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Address review comments

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This commit is contained in:
YuhanLiin 2022-03-09 21:04:43 -05:00
parent 325618ba22
commit 1acd48f6f1
2 changed files with 15 additions and 7 deletions
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10
src/linalg/svd.rs
View File

@ -2,6 +2,7 @@
use serde::{Deserialize, Serialize}; use serde::{Deserialize, Serialize};
use std::any::TypeId; use std::any::TypeId;
use approx::AbsDiffEq;
use num::{One, Zero}; use num::{One, Zero};
use crate::allocator::Allocator; use crate::allocator::Allocator;
@ -93,7 +94,14 @@ where
/// The singular values are not guaranteed to be sorted in any particular order. /// The singular values are not guaranteed to be sorted in any particular order.
/// If a descending order is required, consider using `new` instead. /// If a descending order is required, consider using `new` instead.
pub fn new_unordered(matrix: OMatrix<T, R, C>, compute_u: bool, compute_v: bool) -> Self { pub fn new_unordered(matrix: OMatrix<T, R, C>, compute_u: bool, compute_v: bool) -> Self {
Self::try_new_unordered(matrix, compute_u, compute_v, crate::convert(1e-15), 0).unwrap() Self::try_new_unordered(
matrix,
compute_u,
compute_v,
T::RealField::default_epsilon() * crate::convert(5.0),
0,
)
.unwrap()
} }
/// Attempts to compute the Singular Value Decomposition of `matrix` using implicit shift. /// Attempts to compute the Singular Value Decomposition of `matrix` using implicit shift.

12
tests/linalg/svd.rs
View File

@ -462,8 +462,8 @@ fn svd_sorted() {
} }
#[test] #[test]
// Exercises bug reported in issue #983 of nalgebra // Exercises bug reported in issue #983 of nalgebra (https://github.com/dimforge/nalgebra/issues/983)
fn svd_consistent() { fn svd_regression_issue_983() {
let m = nalgebra::dmatrix![ let m = nalgebra::dmatrix![
10.74785316637712f64, -5.994983325167452, -6.064492921857296; 10.74785316637712f64, -5.994983325167452, -6.064492921857296;
-4.149751381521569, 20.654504205822462, -4.470436210703133; -4.149751381521569, 20.654504205822462, -4.470436210703133;
@ -475,12 +475,12 @@ fn svd_consistent() {
let svd3 = m.clone().svd(true, false); let svd3 = m.clone().svd(true, false);
let svd4 = m.svd(false, false); let svd4 = m.svd(false, false);
assert_relative_eq!(svd1.singular_values, svd2.singular_values, epsilon = 1e-5); assert_relative_eq!(svd1.singular_values, svd2.singular_values, epsilon = 1e-9);
assert_relative_eq!(svd1.singular_values, svd3.singular_values, epsilon = 1e-5); assert_relative_eq!(svd1.singular_values, svd3.singular_values, epsilon = 1e-9);
assert_relative_eq!(svd1.singular_values, svd4.singular_values, epsilon = 1e-5); assert_relative_eq!(svd1.singular_values, svd4.singular_values, epsilon = 1e-9);
assert_relative_eq!( assert_relative_eq!(
svd1.singular_values, svd1.singular_values,
nalgebra::dvector![3.16188022e+01, 2.23811978e+01, 0.], nalgebra::dvector![3.16188022e+01, 2.23811978e+01, 0.],
epsilon = 1e-5 epsilon = 1e-6
); );
} }