#![cfg_attr(rustfmt, rustfmt_skip)] use na::Matrix3; #[test] fn lu_simple() { let m = Matrix3::new( 2.0, -1.0, 0.0, -1.0, 2.0, -1.0, 0.0, -1.0, 2.0); let lu = m.lu(); assert_eq!(lu.determinant(), 4.0); let (p, l, u) = lu.unpack(); let mut lu = l * u; p.inv_permute_rows(&mut lu); assert!(relative_eq!(m, lu, epsilon = 1.0e-7)); } #[test] fn lu_simple_with_pivot() { let m = Matrix3::new( 0.0, -1.0, 2.0, -1.0, 2.0, -1.0, 2.0, -1.0, 0.0); let lu = m.lu(); assert_eq!(lu.determinant(), -4.0); let (p, l, u) = lu.unpack(); let mut lu = l * u; p.inv_permute_rows(&mut lu); assert!(relative_eq!(m, lu, epsilon = 1.0e-7)); } #[cfg(feature = "arbitrary")] mod quickcheck_tests { #[allow(unused_imports)] use crate::core::helper::{RandScalar, RandComplex}; macro_rules! gen_tests( ($module: ident, $scalar: ty) => { mod $module { use std::cmp; use na::{DMatrix, Matrix4, Matrix4x3, Matrix5x3, Matrix3x5, DVector, Vector4}; #[allow(unused_imports)] use crate::core::helper::{RandScalar, RandComplex}; quickcheck! { fn lu(m: DMatrix<$scalar>) -> bool { let mut m = m; if m.len() == 0 { m = DMatrix::<$scalar>::new_random(1, 1); } let m = m.map(|e| e.0); let lu = m.clone().lu(); let (p, l, u) = lu.unpack(); let mut lu = l * u; p.inv_permute_rows(&mut lu); relative_eq!(m, lu, epsilon = 1.0e-7) } fn lu_static_3_5(m: Matrix3x5<$scalar>) -> bool { let m = m.map(|e| e.0); let lu = m.lu(); let (p, l, u) = lu.unpack(); let mut lu = l * u; p.inv_permute_rows(&mut lu); relative_eq!(m, lu, epsilon = 1.0e-7) } fn lu_static_5_3(m: Matrix5x3<$scalar>) -> bool { let m = m.map(|e| e.0); let lu = m.lu(); let (p, l, u) = lu.unpack(); let mut lu = l * u; p.inv_permute_rows(&mut lu); relative_eq!(m, lu, epsilon = 1.0e-7) } fn lu_static_square(m: Matrix4<$scalar>) -> bool { let m = m.map(|e| e.0); let lu = m.lu(); let (p, l, u) = lu.unpack(); let mut lu = l * u; p.inv_permute_rows(&mut lu); relative_eq!(m, lu, epsilon = 1.0e-7) } fn lu_solve(n: usize, nb: usize) -> bool { if n != 0 && nb != 0 { let n = cmp::min(n, 50); // To avoid slowing down the test too much. let nb = cmp::min(nb, 50); // To avoid slowing down the test too much. let m = DMatrix::<$scalar>::new_random(n, n).map(|e| e.0); let lu = m.clone().lu(); let b1 = DVector::<$scalar>::new_random(n).map(|e| e.0); let b2 = DMatrix::<$scalar>::new_random(n, nb).map(|e| e.0); let sol1 = lu.solve(&b1); let sol2 = lu.solve(&b2); return (sol1.is_none() || relative_eq!(&m * sol1.unwrap(), b1, epsilon = 1.0e-6)) && (sol2.is_none() || relative_eq!(&m * sol2.unwrap(), b2, epsilon = 1.0e-6)) } return true; } fn lu_solve_static(m: Matrix4<$scalar>) -> bool { let m = m.map(|e| e.0); let lu = m.lu(); let b1 = Vector4::<$scalar>::new_random().map(|e| e.0); let b2 = Matrix4x3::<$scalar>::new_random().map(|e| e.0); let sol1 = lu.solve(&b1); let sol2 = lu.solve(&b2); return (sol1.is_none() || relative_eq!(&m * sol1.unwrap(), b1, epsilon = 1.0e-6)) && (sol2.is_none() || relative_eq!(&m * sol2.unwrap(), b2, epsilon = 1.0e-6)) } fn lu_inverse(n: usize) -> bool { let n = cmp::max(1, cmp::min(n, 15)); // To avoid slowing down the test too much. let m = DMatrix::<$scalar>::new_random(n, n).map(|e| e.0); let mut l = m.lower_triangle(); let mut u = m.upper_triangle(); // Ensure the matrix is well conditioned for inversion. l.fill_diagonal(na::one()); u.fill_diagonal(na::one()); let m = l * u; let m1 = m.clone().lu().try_inverse().unwrap(); let id1 = &m * &m1; let id2 = &m1 * &m; return id1.is_identity(1.0e-5) && id2.is_identity(1.0e-5); } fn lu_inverse_static(m: Matrix4<$scalar>) -> bool { let m = m.map(|e| e.0); let lu = m.lu(); if let Some(m1) = lu.try_inverse() { let id1 = &m * &m1; let id2 = &m1 * &m; id1.is_identity(1.0e-5) && id2.is_identity(1.0e-5) } else { true } } } } } ); gen_tests!(complex, RandComplex); gen_tests!(f64, RandScalar); }