Clean up dependencies

src/kernel.rs

@@ -10,21 +10,6 @@ pub use exponential::Exponential;
 pub use matern32::Matern32;
 pub use matern52::Matern52;
 
-#[inline]
-pub(crate) fn transition(t0: f64, t1: f64, feedback: Array2<f64>) -> Array2<f64> {
-    let a = feedback * (t1 - t0);
-
-    if a.shape() == [1, 1] {
-        array![[a[(0, 0)].exp()]]
-    } else {
-        let mut b = Array2::<f64>::zeros(a.dim());
-
-        crate::expm::expm(&a, &mut b);
-
-        b
-    }
-}
-
 pub(crate) fn distance(ts1: &[f64], ts2: &[f64]) -> Array2<f64> {
     let mut r = Array2::zeros((ts1.len(), ts2.len()));
 
@@ -54,27 +39,9 @@ pub trait Kernel {
         unimplemented!();
     }
 
-    fn transition(&self, t0: f64, t1: f64) -> Array2<f64> {
-        transition(t0, t1, self.feedback())
-    }
+    fn transition(&self, t0: f64, t1: f64) -> Array2<f64>;
 
     fn noise_cov(&self, _t0: f64, _t1: f64) -> Array2<f64> {
-        /*
-        mat = self.noise_effect.dot(self.noise_density).dot(self.noise_effect.T)
-        #print(g)
-        print(mat)
-        Phi = np.vstack((
-                np.hstack((self.feedback, mat)),
-                np.hstack((np.zeros_like(mat), -self.feedback.T))))
-        print(Phi)
-        m = self.order
-        AB = np.dot(sp.linalg.expm(Phi * (t2 - t1)), np.eye(2*m, m, k=-m))
-        print(AB)
-        return sp.linalg.solve(AB[m:,:].T, AB[:m,:].T)
-        */
-
-        // let mat = self.noise_effect()
-
         todo!();
     }
 }