//! 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 + Add + Sub + Add + 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 { control_points: Vec<[P; 4]>, } impl Bezier

{ /// Create a new Bezier curve from sets of control points. pub fn new(control_points: impl Into>) -> Self { Self { control_points: control_points.into(), } } } impl CubicGenerator

for Bezier

{ #[inline] fn to_curve(&self) -> CubicCurve

{ 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 { control_points: Vec<(P, P)>, } impl Hermite

{ /// Create a new Hermite curve from sets of control points. pub fn new( control_points: impl IntoIterator, tangents: impl IntoIterator, ) -> Self { Self { control_points: control_points.into_iter().zip(tangents).collect(), } } } impl CubicGenerator

for Hermite

{ #[inline] fn to_curve(&self) -> CubicCurve

{ 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 { tension: f32, control_points: Vec

, } impl CardinalSpline

{ /// Build a new Cardinal spline. pub fn new(tension: f32, control_points: impl Into>) -> 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>) -> Self { Self { tension: 0.5, control_points: control_points.into(), } } } impl CubicGenerator

for CardinalSpline

{ #[inline] fn to_curve(&self) -> CubicCurve

{ 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 { control_points: Vec

, } impl BSpline

{ /// Build a new Cardinal spline. pub fn new(control_points: impl Into>) -> Self { Self { control_points: control_points.into(), } } } impl CubicGenerator

for BSpline

{ #[inline] fn to_curve(&self) -> CubicCurve

{ 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 { /// Build a [`CubicCurve`] by computing the interpolation coefficients for each curve segment. fn to_curve(&self) -> CubicCurve

; } /// 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 { coeff: [P; 4], } impl CubicSegment

{ /// 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` 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 { /// 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, p2: impl Into) -> 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 { segments: Vec>, } impl CubicCurve

{ /// 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 = n), where `n = self.segment_count()`, /// returning an iterator evaluating the curve with the supplied `sample_function` at each `t`. /// /// For `subdivisions = 2`, this will split the curve into two lines, or three points, and /// return an iterator with 3 items, the three points, one at the start, middle, and end. #[inline] pub fn iter_samples<'a, 'b: 'a>( &'b self, subdivisions: usize, mut sample_function: impl FnMut(&Self, f32) -> P + 'a, ) -> impl Iterator + 'a { self.iter_uniformly(subdivisions) .map(move |t| sample_function(self, t)) } /// An iterator that returns values of `t` uniformly spaced over `0..=subdivisions`. #[inline] fn iter_uniformly(&self, subdivisions: usize) -> impl Iterator { let segments = self.segments.len() as f32; let step = segments / subdivisions as f32; (0..=subdivisions).map(move |i| i as f32 * step) } /// The list of segments contained in this `CubicCurve`. /// /// This spline's global `t` value is equal to how many segments it has. /// /// All method accepting `t` on `CubicCurve` depends on the global `t`. /// When sampling over the entire curve, you should either use one of the /// `iter_*` methods or account for the segment count using `curve.segments().len()`. #[inline] pub fn segments(&self) -> &[CubicSegment

] { &self.segments } /// Iterate over the curve split into `subdivisions`, sampling the position at each step. pub fn iter_positions(&self, subdivisions: usize) -> impl Iterator + '_ { 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 + '_ { 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 + '_ { 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

, 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

{ 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); } }