use crate::{DotProduct, VectorSpace};
use num_traits::real::Real;
pub trait InnerSpace: DotProduct<Output = <Self as VectorSpace>::Scalar> {
fn magnitude2(self) -> Self::Scalar {
self.dot(self)
}
fn magnitude(self) -> Self::Scalar {
self.magnitude2().sqrt()
}
fn normalize(self) -> Self {
self / self.magnitude()
}
fn angle(self, other: Self) -> Self::Scalar {
(self.dot(other) / (self.magnitude() * other.magnitude())).acos()
}
fn distance(self, other: Self) -> Self::Scalar {
(self - other).magnitude()
}
fn with_magnitude(self, magnitude: Self::Scalar) -> Self {
self * (magnitude / self.magnitude())
}
fn with_direction(self, dir: Self) -> Self {
dir * self.magnitude()
}
fn query_axis(self, dir: Self) -> Self::Scalar {
self.dot(dir.normalize())
}
fn normalized_project(self, dir: Self) -> Self {
dir * self.dot(dir)
}
fn project(self, dir: Self) -> Self {
self.normalized_project(dir.normalize())
}
fn normalized_reject(self, dir: Self) -> Self {
self - self.normalized_project(dir)
}
fn reject(self, dir: Self) -> Self {
self.normalized_reject(dir.normalize())
}
fn normalized_reflect(self, dir: Self) -> Self {
let proj = self.normalized_project(dir);
proj + proj - self
}
fn reflect(self, dir: Self) -> Self {
self.normalized_reflect(dir.normalize())
}
}
impl InnerSpace for f32 {}
impl InnerSpace for f64 {}