2018-08-05 14:47:24 +02:00
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//! # Spline interpolation made easy.
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2018-08-05 01:12:22 +02:00
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//!
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//! This crate exposes splines for which each sections can be interpolated independently of each
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//! other – i.e. it’s possible to interpolate with a linear interpolator on one section and then
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2018-08-05 14:47:24 +02:00
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//! switch to a cubic Hermite interpolator for the next section.
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2018-08-05 01:12:22 +02:00
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//!
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2018-08-05 14:47:24 +02:00
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//! Most of the crate consists of three types:
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2018-08-05 01:12:22 +02:00
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//!
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//! - [`Key`], which represents the control points by which the spline must pass.
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//! - [`Interpolation`], the type of possible interpolation for each segment.
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//! - [`Spline`], a spline from which you can *sample* points by interpolation.
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//!
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//! When adding control points, you add new sections. Two control points define a section – i.e.
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//! it’s not possible to define a spline without at least two control points. Every time you add a
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//! new control point, a new section is created. Each section is assigned an interpolation mode that
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//! is picked from its lower control point.
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//!
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2018-08-05 14:47:24 +02:00
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//! # Quickly create splines
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//!
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2018-08-05 01:12:22 +02:00
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//! ```
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//! use splines::{Interpolation, Key, Spline};
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//!
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//! let start = Key::new(0., 0., Interpolation::Linear);
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2018-08-05 17:11:44 +02:00
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//! let end = Key::new(1., 10., Interpolation::default());
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//! let spline = Spline::from_vec(vec![start, end]);
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2018-08-05 14:47:24 +02:00
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//! ```
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//!
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2018-08-05 17:11:44 +02:00
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//! You will notice that we used `Interpolation::Linear` for the first key. The first key `start`’s
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2018-08-05 14:47:24 +02:00
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//! interpolation will be used for the whole segment defined by those two keys. The `end`’s
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//! interpolation won’t be used. You can in theory use any [`Interpolation`] you want for the last
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2018-08-05 17:11:44 +02:00
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//! key. We use the default one because we don’t care.
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2018-08-05 14:47:24 +02:00
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//!
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//! # Interpolate values
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2018-08-05 01:12:22 +02:00
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//!
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2018-08-05 14:47:24 +02:00
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//! The whole purpose of splines is to interpolate discrete values to yield continuous ones. This is
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//! usually done with the `Spline::sample` method. This method expects the interpolation parameter
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//! (often, this will be the time of your simulation) as argument and will yield an interpolated
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//! value.
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//!
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//! If you try to sample in out-of-bounds interpolation parameter, you’ll get no value.
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//!
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//! ```
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//! # use splines::{Interpolation, Key, Spline};
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//! # let start = Key::new(0., 0., Interpolation::Linear);
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//! # let end = Key::new(1., 10., Interpolation::Linear);
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2018-08-05 17:11:44 +02:00
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//! # let spline = Spline::from_vec(vec![start, end]);
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2018-08-05 01:12:22 +02:00
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//! assert_eq!(spline.sample(0.), Some(0.));
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2018-08-05 17:11:44 +02:00
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//! assert_eq!(spline.clamped_sample(1.), 10.);
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2018-08-05 14:47:24 +02:00
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//! assert_eq!(spline.sample(1.1), None);
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2018-08-05 01:12:22 +02:00
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//! ```
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2018-08-05 17:11:44 +02:00
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//!
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//! It’s possible that you want to get a value even if you’re out-of-bounds. This is especially
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//! important for simulations / animations. Feel free to use the `Spline::clamped_interpolation` for
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//! that purpose.
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//!
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//! ```
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//! # use splines::{Interpolation, Key, Spline};
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//! # let start = Key::new(0., 0., Interpolation::Linear);
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//! # let end = Key::new(1., 10., Interpolation::Linear);
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//! # let spline = Spline::from_vec(vec![start, end]);
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//! assert_eq!(spline.clamped_sample(-0.9), 0.); // clamped to the first key
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//! assert_eq!(spline.clamped_sample(1.1), 10.); // clamped to the last key
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//! ```
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2018-08-08 00:35:24 +02:00
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//! # Features and customization
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2018-08-05 17:11:44 +02:00
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//!
