5144e31492
* gnu/packages/algebra.scm (eigen): Update to 3.3.7. [source]: Add a patch to fix a test failure. * gnu/packages/patches/eigen-stabilise-sparseqr-test.patch: New file. * gnu/local.mk (dist_patch_DATA): Add it.
74 lines
2.4 KiB
Diff
74 lines
2.4 KiB
Diff
From: Tobias Geerinckx-Rice <me@tobias.gr>
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Date: Mon, 16 Mar 2020 22:51:37 +0000
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Subject: gnu: eigen: Stabilise sparseqr test.
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Taken verbatim from this[0] upstream commit.
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[0]: https://gitlab.com/libeigen/eigen/-/commit/3b5deeb546d4017b24846f5b0dc3296a50a039fe
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From 3b5deeb546d4017b24846f5b0dc3296a50a039fe Mon Sep 17 00:00:00 2001
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From: Gael Guennebaud <g.gael@free.fr>
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Date: Tue, 19 Feb 2019 22:57:51 +0100
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Subject: [PATCH] bug #899: make sparseqr unit test more stable by 1) trying
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with larger threshold and 2) relax rank computation for rank-deficient
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problems.
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---
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test/sparseqr.cpp | 31 ++++++++++++++++++++++++++-----
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1 file changed, 26 insertions(+), 5 deletions(-)
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diff --git a/test/sparseqr.cpp b/test/sparseqr.cpp
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index 3ffe62314..3576cc626 100644
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--- a/test/sparseqr.cpp
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+++ b/test/sparseqr.cpp
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@@ -43,6 +43,7 @@ int generate_sparse_rectangular_problem(MatrixType& A, DenseMat& dA, int maxRows
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template<typename Scalar> void test_sparseqr_scalar()
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{
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+ typedef typename NumTraits<Scalar>::Real RealScalar;
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typedef SparseMatrix<Scalar,ColMajor> MatrixType;
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typedef Matrix<Scalar,Dynamic,Dynamic> DenseMat;
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typedef Matrix<Scalar,Dynamic,1> DenseVector;
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@@ -91,14 +92,34 @@ template<typename Scalar> void test_sparseqr_scalar()
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exit(0);
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return;
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}
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-
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- VERIFY_IS_APPROX(A * x, b);
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-
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- //Compare with a dense QR solver
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+
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+ // Compare with a dense QR solver
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ColPivHouseholderQR<DenseMat> dqr(dA);
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refX = dqr.solve(b);
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- VERIFY_IS_EQUAL(dqr.rank(), solver.rank());
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+ bool rank_deficient = A.cols()>A.rows() || dqr.rank()<A.cols();
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+ if(rank_deficient)
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+ {
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+ // rank deficient problem -> we might have to increase the threshold
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+ // to get a correct solution.
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+ RealScalar th = RealScalar(20)*dA.colwise().norm().maxCoeff()*(A.rows()+A.cols()) * NumTraits<RealScalar>::epsilon();
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+ for(Index k=0; (k<16) && !test_isApprox(A*x,b); ++k)
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+ {
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+ th *= RealScalar(10);
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+ solver.setPivotThreshold(th);
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+ solver.compute(A);
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+ x = solver.solve(b);
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+ }
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+ }
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+
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+ VERIFY_IS_APPROX(A * x, b);
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+
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+ // For rank deficient problem, the estimated rank might
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+ // be slightly off, so let's only raise a warning in such cases.
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+ if(rank_deficient) ++g_test_level;
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+ VERIFY_IS_EQUAL(solver.rank(), dqr.rank());
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+ if(rank_deficient) --g_test_level;
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+
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if(solver.rank()==A.cols()) // full rank
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VERIFY_IS_APPROX(x, refX);
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// else
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--
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2.24.1
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