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Add support for polymorphic sampling type.

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This commit is contained in:
Dimitri Sabadie 2019-04-15 00:04:03 +02:00
parent 2b5aac42dd
commit f3bd7cee24
2 changed files with 85 additions and 68 deletions
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3
Cargo.toml
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@ -26,6 +26,9 @@ std = []
impl-cgmath = ["cgmath"]
impl-nalgebra = ["nalgebra"]
[dependencies]
num-traits = "0.2"
[dependencies.nalgebra]
version = ">=0.14, <0.17"
optional = true

148
src/lib.rs
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@ -107,21 +107,24 @@
#[cfg(feature = "serialization")] extern crate serde;
#[cfg(feature = "serialization")] #[macro_use] extern crate serde_derive;
#[cfg(feature = "impl-cgmath")] use cgmath::{InnerSpace, Quaternion, Vector2, Vector3, Vector4};
#[cfg(feature = "impl-cgmath")]
use cgmath::{
BaseFloat, InnerSpace, Quaternion, Vector2, Vector3, Vector4
};
#[cfg(feature = "impl-nalgebra")] use nalgebra as na;
#[cfg(feature = "impl-nalgebra")] use nalgebra::core::{DimName, DefaultAllocator, Scalar};
#[cfg(feature = "impl-nalgebra")] use nalgebra::core::allocator::Allocator;
#[cfg(feature = "std")] use std::cmp::Ordering;
#[cfg(feature = "std")] use std::f32::consts;
#[cfg(feature = "std")] use std::ops::{Add, Div, Mul, Sub};
#[cfg(not(feature = "std"))] use alloc::vec::Vec;
#[cfg(not(feature = "std"))] use core::cmp::Ordering;
#[cfg(not(feature = "std"))] use core::f32::consts;
#[cfg(not(feature = "std"))] use core::ops::{Add, Div, Mul, Sub};
use num_traits::{Float, FloatConst};
/// A spline control point.
///
/// This type associates a value at a given interpolation parameter value. It also contains an
@ -130,23 +133,19 @@
#[derive(Copy, Clone, Debug)]
#[cfg_attr(feature = "serialization", derive(Deserialize, Serialize))]
#[cfg_attr(feature = "serialization", serde(rename_all = "snake_case"))]
pub struct Key<T> {
pub struct Key<T, V> {
/// Interpolation parameter at which the [`Key`] should be reached.
pub t: f32,
pub t: T,
/// Held value.
pub value: T,
pub value: V,
/// Interpolation mode.
pub interpolation: Interpolation
pub interpolation: Interpolation<T>
}
impl<T> Key<T> {
impl<T, V> Key<T, V> {
/// Create a new key.
pub fn new(t: f32, value: T, interpolation: Interpolation) -> Self {
Key {
t: t,
value: value,
interpolation: interpolation
}
pub fn new(t: T, value: V, interpolation: Interpolation<T>) -> Self {
Key { t, value, interpolation }
}
}
@ -154,7 +153,7 @@ impl<T> Key<T> {
#[derive(Copy, Clone, Debug)]
#[cfg_attr(feature = "serialization", derive(Deserialize, Serialize))]
#[cfg_attr(feature = "serialization", serde(rename_all = "snake_case"))]
pub enum Interpolation {
pub enum Interpolation<T> {
/// Hold a [`Key`] until the time passes the normalized step threshold, in which case the next
/// key is used.
///
@ -162,7 +161,7 @@ pub enum Interpolation {
/// between the two keys; the second key will be in used afterwards. If you set it to `1.0`, the
/// first key will be kept until the next key. Set it to `0.` and the first key will never be
/// used.*
Step(f32),
Step(T),
/// Linear interpolation between a key and the next one.
Linear,
/// Cosine interpolation between a key and the next one.
@ -171,7 +170,7 @@ pub enum Interpolation {
CatmullRom
}
impl Default for Interpolation {
impl<T> Default for Interpolation<T> {
/// `Interpolation::Linear` is the default.
fn default() -> Self {
Interpolation::Linear
@ -181,12 +180,12 @@ impl Default for Interpolation {
/// Spline curve used to provide interpolation between control points (keys).
#[derive(Debug, Clone)]
#[cfg_attr(feature = "serialization", derive(Deserialize, Serialize))]
pub struct Spline<T>(Vec<Key<T>>);
pub struct Spline<T, V>(Vec<Key<T, V>>);
impl<T> Spline<T> {
impl<T, V> Spline<T, V> {
/// Create a new spline out of keys. The keys don’t have to be sorted even though it’s recommended
/// to provide ascending sorted ones (for performance purposes).
pub fn from_vec(mut keys: Vec<Key<T>>) -> Self {
pub fn from_vec(mut keys: Vec<Key<T, V>>) -> Self where T: PartialOrd {
keys.sort_by(|k0, k1| k0.t.partial_cmp(&k1.t).unwrap_or(Ordering::Less));
Spline(keys)
@ -199,12 +198,12 @@ impl<T> Spline<T> {
///
/// It’s valid to use any iterator that implements `Iterator<Item = Key<T>>`. However, you should
/// use `Spline::from_vec` if you are passing a `Vec<_>`. This will remove dynamic allocations.