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2018-08-08 00:35:24 +02:00
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//! This crate was written with features baked in and hidden behind feature-gates. The idea is that
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//! the default configuration (i.e. you just add `"spline = …"` to your `Cargo.toml`) will always
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//! give you the minimal, core and raw concepts of what splines, keys / knots and interpolation
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//! modes are. However, you might want more. Instead of letting other people do the extra work to
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//! add implementations for very famous and useful traits – and do it in less efficient way, because
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//! they wouldn’t have access to the internals of this crate, it’s possible to enable features in an
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//! ad hoc way.
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//!
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//! This mechanism is not final and this is currently an experiment to see how people like it or
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//! not. It’s especially important to see how it copes with the documentation.
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//!
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//! So here’s a list of currently supported features and how to enable them:
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//!
|
2018-08-09 01:23:45 +02:00
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//! - **Serialization / deserialization.**
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2018-08-08 00:35:24 +02:00
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//! + This feature implements both the `Serialize` and `Deserialize` traits from `serde`.
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2018-08-09 01:23:45 +02:00
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//! + Enable with the `"serialization"` feature.
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//! - **Standard library / no stdandard library**
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//! + It’s possible to compile against the standard library or go on your own without it.
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//! + Compiling with the standard library is enabled by default.
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//! + Use `defaut-features = []` in your `Cargo.toml` to disable.
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//! + Enable explicitly with the `"std"` feataure.
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#![cfg_attr(not(feature = "std"), no_std)]
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#![cfg_attr(not(feature = "std"), feature(alloc))]
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// on no_std, we also need the alloc crate for Vec
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#[cfg(not(feature = "std"))] extern crate alloc;
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2018-08-05 01:12:22 +02:00
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2018-08-05 17:23:30 +02:00
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extern crate cgmath;
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2018-08-07 23:40:52 +02:00
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#[cfg(feature = "serialization")] extern crate serde;
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#[cfg(feature = "serialization")] #[macro_use] extern crate serde_derive;
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2018-08-05 17:23:30 +02:00
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use cgmath::{InnerSpace, Quaternion, Vector2, Vector3, Vector4};
|
2018-08-09 01:23:45 +02:00
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#[cfg(feature = "std")] use std::cmp::Ordering;
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#[cfg(feature = "std")] use std::f32::consts;
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#[cfg(feature = "std")] use std::ops::{Add, Div, Mul, Sub};
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#[cfg(not(feature = "std"))] use alloc::vec::Vec;
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#[cfg(not(feature = "std"))] use core::cmp::Ordering;
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#[cfg(not(feature = "std"))] use core::f32::consts;
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#[cfg(not(feature = "std"))] use core::ops::{Add, Div, Mul, Sub};
|
2018-08-05 01:12:22 +02:00
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/// A spline control point.
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///
|
2018-08-05 17:11:44 +02:00
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/// This type associates a value at a given interpolation parameter value. It also contains an
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/// interpolation hint used to determine how to interpolate values on the segment defined by this
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/// key and the next one – if existing.
|
2018-08-05 01:12:22 +02:00
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#[derive(Copy, Clone, Debug)]
|
2018-08-07 23:40:52 +02:00
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#[cfg_attr(feature = "serialization", derive(Deserialize, Serialize))]
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#[cfg_attr(feature = "serialization", serde(rename_all = "snake_case"))]
|
2018-08-05 01:12:22 +02:00
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pub struct Key<T> {
|
2018-08-05 17:11:44 +02:00
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/// Interpolation parameter at which the [`Key`] should be reached.
|
2018-08-05 01:12:22 +02:00
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|
pub t: f32,
|
2018-08-05 17:11:44 +02:00
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/// Held value.
|
2018-08-05 01:12:22 +02:00
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|
pub value: T,
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|
/// Interpolation mode.
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pub interpolation: Interpolation
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|
}
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impl<T> Key<T> {
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/// Create a new key.
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pub fn new(t: f32, value: T, interpolation: Interpolation) -> Self {
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Key {
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t: t,
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value: value,
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interpolation: interpolation
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}
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}
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}
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/// Interpolation mode.
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#[derive(Copy, Clone, Debug)]
|
2018-08-07 23:40:52 +02:00
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#[cfg_attr(feature = "serialization", derive(Deserialize, Serialize))]
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|
#[cfg_attr(feature = "serialization", serde(rename_all = "snake_case"))]
|
2018-08-05 01:12:22 +02:00
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pub enum Interpolation {
|
2018-08-05 01:17:17 +02:00
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/// Hold a [`Key`] until the time passes the normalized step threshold, in which case the next
|
2018-08-05 01:12:22 +02:00
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/// key is used.
