Implement impl-nalgebra feature.
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427895ab10
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@ -21,14 +21,15 @@ maintenance = { status = "actively-developed" }
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[features]
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[features]
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default = ["std"]
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default = ["std"]
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serialization = ["serde", "serde_derive"]
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std = ["num-traits/std"]
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impl-cgmath = ["cgmath"]
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impl-cgmath = ["cgmath"]
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impl-nalgebra = ["nalgebra"]
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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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[dependencies]
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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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cgmath = { version = "0.17", optional = true }
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nalgebra = { version = ">=0.14, <0.19", optional = true }
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nalgebra = { version = ">=0.14, <0.19", optional = true }
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num-traits = { version = "0.2", default-features = false }
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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 = { version = "1", optional = true }
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serde_derive = { version = "1", optional = true }
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serde_derive = { version = "1", optional = true }
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@ -1,7 +1,11 @@
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#[cfg(feature = "std")] use std::ops::{Div, Mul};
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#[cfg(feature = "std")] use std::f32;
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#[cfg(not(feature = "std"))] use core::ops::{Div, Mul};
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#[cfg(not(feature = "std"))] use core::f32;
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#[cfg(not(feature = "std"))] use core::intrinsics::cosf32;
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use num_traits::Float;
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#[cfg(feature = "std")] use std::f64;
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#[cfg(not(feature = "std"))] use core::f64;
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#[cfg(not(feature = "std"))] use core::intrinsics::cosf64;
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#[cfg(feature = "std")] use std::ops::{Add, Mul, Sub};
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#[cfg(not(feature = "std"))] use core::ops::{Add, Mul, Sub};
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/// Keys that can be interpolated in between. Implementing this trait is required to perform
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/// Keys that can be interpolated in between. Implementing this trait is required to perform
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/// sampling on splines.
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/// sampling on splines.
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@ -20,15 +24,147 @@ pub trait Interpolate<T>: Sized + Copy {
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}
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}
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}
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}
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/// A trait for anything that supports additions, subtraction, multiplication and division.
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pub trait Additive:
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Copy +
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PartialEq +
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PartialOrd +
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Add<Self, Output = Self> +
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Sub<Self, Output = Self> {
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}
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impl<T> Additive for T
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where T: Copy +
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PartialEq +
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PartialOrd +
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Add<Self, Output = Self> +
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Sub<Self, Output = Self> {
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}
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/// Linear combination.
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pub trait Linear<T> {
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/// Apply an outer multiplication law.
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fn outer_mul(self, t: T) -> Self;
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/// Apply an outer division law.
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fn outer_div(self, t: T) -> Self;
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}
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macro_rules! impl_linear_simple {
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($t:ty) => {
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impl Linear<$t> for $t {
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fn outer_mul(self, t: $t) -> Self {
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self * t
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}
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/// Apply an outer division law.
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fn outer_div(self, t: $t) -> Self {
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self / t
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}
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}
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}
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}
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impl_linear_simple!(f32);
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impl_linear_simple!(f64);
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macro_rules! impl_linear_cast {
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($t:ty, $q:ty) => {
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impl Linear<$t> for $q {
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fn outer_mul(self, t: $t) -> Self {
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self * t as $q
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}
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/// Apply an outer division law.
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fn outer_div(self, t: $t) -> Self {
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self / t as $q
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}
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}
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}
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}
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impl_linear_cast!(f32, f64);
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impl_linear_cast!(f64, f32);
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/// Types with a neutral element for multiplication.
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pub trait One {
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/// Return the neutral element for the multiplicative monoid.
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fn one() -> Self;
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}
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macro_rules! impl_one_float {
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($t:ty) => {
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impl One for $t {
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#[inline(always)]
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fn one() -> Self {
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1.
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}
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}
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}
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}
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impl_one_float!(f32);
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impl_one_float!(f64);
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/// Types with a sane definition of π and cosine.
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pub trait Trigo {
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/// π.
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fn pi() -> Self;
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/// Cosine of the argument.
