Compare commits
27 Commits
0.2.1
...
1.0.0-rc.1
Author | SHA1 | Date | |
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8de0f10572 | |||
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ed222e001d | |||
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882b9e7b34 | |||
0dcfe48415 | |||
24cd0d7fca |
@ -19,6 +19,5 @@ script:
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- echo "Testing feature serialization"
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- cargo build --verbose --features serialization
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- cargo test --verbose --features serialization
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||||
- echo "Testing without std"
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||||
- echo "Building without std"
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||||
- cargo build --verbose --no-default-features
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- cargo test --verbose --no-default-features
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||||
|
20
CHANGELOG.md
20
CHANGELOG.md
@ -1,4 +1,19 @@
|
||||
# 0.2.1
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## 0.2.3
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||||
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||||
> Sat 13th October 2018
|
||||
|
||||
- Add the `"impl-nalgebra"` feature gate. It gives access to some implementors for the `nalgebra`
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crate.
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- Enhance the documentation.
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||||
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## 0.2.2
|
||||
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||||
> Sun 30th September 2018
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||||
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||||
- Bump version numbers (`splines-0.2`) in examples.
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||||
- Fix several typos in the documentation.
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||||
|
||||
## 0.2.1
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||||
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||||
> Thu 20th September 2018
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@ -9,7 +24,8 @@
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> Thu 6th September 2018
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||||
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||||
- Add the `"std"` feature gate, that can be used to compile with the standard library.
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- Add the `"impl-cgmath"` in order to make it optional, if wanted, the `cgmath` dependency.
|
||||
- Add the `"impl-cgmath"` feature gate in order to make optional, if wanted, the `cgmath`
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||||
dependency.
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- Enhance the documentation.
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||||
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## 0.1.1
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|
27
Cargo.toml
27
Cargo.toml
@ -1,6 +1,6 @@
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[package]
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name = "splines"
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version = "0.2.1"
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version = "1.0.0-rc.1"
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license = "BSD-3-Clause"
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authors = ["Dimitri Sabadie <dimitri.sabadie@gmail.com>"]
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description = "Spline interpolation made easy"
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@ -11,6 +11,8 @@ repository = "https://github.com/phaazon/splines"
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documentation = "https://docs.rs/splines"
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readme = "README.md"
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edition = "2018"
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[badges]
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travis-ci = { repository = "phaazon/splines", branch = "master" }
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is-it-maintained-issue-resolution = { repository = "phaazon/splines" }
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@ -18,19 +20,16 @@ is-it-maintained-open-issues = { repository = "phaazon/splines" }
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maintenance = { status = "actively-developed" }
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[features]
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default = ["std", "impl-cgmath"]
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default = ["std"]
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impl-cgmath = ["cgmath"]
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impl-nalgebra = ["alga", "nalgebra", "num-traits"]
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serialization = ["serde", "serde_derive"]
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std = []
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impl-cgmath = ["cgmath"]
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[dependencies.cgmath]
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version = "0.16"
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optional = true
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[dependencies.serde]
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version = "1"
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optional = true
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[dependencies.serde_derive]
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version = "1"
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optional = true
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[dependencies]
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alga = { version = "0.9", optional = true }
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cgmath = { version = "0.17", optional = true }
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nalgebra = { version = ">=0.14, <0.19", optional = true }
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num-traits = { version = "0.2", optional = true }
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serde = { version = "1", optional = true }
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serde_derive = { version = "1", optional = true }
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|
111
README.md
111
README.md
@ -1,22 +1,103 @@
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# splines
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This crate provides [splines](https://en.wikipedia.org/wiki/Spline_(mathematics)), mathematic curves
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defined piecewise through control keys a.k.a. knots.
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Feel free to dig in the [online documentation](https://docs.rs/splines) for further information.
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## A note on features
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||||
<!-- cargo-sync-readme start -->
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||||
|
||||
This crate has features! Here’s a comprehensive list of what you can enable:
|
||||
# Spline interpolation made easy.
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|
||||
- **Serialization / deserialization.**
|
||||
+ This feature implements both the `Serialize` and `Deserialize` traits from `serde`.
|
||||
+ Enable with the `"serialization"` feature.
|
||||
- **[cgmath](https://crates.io/crates/cgmath) implementors**
|
||||
+ Adds some usefull implementations of `Interpolate` for some cgmath types.
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||||
+ Enable with the `"impl-cgmath"` feature.
|
||||
- **Standard library / no stdandard library.**
|
||||
+ It’s possible to compile against the standard library or go on your own without it.
|
||||
+ Compiling with the standard library is enabled by default.
|
||||
+ Use `defaut-features = []` in your `Cargo.toml` to disable.
|
||||
+ Enable explicitly with the `"std"` feataure.
|
||||
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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switch to a cubic Hermite interpolator for the next section.
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||||
Most of the crate consists of three types:
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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
|
||||
is picked from its lower control point.
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||||
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||||
# Quickly create splines
|
||||
|
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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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let end = Key::new(1., 10., Interpolation::default());
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||||
let spline = Spline::from_vec(vec![start, end]);
|
||||
```
|
||||
|
||||
You will notice that we used `Interpolation::Linear` for the first key. The first key `start`’s
|
||||
interpolation will be used for the whole segment defined by those two keys. The `end`’s
|
||||
interpolation won’t be used. You can in theory use any [`Interpolation`] you want for the last
|
||||
key. We use the default one because we don’t care.
|
||||
|
||||
# Interpolate values
|
||||
|
||||
The whole purpose of splines is to interpolate discrete values to yield continuous ones. This is
|
||||
usually done with the `Spline::sample` method. This method expects the interpolation parameter
|
||||
(often, this will be the time of your simulation) as argument and will yield an interpolated
|
||||
value.
|
||||
|
||||
If you try to sample in out-of-bounds interpolation parameter, you’ll get no value.
|
||||
|
||||
```
|
||||
# use splines::{Interpolation, Key, Spline};
|
||||
# let start = Key::new(0., 0., Interpolation::Linear);
|
||||
# let end = Key::new(1., 10., Interpolation::Linear);
|
||||
# let spline = Spline::from_vec(vec![start, end]);
|
||||
assert_eq!(spline.sample(0.), Some(0.));
|
||||
assert_eq!(spline.clamped_sample(1.), Some(10.));
|
||||
assert_eq!(spline.sample(1.1), None);
|
||||
```
|
||||
|
||||
It’s possible that you want to get a value even if you’re out-of-bounds. This is especially
|
||||
important for simulations / animations. Feel free to use the `Spline::clamped_interpolation` for
|
||||
that purpose.
|
||||
|
||||
```
|
||||
# use splines::{Interpolation, Key, Spline};
|
||||
# let start = Key::new(0., 0., Interpolation::Linear);
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||||
# let end = Key::new(1., 10., Interpolation::Linear);
|
||||
# let spline = Spline::from_vec(vec![start, end]);
|
||||
assert_eq!(spline.clamped_sample(-0.9), Some(0.)); // clamped to the first key
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||||
assert_eq!(spline.clamped_sample(1.1), Some(10.)); // clamped to the last key
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||||
```
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||||
|
||||
# Features and customization
|
||||
|
||||
This crate was written with features baked in and hidden behind feature-gates. The idea is that
|
||||
the default configuration (i.e. you just add `"splines = …"` to your `Cargo.toml`) will always
|
||||
give you the minimal, core and raw concepts of what splines, keys / knots and interpolation
|
||||
modes are. However, you might want more. Instead of letting other people do the extra work to
|
||||
add implementations for very famous and useful traits – and do it in less efficient way, because
|
||||
they wouldn’t have access to the internals of this crate, it’s possible to enable features in an
|
||||
ad hoc way.