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///
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/// *Note: if you set the threshold to `0.5`, the first key will be used until the time is half
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/// between the two keys; the second key will be in used afterwards. If you set it to `1.0`, the
|
2018-08-05 01:17:17 +02:00
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/// first key will be kept until the next key. Set it to `0.` and the first key will never be
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/// used.*
|
2018-08-05 01:12:22 +02:00
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|
Step(f32),
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|
/// Linear interpolation between a key and the next one.
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Linear,
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/// Cosine interpolation between a key and the next one.
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Cosine,
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/// Catmull-Rom interpolation.
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CatmullRom
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}
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impl Default for Interpolation {
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/// `Interpolation::Linear` is the default.
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fn default() -> Self {
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Interpolation::Linear
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}
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}
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/// Spline curve used to provide interpolation between control points (keys).
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|
#[derive(Debug, Clone)]
|
2018-08-07 23:40:52 +02:00
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#[cfg_attr(feature = "serialization", derive(Deserialize, Serialize))]
|
2018-08-05 01:12:22 +02:00
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pub struct Spline<T>(Vec<Key<T>>);
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impl<T> Spline<T> {
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2018-08-05 17:11:44 +02:00
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/// Create a new spline out of keys. The keys don’t have to be sorted even though it’s recommended
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/// to provide ascending sorted ones (for performance purposes).
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pub fn from_vec(mut keys: Vec<Key<T>>) -> Self {
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2018-08-05 01:12:22 +02:00
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keys.sort_by(|k0, k1| k0.t.partial_cmp(&k1.t).unwrap_or(Ordering::Less));
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Spline(keys)
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}
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2018-08-05 17:11:44 +02:00
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/// Create a new spline by consuming an `Iterater<Item = Key<T>>`. They keys don’t have to be
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/// sorted.
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///
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/// # Note on iterators
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///
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/// It’s valid to use any iterator that implements `Iterator<Item = Key<T>>`. However, you should
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/// use `Spline::from_vec` if you are passing a `Vec<_>`. This will remove dynamic allocations.
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pub fn from_iter<I>(iter: I) -> Self where I: Iterator<Item = Key<T>> {
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Self::from_vec(iter.collect())
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}
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2018-08-05 01:12:22 +02:00
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/// Retrieve the keys of a spline.
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pub fn keys(&self) -> &[Key<T>] {
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&self.0
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}
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/// Sample a spline at a given time.
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///
|
2018-08-05 17:11:44 +02:00
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/// The current implementation, based on immutability, cannot perform in constant time. This means
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/// that sampling’s processing complexity is currently *O(log n)*. It’s possible to achieve *O(1)*
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/// performance by using a slightly different spline type. If you are interested by this feature,
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/// an implementation for a dedicated type is foreseen yet not started yet.
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///
|
2018-08-05 01:12:22 +02:00
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/// # Return
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///
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/// `None` if you try to sample a value at a time that has no key associated with. That can also
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/// happen if you try to sample between two keys with a specific interpolation mode that make the
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/// sampling impossible. For instance, `Interpolate::CatmullRom` requires *four* keys. If you’re
|
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/// near the beginning of the spline or its end, ensure you have enough keys around to make the
|
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/// sampling.
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pub fn sample(&self, t: f32) -> Option<T> where T: Interpolate {
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let keys = &self.0;
|
2018-08-05 17:11:44 +02:00
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let i = search_lower_cp(keys, t)?;
|
2018-08-05 01:12:22 +02:00
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|
let cp0 = &keys[i];
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|
match cp0.interpolation {
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|
Interpolation::Step(threshold) => {
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|
let cp1 = &keys[i+1];
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|
let nt = normalize_time(t, cp0, cp1);
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|
Some(if nt < threshold { cp0.value } else { cp1.value })
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},
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|
Interpolation::Linear => {
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|
let cp1 = &keys[i+1];
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|
let nt = normalize_time(t, cp0, cp1);
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Some(Interpolate::lerp(cp0.value, cp1.value, nt))
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|
},
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|
Interpolation::Cosine => {
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|
|
let cp1 = &keys[i+1];
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|
|
|
let nt = normalize_time(t, cp0, cp1);
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|
|
let cos_nt = (1. - f32::cos(nt * consts::PI)) * 0.5;
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|
Some(Interpolate::lerp(cp0.value, cp1.value, cos_nt))
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|
|
},
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|
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|
|
Interpolation::CatmullRom => {
|
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|
|
// We need at least four points for Catmull Rom; ensure we have them, otherwise, return
|
|
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|
|
// None.
