diff options
Diffstat (limited to 'test/svd_common.h')
| -rw-r--r-- | test/svd_common.h | 56 |
1 files changed, 47 insertions, 9 deletions
diff --git a/test/svd_common.h b/test/svd_common.h index 605d5dfef..eae4c0bfe 100644 --- a/test/svd_common.h +++ b/test/svd_common.h @@ -17,13 +17,13 @@ #endif #include "svd_fill.h" +#include "solverbase.h" // Check that the matrix m is properly reconstructed and that the U and V factors are unitary // The SVD must have already been computed. template<typename SvdType, typename MatrixType> void svd_check_full(const MatrixType& m, const SvdType& svd) { - typedef typename MatrixType::Index Index; Index rows = m.rows(); Index cols = m.cols(); @@ -101,7 +101,6 @@ void svd_least_square(const MatrixType& m, unsigned int computationOptions) { typedef typename MatrixType::Scalar Scalar; typedef typename MatrixType::RealScalar RealScalar; - typedef typename MatrixType::Index Index; Index rows = m.rows(); Index cols = m.cols(); @@ -168,7 +167,6 @@ template<typename MatrixType> void svd_min_norm(const MatrixType& m, unsigned int computationOptions) { typedef typename MatrixType::Scalar Scalar; - typedef typename MatrixType::Index Index; Index cols = m.cols(); enum { @@ -222,12 +220,33 @@ void svd_min_norm(const MatrixType& m, unsigned int computationOptions) VERIFY_IS_APPROX(x21, x3); } +template<typename MatrixType, typename SolverType> +void svd_test_solvers(const MatrixType& m, const SolverType& solver) { + Index rows, cols, cols2; + + rows = m.rows(); + cols = m.cols(); + + if(MatrixType::ColsAtCompileTime==Dynamic) + { + cols2 = internal::random<int>(2,EIGEN_TEST_MAX_SIZE); + } + else + { + cols2 = cols; + } + typedef Matrix<typename MatrixType::Scalar, MatrixType::ColsAtCompileTime, MatrixType::ColsAtCompileTime> CMatrixType; + check_solverbase<CMatrixType, MatrixType>(m, solver, rows, cols, cols2); +} + // Check full, compare_to_full, least_square, and min_norm for all possible compute-options template<typename SvdType, typename MatrixType> void svd_test_all_computation_options(const MatrixType& m, bool full_only) { // if (QRPreconditioner == NoQRPreconditioner && m.rows() != m.cols()) // return; + STATIC_CHECK(( internal::is_same<typename SvdType::StorageIndex,int>::value )); + SvdType fullSvd(m, ComputeFullU|ComputeFullV); CALL_SUBTEST(( svd_check_full(m, fullSvd) )); CALL_SUBTEST(( svd_least_square<SvdType>(m, ComputeFullU | ComputeFullV) )); @@ -237,6 +256,9 @@ void svd_test_all_computation_options(const MatrixType& m, bool full_only) // remark #111: statement is unreachable #pragma warning disable 111 #endif + + svd_test_solvers(m, fullSvd); + if(full_only) return; @@ -261,7 +283,6 @@ void svd_test_all_computation_options(const MatrixType& m, bool full_only) CALL_SUBTEST(( svd_min_norm(m, ComputeThinU | ComputeThinV) )); // test reconstruction - typedef typename MatrixType::Index Index; Index diagSize = (std::min)(m.rows(), m.cols()); SvdType svd(m, ComputeThinU | ComputeThinV); VERIFY_IS_APPROX(m, svd.matrixU().leftCols(diagSize) * svd.singularValues().asDiagonal() * svd.matrixV().leftCols(diagSize).adjoint()); @@ -277,7 +298,8 @@ EIGEN_DONT_INLINE Scalar zero() { return Scalar(0); } // workaround aggressive optimization in ICC template<typename T> EIGEN_DONT_INLINE T sub(T a, T b) { return a - b; } -// all this function does is verify we don't iterate infinitely on nan/inf values +// This function verifies we don't iterate infinitely on nan/inf values, +// and that info() returns InvalidInput. template<typename SvdType, typename MatrixType> void svd_inf_nan() { @@ -286,18 +308,22 @@ void svd_inf_nan() Scalar some_inf = Scalar(1) / zero<Scalar>(); VERIFY(sub(some_inf, some_inf) != sub(some_inf, some_inf)); svd.compute(MatrixType::Constant(10,10,some_inf), ComputeFullU | ComputeFullV); + VERIFY(svd.info() == InvalidInput); Scalar nan = std::numeric_limits<Scalar>::quiet_NaN(); VERIFY(nan != nan); svd.compute(MatrixType::Constant(10,10,nan), ComputeFullU | ComputeFullV); + VERIFY(svd.info() == InvalidInput); MatrixType m = MatrixType::Zero(10,10); m(internal::random<int>(0,9), internal::random<int>(0,9)) = some_inf; svd.compute(m, ComputeFullU | ComputeFullV); + VERIFY(svd.info() == InvalidInput); m = MatrixType::Zero(10,10); m(internal::random<int>(0,9), internal::random<int>(0,9)) = nan; svd.compute(m, ComputeFullU | ComputeFullV); + VERIFY(svd.info() == InvalidInput); // regression test for bug 791 m.resize(3,3); @@ -305,6 +331,7 @@ void svd_inf_nan() 0, -0.5, 0, nan, 0, 0; svd.compute(m, ComputeFullU | ComputeFullV); + VERIFY(svd.info() == InvalidInput); m.resize(4,4); m << 1, 0, 0, 0, @@ -312,6 +339,7 @@ void svd_inf_nan() 1, 0, 1, nan, 0, nan, nan, 0; svd.compute(m, ComputeFullU | ComputeFullV); + VERIFY(svd.info() == InvalidInput); } // Regression test for bug 286: JacobiSVD loops indefinitely with some @@ -434,10 +462,9 @@ void svd_preallocate() } template<typename SvdType,typename MatrixType> -void svd_verify_assert(const MatrixType& m) +void svd_verify_assert(const MatrixType& m, bool fullOnly = false) { typedef typename MatrixType::Scalar Scalar; - typedef typename MatrixType::Index Index; Index rows = m.rows(); Index cols = m.cols(); @@ -453,6 +480,8 @@ void svd_verify_assert(const MatrixType& m) VERIFY_RAISES_ASSERT(svd.singularValues()) VERIFY_RAISES_ASSERT(svd.matrixV()) VERIFY_RAISES_ASSERT(svd.solve(rhs)) + VERIFY_RAISES_ASSERT(svd.transpose().solve(rhs)) + VERIFY_RAISES_ASSERT(svd.adjoint().solve(rhs)) MatrixType a = MatrixType::Zero(rows, cols); a.setZero(); svd.compute(a, 0); @@ -460,8 +489,17 @@ void svd_verify_assert(const MatrixType& m) VERIFY_RAISES_ASSERT(svd.matrixV()) svd.singularValues(); VERIFY_RAISES_ASSERT(svd.solve(rhs)) - - if (ColsAtCompileTime == Dynamic) + + svd.compute(a, ComputeFullU); + svd.matrixU(); + VERIFY_RAISES_ASSERT(svd.matrixV()) + VERIFY_RAISES_ASSERT(svd.solve(rhs)) + svd.compute(a, ComputeFullV); + svd.matrixV(); + VERIFY_RAISES_ASSERT(svd.matrixU()) + VERIFY_RAISES_ASSERT(svd.solve(rhs)) + + if (!fullOnly && ColsAtCompileTime == Dynamic) { svd.compute(a, ComputeThinU); svd.matrixU(); |