|
||||
|
||||
This mechanism is not final and this is currently an experiment to see how people like it or
|
||||
not. It’s especially important to see how it copes with the documentation.
|
||||
|
||||
So here’s a list of currently supported features and how to enable them:
|
||||
|
||||
- **Serialization / deserialization.**
|
||||
+ This feature implements both the `Serialize` and `Deserialize` traits from `serde` for all
|
||||
types exported by this crate.
|
||||
+ Enable with the `"serialization"` feature.
|
||||
- **[cgmath](https://crates.io/crates/cgmath) implementors.**
|
||||
+ Adds some useful implementations of `Interpolate` for some cgmath types.
|
||||
+ Enable with the `"impl-cgmath"` feature.
|
||||
- **[nalgebra](https://crates.io/crates/nalgebra) implementors.**
|
||||
+ Adds some useful implementations of `Interpolate` for some nalgebra types.
|
||||
+ Enable with the `"impl-nalgebra"` feature.
|
||||
- **Standard library / no standard library.**
|
||||
+ It’s possible to compile against the standard library or go on your own without it.
|
||||
+ Compiling with the standard library is enabled by default.
|
||||
+ Use `default-features = []` in your `Cargo.toml` to disable.
|
||||
+ Enable explicitly with the `"std"` feature.
|
||||
|
||||
<!-- cargo-sync-readme end -->
|
||||
|
@ -1,7 +1,7 @@
|
||||
[package]
|
||||
name = "hello-world"
|
||||
version = "0.1.0"
|
||||
version = "0.2.0"
|
||||
authors = ["Dimitri Sabadie <dimitri.sabadie@gmail.com>"]
|
||||
|
||||
[dependencies]
|
||||
splines = "0.1"
|
||||
splines = "0.2"
|
||||
|
@ -6,6 +6,6 @@ fn main() {
|
||||
let keys = vec![Key::new(0., 0., Interpolation::default()), Key::new(5., 1., Interpolation::default())];
|
||||
let spline = Spline::from_vec(keys);
|
||||
|
||||
println!("value at 0: {}", spline.clamped_sample(0.));
|
||||
println!("value at 3: {}", spline.clamped_sample(3.));
|
||||
println!("value at 0: {:?}", spline.clamped_sample(0.));
|
||||
println!("value at 3: {:?}", spline.clamped_sample(3.));
|
||||
}
|
||||
|
@ -1,11 +1,11 @@
|
||||
[package]
|
||||
name = "serialization"
|
||||
version = "0.1.0"
|
||||
version = "0.2.0"
|
||||
authors = ["Dimitri Sabadie <dimitri.sabadie@gmail.com>"]
|
||||
|
||||
[dependencies]
|
||||
serde_json = "1"
|
||||
|
||||
[dependencies.splines]
|
||||
version = "0.1"
|
||||
version = "0.2"
|
||||
features = ["serialization"]
|
||||
|
@ -1,7 +1,7 @@
|
||||
#[macro_use] extern crate serde_json;
|
||||
extern crate splines;
|
||||
|
||||
use serde_json::{Value, from_value};
|
||||
use serde_json::from_value;
|
||||
use splines::Spline;
|
||||
|
||||
fn main() {
|
||||
@ -25,6 +25,6 @@ fn main() {
|
||||
]
|
||||
};
|
||||
|
||||
let spline = from_value::<Spline<f32>>(value);
|
||||
let spline = from_value::<Spline<f32, f32>>(value);
|
||||
println!("{:?}", spline);
|
||||
}
|
||||
|
64
src/cgmath.rs
Normal file
64
src/cgmath.rs
Normal file
@ -0,0 +1,64 @@
|
||||
use cgmath::{
|
||||
BaseFloat, BaseNum, InnerSpace, Quaternion, Vector1, Vector2, Vector3, Vector4, VectorSpace
|
||||
};
|
||||
|
||||
use crate::interpolate::{Additive, Interpolate, Linear, One, cubic_hermite_def};
|
||||
|
||||
macro_rules! impl_interpolate_vec {
|
||||
($($t:tt)*) => {
|
||||
impl<T> Linear<T> for $($t)*<T> where T: BaseNum {
|
||||
#[inline(always)]
|
||||
fn outer_mul(self, t: T) -> Self {
|
||||
self * t
|
||||
}
|
||||
|
||||
#[inline(always)]
|
||||
fn outer_div(self, t: T) -> Self {
|
||||
self / t
|
||||
}
|
||||
}
|
||||
|
||||
impl<T> Interpolate<T> for $($t)*<T>
|
||||
where Self: InnerSpace<Scalar = T>, T: Additive + BaseFloat + One {
|
||||
#[inline(always)]
|
||||
fn lerp(a: Self, b: Self, t: T) -> Self {
|
||||
a.lerp(b, t)
|
||||
}
|
||||
|
||||
#[inline(always)]
|
||||
fn cubic_hermite(x: (Self, T), a: (Self, T), b: (Self, T), y: (Self, T), t: T) -> Self {
|
||||
cubic_hermite_def(x, a, b, y, t)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl_interpolate_vec!(Vector1);
|
||||
impl_interpolate_vec!(Vector2);
|
||||
impl_interpolate_vec!(Vector3);
|
||||
impl_interpolate_vec!(Vector4);
|
||||
|
||||
impl<T> Linear<T> for Quaternion<T> where T: BaseFloat {
|
||||
#[inline(always)]
|
||||
fn outer_mul(self, t: T) -> Self {
|
||||
self * t
|
||||
}
|
||||
|
||||
#[inline(always)]
|
||||
fn outer_div(self, t: T) -> Self {
|
||||
self / t
|
||||
}
|
||||
}
|
||||
|
||||
impl<T> Interpolate<T> for Quaternion<T>
|
||||
where Self: InnerSpace<Scalar = T>, T: Additive + BaseFloat + One {
|
||||
#[inline(always)]
|
||||
fn lerp(a: Self, b: Self, t: T) -> Self {
|
||||
a.nlerp(b, t)
|
||||
}
|
||||
|
||||
#[inline(always)]
|
||||
fn cubic_hermite(x: (Self, T), a: (Self, T), b: (Self, T), y: (Self, T), t: T) -> Self {
|
||||
cubic_hermite_def(x, a, b, y, t)
|
||||
}
|
||||
}
|
210
src/interpolate.rs
Normal file
210
src/interpolate.rs
Normal file
@ -0,0 +1,210 @@
|
||||
#[cfg(feature = "std")] use std::f32;
|
||||
#[cfg(not(feature = "std"))] use core::f32;
|
||||
#[cfg(not(feature = "std"))] use core::intrinsics::cosf32;
|
||||
#[cfg(feature = "std")] use std::f64;
|
||||
#[cfg(not(feature = "std"))] use core::f64;
|
||||
#[cfg(not(feature = "std"))] use core::intrinsics::cosf64;
|
||||
#[cfg(feature = "std")] use std::ops::{Add, Mul, Sub};
|
||||
#[cfg(not(feature = "std"))] use core::ops::{Add, Mul, Sub};
|
||||
|
||||
/// Keys that can be interpolated in between. Implementing this trait is required to perform
|
||||
/// sampling on splines.
