M-Labs
/
nalgebra
3
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Fix syntax error.

This commit is contained in:
sebcrozet 2018-10-27 14:05:17 +02:00 committed by Sébastien Crozet
parent 4ce6555b96
commit 92d9f82caf
1 changed files with 2 additions and 87 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

89
tests/linalg/eigen.rs
View File

@ -1,4 +1,5 @@
t #![cfg_attr(rustfmt, rustfmt_skip)]
use na::DMatrix; use na::DMatrix;
#[cfg(feature = "arbitrary")] #[cfg(feature = "arbitrary")]
@ -103,89 +104,3 @@ fn symmetric_eigen_singular_24x24() {
epsilon = 1.0e-5 epsilon = 1.0e-5
)); ));
} }
// #[cfg(feature = "arbitrary")]
// quickcheck! {
// FIXME: full eigendecomposition is not implemented yet because of its complexity when some
// eigenvalues have multiplicity > 1.
//
// /*
// * NOTE: for the following tests, we use only upper-triangular matrices.
// * Thes ensures the schur decomposition will work, and allows use to test the eigenvector
// * computation.
// */
// fn eigen(n: usize) -> bool {
// let n = cmp::max(1, cmp::min(n, 10));
// let m = DMatrix::<f64>::new_random(n, n).upper_triangle();
//
// let eig = RealEigen::new(m.clone()).unwrap();
// verify_eigenvectors(m, eig)
// }
//
// fn eigen_with_adjascent_duplicate_diagonals(n: usize) -> bool {
// let n = cmp::max(1, cmp::min(n, 10));
// let mut m = DMatrix::<f64>::new_random(n, n).upper_triangle();
//
// // Suplicate some adjascent diagonal elements.
// for i in 0 .. n / 2 {
// m[(i * 2 + 1, i * 2 + 1)] = m[(i * 2, i * 2)];
// }
//
// let eig = RealEigen::new(m.clone()).unwrap();
// verify_eigenvectors(m, eig)
// }
//
// fn eigen_with_nonadjascent_duplicate_diagonals(n: usize) -> bool {
// let n = cmp::max(3, cmp::min(n, 10));
// let mut m = DMatrix::<f64>::new_random(n, n).upper_triangle();
//
// // Suplicate some diagonal elements.
// for i in n / 2 .. n {
// m[(i, i)] = m[(i - n / 2, i - n / 2)];
// }
//
// let eig = RealEigen::new(m.clone()).unwrap();
// verify_eigenvectors(m, eig)
// }
//
// fn eigen_static_square_4x4(m: Matrix4<f64>) -> bool {
// let m = m.upper_triangle();
// let eig = RealEigen::new(m.clone()).unwrap();
// verify_eigenvectors(m, eig)
// }
//
// fn eigen_static_square_3x3(m: Matrix3<f64>) -> bool {
// let m = m.upper_triangle();
// let eig = RealEigen::new(m.clone()).unwrap();
// verify_eigenvectors(m, eig)
// }
//
// fn eigen_static_square_2x2(m: Matrix2<f64>) -> bool {
// let m = m.upper_triangle();
// println!("{}", m);
// let eig = RealEigen::new(m.clone()).unwrap();
// verify_eigenvectors(m, eig)
// }
// }
//
// fn verify_eigenvectors<D: Dim>(m: MatrixN<f64, D>, mut eig: RealEigen<f64, D>) -> bool
// where DefaultAllocator: Allocator<f64, D, D> +
// Allocator<f64, D> +
// Allocator<usize, D, D> +
// Allocator<usize, D>,
// MatrixN<f64, D>: Display,
// VectorN<f64, D>: Display {
// let mv = &m * &eig.eigenvectors;
//
// println!("eigenvalues: {}eigenvectors: {}", eig.eigenvalues, eig.eigenvectors);
//
// let dim = m.nrows();
// for i in 0 .. dim {
// let mut col = eig.eigenvectors.column_mut(i);
// col *= eig.eigenvalues[i];
// }
//
// println!("{}{:.5}{:.5}", m, mv, eig.eigenvectors);
//
// relative_eq!(eig.eigenvectors, mv, epsilon = 1.0e-5)
// }