pub fn from_iter<I>(iter: I) -> Self where I: Iterator<Item = Key<T>> {
pub fn from_iter<I>(iter: I) -> Self where I: Iterator<Item = Key<T, V>>, T: PartialOrd {
Self::from_vec(iter.collect())
}
/// Retrieve the keys of a spline.
pub fn keys(&self) -> &[Key<T>] {
pub fn keys(&self) -> &[Key<T, V>] {
&self.0
}
@ -222,7 +221,7 @@ impl<T> Spline<T> {
/// sampling impossible. For instance, `Interpolate::CatmullRom` requires *four* keys. If you’re
/// near the beginning of the spline or its end, ensure you have enough keys around to make the
/// sampling.
pub fn sample(&self, t: f32) -> Option<T> where T: Interpolate {
pub fn sample(&self, t: T) -> Option<V> where V: Interpolate<T>, T: Float {
let keys = &self.0;
let i = search_lower_cp(keys, t)?;
let cp0 = &keys[i];
@ -244,18 +243,7 @@ impl<T> Spline<T> {
Interpolation::Cosine => {
let cp1 = &keys[i+1];
let nt = normalize_time(t, cp0, cp1);
let cos_nt = {
#[cfg(feature = "std")]
{
(1. - f32::cos(nt * consts::PI)) * 0.5
}
#[cfg(not(feature = "std"))]
{
use core::intrinsics::cosf32;
unsafe { (1. - cosf32(nt * consts::PI)) * 0.5 }
}
};
let cos_nt = (1. - (nt * T::PI).cos()) * 0.5;
Some(Interpolate::lerp(cp0.value, cp1.value, cos_nt))
}
@ -310,13 +298,13 @@ impl<T> Spline<T> {
/// Iterator over spline keys.
///
/// This iterator type assures you to iterate over sorted keys.
pub struct Iter<'a, T> where T: 'a {
anim_param: &'a Spline<T>,
pub struct Iter<'a, T, V> where T: 'a, V: 'a {
anim_param: &'a Spline<T, V>,
i: usize
}
impl<'a, T> Iterator for Iter<'a, T> {
type Item = &'a Key<T>;
impl<'a, T, V> Iterator for Iter<'a, T, V> {
type Item = &'a Key<T, V>;
fn next(&mut self) -> Option<Self::Item> {
let r = self.anim_param.0.get(self.i);
@ -329,9 +317,9 @@ impl<'a, T> Iterator for Iter<'a, T> {
}
}
impl<'a, T> IntoIterator for &'a Spline<T> {
type Item = &'a Key<T>;
type IntoIter = Iter<'a, T>;
impl<'a, T, V> IntoIterator for &'a Spline<T, V> {
type Item = &'a Key<T, V>;
type IntoIter = Iter<'a, T, V>;
fn into_iter(self) -> Self::IntoIter {
Iter {
@ -343,18 +331,22 @@ impl<'a, T> IntoIterator for &'a Spline<T> {
/// Keys that can be interpolated in between. Implementing this trait is required to perform
/// sampling on splines.
pub trait Interpolate: Copy {
///
/// `T` is the variable used to sample with. Typical implementations use `f32` or `f64`, but you’re
/// free to use the ones you like.
pub trait Interpolate<T>: Copy where T: Copy + Float {
/// Linear interpolation.
fn lerp(a: Self, b: Self, t: f32) -> Self;
fn lerp(a: Self, b: Self, t: T) -> Self;
/// Cubic hermite interpolation.
///
/// Default to `Self::lerp`.