|
||||
///
|
||||
/// `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>: Sized + Copy {
|
||||
/// Linear interpolation.
|
||||
fn lerp(a: Self, b: Self, t: T) -> Self;
|
||||
|
||||
/// Cubic hermite interpolation.
|
||||
///
|
||||
/// Default to `Self::lerp`.
|
||||
fn cubic_hermite(_: (Self, T), a: (Self, T), b: (Self, T), _: (Self, T), t: T) -> Self {
|
||||
Self::lerp(a.0, b.0, t)
|
||||
}
|
||||
}
|
||||
|
||||
/// A trait for anything that supports additions, subtraction, multiplication and division.
|
||||
pub trait Additive:
|
||||
Copy +
|
||||
Add<Self, Output = Self> +
|
||||
Sub<Self, Output = Self> {
|
||||
}
|
||||
|
||||
impl<T> Additive for T
|
||||
where T: Copy +
|
||||
Add<Self, Output = Self> +
|
||||
Sub<Self, Output = Self> {
|
||||
}
|
||||
|
||||
/// Linear combination.
|
||||
pub trait Linear<T> {
|
||||
/// Apply an outer multiplication law.
|
||||
fn outer_mul(self, t: T) -> Self;
|
||||
|
||||
/// Apply an outer division law.
|
||||
fn outer_div(self, t: T) -> Self;
|
||||
}
|
||||
|
||||
macro_rules! impl_linear_simple {
|
||||
($t:ty) => {
|
||||
impl Linear<$t> for $t {
|
||||
fn outer_mul(self, t: $t) -> Self {
|
||||
self * t
|
||||
}
|
||||
|
||||
/// Apply an outer division law.
|
||||
fn outer_div(self, t: $t) -> Self {
|
||||
self / t
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl_linear_simple!(f32);
|
||||
impl_linear_simple!(f64);
|
||||
|
||||
macro_rules! impl_linear_cast {
|
||||
($t:ty, $q:ty) => {
|
||||
impl Linear<$t> for $q {
|
||||
fn outer_mul(self, t: $t) -> Self {
|
||||
self * t as $q
|
||||
}
|
||||
|
||||
/// Apply an outer division law.
|
||||
fn outer_div(self, t: $t) -> Self {
|
||||
self / t as $q
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl_linear_cast!(f32, f64);
|
||||
impl_linear_cast!(f64, f32);
|
||||
|
||||
/// Types with a neutral element for multiplication.
|
||||
pub trait One {
|
||||
/// Return the neutral element for the multiplicative monoid.
|
||||
fn one() -> Self;
|
||||
}
|
||||
|
||||
macro_rules! impl_one_float {
|
||||
($t:ty) => {
|
||||
impl One for $t {
|
||||
#[inline(always)]
|
||||
fn one() -> Self {
|
||||
1.
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl_one_float!(f32);
|
||||
impl_one_float!(f64);
|
||||
|
||||
/// Types with a sane definition of π and cosine.
|
||||
pub trait Trigo {
|
||||
/// π.
|
||||
fn pi() -> Self;
|
||||
|
||||
/// Cosine of the argument.
|
||||
fn cos(self) -> Self;
|
||||
}
|
||||
|
||||
impl Trigo for f32 {
|
||||
#[inline(always)]
|
||||
fn pi() -> Self {
|
||||
f32::consts::PI
|
||||
}
|
||||
|
||||
#[inline(always)]
|
||||
fn cos(self) -> Self {
|
||||
#[cfg(feature = "std")]
|
||||
{
|
||||
self.cos()
|
||||
}
|
||||
|
||||
#[cfg(not(feature = "std"))]
|
||||
{
|
||||
unsafe { cosf32(self) }
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl Trigo for f64 {
|
||||
#[inline(always)]
|
||||
fn pi() -> Self {
|
||||
f64::consts::PI
|
||||
}
|
||||
|
||||
#[inline(always)]
|
||||
fn cos(self) -> Self {
|
||||
#[cfg(feature = "std")]
|
||||
{
|
||||
self.cos()
|
||||
}
|
||||
|
||||
#[cfg(not(feature = "std"))]
|
||||
{
|
||||
unsafe { cosf64(self) }
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// 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_def<V, T>(x: (V, T), a: (V, T), b: (V, T), y: (V, T), t: T) -> V
|
||||
where V: Additive + Linear<T>,
|
||||
T: Additive + Mul<T, Output = T> + One {
|
||||
// some stupid generic constants, because Rust doesn’t have polymorphic literals…
|
||||
let one_t = T::one();
|
||||
let two_t = one_t + one_t; // lolololol
|
||||
let three_t = two_t + one_t; // megalol
|
||||
|
||||
// sampler stuff
|
||||
let t2 = t * t;
|
||||
let t3 = t2 * t;
|
||||
let two_t3 = t3 * two_t;
|
||||
let three_t2 = t2 * three_t;
|
||||
|
||||
// tangents
|
||||
let m0 = (b.0 - x.0).outer_div(b.1 - x.1);
|
||||
let m1 = (y.0 - a.0).outer_div(y.1 - a.1);
|
||||
|
||||
a.0.outer_mul(two_t3 - three_t2 + one_t) + m0.outer_mul(t3 - t2 * two_t + t) + b.0.outer_mul(three_t2 - two_t3) + m1.outer_mul(t3 - t2)
|
||||
}
|
||||
|
||||
macro_rules! impl_interpolate_simple {
|
||||
($t:ty) => {
|
||||
impl Interpolate<$t> for $t {
|
||||
fn lerp(a: Self, b: Self, t: $t) -> Self {
|
||||
a * (1. - t) + b * t
|
||||
}
|
||||
|
||||
fn cubic_hermite(x: (Self, $t), a: (Self, $t), b: (Self, $t), y: (Self, $t), t: $t) -> Self {
|
||||
cubic_hermite_def(x, a, b, y, t)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl_interpolate_simple!(f32);
|
||||
impl_interpolate_simple!(f64);
|
||||
|
||||
macro_rules! impl_interpolate_via {
|
||||
($t:ty, $v:ty) => {
|
||||
impl Interpolate<$t> for $v {
|
||||
fn lerp(a: Self, b: Self, t: $t) -> Self {
|
||||
a * (1. - t as $v) + b * t as $v
|
||||
}
|
||||
|
||||
fn cubic_hermite((x, xt): (Self, $t), (a, at): (Self, $t), (b, bt): (Self, $t), (y, yt): (Self, $t), t: $t) -> Self {
|
||||
cubic_hermite_def((x, xt as $v), (a, at as $v), (b, bt as $v), (y, yt as $v), t as $v)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl_interpolate_via!(f32, f64);
|
||||
impl_interpolate_via!(f64, f32);
|
30
src/interpolation.rs
Normal file
30
src/interpolation.rs
Normal file
@ -0,0 +1,30 @@
|
||||
#[cfg(feature = "serialization")] use serde_derive::{Deserialize, Serialize};
|
||||
|
||||
/// Interpolation mode.