|
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|
|
if i == 0 || i >= keys.len() - 2 {
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|
None
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|
|
} else {
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|
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|
|
let cp1 = &keys[i+1];
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|
|
|
let cpm0 = &keys[i-1];
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|
|
let cpm1 = &keys[i+2];
|
|
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|
|
let nt = normalize_time(t, cp0, cp1);
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|
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|
|
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|
|
Some(Interpolate::cubic_hermite((cpm0.value, cpm0.t), (cp0.value, cp0.t), (cp1.value, cp1.t), (cpm1.value, cpm1.t), nt))
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|
|
}
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|
|
}
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|
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|
|
}
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|
|
}
|
2018-08-05 14:47:24 +02:00
|
|
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|
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|
|
/// Sample a spline at a given time with clamping.
|
|
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|
|
///
|
|
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|
|
/// # Return
|
|
|
|
|
///
|
|
|
|
|
/// If you sample before the first key or after the last one, return the first key or the last
|
|
|
|
|
/// one, respectively. Otherwise, behave the same way as `Spline::sample`.
|
|
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|
///
|
|
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|
|
/// # Panic
|
|
|
|
|
///
|
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/// This function panics if you have no key.
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pub fn clamped_sample(&self, t: f32) -> T where T: Interpolate {
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|
let first = self.0.first().unwrap();
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|
let last = self.0.last().unwrap();
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if t <= first.t {
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return first.value;
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} else if t >= last.t {
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|
return last.value;
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|
}
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|
self.sample(t).unwrap()
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}
|
2018-08-05 01:12:22 +02:00
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|
}
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/// Iterator over spline keys.
|
2018-08-05 17:11:44 +02:00
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///
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/// This iterator type assures you to iterate over sorted keys.
|
2018-08-05 01:14:55 +02:00
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|
|
pub struct Iter<'a, T> where T: 'a {
|
2018-08-05 01:12:22 +02:00
|
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|
anim_param: &'a Spline<T>,
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|
|
i: usize
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|
}
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|
2018-08-05 01:14:55 +02:00
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|
|
impl<'a, T> Iterator for Iter<'a, T> {
|
2018-08-05 01:12:22 +02:00
|
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|
|
type Item = &'a Key<T>;
|
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|
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|
|
fn next(&mut self) -> Option<Self::Item> {
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|
|
|
let r = self.anim_param.0.get(self.i);
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|
|
if let Some(_) = r {
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|
self.i += 1;
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|
}
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|
r
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|
}
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|
|
|
}
|
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|
|
|
impl<'a, T> IntoIterator for &'a Spline<T> {
|
|
|
|
|
type Item = &'a Key<T>;
|
2018-08-05 01:14:55 +02:00
|
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|
|
type IntoIter = Iter<'a, T>;
|
2018-08-05 01:12:22 +02:00
|
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|
|
|
|
|
|
|
fn into_iter(self) -> Self::IntoIter {
|
2018-08-05 01:14:55 +02:00
|
|
|
|
Iter {
|
2018-08-05 01:12:22 +02:00
|
|
|
|
anim_param: self,
|
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|
|
|
i: 0
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
/// Keys that can be interpolated in between. Implementing this trait is required to perform
|
|
|
|
|
/// sampling on splines.
|
|
|
|
|
pub trait Interpolate: Copy {
|
|
|
|
|
/// Linear interpolation.
|
|
|
|
|
fn lerp(a: Self, b: Self, t: f32) -> Self;
|
|
|
|
|
/// Cubic hermite interpolation.
|
|
|
|
|
///
|
|
|
|
|
/// Default to `Self::lerp`.
