nalgebra/tests/linalg/cholesky.rs

81 lines
2.3 KiB
Rust

use std::cmp;
use na::{DMatrix, Matrix4x3, DVector, Vector4};
use na::dimension::U4;
use na::debug::RandomSDP;
#[cfg(feature = "arbitrary")]
quickcheck! {
fn cholesky(m: RandomSDP<f64>) -> bool {
let mut m = m.unwrap();
// Put garbage on the upper triangle to make sure it is not read by the decomposition.
m.fill_upper_triangle(23.0, 1);
let l = m.clone().cholesky().unwrap().unpack();
m.fill_upper_triangle_with_lower_triangle();
relative_eq!(m, &l * l.transpose(), epsilon = 1.0e-7)
}
fn cholesky_static(m: RandomSDP<f64, U4>) -> bool {
let m = m.unwrap();
let chol = m.cholesky().unwrap();
let l = chol.unpack();
if !relative_eq!(m, &l * l.transpose(), epsilon = 1.0e-7) {
false
}
else {
true
}
}
fn cholesky_solve(m: RandomSDP<f64>, nb: usize) -> bool {
let m = m.unwrap();
let n = m.nrows();
let nb = cmp::min(nb, 50); // To avoid slowing down the test too much.
let chol = m.clone().cholesky().unwrap();
let b1 = DVector::new_random(n);
let b2 = DMatrix::new_random(n, nb);
let sol1 = chol.solve(&b1);
let sol2 = chol.solve(&b2);
relative_eq!(&m * &sol1, b1, epsilon = 1.0e-7) &&
relative_eq!(&m * &sol2, b2, epsilon = 1.0e-7)
}
fn cholesky_solve_static(m: RandomSDP<f64, U4>) -> bool {
let m = m.unwrap();
let chol = m.clone().cholesky().unwrap();
let b1 = Vector4::new_random();
let b2 = Matrix4x3::new_random();
let sol1 = chol.solve(&b1);
let sol2 = chol.solve(&b2);
relative_eq!(m * sol1, b1, epsilon = 1.0e-7) &&
relative_eq!(m * sol2, b2, epsilon = 1.0e-7)
}
fn cholesky_inverse(m: RandomSDP<f64>) -> bool {
let m = m.unwrap();
let m1 = m.clone().cholesky().unwrap().inverse();
let id1 = &m * &m1;
let id2 = &m1 * &m;
id1.is_identity(1.0e-7) && id2.is_identity(1.0e-7)
}
fn cholesky_inverse_static(m: RandomSDP<f64, U4>) -> bool {
let m = m.unwrap();
let m1 = m.clone().cholesky().unwrap().inverse();
let id1 = &m * &m1;
let id2 = &m1 * &m;
id1.is_identity(1.0e-7) && id2.is_identity(1.0e-7)
}
}