diff options
Diffstat (limited to 'test/eigensolver_generic.cpp')
-rw-r--r-- | test/eigensolver_generic.cpp | 57 |
1 files changed, 30 insertions, 27 deletions
diff --git a/test/eigensolver_generic.cpp b/test/eigensolver_generic.cpp index d0e644d4b..e0e435151 100644 --- a/test/eigensolver_generic.cpp +++ b/test/eigensolver_generic.cpp @@ -14,7 +14,6 @@ template<typename MatrixType> void eigensolver(const MatrixType& m) { - typedef typename MatrixType::Index Index; /* this test covers the following files: EigenSolver.h */ @@ -101,7 +100,35 @@ template<typename MatrixType> void eigensolver_verify_assert(const MatrixType& m VERIFY_RAISES_ASSERT(eig.pseudoEigenvectors()); } -void test_eigensolver_generic() +template<int> +void eigensolver_generic_extra() +{ + { + // regression test for bug 793 + MatrixXd a(3,3); + a << 0, 0, 1, + 1, 1, 1, + 1, 1e+200, 1; + Eigen::EigenSolver<MatrixXd> eig(a); + double scale = 1e-200; // scale to avoid overflow during the comparisons + VERIFY_IS_APPROX(a * eig.pseudoEigenvectors()*scale, eig.pseudoEigenvectors() * eig.pseudoEigenvalueMatrix()*scale); + VERIFY_IS_APPROX(a * eig.eigenvectors()*scale, eig.eigenvectors() * eig.eigenvalues().asDiagonal()*scale); + } + { + // check a case where all eigenvalues are null. + MatrixXd a(2,2); + a << 1, 1, + -1, -1; + Eigen::EigenSolver<MatrixXd> eig(a); + VERIFY_IS_APPROX(eig.pseudoEigenvectors().squaredNorm(), 2.); + VERIFY_IS_APPROX((a * eig.pseudoEigenvectors()).norm()+1., 1.); + VERIFY_IS_APPROX((eig.pseudoEigenvectors() * eig.pseudoEigenvalueMatrix()).norm()+1., 1.); + VERIFY_IS_APPROX((a * eig.eigenvectors()).norm()+1., 1.); + VERIFY_IS_APPROX((eig.eigenvectors() * eig.eigenvalues().asDiagonal()).norm()+1., 1.); + } +} + +EIGEN_DECLARE_TEST(eigensolver_generic) { int s = 0; for(int i = 0; i < g_repeat; i++) { @@ -136,31 +163,7 @@ void test_eigensolver_generic() } ); -#ifdef EIGEN_TEST_PART_2 - { - // regression test for bug 793 - MatrixXd a(3,3); - a << 0, 0, 1, - 1, 1, 1, - 1, 1e+200, 1; - Eigen::EigenSolver<MatrixXd> eig(a); - double scale = 1e-200; // scale to avoid overflow during the comparisons - VERIFY_IS_APPROX(a * eig.pseudoEigenvectors()*scale, eig.pseudoEigenvectors() * eig.pseudoEigenvalueMatrix()*scale); - VERIFY_IS_APPROX(a * eig.eigenvectors()*scale, eig.eigenvectors() * eig.eigenvalues().asDiagonal()*scale); - } - { - // check a case where all eigenvalues are null. - MatrixXd a(2,2); - a << 1, 1, - -1, -1; - Eigen::EigenSolver<MatrixXd> eig(a); - VERIFY_IS_APPROX(eig.pseudoEigenvectors().squaredNorm(), 2.); - VERIFY_IS_APPROX((a * eig.pseudoEigenvectors()).norm()+1., 1.); - VERIFY_IS_APPROX((eig.pseudoEigenvectors() * eig.pseudoEigenvalueMatrix()).norm()+1., 1.); - VERIFY_IS_APPROX((a * eig.eigenvectors()).norm()+1., 1.); - VERIFY_IS_APPROX((eig.eigenvectors() * eig.eigenvalues().asDiagonal()).norm()+1., 1.); - } -#endif + CALL_SUBTEST_2( eigensolver_generic_extra<0>() ); TEST_SET_BUT_UNUSED_VARIABLE(s) } |