|
|
|
|
|
fn cubic_hermite(_: (Self, f32), a: (Self, f32), b: (Self, f32), _: (Self, f32), t: f32) -> Self {
|
|
|
|
|
Self::lerp(a.0, b.0, t)
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
impl Interpolate for f32 {
|
|
|
|
|
fn lerp(a: Self, b: Self, t: f32) -> Self {
|
|
|
|
|
a * (1. - t) + b * t
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
fn cubic_hermite(x: (Self, f32), a: (Self, f32), b: (Self, f32), y: (Self, f32), t: f32) -> Self {
|
|
|
|
|
cubic_hermite(x, a, b, y, t)
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
2018-08-05 17:23:30 +02:00
|
|
|
|
impl Interpolate for Vector2<f32> {
|
|
|
|
|
fn lerp(a: Self, b: Self, t: f32) -> Self {
|
|
|
|
|
a.lerp(b, t)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
fn cubic_hermite(x: (Self, f32), a: (Self, f32), b: (Self, f32), y: (Self, f32), t: f32) -> Self {
|
|
|
|
|
cubic_hermite(x, a, b, y, t)
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
impl Interpolate for Vector3<f32> {
|
|
|
|
|
fn lerp(a: Self, b: Self, t: f32) -> Self {
|
|
|
|
|
a.lerp(b, t)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
fn cubic_hermite(x: (Self, f32), a: (Self, f32), b: (Self, f32), y: (Self, f32), t: f32) -> Self {
|
|
|
|
|
cubic_hermite(x, a, b, y, t)
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
impl Interpolate for Vector4<f32> {
|
|
|
|
|
fn lerp(a: Self, b: Self, t: f32) -> Self {
|
|
|
|
|
a.lerp(b, t)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
fn cubic_hermite(x: (Self, f32), a: (Self, f32), b: (Self, f32), y: (Self, f32), t: f32) -> Self {
|
|
|
|
|
cubic_hermite(x, a, b, y, t)
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
impl Interpolate for Quaternion<f32> {
|
|
|
|
|
fn lerp(a: Self, b: Self, t: f32) -> Self {
|
|
|
|
|
a.nlerp(b, t)
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
2018-08-05 01:12:22 +02:00
|
|
|
|
// Default implementation of Interpolate::cubic_hermit.
|
2018-08-05 01:18:50 +02:00
|
|
|
|
pub(crate) fn cubic_hermite<T>(x: (T, f32), a: (T, f32), b: (T, f32), y: (T, f32), t: f32) -> T
|
2018-08-05 01:12:22 +02:00
|
|
|
|
where T: Copy + Add<Output = T> + Sub<Output = T> + Mul<f32, Output = T> + Div<f32, Output = T> {
|
|
|
|
|
// time stuff
|
|
|
|
|
let t2 = t * t;
|
|
|
|
|
let t3 = t2 * t;
|
|
|
|
|
let two_t3 = 2. * t3;
|
|
|
|
|
let three_t2 = 3. * t2;
|
|
|
|
|
|
|
|
|
|
// 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)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Normalize a time ([0;1]) given two control points.
|
|
|
|
|
#[inline(always)]
|
2018-08-05 01:18:50 +02:00
|
|
|
|
pub(crate) fn normalize_time<T>(t: f32, cp: &Key<T>, cp1: &Key<T>) -> f32 {
|
2018-08-05 14:47:24 +02:00
|
|
|
|
assert!(cp1.t != cp.t, "overlapping keys");
|
2018-08-05 01:12:22 +02:00
|
|
|
|
|
|
|
|
|
(t - cp.t) / (cp1.t - cp.t)
|
|
|
|
|
}
|
2018-08-05 17:11:44 +02:00
|
|
|
|
|
|
|
|
|
// Find the lower control point corresponding to a given time.
|
|
|
|
|
fn search_lower_cp<T>(cps: &[Key<T>], t: f32) -> Option<usize> {
|
|
|
|
|
let mut i = 0;
|
|
|
|
|
let len = cps.len();
|
|
|
|
|
|
|
|
|
|
if len < 2 {
|
|
|
|
|
return None;
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
loop {
|
|
|
|
|
let cp = &cps[i];
|
|
|
|
|
let cp1 = &cps[i+1];
|
|
|
|
|
|
|
|
|
|
if t >= cp1.t {
|
|
|
|
|
if i >= len - 2 {
|
|
|
|
|
return None;
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
i += 1;
|
|
|
|
|
} else if t < cp.t {
|
|
|
|
|
if i == 0 {
|
|
|
|
|
return None;
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
i -= 1;
|
|
|
|
|
} else {
|
|
|
|
|
break; // found
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
Some(i)
|
|
|
|
|
}
|