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

Merge pull request #669 from daingun/patch-2 

Use same algorithm to solve 2x2 eigenvalue problem
This commit is contained in:
Sébastien Crozet 2019-11-05 23:02:13 +01:00 committed by GitHub
parent f03bd552c2 97374f41b9
commit 31ef5f0ab0
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 7 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

13
src/linalg/schur.rs
View File

@ -309,16 +309,17 @@ where
let hmn = t[(m, n)];
let hnn = t[(n, n)];
let tra = hnn + hmm;
let det = hnn * hmm - hnm * hmn;
let discr = tra * tra * crate::convert(0.25) - det;
// NOTE: use the same algorithm as in compute_2x2_eigvals.
let val = (hmm - hnn) * crate::convert(0.5);
let discr = hnm * hmn + val * val;
// All 2x2 blocks have negative discriminant because we already decoupled those
// with positive eigenvalues..
// with positive eigenvalues.
let sqrt_discr = NumComplex::new(N::zero(), (-discr).sqrt());
out[m] = NumComplex::new(tra * crate::convert(0.5), N::zero()) + sqrt_discr;
out[m + 1] = NumComplex::new(tra * crate::convert(0.5), N::zero()) - sqrt_discr;
let half_tra = (hnn + hmm) * crate::convert(0.5);
out[m] = NumComplex::new(half_tra, N::zero()) + sqrt_discr;
out[m + 1] = NumComplex::new(half_tra, N::zero()) - sqrt_discr;
m += 2;
}