug, Default, PartialEq)]
pub struct CubicSegment<P: Point> {
coeff: [P; 4],
}
impl<P: Point> CubicSegment<P> {
/// Instantaneous position of a point at parametric value `t`.
#[inline]
pub fn position(&self, t: f32) -> P {
let [a, b, c, d] = self.coeff;
a + b * t + c * t.powi(2) + d * t.powi(3)
}
/// Instantaneous velocity of a point at parametric value `t`.
#[inline]
pub fn velocity(&self, t: f32) -> P {
let [_, b, c, d] = self.coeff;
b + c * 2.0 * t + d * 3.0 * t.powi(2)
}
/// Instantaneous acceleration of a point at parametric value `t`.
#[inline]
pub fn acceleration(&self, t: f32) -> P {
let [_, _, c, d] = self.coeff;
c * 2.0 + d * 6.0 * t
}
}
/// The `CubicSegment<Vec2>` can be used as a 2-dimensional easing curve for animation.
///
/// The x-axis of the curve is time, and the y-axis is the output value. This struct provides
/// methods for extremely fast solves for y given x.
impl CubicSegment<Vec2> {
/// Construct a cubic Bezier curve for animation easing, with control points `p1` and `p2`. A
/// cubic Bezier easing curve has control point `p0` at (0, 0) and `p3` at (1, 1), leaving only
/// `p1` and `p2` as the remaining degrees of freedom. The first and last control points are
/// fixed to ensure the animation begins at 0, and ends at 1.
///
/// This is a very common tool for UI animations that accelerate and decelerate smoothly. For
/// example, the ubiquitous "ease-in-out" is defined as `(0.25, 0.1), (0.25, 1.0)`.
pub fn new_bezier(p1: impl Into<Vec2>, p2: impl Into<Vec2>) -> Self {
let (p0, p3) = (Vec2::ZERO, Vec2::ONE);
let bezier = Bezier::new([[p0, p1.into(), p2.into(), p3]]).to_curve();
bezier.segments[0].clone()
}
/// Maximum allowable error for iterative Bezier solve
const MAX_ERROR: f32 = 1e-5;
/// Maximum number of iterations during Bezier solve
const MAX_ITERS: u8 = 8;
/// Given a `time` within `0..=1`, returns an eased value that follows the cubic curve instead
/// of a straight line. This eased result may be outside the range `0..=1`, however it will
/// always start at 0 and end at 1: `ease(0) = 0` and `ease(1) = 1`.
///
/// ```
/// # use bevy_math::prelude::*;
/// let cubic_bezier = CubicSegment::new_bezier((0.25, 0.1), (0.25, 1.0));
/// assert_eq!(cubic_bezier.ease(0.0), 0.0);
/// assert_eq!(cubic_bezier.ease(1.0), 1.0);
/// ```
///
/// # How cubic easing works
///
/// Easing is generally accomplished with the help of "shaping functions". These are curves that
/// start at (0,0) and end at (1,1). The x-axis of this plot is the current `time` of the
/// animation, from 0 to 1. The y-axis is how far along the animation is, also from 0 to 1. You
/// can imagine that if the shaping function is a straight line, there is a 1:1 mapping between
/// the `time` and how far along your animation is. If the `time` = 0.5, the animation is
/// halfway through. This is known as linear interpolation, and results in objects animating
/// with a constant velocity, and no smooth acceleration or deceleration at the start or end.
///
/// ```text
/// y
/// │ ●
/// │ ⬈
/// │ ⬈
/// │ ⬈
/// │ ⬈
/// ●─────────── x (time)
/// ```
///
/// Using cubic Beziers, we have a curve that starts at (0,0), ends at (1,1), and follows a path
/// determined by the two remaining control points (handles). These handles allow us to define a
/// smooth curve. As `time` (x-axis) progresses, we now follow the curve, and use the `y` value
/// to determine how far along the animation is.