|
||||
#[derive(Copy, Clone, Debug)]
|
||||
#[cfg_attr(feature = "serialization", derive(Deserialize, Serialize))]
|
||||
#[cfg_attr(feature = "serialization", serde(rename_all = "snake_case"))]
|
||||
pub enum Interpolation<T> {
|
||||
/// Hold a [`Key`] until the interpolator value passes the normalized step threshold, in which
|
||||
/// case the next key is used.
|
||||
///
|
||||
/// > Note: if you set the threshold to `0.5`, the first key will be used until half the time
|
||||
/// > 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(T),
|
||||
/// Linear interpolation between a key and the next one.
|
||||
Linear,
|
||||
/// Cosine interpolation between a key and the next one.
|
||||
Cosine,
|
||||
/// Catmull-Rom interpolation, performing a cubic Hermite interpolation using four keys.
|
||||
CatmullRom
|
||||
}
|
||||
|
||||
impl<T> Default for Interpolation<T> {
|
||||
/// `Interpolation::Linear` is the default.
|
||||
fn default() -> Self {
|
||||
Interpolation::Linear
|
||||
}
|
||||
}
|
||||
|
36
src/iter.rs
Normal file
36
src/iter.rs
Normal file
@ -0,0 +1,36 @@
|
||||
use crate::{Key, Spline};
|
||||
|
||||
/// Iterator over spline keys.
|
||||
///
|
||||
/// This iterator type assures you to iterate over sorted keys.
|
||||
pub struct Iter<'a, T, V> where T: 'a, V: 'a {
|
||||
anim_param: &'a Spline<T, V>,
|
||||
i: usize
|
||||
}
|
||||
|
||||
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);
|
||||
|
||||
if let Some(_) = r {
|
||||
self.i += 1;
|
||||
}
|
||||
|
||||
r
|
||||
}
|
||||
}
|
||||
|
||||
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 {
|
||||
anim_param: self,
|
||||
i: 0
|
||||
}
|
||||
}
|
||||
}
|
||||
|
28
src/key.rs
Normal file
28
src/key.rs
Normal file
@ -0,0 +1,28 @@
|
||||
#[cfg(feature = "serialization")] use serde_derive::{Deserialize, Serialize};
|
||||
|
||||
use crate::interpolation::Interpolation;
|
||||
|
||||
/// A spline control point.
|
||||
///
|
||||
/// This type associates a value at a given interpolation parameter value. It also contains an
|
||||
/// interpolation hint used to determine how to interpolate values on the segment defined by this
|
||||
/// key and the next one – if existing.
|
||||
#[derive(Copy, Clone, Debug)]
|
||||
#[cfg_attr(feature = "serialization", derive(Deserialize, Serialize))]
|
||||
#[cfg_attr(feature = "serialization", serde(rename_all = "snake_case"))]
|
||||
pub struct Key<T, V> {
|
||||
/// Interpolation parameter at which the [`Key`] should be reached.
|
||||
pub t: T,
|
||||
/// Held value.
|
||||
pub value: V,
|
||||
/// Interpolation mode.
|
||||
pub interpolation: Interpolation<T>
|
||||
}
|
||||
|
||||
impl<T, V> Key<T, V> {
|
||||
/// Create a new key.
|
||||
pub fn new(t: T, value: V, interpolation: Interpolation<T>) -> Self {
|
||||
Key { t, value, interpolation }
|
||||
}
|
||||
}
|
||||
|
376
src/lib.rs
376
src/lib.rs
@ -45,7 +45,7 @@
|
||||
//! # let end = Key::new(1., 10., Interpolation::Linear);
|
||||
//! # let spline = Spline::from_vec(vec![start, end]);
|
||||
//! assert_eq!(spline.sample(0.), Some(0.));
|
||||
//! assert_eq!(spline.clamped_sample(1.), 10.);
|
||||
//! assert_eq!(spline.clamped_sample(1.), Some(10.));
|
||||
//! assert_eq!(spline.sample(1.1), None);
|
||||
//! ```
|
||||
//!
|
||||
@ -58,13 +58,14 @@
|
||||
//! # let start = Key::new(0., 0., Interpolation::Linear);
|
||||
//! # let end = Key::new(1., 10., Interpolation::Linear);
|
||||
//! # let spline = Spline::from_vec(vec![start, end]);
|
||||
//! assert_eq!(spline.clamped_sample(-0.9), 0.); // clamped to the first key
|
||||
//! assert_eq!(spline.clamped_sample(1.1), 10.); // clamped to the last key
|
||||
//! assert_eq!(spline.clamped_sample(-0.9), Some(0.)); // clamped to the first key
|
||||
//! assert_eq!(spline.clamped_sample(1.1), Some(10.)); // clamped to the last key
|
||||
//! ```
|
||||
//!
|
||||
//! # Features and customization
|
||||
//!
|
||||
//! This crate was written with features baked in and hidden behind feature-gates. The idea is that
|
||||
//! the default configuration (i.e. you just add `"spline = …"` to your `Cargo.toml`) will always
|
||||
//! the default configuration (i.e. you just add `"splines = …"` to your `Cargo.toml`) will always
|
||||
//! give you the minimal, core and raw concepts of what splines, keys / knots and interpolation
|
||||
//! modes are. However, you might want more. Instead of letting other people do the extra work to
|
||||
//! add implementations for very famous and useful traits – and do it in less efficient way, because
|
||||
@ -81,363 +82,32 @@
|
||||
//! types exported by this crate.
|
||||
//! + Enable with the `"serialization"` feature.
|
||||
//! - **[cgmath](https://crates.io/crates/cgmath) implementors.**
|
||||
//! + Adds some usefull implementations of `Interpolate` for some cgmath types.
|
||||
//! + Adds some useful implementations of `Interpolate` for some cgmath types.
|
||||
//! + Enable with the `"impl-cgmath"` feature.
|
||||
//! - **Standard library / no stdandard library.**
|
||||
//! - **[nalgebra](https://crates.io/crates/nalgebra) implementors.**
|
||||
//! + Adds some useful implementations of `Interpolate` for some nalgebra types.
|
||||
//! + Enable with the `"impl-nalgebra"` feature.
|
||||
//! - **Standard library / no standard library.**
|
||||
//! + It’s possible to compile against the standard library or go on your own without it.
|
||||
//! + Compiling with the standard library is enabled by default.
|
||||
//! + Use `defaut-features = []` in your `Cargo.toml` to disable.
|
||||
//! + Enable explicitly with the `"std"` feataure.
|
||||
//! + Use `default-features = []` in your `Cargo.toml` to disable.
|
||||
//! + Enable explicitly with the `"std"` feature.
