nalgebra/nalgebra-lapack/tests/linalg/lu.rs

108 lines
3.2 KiB
Rust

use std::cmp;
use nl::LU;
use na::{DMatrix, DVector, Matrix3x4, Matrix4, Matrix4x3, Vector4};
quickcheck!{
fn lup(m: DMatrix<f64>) -> bool {
if m.len() != 0 {
let lup = LU::new(m.clone());
let l = lup.l();
let u = lup.u();
let mut computed1 = &l * &u;
lup.permute(&mut computed1);
let computed2 = lup.p() * l * u;
relative_eq!(computed1, m, epsilon = 1.0e-7) &&
relative_eq!(computed2, m, epsilon = 1.0e-7)
}
else {
true
}
}
fn lu_static(m: Matrix3x4<f64>) -> bool {
let lup = LU::new(m);
let l = lup.l();
let u = lup.u();
let mut computed1 = l * u;
lup.permute(&mut computed1);
let computed2 = lup.p() * l * u;
relative_eq!(computed1, m, epsilon = 1.0e-7) &&
relative_eq!(computed2, m, epsilon = 1.0e-7)
}
fn lu_solve(n: usize, nb: usize) -> bool {
if n != 0 {
let n = cmp::min(n, 25); // To avoid slowing down the test too much.
let nb = cmp::min(nb, 25); // To avoid slowing down the test too much.
let m = DMatrix::<f64>::new_random(n, n);
let lup = LU::new(m.clone());
let b1 = DVector::new_random(n);
let b2 = DMatrix::new_random(n, nb);
let sol1 = lup.solve(&b1).unwrap();
let sol2 = lup.solve(&b2).unwrap();
let tr_sol1 = lup.solve_transpose(&b1).unwrap();
let tr_sol2 = lup.solve_transpose(&b2).unwrap();
relative_eq!(&m * sol1, b1, epsilon = 1.0e-7) &&
relative_eq!(&m * sol2, b2, epsilon = 1.0e-7) &&
relative_eq!(m.transpose() * tr_sol1, b1, epsilon = 1.0e-7) &&
relative_eq!(m.transpose() * tr_sol2, b2, epsilon = 1.0e-7)
}
else {
true
}
}
fn lu_solve_static(m: Matrix4<f64>) -> bool {
let lup = LU::new(m);
let b1 = Vector4::new_random();
let b2 = Matrix4x3::new_random();
let sol1 = lup.solve(&b1).unwrap();
let sol2 = lup.solve(&b2).unwrap();
let tr_sol1 = lup.solve_transpose(&b1).unwrap();
let tr_sol2 = lup.solve_transpose(&b2).unwrap();
relative_eq!(m * sol1, b1, epsilon = 1.0e-7) &&
relative_eq!(m * sol2, b2, epsilon = 1.0e-7) &&
relative_eq!(m.transpose() * tr_sol1, b1, epsilon = 1.0e-7) &&
relative_eq!(m.transpose() * tr_sol2, b2, epsilon = 1.0e-7)
}
fn lu_inverse(n: usize) -> bool {
if n != 0 {
let n = cmp::min(n, 25); // To avoid slowing down the test too much.
let m = DMatrix::<f64>::new_random(n, n);
if let Some(m1) = LU::new(m.clone()).inverse() {
let id1 = &m * &m1;
let id2 = &m1 * &m;
return id1.is_identity(1.0e-7) && id2.is_identity(1.0e-7);
}
}
return true;
}
fn lu_inverse_static(m: Matrix4<f64>) -> bool {
match LU::new(m.clone()).inverse() {
Some(m1) => {
let id1 = &m * &m1;
let id2 = &m1 * &m;
id1.is_identity(1.0e-5) && id2.is_identity(1.0e-5)
},
None => true
}
}
}