Mercurial > repos > non-riemannian-opt / file revision

/*!
Implementations of the distance function and the distance function squared, on manifolds.
*/

use alg_tools::mapping::Apply;
use crate::manifold::ManifoldPoint;
use crate::fb::{Grad, Desc};

/// Structure for distance-to functions
pub struct DistTo<M : ManifoldPoint>(pub M);

impl<M : ManifoldPoint> Apply<M> for DistTo<M> {
    type Output = f64;

    fn apply(&self, x : M) -> Self::Output {
        self.0.dist_to(&x)
    }
}

impl<'a, M : ManifoldPoint> Apply<&'a M> for DistTo<M> {
    type Output = f64;

    fn apply(&self, x : &'a M) -> Self::Output {
        self.0.dist_to(x)
    }
}

/// Structure for distance-to functions
pub struct DistToSquaredDiv2<M : ManifoldPoint>(pub M);

impl<M : ManifoldPoint> Apply<M> for DistToSquaredDiv2<M> {
    type Output = f64;

    fn apply(&self, x : M) -> Self::Output {
        let d = self.0.dist_to(&x);
        d*d / 2.0
    }
}

impl<'a, M : ManifoldPoint> Apply<&'a M> for DistToSquaredDiv2<M> {
    type Output = f64;

    fn apply(&self, x : &'a M) -> Self::Output {
        let d = self.0.dist_to(x);
        d*d / 2.0
    }
}

impl<M : ManifoldPoint> Desc<M> for DistToSquaredDiv2<M> {
    fn desc(&self, τ : f64, x : M) -> M {
        let t = self.grad(&x) * τ;
        x.exp(&t)
    }
}

impl<M : ManifoldPoint> Grad<M> for DistToSquaredDiv2<M> {
    fn grad(&self, x : &M) -> M::Tangent {
       x.log(&self.0)
    }
}