|
||||
|
||||
#![cfg_attr(not(feature = "std"), no_std)]
|
||||
#![cfg_attr(not(feature = "std"), feature(alloc))]
|
||||
#![cfg_attr(not(feature = "std"), feature(core_intrinsics))]
|
||||
|
||||
// on no_std, we also need the alloc crate for Vec
|
||||
#[cfg(not(feature = "std"))] extern crate alloc;
|
||||
|
||||
#[cfg(feature = "impl-cgmath")] extern crate cgmath;
|
||||
#[cfg(feature = "impl-cgmath")] mod cgmath;
|
||||
pub mod interpolate;
|
||||
pub mod interpolation;
|
||||
pub mod iter;
|
||||
pub mod key;
|
||||
#[cfg(feature = "impl-nalgebra")] mod nalgebra;
|
||||
pub mod spline;
|
||||
|
||||
#[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 = "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};
|
||||
|
||||
/// A spline control point.
|
||||
///
|
||||
/// This type associates a value at a given interpolation parameter value. It also contains an
|
||||
/// interpolation hint used to determine how to interpolate values on the segment defined by this
|
||||
/// key and the next one – if existing.
|
||||
#[derive(Copy, Clone, Debug)]
|
||||
#[cfg_attr(feature = "serialization", derive(Deserialize, Serialize))]
|
||||
#[cfg_attr(feature = "serialization", serde(rename_all = "snake_case"))]
|
||||
pub struct Key<T> {
|
||||
/// Interpolation parameter at which the [`Key`] should be reached.
|
||||
pub t: f32,
|
||||
/// Held value.
|
||||
pub value: T,
|
||||
/// Interpolation mode.
|
||||
pub interpolation: Interpolation
|
||||
}
|
||||
|
||||
impl<T> Key<T> {
|
||||
/// Create a new key.
|
||||
pub fn new(t: f32, value: T, interpolation: Interpolation) -> Self {
|
||||
Key {
|
||||
t: t,
|
||||
value: value,
|
||||
interpolation: interpolation
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Interpolation mode.
|
||||
#[derive(Copy, Clone, Debug)]
|
||||
#[cfg_attr(feature = "serialization", derive(Deserialize, Serialize))]
|
||||
#[cfg_attr(feature = "serialization", serde(rename_all = "snake_case"))]
|
||||
pub enum Interpolation {
|
||||
/// Hold a [`Key`] until the time passes the normalized step threshold, in which case the next
|
||||
/// key is used.
|
||||
///
|
||||
/// *Note: if you set the threshold to `0.5`, the first key will be used until the time is half
|
||||
/// 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),
|
||||
/// Linear interpolation between a key and the next one.
|
||||
Linear,
|
||||
/// Cosine interpolation between a key and the next one.
|
||||
Cosine,
|
||||
/// Catmull-Rom interpolation.
|
||||
CatmullRom
|
||||
}
|
||||
|
||||
impl Default for Interpolation {
|
||||
/// `Interpolation::Linear` is the default.
|
||||
fn default() -> Self {
|
||||
Interpolation::Linear
|
||||
}
|
||||
}
|
||||
|
||||
/// 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>>);
|
||||
|
||||
impl<T> Spline<T> {
|
||||
/// 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 {
|
||||
keys.sort_by(|k0, k1| k0.t.partial_cmp(&k1.t).unwrap_or(Ordering::Less));
|
||||
|
||||
Spline(keys)
|
||||
}
|
||||
|
||||
/// Create a new spline by consuming an `Iterater<Item = Key<T>>`. They keys don’t have to be
|
||||
/// sorted.
|
||||
///
|
||||
/// # Note on iterators
|
||||
///
|
||||
/// 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>> {
|
||||
Self::from_vec(iter.collect())
|
||||
}
|
||||
|
||||
/// Retrieve the keys of a spline.
|
||||
pub fn keys(&self) -> &[Key<T>] {
|
||||
&self.0
|
||||
}
|
||||
|
||||
/// Sample a spline at a given time.
|
||||
///
|
||||
/// The current implementation, based on immutability, cannot perform in constant time. This means
|
||||
/// that sampling’s processing complexity is currently *O(log n)*. It’s possible to achieve *O(1)*
|
||||
/// performance by using a slightly different spline type. If you are interested by this feature,
|
||||
/// an implementation for a dedicated type is foreseen yet not started yet.
|
||||
///
|
||||
/// # Return
|
||||
///
|
||||
/// `None` if you try to sample a value at a time that has no key associated with. That can also
|
||||
/// happen if you try to sample between two keys with a specific interpolation mode that make the
|
||||
/// 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 {
|
||||
let keys = &self.0;
|
||||
let i = search_lower_cp(keys, t)?;
|
||||
let cp0 = &keys[i];
|
||||
|
||||
match cp0.interpolation {
|
||||
Interpolation::Step(threshold) => {
|
||||
let cp1 = &keys[i+1];
|
||||
let nt = normalize_time(t, cp0, cp1);
|
||||
Some(if nt < threshold { cp0.value } else { cp1.value })
|
||||
},
|
||||
Interpolation::Linear => {
|
||||
let cp1 = &keys[i+1];
|
||||
let nt = normalize_time(t, cp0, cp1);
|
||||
|
||||
Some(Interpolate::lerp(cp0.value, cp1.value, nt))
|
||||
},
|
||||
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 }
|
||||
}
|
||||
};
|
||||
|
||||
Some(Interpolate::lerp(cp0.value, cp1.value, cos_nt))
|
||||
},
|
||||
Interpolation::CatmullRom => {
|
||||
// We need at least four points for Catmull Rom; ensure we have them, otherwise, return
|
||||
// None.
|
||||
if i == 0 || i >= keys.len() - 2 {
|
||||
None
|
||||
} else {
|
||||
let cp1 = &keys[i+1];
|
||||
let cpm0 = &keys[i-1];
|
||||
let cpm1 = &keys[i+2];
|
||||
let nt = normalize_time(t, cp0, cp1);
|
||||
|
||||
Some(Interpolate::cubic_hermite((cpm0.value, cpm0.t), (cp0.value, cp0.t), (cp1.value, cp1.t), (cpm1.value, cpm1.t), nt))
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Sample a spline at a given time with clamping.
|
||||
///
|
||||
/// # 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`.
|
||||
///
|
||||
/// # Panic
|
||||
///
|
||||
/// This function panics if you have no key.