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fn cos(self) -> Self;
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}
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impl Trigo for f32 {
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#[inline(always)]
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fn pi() -> Self {
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f32::consts::PI
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}
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#[inline(always)]
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fn cos(self) -> Self {
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#[cfg(feature = "std")]
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{
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self.cos()
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}
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#[cfg(not(feature = "std"))]
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{
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unsafe { cosf32(self) }
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}
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}
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}
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impl Trigo for f64 {
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#[inline(always)]
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fn pi() -> Self {
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f64::consts::PI
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}
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#[inline(always)]
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fn cos(self) -> Self {
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#[cfg(feature = "std")]
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{
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self.cos()
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}
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#[cfg(not(feature = "std"))]
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{
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unsafe { cosf64(self) }
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}
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}
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}
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// Default implementation of Interpolate::cubic_hermite.
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// Default implementation of Interpolate::cubic_hermite.
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//
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//
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// `V` is the value being interpolated. `T` is the sampling value (also sometimes called time).
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// `V` is the value being interpolated. `T` is the sampling value (also sometimes called time).
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pub(crate) fn cubic_hermite_def<V, T>(x: (V, T), a: (V, T), b: (V, T), y: (V, T), t: T) -> V
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pub(crate) fn cubic_hermite_def<V, T>(x: (V, T), a: (V, T), b: (V, T), y: (V, T), t: T) -> V
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where V: Float + Mul<T, Output = V> + Div<T, Output = V>,
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where V: Additive + Linear<T>,
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T: Float {
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T: Additive + Mul<T, Output = T> + One {
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// some stupid generic constants, because Rust doesn’t have polymorphic literals…
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// some stupid generic constants, because Rust doesn’t have polymorphic literals…
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let two_t = T::one() + T::one(); // lolololol
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let one_t = T::one();
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let three_t = two_t + T::one(); // megalol
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let two_t = one_t + one_t; // lolololol
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let three_t = two_t + one_t; // megalol
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// sampler stuff
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// sampler stuff
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let t2 = t * t;
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let t2 = t * t;
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@ -37,10 +173,10 @@ where V: Float + Mul<T, Output = V> + Div<T, Output = V>,
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let three_t2 = t2 * three_t;
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let three_t2 = t2 * three_t;
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// tangents
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// tangents
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let m0 = (b.0 - x.0) / (b.1 - x.1);
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let m0 = (b.0 - x.0).outer_div(b.1 - x.1);
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let m1 = (y.0 - a.0) / (y.1 - a.1);
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let m1 = (y.0 - a.0).outer_div(y.1 - a.1);
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a.0 * (two_t3 - three_t2 + T::one()) + m0 * (t3 - t2 * two_t + t) + b.0 * (three_t2 - two_t3) + m1 * (t3 - t2)
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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)
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}
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}
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macro_rules! impl_interpolate_simple {
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macro_rules! impl_interpolate_simple {
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@ -76,4 +212,3 @@ macro_rules! impl_interpolate_via {
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impl_interpolate_via!(f32, f64);
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impl_interpolate_via!(f32, f64);
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impl_interpolate_via!(f64, f32);
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impl_interpolate_via!(f64, f32);
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@ -97,6 +97,8 @@
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#![cfg_attr(not(feature = "std"), feature(alloc))]
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#![cfg_attr(not(feature = "std"), feature(alloc))]
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#![cfg_attr(not(feature = "std"), feature(core_intrinsics))]
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#![cfg_attr(not(feature = "std"), feature(core_intrinsics))]
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#[cfg(not(feature = "std"))] extern crate alloc;