///
/// ```text
/// y
/// ⬈➔●
/// │ ⬈
/// │ ↑
/// │ ↑
/// │ ⬈
/// ●➔⬈───────── x (time)
/// ```
///
/// To accomplish this, we need to be able to find the position `y` on a curve, given the `x`
/// value. Cubic curves are implicit parametric functions like B(t) = (x,y). To find `y`, we
/// first solve for `t` that corresponds to the given `x` (`time`). We use the Newton-Raphson
/// root-finding method to quickly find a value of `t` that is very near the desired value of
/// `x`. Once we have this we can easily plug that `t` into our curve's `position` function, to
/// find the `y` component, which is how far along our animation should be. In other words:
///
/// > Given `time` in `0..=1`
///
/// > Use Newton's method to find a value of `t` that results in B(t) = (x,y) where `x == time`
///
/// > Once a solution is found, use the resulting `y` value as the final result
#[inline]
pub fn ease(&self, time: f32) -> f32 {
let x = time.clamp(0.0, 1.0);
self.find_y_given_x(x)
}
/// Find the `y` value of the curve at the given `x` value using the Newton-Raphson method.
#[inline]
fn find_y_given_x(&self, x: f32) -> f32 {
let mut t_guess = x;
let mut pos_guess = Vec2::ZERO;
for _ in 0..Self::MAX_ITERS {
pos_guess = self.position(t_guess);
let error = pos_guess.x - x;
if error.abs() <= Self::MAX_ERROR {
break;
}
// Using Newton's method, use the tangent line to estimate a better guess value.
let slope = self.velocity(t_guess).x; // dx/dt
t_guess -= error / slope;
}
pos_guess.y
}
}
/// A collection of [`CubicSegment`]s chained into a curve.
#[derive(Clone, Debug, Default, PartialEq)]
pub struct CubicCurve<P: Point> {
segments: Vec<CubicSegment<P>>,
}
impl<P: Point> CubicCurve<P> {
/// Compute the position of a point on the cubic curve at the parametric value `t`.
///
/// Note that `t` varies from `0..=(n_points - 3)`.
#[inline]
pub fn position(&self, t: f32) -> P {
let (segment, t) = self.segment(t);
segment.position(t)
}
/// Compute the first derivative with respect to t at `t`. This is the instantaneous velocity of
/// a point on the cubic curve at `t`.
///
/// Note that `t` varies from `0..=(n_points - 3)`.
#[inline]
pub fn velocity(&self, t: f32) -> P {
let (segment, t) = self.segment(t);
segment.velocity(t)
}
/// Compute the second derivative with respect to t at `t`. This is the instantaneous
/// acceleration of a point on the cubic curve at `t`.
///
/// Note that `t` varies from `0..=(n_points - 3)`.
#[inline]
pub fn acceleration(&self, t: f32) -> P {
let (segment, t) = self.segment(t);
segment.acceleration(t)
}
/// A flexible iterator used to sample curves with arbitrary functions.
///
/// This splits the curve into `subdivisions` of evenly spaced `t` values across the
/// length of the curve from start (t = 0) to end (t = 1), returning an iterator that evaluates
/// the curve with the supplied `sample_function` at each `t`.
///
/// Given `subdivisions = 2`, this will split the curve into two lines, or three points, and
/// return an iterator over those three points, one at the start, middle, and end.
#[inline]
pub fn iter_samples(
&self,
subdivisions: usize,
sample_function: fn(&Self, f32) -> P,
) -> impl Iterator<Item = P> + '_ {
(0..subdivisions).map(move |i| {
let segments = self.segments.len() as f32;
let t = i as f32 / subdivisions as f32 * segments;
sample_function(self, t)
})
}
/// Iterate over the curve split into `subdivisions`, sampling the position at each step.
pub fn iter_positions(&self, subdivisions: usize) -> impl Iterator<Item = P> + '_ {
self.iter_samples(subdivisions, Self::position)
}
/// Iterate over the curve split into `subdivisions`, sampling the velocity at each step.
pub fn iter_velocities(&self, subdivisions: usize) -> impl Iterator<Item = P> + '_ {
self.iter_samples(subdivisions, Self::velocity)
}
/// Iterate over the curve split into `subdivisions`, sampling the acceleration at each step.
pub fn iter_accelerations(&self, subdivisions: usize) -> impl Iterator<Item = P> + '_ {
self.iter_samples(subdivisions, Self::acceleration)
}
/// Returns the [`CubicSegment`] and local `t` value given a spline's global `t` value.
