nalgebra/tests/linalg/bidiagonal.rs

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#![cfg(feature = "arbitrary")]
macro_rules! gen_tests(
($module: ident, $scalar: ty) => {
mod $module {
use na::{DMatrix, Matrix2, Matrix3x5, Matrix4, Matrix5x3};
#[allow(unused_imports)]
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use crate::core::helper::{RandScalar, RandComplex};
quickcheck! {
fn bidiagonal(m: DMatrix<$scalar>) -> bool {
let m = m.map(|e| e.0);
if m.len() == 0 {
return true;
}
let bidiagonal = m.clone().bidiagonalize();
let (u, d, v_t) = bidiagonal.unpack();
relative_eq!(m, &u * d * &v_t, epsilon = 1.0e-7)
}
fn bidiagonal_static_5_3(m: Matrix5x3<$scalar>) -> bool {
let m = m.map(|e| e.0);
let bidiagonal = m.bidiagonalize();
let (u, d, v_t) = bidiagonal.unpack();
relative_eq!(m, &u * d * &v_t, epsilon = 1.0e-7)
}
fn bidiagonal_static_3_5(m: Matrix3x5<$scalar>) -> bool {
let m = m.map(|e| e.0);
let bidiagonal = m.bidiagonalize();
let (u, d, v_t) = bidiagonal.unpack();
relative_eq!(m, &u * d * &v_t, epsilon = 1.0e-7)
}
fn bidiagonal_static_square(m: Matrix4<$scalar>) -> bool {
let m = m.map(|e| e.0);
let bidiagonal = m.bidiagonalize();
let (u, d, v_t) = bidiagonal.unpack();
relative_eq!(m, &u * d * &v_t, epsilon = 1.0e-7)
}
fn bidiagonal_static_square_2x2(m: Matrix2<$scalar>) -> bool {
let m = m.map(|e| e.0);
let bidiagonal = m.bidiagonalize();
let (u, d, v_t) = bidiagonal.unpack();
relative_eq!(m, &u * d * &v_t, epsilon = 1.0e-7)
}
}
}
}
);
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gen_tests!(complex, RandComplex<f64>);
gen_tests!(f64, RandScalar<f64>);
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#[test]
fn bidiagonal_identity() {
let m = na::DMatrix::<f64>::identity(10, 10);
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let bidiagonal = m.clone().bidiagonalize();
let (u, d, v_t) = bidiagonal.unpack();
assert_eq!(m, &u * d * &v_t);
let m = na::DMatrix::<f64>::identity(10, 15);
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let bidiagonal = m.clone().bidiagonalize();
let (u, d, v_t) = bidiagonal.unpack();
assert_eq!(m, &u * d * &v_t);
let m = na::DMatrix::<f64>::identity(15, 10);
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let bidiagonal = m.clone().bidiagonalize();
let (u, d, v_t) = bidiagonal.unpack();
assert_eq!(m, &u * d * &v_t);
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}