|
||||
pub fn clamped_sample(&self, t: f32) -> T where T: Interpolate {
|
||||
let first = self.0.first().unwrap();
|
||||
let last = self.0.last().unwrap();
|
||||
|
||||
if t <= first.t {
|
||||
return first.value;
|
||||
} else if t >= last.t {
|
||||
return last.value;
|
||||
}
|
||||
|
||||
self.sample(t).unwrap()
|
||||
}
|
||||
}
|
||||
|
||||
/// 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>,
|
||||
i: usize
|
||||
}
|
||||
|
||||
impl<'a, T> Iterator for Iter<'a, T> {
|
||||
type Item = &'a Key<T>;
|
||||
|
||||
fn next(&mut self) -> Option<Self::Item> {
|
||||
let r = self.anim_param.0.get(self.i);
|
||||
|
||||
if let Some(_) = r {
|
||||
self.i += 1;
|
||||
}
|
||||
|
||||
r
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a, T> IntoIterator for &'a Spline<T> {
|
||||
type Item = &'a Key<T>;
|
||||
type IntoIter = Iter<'a, T>;
|
||||
|
||||
fn into_iter(self) -> Self::IntoIter {
|
||||
Iter {
|
||||
anim_param: self,
|
||||
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)
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(feature = "impl-cgmath")]
|
||||
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)
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(feature = "impl-cgmath")]
|
||||
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)
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(feature = "impl-cgmath")]
|
||||
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)
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(feature = "impl-cgmath")]
|
||||
impl Interpolate for Quaternion<f32> {
|
||||
fn lerp(a: Self, b: Self, t: f32) -> Self {
|
||||
a.nlerp(b, t)
|
||||
}
|
||||
}
|
||||
|
||||
// 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
|
||||
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)]
|
||||
pub(crate) fn normalize_time<T>(t: f32, cp: &Key<T>, cp1: &Key<T>) -> f32 {
|
||||
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> {
|
||||
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)
|
||||
}
|
||||
pub use crate::interpolate::Interpolate;
|
||||
pub use crate::interpolation::Interpolation;
|
||||
pub use crate::key::Key;
|
||||
pub use crate::spline::Spline;
|
||||
|
72
src/nalgebra.rs
Normal file
72
src/nalgebra.rs
Normal file
@ -0,0 +1,72 @@
|
||||
use alga::general::{ClosedAdd, ClosedDiv, ClosedMul, ClosedSub};
|
||||
use nalgebra::{
|
||||
DefaultAllocator, DimName, Point, Scalar, Vector, Vector1, Vector2, Vector3, Vector4, Vector5,
|
||||
Vector6
|
||||
};
|
||||
use nalgebra::allocator::Allocator;
|
||||
use num_traits as nt;
|
||||
use std::ops::Mul;
|
||||
|
||||
use crate::interpolate::{Interpolate, Linear, Additive, One, cubic_hermite_def};
|
||||
|
||||
macro_rules! impl_interpolate_vector {
|
||||
($($t:tt)*) => {
|
||||
// implement Linear
|
||||
impl<T> Linear<T> for $($t)*<T> where T: Scalar + ClosedMul + ClosedDiv {
|
||||
#[inline(always)]
|
||||
fn outer_mul(self, t: T) -> Self {
|
||||
self * t
|
||||
}
|
||||
|
||||
#[inline(always)]
|
||||
fn outer_div(self, t: T) -> Self {
|
||||
self / t
|
||||
}
|
||||
}
|
||||
|
||||
impl<T, V> Interpolate<T> for $($t)*<V>
|
||||
where Self: Linear<T>,
|
||||
T: Additive + One + Mul<T, Output = T>,
|
||||
V: nt::One +
|
||||
nt::Zero +
|
||||
Additive +
|
||||
Scalar +
|
||||
ClosedAdd +
|
||||
ClosedMul +
|
||||
ClosedSub +
|
||||
Interpolate<T> {
|
||||
#[inline(always)]
|
||||
fn lerp(a: Self, b: Self, t: T) -> Self {
|
||||
Vector::zip_map(&a, &b, |c1, c2| Interpolate::lerp(c1, c2, t))
|
||||
}
|
||||
|
||||
#[inline(always)]
|
||||
fn cubic_hermite(x: (Self, T), a: (Self, T), b: (Self, T), y: (Self, T), t: T) -> Self {
|
||||
cubic_hermite_def(x, a, b, y, t)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl_interpolate_vector!(Vector1);
|
||||
impl_interpolate_vector!(Vector2);
|
||||
impl_interpolate_vector!(Vector3);
|
||||
impl_interpolate_vector!(Vector4);
|
||||
impl_interpolate_vector!(Vector5);
|
||||
impl_interpolate_vector!(Vector6);
|
||||
|
||||
impl<T, D> Linear<T> for Point<T, D>
|
||||
where D: DimName,
|
||||
DefaultAllocator: Allocator<T, D>,
|
||||
<DefaultAllocator as Allocator<T, D>>::Buffer: Copy,
|
||||
T: Scalar + ClosedDiv + ClosedMul {
|
||||
#[inline(always)]
|
||||
fn outer_mul(self, t: T) -> Self {
|
||||
self * t
|
||||
}
|
||||
|
||||
#[inline(always)]
|
||||
fn outer_div(self, t: T) -> Self {
|
||||
self / t
|
||||
}
|
||||
}
|
179
src/spline.rs
Normal file
179
src/spline.rs
Normal file
@ -0,0 +1,179 @@
|
||||
#[cfg(feature = "serialization")] use serde_derive::{Deserialize, Serialize};
|
||||
#[cfg(not(feature = "std"))] use alloc::vec::Vec;
|
||||
#[cfg(feature = "std")] use std::cmp::Ordering;
|
||||
#[cfg(feature = "std")] use std::ops::{Div, Mul};
|
||||
#[cfg(not(feature = "std"))] use core::ops::{Div, Mul};
|
||||
#[cfg(not(feature = "std"))] use core::cmp::Ordering;
|
||||
|
||||
use crate::interpolate::{Interpolate, Additive, One, Trigo};
|
||||
use crate::interpolation::Interpolation;
|
||||
use crate::key::Key;
|
||||
|
||||
/// Spline curve used to provide interpolation between control points (keys).
|
||||
#[derive(Debug, Clone)]
|
||||
#[cfg_attr(feature = "serialization", derive(Deserialize, Serialize))]
|
||||
pub struct Spline<T, V>(pub(crate) Vec<Key<T, V>>);
|
||||
|
||||
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, V>>) -> Self where T: PartialOrd {
|
||||
keys.sort_by(|k0, k1| k0.t.partial_cmp(&k1.t).unwrap_or(Ordering::Less));
|
||||
|
||||
Spline(keys)
|
||||
}
|
||||
|
||||
/// Create a new spline by consuming an `Iterater<Item = Key<T>>`. They keys don’t have to be
|
||||
/// sorted.
|
||||
///
|
||||
/// # Note on iterators
|
||||
///
|
||||
/// 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, V>>, T: PartialOrd {
|
||||
Self::from_vec(iter.collect())
|
||||
}
|
||||
|
||||
/// Retrieve the keys of a spline.
|
||||
pub fn keys(&self) -> &[Key<T, V>] {
|
||||
&self.0
|
||||
}
|
||||
|
||||
/// Sample a spline at a given time.
|
||||
///
|
||||
/// The current implementation, based on immutability, cannot perform in constant time. This means
|
||||
/// that sampling’s processing complexity is currently *O(log n)*. It’s possible to achieve *O(1)*
|
||||
/// performance by using a slightly different spline type. If you are interested by this feature,
|
||||
/// an implementation for a dedicated type is foreseen yet not started yet.