#[inline]
fn segment(&self, t: f32) -> (&CubicSegment<P>, f32) {
if self.segments.len() == 1 {
(&self.segments[0], t)
} else {
let i = (t.floor() as usize).clamp(0, self.segments.len() - 1);
(&self.segments[i], t - i as f32)
}
}
#[inline]
fn coefficients(p: [P; 4], multiplier: f32, char_matrix: [[f32; 4]; 4]) -> CubicSegment<P> {
let [c0, c1, c2, c3] = char_matrix;
// These are the polynomial coefficients, computed by multiplying the characteristic
// matrix by the point matrix.
let mut coeff = [
p[0] * c0[0] + p[1] * c0[1] + p[2] * c0[2] + p[3] * c0[3],
p[0] * c1[0] + p[1] * c1[1] + p[2] * c1[2] + p[3] * c1[3],
p[0] * c2[0] + p[1] * c2[1] + p[2] * c2[2] + p[3] * c2[3],
p[0] * c3[0] + p[1] * c3[1] + p[2] * c3[2] + p[3] * c3[3],
];
coeff.iter_mut().for_each(|c| *c = *c * multiplier);
CubicSegment { coeff }
}
}
#[cfg(test)]
mod tests {
use glam::{vec2, Vec2};
use crate::cubic_splines::{Bezier, CubicGenerator, CubicSegment};
/// How close two floats can be and still be considered equal
const FLOAT_EQ: f32 = 1e-5;
/// Sweep along the full length of a 3D cubic Bezier, and manually check the position.
#[test]
fn cubic() {
const N_SAMPLES: usize = 1000;
let points = [[
vec2(-1.0, -20.0),
vec2(3.0, 2.0),
vec2(5.0, 3.0),
vec2(9.0, 8.0),
]];
let bezier = Bezier::new(points).to_curve();
for i in 0..=N_SAMPLES {
let t = i as f32 / N_SAMPLES as f32; // Check along entire length
assert!(bezier.position(t).distance(cubic_manual(t, points[0])) <= FLOAT_EQ);
}
}
/// Manual, hardcoded function for computing the position along a cubic bezier.
fn cubic_manual(t: f32, points: [Vec2; 4]) -> Vec2 {
let p = points;
p[0] * (1.0 - t).powi(3)
+ 3.0 * p[1] * t * (1.0 - t).powi(2)
+ 3.0 * p[2] * t.powi(2) * (1.0 - t)
+ p[3] * t.powi(3)
}
/// Basic cubic Bezier easing test to verify the shape of the curve.
#[test]
fn easing_simple() {
// A curve similar to ease-in-out, but symmetric
let bezier = CubicSegment::new_bezier([1.0, 0.0], [0.0, 1.0]);
assert_eq!(bezier.ease(0.0), 0.0);
assert!(bezier.ease(0.2) < 0.2); // tests curve
assert_eq!(bezier.ease(0.5), 0.5); // true due to symmetry
assert!(bezier.ease(0.8) > 0.8); // tests curve
assert_eq!(bezier.ease(1.0), 1.0);
}
/// A curve that forms an upside-down "U", that should extend below 0.0. Useful for animations
/// that go beyond the start and end positions, e.g. bouncing.
#[test]
fn easing_overshoot() {
// A curve that forms an upside-down "U", that should extend above 1.0
let bezier = CubicSegment::new_bezier([0.0, 2.0], [1.0, 2.0]);
assert_eq!(bezier.ease(0.0), 0.0);
assert!(bezier.ease(0.5) > 1.5);
assert_eq!(bezier.ease(1.0), 1.0);
}
/// A curve that forms a "U", that should extend below 0.0. Useful for animations that go beyond
/// the start and end positions, e.g. bouncing.
#[test]
fn easing_undershoot() {
let bezier = CubicSegment::new_bezier([0.0, -2.0], [1.0, -2.0]);
assert_eq!(bezier.ease(0.0), 0.0);
assert!(bezier.ease(0.5) < -0.5);
assert_eq!(bezier.ease(1.0), 1.0);
}
}