forked from M-Labs/nalgebra
Fix SVD instability bug
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757b99e843
commit
325618ba22
@ -2,7 +2,6 @@
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use serde::{Deserialize, Serialize};
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use std::any::TypeId;
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use approx::AbsDiffEq;
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use num::{One, Zero};
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use crate::allocator::Allocator;
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@ -94,14 +93,7 @@ where
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/// The singular values are not guaranteed to be sorted in any particular order.
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/// If a descending order is required, consider using `new` instead.
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pub fn new_unordered(matrix: OMatrix<T, R, C>, compute_u: bool, compute_v: bool) -> Self {
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Self::try_new_unordered(
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matrix,
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compute_u,
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compute_v,
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T::RealField::default_epsilon(),
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0,
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)
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.unwrap()
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Self::try_new_unordered(matrix, compute_u, compute_v, crate::convert(1e-15), 0).unwrap()
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}
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/// Attempts to compute the Singular Value Decomposition of `matrix` using implicit shift.
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@ -888,13 +880,13 @@ fn compute_2x2_uptrig_svd<T: RealField>(
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v_t = Some(csv.clone());
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}
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if compute_u {
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let cu = (m11.scale(csv.c()) + m12 * csv.s()) / v1.clone();
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let su = (m22 * csv.s()) / v1.clone();
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let (csu, sgn_u) = GivensRotation::new(cu, su);
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v1 *= sgn_u.clone();
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v2 *= sgn_u;
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if compute_u {
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u = Some(csu);
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}
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}
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@ -460,3 +460,27 @@ fn svd_sorted() {
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epsilon = 1.0e-5
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);
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}
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#[test]
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// Exercises bug reported in issue #983 of nalgebra
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fn svd_consistent() {
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let m = nalgebra::dmatrix![
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10.74785316637712f64, -5.994983325167452, -6.064492921857296;
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-4.149751381521569, 20.654504205822462, -4.470436210703133;
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-22.772715014220207, -1.4554372570788008, 18.108113992170573
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]
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.transpose();
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let svd1 = m.clone().svd(true, true);
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let svd2 = m.clone().svd(false, true);
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let svd3 = m.clone().svd(true, false);
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let svd4 = m.svd(false, false);
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assert_relative_eq!(svd1.singular_values, svd2.singular_values, epsilon = 1e-5);
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assert_relative_eq!(svd1.singular_values, svd3.singular_values, epsilon = 1e-5);
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assert_relative_eq!(svd1.singular_values, svd4.singular_values, epsilon = 1e-5);
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assert_relative_eq!(
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svd1.singular_values,
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nalgebra::dvector![3.16188022e+01, 2.23811978e+01, 0.],
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epsilon = 1e-5
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);
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}
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