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#[cfg(feature = "impl-cgmath")] mod cgmath;
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#[cfg(feature = "impl-cgmath")] mod cgmath;
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pub mod interpolate;
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pub mod interpolate;
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pub mod interpolation;
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pub mod interpolation;
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@ -1,36 +1,63 @@
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use crate::Interpolate;
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use alga::general::{ClosedAdd, ClosedDiv, ClosedMul, ClosedSub};
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use nalgebra::{DefaultAllocator, DimName, Point, Scalar, Vector, Vector1, Vector2, Vector3, Vector4, Vector5, Vector6};
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use nalgebra::allocator::Allocator;
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use num_traits as nt;
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use std::ops::Mul;
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use nalgebra as na;
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use crate::interpolate::{Interpolate, Linear, Additive, One, cubic_hermite_def};
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use num_traits::Float;
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macro_rules! impl_interpolate_vector {
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macro_rules! impl_interpolate_na_vector {
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($($t:tt)*) => {
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($($t:tt)*) => {
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impl<T, V> Interpolate<T> for $($t)*<V> where T: Float, V: na::Scalar + Interpolate<T> {
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// implement Linear
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impl<T> Linear<T> for $($t)*<T> where T: Scalar + ClosedMul + ClosedDiv {
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fn outer_mul(self, t: T) -> Self {
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self * t
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}
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fn outer_div(self, t: T) -> Self {
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self / t
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}
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}
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impl<T, V> Interpolate<T> for $($t)*<V>
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where Self: Linear<T>,
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T: Additive + One + Mul<T, Output = T>,
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V: nt::One +
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nt::Zero +
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Additive +
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Scalar +
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ClosedAdd +
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ClosedMul +
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ClosedSub +
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Interpolate<T> {
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fn lerp(a: Self, b: Self, t: T) -> Self {
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fn lerp(a: Self, b: Self, t: T) -> Self {
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na::Vector::zip_map(&a, &b, |c1, c2| Interpolate::lerp(c1, c2, t))
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Vector::zip_map(&a, &b, |c1, c2| Interpolate::lerp(c1, c2, t))
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}
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fn cubic_hermite(x: (Self, T), a: (Self, T), b: (Self, T), y: (Self, T), t: T) -> Self {
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cubic_hermite_def(x, a, b, y, t)
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}
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}
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}
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}
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}
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}
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}
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}
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impl_interpolate_na_vector!(na::Vector1);
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impl_interpolate_vector!(Vector1);
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impl_interpolate_na_vector!(na::Vector2);
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impl_interpolate_vector!(Vector2);
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impl_interpolate_na_vector!(na::Vector3);
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impl_interpolate_vector!(Vector3);
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impl_interpolate_na_vector!(na::Vector4);
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impl_interpolate_vector!(Vector4);
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impl_interpolate_na_vector!(na::Vector5);
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impl_interpolate_vector!(Vector5);
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impl_interpolate_na_vector!(na::Vector6);
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impl_interpolate_vector!(Vector6);
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impl<T, N, D> Interpolate<T> for na::Point<N, D>
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impl<T, D> Linear<T> for Point<T, D>
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where D: na::DimName,
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where D: DimName,
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na::DefaultAllocator: na::allocator::Allocator<N, D>,
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DefaultAllocator: Allocator<T, D>,
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<na::DefaultAllocator as na::allocator::Allocator<N, D>>::Buffer: Copy,
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<DefaultAllocator as Allocator<T, D>>::Buffer: Copy,
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N: na::Scalar + Interpolate<T>,
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T: Scalar + ClosedDiv + ClosedMul {
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T: Float {
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fn outer_mul(self, t: T) -> Self {
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fn lerp(a: Self, b: Self, t: T) -> Self {
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self * t
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// The 'coords' of a point is just a vector, so we can interpolate component-wise
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}
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// over these vectors.