|
||||
///
|
||||
/// # Return
|
||||
///
|
||||
/// `None` if you try to sample a value at a time that has no key associated with. That can also
|
||||
/// happen if you try to sample between two keys with a specific interpolation mode that makes the
|
||||
/// 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: T) -> Option<V>
|
||||
where T: Additive + One + Trigo + Mul<T, Output = T> + Div<T, Output = T> + PartialOrd,
|
||||
V: Interpolate<T> {
|
||||
let keys = &self.0;
|
||||
let i = search_lower_cp(keys, t)?;
|
||||
let cp0 = &keys[i];
|
||||
|
||||
match cp0.interpolation {
|
||||
Interpolation::Step(threshold) => {
|
||||
let cp1 = &keys[i+1];
|
||||
let nt = normalize_time(t, cp0, cp1);
|
||||
Some(if nt < threshold { cp0.value } else { cp1.value })
|
||||
}
|
||||
|
||||
Interpolation::Linear => {
|
||||
let cp1 = &keys[i+1];
|
||||
let nt = normalize_time(t, cp0, cp1);
|
||||
|
||||
Some(Interpolate::lerp(cp0.value, cp1.value, nt))
|
||||
}
|
||||
|
||||
Interpolation::Cosine => {
|
||||
let two_t = T::one() + T::one();
|
||||
let cp1 = &keys[i+1];
|
||||
let nt = normalize_time(t, cp0, cp1);
|
||||
let cos_nt = (T::one() - (nt * T::pi()).cos()) / two_t;
|
||||
|
||||
Some(Interpolate::lerp(cp0.value, cp1.value, cos_nt))
|
||||
}
|
||||
|
||||
Interpolation::CatmullRom => {
|
||||
// We need at least four points for Catmull Rom; ensure we have them, otherwise, return
|
||||
// None.
|
||||
if i == 0 || i >= keys.len() - 2 {
|
||||
None
|
||||
} else {
|
||||
let cp1 = &keys[i+1];
|
||||
let cpm0 = &keys[i-1];
|
||||
let cpm1 = &keys[i+2];
|
||||
let nt = normalize_time(t, cp0, cp1);
|
||||
|
||||
Some(Interpolate::cubic_hermite((cpm0.value, cpm0.t), (cp0.value, cp0.t), (cp1.value, cp1.t), (cpm1.value, cpm1.t), nt))
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Sample a spline at a given time with clamping.
|
||||
///
|
||||
/// # 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`.
|
||||
///
|
||||
/// # Error
|
||||
///
|
||||
/// This function returns `None` if you have no key.
|
||||
pub fn clamped_sample(&self, t: T) -> Option<V>
|
||||
where T: Additive + One + Trigo + Mul<T, Output = T> + Div<T, Output = T> + PartialOrd,
|
||||
V: Interpolate<T> {
|
||||
if self.0.is_empty() {
|
||||
return None;
|
||||
}
|
||||
|
||||
self.sample(t).or_else(move || {
|
||||
let first = self.0.first().unwrap();
|
||||
if t <= first.t {
|
||||
Some(first.value)
|
||||
} else {
|
||||
let last = self.0.last().unwrap();
|
||||
|
||||
if t >= last.t {
|
||||
Some(last.value)
|
||||
} else {
|
||||
None
|
||||
}
|
||||
}
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
// Normalize a time ([0;1]) given two control points.
|
||||
#[inline(always)]
|
||||
pub(crate) fn normalize_time<T, V>(
|
||||
t: T,
|
||||
cp: &Key<T, V>,
|
||||
cp1: &Key<T, V>
|
||||
) -> T where T: Additive + Div<T, Output = T> + PartialEq {
|
||||
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, V>(cps: &[Key<T, V>], t: T) -> Option<usize> where T: PartialOrd {
|
||||
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)
|
||||
}
|
108
tests/mod.rs
108
tests/mod.rs
@ -1,12 +1,13 @@
|
||||
extern crate splines;
|
||||
|
||||
use splines::{Interpolation, Key, Spline};
|
||||
|
||||
#[cfg(feature = "impl-cgmath")] use cgmath as cg;
|
||||
#[cfg(feature = "impl-nalgebra")] use nalgebra as na;
|
||||
|
||||
#[test]
|
||||
fn step_interpolation_0() {
|
||||
let start = Key::new(0., 0., Interpolation::Step(0.));
|
||||
let end = Key::new(1., 10., Interpolation::default());
|
||||
let spline = Spline::from_vec(vec![start, end]);
|
||||
fn step_interpolation_f32() {
|
||||
let start = Key::new(0., 0., Interpolation::Step(0.));
|
||||
let end = Key::new(1., 10., Interpolation::default());
|
||||
let spline = Spline::<f32, _>::from_vec(vec![start, end]);
|
||||
|
||||
assert_eq!(spline.sample(0.), Some(10.));
|
||||
assert_eq!(spline.sample(0.1), Some(10.));
|
||||
@ -14,13 +15,28 @@ fn step_interpolation_0() {
|
||||
assert_eq!(spline.sample(0.5), Some(10.));
|
||||
assert_eq!(spline.sample(0.9), Some(10.));
|
||||
assert_eq!(spline.sample(1.), None);
|
||||
assert_eq!(spline.clamped_sample(1.), 10.);
|
||||
assert_eq!(spline.clamped_sample(1.), Some(10.));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn step_interpolation_f64() {
|
||||
let start = Key::new(0., 0., Interpolation::Step(0.));
|
||||
let end = Key::new(1., 10., Interpolation::default());
|
||||
let spline = Spline::<f64, _>::from_vec(vec![start, end]);
|
||||
|
||||
assert_eq!(spline.sample(0.), Some(10.));
|
||||
assert_eq!(spline.sample(0.1), Some(10.));
|
||||
assert_eq!(spline.sample(0.2), Some(10.));
|
||||
assert_eq!(spline.sample(0.5), Some(10.));
|
||||
assert_eq!(spline.sample(0.9), Some(10.));
|
||||
assert_eq!(spline.sample(1.), None);
|
||||
assert_eq!(spline.clamped_sample(1.), Some(10.));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn step_interpolation_0_5() {
|
||||
let start = Key::new(0., 0., Interpolation::Step(0.5));
|
||||
let end = Key::new(1., 10., Interpolation::default());
|
||||
let start = Key::new(0., 0., Interpolation::Step(0.5));
|
||||
let end = Key::new(1., 10., Interpolation::default());
|
||||
let spline = Spline::from_vec(vec![start, end]);
|
||||
|
||||
assert_eq!(spline.sample(0.), Some(0.));
|
||||
@ -29,13 +45,13 @@ fn step_interpolation_0_5() {
|
||||
assert_eq!(spline.sample(0.5), Some(10.));
|
||||
assert_eq!(spline.sample(0.9), Some(10.));
|
||||
assert_eq!(spline.sample(1.), None);
|
||||
assert_eq!(spline.clamped_sample(1.), 10.);
|
||||
assert_eq!(spline.clamped_sample(1.), Some(10.));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn step_interpolation_0_75() {
|
||||
let start = Key::new(0., 0., Interpolation::Step(0.75));
|
||||
