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