forked from M-Labs/nalgebra
159 lines
5.5 KiB
Rust
159 lines
5.5 KiB
Rust
use na::Matrix3;
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#[test]
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#[rustfmt::skip]
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fn lu_simple() {
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let m = Matrix3::new(
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2.0, -1.0, 0.0,
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-1.0, 2.0, -1.0,
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0.0, -1.0, 2.0);
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let lu = m.lu();
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assert_eq!(lu.determinant(), 4.0);
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let (p, l, u) = lu.unpack();
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let mut lu = l * u;
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p.inv_permute_rows(&mut lu);
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assert!(relative_eq!(m, lu, epsilon = 1.0e-7));
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}
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#[test]
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#[rustfmt::skip]
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fn lu_simple_with_pivot() {
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let m = Matrix3::new(
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0.0, -1.0, 2.0,
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-1.0, 2.0, -1.0,
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2.0, -1.0, 0.0);
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let lu = m.lu();
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assert_eq!(lu.determinant(), -4.0);
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let (p, l, u) = lu.unpack();
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let mut lu = l * u;
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p.inv_permute_rows(&mut lu);
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assert!(relative_eq!(m, lu, epsilon = 1.0e-7));
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}
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#[cfg(feature = "proptest-support")]
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mod proptest_tests {
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macro_rules! gen_tests(
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($module: ident, $scalar: expr, $scalar_type: ty) => {
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mod $module {
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use na::{DMatrix, Matrix4x3, DVector, Vector4};
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#[allow(unused_imports)]
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use crate::core::helper::{RandScalar, RandComplex};
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use crate::proptest::*;
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use proptest::{prop_assert, proptest};
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proptest! {
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#[test]
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fn lu(m in dmatrix_($scalar)) {
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let lu = m.clone().lu();
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let (p, l, u) = lu.unpack();
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let mut lu = l * u;
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p.inv_permute_rows(&mut lu);
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prop_assert!(relative_eq!(m, lu, epsilon = 1.0e-7))
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}
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#[test]
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fn lu_static_3_5(m in matrix3x5_($scalar)) {
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let lu = m.lu();
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let (p, l, u) = lu.unpack();
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let mut lu = l * u;
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p.inv_permute_rows(&mut lu);
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prop_assert!(relative_eq!(m, lu, epsilon = 1.0e-7))
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}
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fn lu_static_5_3(m in matrix5x3_($scalar)) {
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let lu = m.lu();
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let (p, l, u) = lu.unpack();
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let mut lu = l * u;
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p.inv_permute_rows(&mut lu);
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prop_assert!(relative_eq!(m, lu, epsilon = 1.0e-7));
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}
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#[test]
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fn lu_static_square(m in matrix4_($scalar)) {
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let lu = m.lu();
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let (p, l, u) = lu.unpack();
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let mut lu = l * u;
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p.inv_permute_rows(&mut lu);
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prop_assert!(relative_eq!(m, lu, epsilon = 1.0e-7));
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}
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#[test]
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fn lu_solve(n in PROPTEST_MATRIX_DIM, nb in PROPTEST_MATRIX_DIM) {
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let m = DMatrix::<$scalar_type>::new_random(n, n).map(|e| e.0);
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let lu = m.clone().lu();
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let b1 = DVector::<$scalar_type>::new_random(n).map(|e| e.0);
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let b2 = DMatrix::<$scalar_type>::new_random(n, nb).map(|e| e.0);
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let sol1 = lu.solve(&b1);
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let sol2 = lu.solve(&b2);
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prop_assert!(sol1.is_none() || relative_eq!(&m * sol1.unwrap(), b1, epsilon = 1.0e-6));
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prop_assert!(sol2.is_none() || relative_eq!(&m * sol2.unwrap(), b2, epsilon = 1.0e-6));
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}
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#[test]
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fn lu_solve_static(m in matrix4_($scalar)) {
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let lu = m.lu();
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let b1 = Vector4::<$scalar_type>::new_random().map(|e| e.0);
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let b2 = Matrix4x3::<$scalar_type>::new_random().map(|e| e.0);
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let sol1 = lu.solve(&b1);
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let sol2 = lu.solve(&b2);
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prop_assert!(sol1.is_none() || relative_eq!(&m * sol1.unwrap(), b1, epsilon = 1.0e-6));
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prop_assert!(sol2.is_none() || relative_eq!(&m * sol2.unwrap(), b2, epsilon = 1.0e-6));
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}
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#[test]
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fn lu_inverse(n in PROPTEST_MATRIX_DIM) {
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let m = DMatrix::<$scalar_type>::new_random(n, n).map(|e| e.0);
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let mut l = m.lower_triangle();
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let mut u = m.upper_triangle();
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// Ensure the matrix is well conditioned for inversion.
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l.fill_diagonal(na::one());
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u.fill_diagonal(na::one());
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let m = l * u;
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let m1 = m.clone().lu().try_inverse().unwrap();
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let id1 = &m * &m1;
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let id2 = &m1 * &m;
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prop_assert!(id1.is_identity(1.0e-5));
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prop_assert!(id2.is_identity(1.0e-5));
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}
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#[test]
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fn lu_inverse_static(m in matrix4_($scalar)) {
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let lu = m.lu();
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if let Some(m1) = lu.try_inverse() {
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let id1 = &m * &m1;
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let id2 = &m1 * &m;
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prop_assert!(id1.is_identity(1.0e-5));
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prop_assert!(id2.is_identity(1.0e-5));
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}
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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, complex_f64(), RandComplex<f64>);
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gen_tests!(f64, PROPTEST_F64, RandScalar<f64>);
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}
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