let end = Key::new(1., 10., Interpolation::default());
|
||||
let start = Key::new(0., 0., Interpolation::Step(0.75));
|
||||
let end = Key::new(1., 10., Interpolation::default());
|
||||
let spline = Spline::from_vec(vec![start, end]);
|
||||
|
||||
assert_eq!(spline.sample(0.), Some(0.));
|
||||
@ -44,13 +60,13 @@ fn step_interpolation_0_75() {
|
||||
assert_eq!(spline.sample(0.5), Some(0.));
|
||||
assert_eq!(spline.sample(0.9), Some(10.));
|
||||
assert_eq!(spline.sample(1.), None);
|
||||
assert_eq!(spline.clamped_sample(1.), 10.);
|
||||
assert_eq!(spline.clamped_sample(1.), Some(10.));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn step_interpolation_1() {
|
||||
let start = Key::new(0., 0., Interpolation::Step(1.));
|
||||
let end = Key::new(1., 10., Interpolation::default());
|
||||
let start = Key::new(0., 0., Interpolation::Step(1.));
|
||||
let end = Key::new(1., 10., Interpolation::default());
|
||||
let spline = Spline::from_vec(vec![start, end]);
|
||||
|
||||
assert_eq!(spline.sample(0.), Some(0.));
|
||||
@ -59,13 +75,13 @@ fn step_interpolation_1() {
|
||||
assert_eq!(spline.sample(0.5), Some(0.));
|
||||
assert_eq!(spline.sample(0.9), Some(0.));
|
||||
assert_eq!(spline.sample(1.), None);
|
||||
assert_eq!(spline.clamped_sample(1.), 10.);
|
||||
assert_eq!(spline.clamped_sample(1.), Some(10.));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn linear_interpolation() {
|
||||
let start = Key::new(0., 0., Interpolation::Linear);
|
||||
let end = Key::new(1., 10., Interpolation::default());
|
||||
let start = Key::new(0., 0., Interpolation::Linear);
|
||||
let end = Key::new(1., 10., Interpolation::default());
|
||||
let spline = Spline::from_vec(vec![start, end]);
|
||||
|
||||
assert_eq!(spline.sample(0.), Some(0.));
|
||||
@ -74,17 +90,17 @@ fn linear_interpolation() {
|
||||
assert_eq!(spline.sample(0.5), Some(5.));
|
||||
assert_eq!(spline.sample(0.9), Some(9.));
|
||||
assert_eq!(spline.sample(1.), None);
|
||||
assert_eq!(spline.clamped_sample(1.), 10.);
|
||||
assert_eq!(spline.clamped_sample(1.), Some(10.));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn linear_interpolation_several_keys() {
|
||||
let start = Key::new(0., 0., Interpolation::Linear);
|
||||
let k1 = Key::new(1., 5., Interpolation::Linear);
|
||||
let k2 = Key::new(2., 0., Interpolation::Linear);
|
||||
let k3 = Key::new(3., 1., Interpolation::Linear);
|
||||
let k4 = Key::new(10., 2., Interpolation::Linear);
|
||||
let end = Key::new(11., 4., Interpolation::default());
|
||||
let k1 = Key::new(1., 5., Interpolation::Linear);
|
||||
let k2 = Key::new(2., 0., Interpolation::Linear);
|
||||
let k3 = Key::new(3., 1., Interpolation::Linear);
|
||||
let k4 = Key::new(10., 2., Interpolation::Linear);
|
||||
let end = Key::new(11., 4., Interpolation::default());
|
||||
let spline = Spline::from_vec(vec![start, k1, k2, k3, k4, end]);
|
||||
|
||||
assert_eq!(spline.sample(0.), Some(0.));
|
||||
@ -99,17 +115,17 @@ fn linear_interpolation_several_keys() {
|
||||
assert_eq!(spline.sample(3.), Some(1.));
|
||||
assert_eq!(spline.sample(6.5), Some(1.5));
|
||||
assert_eq!(spline.sample(10.), Some(2.));
|
||||
assert_eq!(spline.clamped_sample(11.), 4.);
|
||||
assert_eq!(spline.clamped_sample(11.), Some(4.));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn several_interpolations_several_keys() {
|
||||
let start = Key::new(0., 0., Interpolation::Step(0.5));
|
||||
let k1 = Key::new(1., 5., Interpolation::Linear);
|
||||
let k2 = Key::new(2., 0., Interpolation::Step(0.1));
|
||||
let k3 = Key::new(3., 1., Interpolation::Linear);
|
||||
let k4 = Key::new(10., 2., Interpolation::Linear);
|
||||
let end = Key::new(11., 4., Interpolation::default());
|
||||
let k1 = Key::new(1., 5., Interpolation::Linear);
|
||||
let k2 = Key::new(2., 0., Interpolation::Step(0.1));
|
||||
let k3 = Key::new(3., 1., Interpolation::Linear);
|
||||
let k4 = Key::new(10., 2., Interpolation::Linear);
|
||||
let end = Key::new(11., 4., Interpolation::default());
|
||||
let spline = Spline::from_vec(vec![start, k1, k2, k3, k4, end]);
|
||||
|
||||
assert_eq!(spline.sample(0.), Some(0.));
|
||||
@ -121,10 +137,38 @@ fn several_interpolations_several_keys() {
|
||||
assert_eq!(spline.sample(1.5), Some(2.5));
|
||||
assert_eq!(spline.sample(2.), Some(0.));
|
||||
assert_eq!(spline.sample(2.05), Some(0.));
|
||||
assert_eq!(spline.sample(2.1), Some(0.));
|
||||
assert_eq!(spline.sample(2.099), Some(0.));
|
||||
assert_eq!(spline.sample(2.75), Some(1.));
|
||||
assert_eq!(spline.sample(3.), Some(1.));
|
||||
assert_eq!(spline.sample(6.5), Some(1.5));
|
||||
assert_eq!(spline.sample(10.), Some(2.));
|
||||
assert_eq!(spline.clamped_sample(11.), 4.);
|
||||
assert_eq!(spline.clamped_sample(11.), Some(4.));
|
||||
}
|
||||
|
||||
#[cfg(feature = "impl-cgmath")]
|
||||
#[test]
|
||||
fn cgmath_vector_interpolation() {
|
||||
use splines::Interpolate;
|
||||
|
||||
let start = cg::Vector2::new(0.0, 0.0);
|
||||
let mid = cg::Vector2::new(0.5, 0.5);
|
||||
let end = cg::Vector2::new(1.0, 1.0);
|
||||
|
||||
assert_eq!(Interpolate::lerp(start, end, 0.0), start);
|
||||
assert_eq!(Interpolate::lerp(start, end, 1.0), end);
|
||||
assert_eq!(Interpolate::lerp(start, end, 0.5), mid);
|
||||
}
|
||||
|
||||
#[cfg(feature = "impl-nalgebra")]
|
||||
#[test]
|
||||
fn nalgebra_vector_interpolation() {
|
||||
use splines::Interpolate;
|
||||
|
||||
let start = na::Vector2::new(0.0, 0.0);
|
||||
let mid = na::Vector2::new(0.5, 0.5);
|
||||
let end = na::Vector2::new(1.0, 1.0);
|
||||
|
||||
assert_eq!(Interpolate::lerp(start, end, 0.0), start);
|
||||
assert_eq!(Interpolate::lerp(start, end, 1.0), end);
|
||||
assert_eq!(Interpolate::lerp(start, end, 0.5), mid);
|
||||
}
|
||||
|
Reference in New Issue
Block a user