|Summary:||Neglect small singular value in JacobiSVD::solve and add JacobiSVD::rank()|
|Product:||Eigen||Reporter:||Gael Guennebaud <gael.guennebaud>|
|Bug Depends on:|
Description Gael Guennebaud 2013-06-22 16:48:34 UTC
Created attachment 356 [details] Patch for JacobiSVD::solve and Jacobi::rank Currently JacobiSVD::solve uses all the non zeros singular-values for solving, i.e., without any thresholding. In practice this led to many numerical issue and large errors for hill conditioned matrices. So far I recommended to use ColPivHouseholderQR but it's time to fix JacobiSVD. Here is a quick patch proposal. Perhaps we should offert the possibility to tweak the threshold as in ColPivHouseholderQR? We should also add regression tests.
Comment 1 Gael Guennebaud 2013-06-24 13:12:22 UTC
OK, actually there was a serious issue in Jacobi::solve that explicitly formed the pseudo inverse: this is bad not only regarding the accuracy but also regarding the performance! Fixed and backported: https://bitbucket.org/eigen/eigen/commits/afff5b36628a/ Changeset: afff5b36628a User: ggael Date: 2013-06-24 13:08:09 Summary: Bug 620: fix robustness issue in JacobiSVD::solve (also fix a perf. issue) https://bitbucket.org/eigen/eigen/commits/f47ab17a54f0/ Changeset: f47ab17a54f0 Branch: 3.1 User: ggael Date: 2013-06-24 13:08:09 Summary: Bug 620: fix robustness issue in JacobiSVD::solve (also fix a perf. issue) (transplanted from afff5b36628a642ad0bc1da1efadb7d1c41da3f4) It would still be interesting to add a setThreshold/threshold /rank API but that's less urgent now.
Comment 2 Gael Guennebaud 2015-06-08 13:47:42 UTC
All these features are already available.
Comment 3 Nobody 2019-12-04 12:25:43 UTC
-- GitLab Migration Automatic Message -- This bug has been migrated to gitlab.com's GitLab instance and has been closed from further activity. You can subscribe and participate further through the new bug through this link to our GitLab instance: https://gitlab.com/libeigen/eigen/issues/620.