diff options
Diffstat (limited to 'eigen/test/lu.cpp')
| -rw-r--r-- | eigen/test/lu.cpp | 83 |
1 files changed, 77 insertions, 6 deletions
diff --git a/eigen/test/lu.cpp b/eigen/test/lu.cpp index 3746526..9787f4d 100644 --- a/eigen/test/lu.cpp +++ b/eigen/test/lu.cpp @@ -11,6 +11,11 @@ #include <Eigen/LU> using namespace std; +template<typename MatrixType> +typename MatrixType::RealScalar matrix_l1_norm(const MatrixType& m) { + return m.cwiseAbs().colwise().sum().maxCoeff(); +} + template<typename MatrixType> void lu_non_invertible() { typedef typename MatrixType::Index Index; @@ -92,6 +97,26 @@ template<typename MatrixType> void lu_non_invertible() // test that the code, which does resize(), may be applied to an xpr m2.block(0,0,m2.rows(),m2.cols()) = lu.solve(m3); VERIFY_IS_APPROX(m3, m1*m2); + + // test solve with transposed + m3 = MatrixType::Random(rows,cols2); + m2 = m1.transpose()*m3; + m3 = MatrixType::Random(rows,cols2); + lu.template _solve_impl_transposed<false>(m2, m3); + VERIFY_IS_APPROX(m2, m1.transpose()*m3); + m3 = MatrixType::Random(rows,cols2); + m3 = lu.transpose().solve(m2); + VERIFY_IS_APPROX(m2, m1.transpose()*m3); + + // test solve with conjugate transposed + m3 = MatrixType::Random(rows,cols2); + m2 = m1.adjoint()*m3; + m3 = MatrixType::Random(rows,cols2); + lu.template _solve_impl_transposed<true>(m2, m3); + VERIFY_IS_APPROX(m2, m1.adjoint()*m3); + m3 = MatrixType::Random(rows,cols2); + m3 = lu.adjoint().solve(m2); + VERIFY_IS_APPROX(m2, m1.adjoint()*m3); } template<typename MatrixType> void lu_invertible() @@ -100,9 +125,9 @@ template<typename MatrixType> void lu_invertible() LU.h */ typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar; - DenseIndex size = MatrixType::RowsAtCompileTime; + Index size = MatrixType::RowsAtCompileTime; if( size==Dynamic) - size = internal::random<DenseIndex>(1,EIGEN_TEST_MAX_SIZE); + size = internal::random<Index>(1,EIGEN_TEST_MAX_SIZE); MatrixType m1(size, size), m2(size, size), m3(size, size); FullPivLU<MatrixType> lu; @@ -123,7 +148,28 @@ template<typename MatrixType> void lu_invertible() m3 = MatrixType::Random(size,size); m2 = lu.solve(m3); VERIFY_IS_APPROX(m3, m1*m2); - VERIFY_IS_APPROX(m2, lu.inverse()*m3); + MatrixType m1_inverse = lu.inverse(); + VERIFY_IS_APPROX(m2, m1_inverse*m3); + + RealScalar rcond = (RealScalar(1) / matrix_l1_norm(m1)) / matrix_l1_norm(m1_inverse); + const RealScalar rcond_est = lu.rcond(); + // Verify that the estimated condition number is within a factor of 10 of the + // truth. + VERIFY(rcond_est > rcond / 10 && rcond_est < rcond * 10); + + // test solve with transposed + lu.template _solve_impl_transposed<false>(m3, m2); + VERIFY_IS_APPROX(m3, m1.transpose()*m2); + m3 = MatrixType::Random(size,size); + m3 = lu.transpose().solve(m2); + VERIFY_IS_APPROX(m2, m1.transpose()*m3); + + // test solve with conjugate transposed + lu.template _solve_impl_transposed<true>(m3, m2); + VERIFY_IS_APPROX(m3, m1.adjoint()*m2); + m3 = MatrixType::Random(size,size); + m3 = lu.adjoint().solve(m2); + VERIFY_IS_APPROX(m2, m1.adjoint()*m3); // Regression test for Bug 302 MatrixType m4 = MatrixType::Random(size,size); @@ -136,14 +182,39 @@ template<typename MatrixType> void lu_partial_piv() PartialPivLU.h */ typedef typename MatrixType::Index Index; - Index rows = internal::random<Index>(1,4); - Index cols = rows; + typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar; + Index size = internal::random<Index>(1,4); - MatrixType m1(cols, rows); + MatrixType m1(size, size), m2(size, size), m3(size, size); m1.setRandom(); PartialPivLU<MatrixType> plu(m1); VERIFY_IS_APPROX(m1, plu.reconstructedMatrix()); + + m3 = MatrixType::Random(size,size); + m2 = plu.solve(m3); + VERIFY_IS_APPROX(m3, m1*m2); + MatrixType m1_inverse = plu.inverse(); + VERIFY_IS_APPROX(m2, m1_inverse*m3); + + RealScalar rcond = (RealScalar(1) / matrix_l1_norm(m1)) / matrix_l1_norm(m1_inverse); + const RealScalar rcond_est = plu.rcond(); + // Verify that the estimate is within a factor of 10 of the truth. + VERIFY(rcond_est > rcond / 10 && rcond_est < rcond * 10); + + // test solve with transposed + plu.template _solve_impl_transposed<false>(m3, m2); + VERIFY_IS_APPROX(m3, m1.transpose()*m2); + m3 = MatrixType::Random(size,size); + m3 = plu.transpose().solve(m2); + VERIFY_IS_APPROX(m2, m1.transpose()*m3); + + // test solve with conjugate transposed + plu.template _solve_impl_transposed<true>(m3, m2); + VERIFY_IS_APPROX(m3, m1.adjoint()*m2); + m3 = MatrixType::Random(size,size); + m3 = plu.adjoint().solve(m2); + VERIFY_IS_APPROX(m2, m1.adjoint()*m3); } template<typename MatrixType> void lu_verify_assert() |