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let coords = na::Vector::zip_map(&a.coords, &b.coords, |c1, c2| Interpolate::lerp(c1, c2, t));
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fn outer_div(self, t: T) -> Self {
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na::Point::from(coords)
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self / t
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}
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}
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}
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}
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@ -1,14 +1,14 @@
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#[cfg(feature = "serialization")] use serde_derive::{Deserialize, Serialize};
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#[cfg(feature = "serialization")] use serde_derive::{Deserialize, Serialize};
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#[cfg(feature = "std")] use std::cmp::Ordering;
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#[cfg(not(feature = "std"))] use core::cmp::Ordering;
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#[cfg(not(feature = "std"))] use alloc::vec::Vec;
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#[cfg(not(feature = "std"))] use alloc::vec::Vec;
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#[cfg(feature = "std")] use std::cmp::Ordering;
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#[cfg(feature = "std")] use std::ops::{Div, Mul};
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#[cfg(not(feature = "std"))] use core::ops::{Div, Mul};
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#[cfg(not(feature = "std"))] use core::cmp::Ordering;
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use crate::interpolate::Interpolate;
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use crate::interpolate::{Interpolate, Additive, One, Trigo};
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use crate::interpolation::Interpolation;
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use crate::interpolation::Interpolation;
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use crate::key::Key;
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use crate::key::Key;
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use num_traits::{Float, FloatConst};
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/// Spline curve used to provide interpolation between control points (keys).
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/// Spline curve used to provide interpolation between control points (keys).
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#[derive(Debug, Clone)]
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#[derive(Debug, Clone)]
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#[cfg_attr(feature = "serialization", derive(Deserialize, Serialize))]
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#[cfg_attr(feature = "serialization", derive(Deserialize, Serialize))]
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@ -53,7 +53,7 @@ impl<T, V> Spline<T, V> {
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/// sampling impossible. For instance, `Interpolate::CatmullRom` requires *four* keys. If you’re
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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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/// 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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/// sampling.
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pub fn sample(&self, t: T) -> Option<V> where T: Float + FloatConst, V: Interpolate<T> {
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pub fn sample(&self, t: T) -> Option<V> where T: Additive + One + Trigo + Mul<T, Output = T> + Div<T, Output = T>, V: Interpolate<T> {
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let keys = &self.0;
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let keys = &self.0;
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let i = search_lower_cp(keys, t)?;
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let i = search_lower_cp(keys, t)?;
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let cp0 = &keys[i];
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let cp0 = &keys[i];
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@ -76,7 +76,7 @@ impl<T, V> Spline<T, V> {
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let two_t = T::one() + T::one();
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let two_t = T::one() + T::one();
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let cp1 = &keys[i+1];
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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 nt = normalize_time(t, cp0, cp1);
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let cos_nt = (T::one() - (nt * T::PI()).cos()) / two_t;
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let cos_nt = (T::one() - (nt * T::pi()).cos()) / two_t;
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Some(Interpolate::lerp(cp0.value, cp1.value, cos_nt))
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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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@ -108,7 +108,7 @@ impl<T, V> Spline<T, V> {
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/// # Error
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/// # Error
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///
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///
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/// This function returns `None` if you have no key.
|
/// This function returns `None` if you have no key.
|
||||||
pub fn clamped_sample(&self, t: T) -> Option<V> where T: Float + FloatConst, V: Interpolate<T> {
|
pub fn clamped_sample(&self, t: T) -> Option<V> where T: Additive + One + Trigo + Mul<T, Output = T> + Div<T, Output = T>, V: Interpolate<T> {
|
||||||
if self.0.is_empty() {
|
if self.0.is_empty() {
|
||||||
return None;
|
return None;
|
||||||
}
|
}
|
||||||
@ -136,7 +136,7 @@ pub(crate) fn normalize_time<T, V>(
|
|||||||
t: T,
|
t: T,
|
||||||
cp: &Key<T, V>,
|
cp: &Key<T, V>,
|
||||||
cp1: &Key<T, V>
|
cp1: &Key<T, V>
|
||||||
) -> T where T: Float {
|
) -> T where T: Additive + Div<T, Output = T> {
|
||||||
assert!(cp1.t != cp.t, "overlapping keys");
|
assert!(cp1.t != cp.t, "overlapping keys");
|
||||||
(t - cp.t) / (cp1.t - cp.t)
|
(t - cp.t) / (cp1.t - cp.t)
|
||||||
}
|
}
|
||||||
|
Loading…
Reference in New Issue
Block a user