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authorGravatar Gael Guennebaud <g.gael@free.fr>2015-06-08 16:16:42 +0200
committerGravatar Gael Guennebaud <g.gael@free.fr>2015-06-08 16:16:42 +0200
commitcd8b996f99de67035a0504cbaf0a627fb68f0f1d (patch)
tree7321a99c33157a2a696c7b4f5c2efc7d4d7dd6b7
parent913a61870da36dab308b38c48cb3553487dca8ff (diff)
Extend unit test and documentation of SelfAdjointEigenSolver::computeDirect
-rw-r--r--Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h10
-rw-r--r--test/eigensolver_selfadjoint.cpp32
2 files changed, 29 insertions, 13 deletions
diff --git a/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h b/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
index 1830b99c1..27a014a96 100644
--- a/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
+++ b/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
@@ -198,17 +198,21 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
EIGEN_DEVICE_FUNC
SelfAdjointEigenSolver& compute(const MatrixType& matrix, int options = ComputeEigenvectors);
- /** \brief Computes eigendecomposition of given matrix using a direct algorithm
+ /** \brief Computes eigendecomposition of given matrix using a closed-form algorithm
*
* This is a variant of compute(const MatrixType&, int options) which
* directly solves the underlying polynomial equation.
*
- * Currently only 3x3 matrices for which the sizes are known at compile time are supported (e.g., Matrix3d).
+ * Currently only 2x2 and 3x3 matrices for which the sizes are known at compile time are supported (e.g., Matrix3d).
*
- * This method is usually significantly faster than the QR algorithm
+ * This method is usually significantly faster than the QR iterative algorithm
* but it might also be less accurate. It is also worth noting that
* for 3x3 matrices it involves trigonometric operations which are
* not necessarily available for all scalar types.
+ *
+ * For the 3x3 case, we observed the following worst case relative error regarding the eigenvalues:
+ * - double: 1e-8
+ * - float: 1e-3
*
* \sa compute(const MatrixType&, int options)
*/
diff --git a/test/eigensolver_selfadjoint.cpp b/test/eigensolver_selfadjoint.cpp
index 6750c7609..41b6d99ab 100644
--- a/test/eigensolver_selfadjoint.cpp
+++ b/test/eigensolver_selfadjoint.cpp
@@ -18,22 +18,34 @@ template<typename MatrixType> void selfadjointeigensolver_essential_check(const
{
typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
- RealScalar largerEps = 10*test_precision<RealScalar>();
+ RealScalar eival_eps = (std::min)(test_precision<RealScalar>(), NumTraits<Scalar>::dummy_precision()*20000);
SelfAdjointEigenSolver<MatrixType> eiSymm(m);
VERIFY_IS_EQUAL(eiSymm.info(), Success);
- VERIFY((m.template selfadjointView<Lower>() * eiSymm.eigenvectors()).isApprox(
- eiSymm.eigenvectors() * eiSymm.eigenvalues().asDiagonal(), largerEps));
+ VERIFY_IS_APPROX(m.template selfadjointView<Lower>() * eiSymm.eigenvectors(),
+ eiSymm.eigenvectors() * eiSymm.eigenvalues().asDiagonal());
VERIFY_IS_APPROX(m.template selfadjointView<Lower>().eigenvalues(), eiSymm.eigenvalues());
VERIFY_IS_UNITARY(eiSymm.eigenvectors());
- SelfAdjointEigenSolver<MatrixType> eiDirect;
- eiDirect.computeDirect(m);
- VERIFY_IS_EQUAL(eiDirect.info(), Success);
- VERIFY((m.template selfadjointView<Lower>() * eiDirect.eigenvectors()).isApprox(
- eiDirect.eigenvectors() * eiDirect.eigenvalues().asDiagonal(), largerEps));
- VERIFY_IS_APPROX(m.template selfadjointView<Lower>().eigenvalues(), eiDirect.eigenvalues());
- VERIFY_IS_UNITARY(eiDirect.eigenvectors());
+ if(m.cols()<=4)
+ {
+ SelfAdjointEigenSolver<MatrixType> eiDirect;
+ eiDirect.computeDirect(m);
+ VERIFY_IS_EQUAL(eiDirect.info(), Success);
+ VERIFY_IS_APPROX(eiSymm.eigenvalues(), eiDirect.eigenvalues());
+ if(! eiSymm.eigenvalues().isApprox(eiDirect.eigenvalues(), eival_eps) )
+ {
+ std::cerr << "reference eigenvalues: " << eiSymm.eigenvalues().transpose() << "\n"
+ << "obtained eigenvalues: " << eiDirect.eigenvalues().transpose() << "\n"
+ << "diff: " << (eiSymm.eigenvalues()-eiDirect.eigenvalues()).transpose() << "\n"
+ << "error (eps): " << (eiSymm.eigenvalues()-eiDirect.eigenvalues()).norm() / eiSymm.eigenvalues().norm() << " (" << eival_eps << ")\n";
+ }
+ VERIFY(eiSymm.eigenvalues().isApprox(eiDirect.eigenvalues(), eival_eps));
+ VERIFY_IS_APPROX(m.template selfadjointView<Lower>() * eiDirect.eigenvectors(),
+ eiDirect.eigenvectors() * eiDirect.eigenvalues().asDiagonal());
+ VERIFY_IS_APPROX(m.template selfadjointView<Lower>().eigenvalues(), eiDirect.eigenvalues());
+ VERIFY_IS_UNITARY(eiDirect.eigenvectors());
+ }
}
template<typename MatrixType> void selfadjointeigensolver(const MatrixType& m)