fn cubic_hermite(_: (Self, f32), a: (Self, f32), b: (Self, f32), _: (Self, f32), t: f32) -> Self {
fn cubic_hermite(_: (Self, T), a: (Self, T), b: (Self, T), _: (Self, T), t: T) -> Self {
Self::lerp(a.0, b.0, t)
}
}
impl Interpolate for f32 {
impl Interpolate<f32> for f32 {
fn lerp(a: Self, b: Self, t: f32) -> Self {
a * (1. - t) + b * t
}
@ -364,42 +356,58 @@ impl Interpolate for f32 {
}
}
#[cfg(feature = "impl-cgmath")]
impl Interpolate for Vector2<f32> {
impl Interpolate<f32> for f64 {
fn lerp(a: Self, b: Self, t: f32) -> Self {
a * (1. - t as f64) + b * t as f64
}
fn cubic_hermite(
(x, tx): (Self, f32),
(a, ta): (Self, f32),
(b, tb): (Self, f32),
(y, ty): (Self, f32),
t: f32
) -> Self {
cubic_hermite((x, tx as f64), (a, ta as f64), (b, tb as f64), (y, ty as f64), t as f64)
}
}
#[cfg(feature = "impl-cgmath")]
impl<T> Interpolate<T> for Vector2<T> where T: BaseFloat {
fn lerp(a: Self, b: Self, t: T) -> Self {
a.lerp(b, t)
}
fn cubic_hermite(x: (Self, f32), a: (Self, f32), b: (Self, f32), y: (Self, f32), t: f32) -> Self {
fn cubic_hermite(x: (Self, T), a: (Self, T), b: (Self, T), y: (Self, T), t: T) -> Self {
cubic_hermite(x, a, b, y, t)
}
}
#[cfg(feature = "impl-cgmath")]
impl Interpolate for Vector3<f32> {
fn lerp(a: Self, b: Self, t: f32) -> Self {
impl<T> Interpolate<T> for Vector3<T> where T: BaseFloat {
fn lerp(a: Self, b: Self, t: T) -> Self {
a.lerp(b, t)
}
fn cubic_hermite(x: (Self, f32), a: (Self, f32), b: (Self, f32), y: (Self, f32), t: f32) -> Self {
fn cubic_hermite(x: (Self, T), a: (Self, T), b: (Self, T), y: (Self, T), t: T) -> Self {
cubic_hermite(x, a, b, y, t)
}
}
#[cfg(feature = "impl-cgmath")]
impl Interpolate for Vector4<f32> {
fn lerp(a: Self, b: Self, t: f32) -> Self {
impl<T> Interpolate<T> for Vector4<T> where T: BaseFloat {
fn lerp(a: Self, b: Self, t: T) -> Self {
a.lerp(b, t)
}
fn cubic_hermite(x: (Self, f32), a: (Self, f32), b: (Self, f32), y: (Self, f32), t: f32) -> Self {
fn cubic_hermite(x: (Self, T), a: (Self, T), b: (Self, T), y: (Self, T), t: T) -> Self {
cubic_hermite(x, a, b, y, t)
}
}
#[cfg(feature = "impl-cgmath")]
impl Interpolate for Quaternion<f32> {
fn lerp(a: Self, b: Self, t: f32) -> Self {
impl<T> Interpolate<T> for Quaternion<T> where T: BaseFloat {
fn lerp(a: Self, b: Self, t: T) -> Self {
a.nlerp(b, t)
}
}
@ -460,32 +468,38 @@ impl Interpolate for na::Vector6<f32> {
}
}
// Default implementation of Interpolate::cubic_hermit.
pub(crate) fn cubic_hermite<T>(x: (T, f32), a: (T, f32), b: (T, f32), y: (T, f32), t: f32) -> T
where T: Copy + Add<Output = T> + Sub<Output = T> + Mul<f32, Output = T> + Div<f32, Output = T> {
// time stuff
// Default implementation of Interpolate::cubic_hermite.
//
// `V` is the value being interpolated. `T` is the sampling value (also sometimes called time).
pub(crate) fn cubic_hermite<V, T>(x: (V, T), a: (V, T), b: (V, T), y: (V, T), t: T) -> V
where V: Copy + Add<Output = V> + Sub<Output = V> + Mul<T, Output = V> + Div<T, Output = V>,
T: Mul<Output = T> + Mul<f32, Output = T> + Add<Output = T> + Add<f32, Output = T> + Sub<Output = T> {
// sampler stuff
let t2 = t* t;
let t3 = t2 * t;
let two_t3 = 2. * t3;
let three_t2 = 3. * t2;
let two_t3 = t3 * 2.;
let three_t2 = t2 * 3.;
// tangents
let m0 = (b.0 - x.0) / (b.1 - x.1);
let m1 = (y.0 - a.0) / (y.1 - a.1);
a.0 * (two_t3 - three_t2 + 1.) + m0 * (t3 - 2. * t2 + t) + b.0 * (-two_t3 + three_t2) + m1 * (t3 - t2)
a.0 * (two_t3 - three_t2 + 1.) + m0 * (t3 - t2 * 2. + t) + b.0 * (three_t2 - two_t3) + m1 * (t3 - t2)
}
// Normalize a time ([0;1]) given two control points.
#[inline(always)]
pub(crate) fn normalize_time<T>(t: f32, cp: &Key<T>, cp1: &Key<T>) -> f32 {
pub(crate) fn normalize_time<T, V>(
t: T,
cp: &Key<T, V>,
cp1: &Key<T, V>
) -> T where T: PartialEq + Sub<Output = T> + Div<Output = T> {
assert!(cp1.t != cp.t, "overlapping keys");
(t - cp.t) / (cp1.t - cp.t)
}
// Find the lower control point corresponding to a given time.
fn search_lower_cp<T>(cps: &[Key<T>], t: f32) -> Option<usize> {
fn search_lower_cp<T, V>(cps: &[Key<T, V>], t: T) -> Option<usize> where T: PartialOrd {
let mut i = 0;
let len = cps.len();