nalgebra/tests/linalg/tridiagonal.rs

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#![cfg(feature = "arbitrary")]
macro_rules! gen_tests(
($module: ident, $scalar: ty) => {
mod $module {
use std::cmp;
use na::{DMatrix, Matrix2, Matrix4};
#[allow(unused_imports)]
use core::helper::{RandScalar, RandComplex};
quickcheck! {
fn symm_tridiagonal(n: usize) -> bool {
let n = cmp::max(1, cmp::min(n, 50));
let m = DMatrix::<$scalar>::new_random(n, n).map(|e| e.0).hermitian_part();
let tri = m.clone().symmetric_tridiagonalize();
let recomp = tri.recompose();
relative_eq!(m.lower_triangle(), recomp.lower_triangle(), epsilon = 1.0e-7)
}
fn symm_tridiagonal_singular(n: usize) -> bool {
let n = cmp::max(1, cmp::min(n, 4));
let mut m = DMatrix::<$scalar>::new_random(n, n).map(|e| e.0).hermitian_part();
m.row_mut(n / 2).fill(na::zero());
m.column_mut(n / 2).fill(na::zero());
let tri = m.clone().symmetric_tridiagonalize();
let recomp = tri.recompose();
relative_eq!(m.lower_triangle(), recomp.lower_triangle(), epsilon = 1.0e-7)
}
fn symm_tridiagonal_static_square(m: Matrix4<$scalar>) -> bool {
let m = m.map(|e| e.0).hermitian_part();
let tri = m.symmetric_tridiagonalize();
let recomp = tri.recompose();
relative_eq!(m.lower_triangle(), recomp.lower_triangle(), epsilon = 1.0e-7)
}
fn symm_tridiagonal_static_square_2x2(m: Matrix2<$scalar>) -> bool {
let m = m.map(|e| e.0).hermitian_part();
let tri = m.symmetric_tridiagonalize();
let recomp = tri.recompose();
relative_eq!(m.lower_triangle(), recomp.lower_triangle(), epsilon = 1.0e-7)
}
}
}
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}
);
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gen_tests!(complex, RandComplex<f64>);
gen_tests!(f64, RandScalar<f64>);