51 lines
1.6 KiB
Rust
51 lines
1.6 KiB
Rust
#![cfg(feature = "arbitrary")]
|
|
|
|
use na::Matrix2;
|
|
|
|
#[test]
|
|
fn hessenberg_simple() {
|
|
let m = Matrix2::new(1.0, 0.0, 1.0, 3.0);
|
|
let hess = m.hessenberg();
|
|
let (p, h) = hess.unpack();
|
|
assert!(relative_eq!(m, p * h * p.transpose(), epsilon = 1.0e-7))
|
|
}
|
|
|
|
macro_rules! gen_tests(
|
|
($module: ident, $scalar: ty) => {
|
|
mod $module {
|
|
use na::{DMatrix, Matrix2, Matrix4};
|
|
use std::cmp;
|
|
#[allow(unused_imports)]
|
|
use crate::core::helper::{RandScalar, RandComplex};
|
|
|
|
quickcheck! {
|
|
fn hessenberg(n: usize) -> bool {
|
|
let n = cmp::max(1, cmp::min(n, 50));
|
|
let m = DMatrix::<$scalar>::new_random(n, n).map(|e| e.0);
|
|
|
|
let hess = m.clone().hessenberg();
|
|
let (p, h) = hess.unpack();
|
|
relative_eq!(m, &p * h * p.adjoint(), epsilon = 1.0e-7)
|
|
}
|
|
|
|
fn hessenberg_static_mat2(m: Matrix2<$scalar>) -> bool {
|
|
let m = m.map(|e| e.0);
|
|
let hess = m.hessenberg();
|
|
let (p, h) = hess.unpack();
|
|
relative_eq!(m, p * h * p.adjoint(), epsilon = 1.0e-7)
|
|
}
|
|
|
|
fn hessenberg_static(m: Matrix4<$scalar>) -> bool {
|
|
let m = m.map(|e| e.0);
|
|
let hess = m.hessenberg();
|
|
let (p, h) = hess.unpack();
|
|
relative_eq!(m, p * h * p.adjoint(), epsilon = 1.0e-7)
|
|
}
|
|
}
|
|
}
|
|
}
|
|
);
|
|
|
|
gen_tests!(complex, RandComplex<f64>);
|
|
gen_tests!(f64, RandScalar<f64>);
|