diff options
Diffstat (limited to 'gnu/packages/patches/eigen-stabilise-sparseqr-test.patch')
| -rw-r--r-- | gnu/packages/patches/eigen-stabilise-sparseqr-test.patch | 74 |
1 files changed, 74 insertions, 0 deletions
diff --git a/gnu/packages/patches/eigen-stabilise-sparseqr-test.patch b/gnu/packages/patches/eigen-stabilise-sparseqr-test.patch new file mode 100644 index 0000000000..b95b46077a --- /dev/null +++ b/gnu/packages/patches/eigen-stabilise-sparseqr-test.patch @@ -0,0 +1,74 @@ +From: Tobias Geerinckx-Rice <me@tobias.gr> +Date: Mon, 16 Mar 2020 22:51:37 +0000 +Subject: gnu: eigen: Stabilise sparseqr test. + +Taken verbatim from this[0] upstream commit. + +[0]: https://gitlab.com/libeigen/eigen/-/commit/3b5deeb546d4017b24846f5b0dc3296a50a039fe + +From 3b5deeb546d4017b24846f5b0dc3296a50a039fe Mon Sep 17 00:00:00 2001 +From: Gael Guennebaud <g.gael@free.fr> +Date: Tue, 19 Feb 2019 22:57:51 +0100 +Subject: [PATCH] bug #899: make sparseqr unit test more stable by 1) trying + with larger threshold and 2) relax rank computation for rank-deficient + problems. + +--- + test/sparseqr.cpp | 31 ++++++++++++++++++++++++++----- + 1 file changed, 26 insertions(+), 5 deletions(-) + +diff --git a/test/sparseqr.cpp b/test/sparseqr.cpp +index 3ffe62314..3576cc626 100644 +--- a/test/sparseqr.cpp ++++ b/test/sparseqr.cpp +@@ -43,6 +43,7 @@ int generate_sparse_rectangular_problem(MatrixType& A, DenseMat& dA, int maxRows + + template<typename Scalar> void test_sparseqr_scalar() + { ++ typedef typename NumTraits<Scalar>::Real RealScalar; + typedef SparseMatrix<Scalar,ColMajor> MatrixType; + typedef Matrix<Scalar,Dynamic,Dynamic> DenseMat; + typedef Matrix<Scalar,Dynamic,1> DenseVector; +@@ -91,14 +92,34 @@ template<typename Scalar> void test_sparseqr_scalar() + exit(0); + return; + } +- +- VERIFY_IS_APPROX(A * x, b); +- +- //Compare with a dense QR solver ++ ++ // Compare with a dense QR solver + ColPivHouseholderQR<DenseMat> dqr(dA); + refX = dqr.solve(b); + +- VERIFY_IS_EQUAL(dqr.rank(), solver.rank()); ++ bool rank_deficient = A.cols()>A.rows() || dqr.rank()<A.cols(); ++ if(rank_deficient) ++ { ++ // rank deficient problem -> we might have to increase the threshold ++ // to get a correct solution. ++ RealScalar th = RealScalar(20)*dA.colwise().norm().maxCoeff()*(A.rows()+A.cols()) * NumTraits<RealScalar>::epsilon(); ++ for(Index k=0; (k<16) && !test_isApprox(A*x,b); ++k) ++ { ++ th *= RealScalar(10); ++ solver.setPivotThreshold(th); ++ solver.compute(A); ++ x = solver.solve(b); ++ } ++ } ++ ++ VERIFY_IS_APPROX(A * x, b); ++ ++ // For rank deficient problem, the estimated rank might ++ // be slightly off, so let's only raise a warning in such cases. ++ if(rank_deficient) ++g_test_level; ++ VERIFY_IS_EQUAL(solver.rank(), dqr.rank()); ++ if(rank_deficient) --g_test_level; ++ + if(solver.rank()==A.cols()) // full rank + VERIFY_IS_APPROX(x, refX); + // else +-- +2.24.1 + |