diff --git a/Eigen/src/SVD/JacobiSVD.h b/Eigen/src/SVD/JacobiSVD.h index 439eb5d29..412daa746 100644 --- a/Eigen/src/SVD/JacobiSVD.h +++ b/Eigen/src/SVD/JacobiSVD.h @@ -375,17 +375,19 @@ struct svd_precondition_2x2_block_to_be_real Scalar z; JacobiRotation rot; RealScalar n = sqrt(numext::abs2(work_matrix.coeff(p,p)) + numext::abs2(work_matrix.coeff(q,p))); + if(n==0) { z = abs(work_matrix.coeff(p,q)) / work_matrix.coeff(p,q); work_matrix.row(p) *= z; if(svd.computeU()) svd.m_matrixU.col(p) *= conj(z); if(work_matrix.coeff(q,q)!=Scalar(0)) + { z = abs(work_matrix.coeff(q,q)) / work_matrix.coeff(q,q); - else - z = Scalar(0); - work_matrix.row(q) *= z; - if(svd.computeU()) svd.m_matrixU.col(q) *= conj(z); + work_matrix.row(q) *= z; + if(svd.computeU()) svd.m_matrixU.col(q) *= conj(z); + } + // otherwise the second row is already zero, so we have nothing to do. } else { @@ -835,7 +837,7 @@ JacobiSVD::compute(const MatrixType& matrix, unsig if(m_computeThinV) m_matrixV.setIdentity(m_cols, m_diagSize); } - // Scaling factor to reducover/under-flows + // Scaling factor to reduce over/under-flows RealScalar scale = m_workMatrix.cwiseAbs().maxCoeff(); if(scale==RealScalar(0)) scale = RealScalar(1); m_workMatrix /= scale; diff --git a/test/jacobisvd.cpp b/test/jacobisvd.cpp index d441a6eca..36721b496 100644 --- a/test/jacobisvd.cpp +++ b/test/jacobisvd.cpp @@ -67,6 +67,7 @@ template void jacobisvd_solve(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(); @@ -81,9 +82,37 @@ void jacobisvd_solve(const MatrixType& m, unsigned int computationOptions) RhsType rhs = RhsType::Random(rows, internal::random(1, cols)); JacobiSVD svd(m, computationOptions); + + if(internal::is_same::value) svd.setThreshold(1e-8); + else if(internal::is_same::value) svd.setThreshold(1e-4); + SolutionType x = svd.solve(rhs); + + RealScalar residual = (m*x-rhs).norm(); + // Check that there is no significantly better solution in the neighborhood of x + if(!test_isMuchSmallerThan(residual,rhs.norm())) + { + // If the residual is very small, then we have an exact solution, so we are already good. + for(int k=0;k::epsilon(); + RealScalar residual_y = (m*y-rhs).norm(); + VERIFY( test_isApprox(residual_y,residual) || residual < residual_y ); + + y.row(k) = x.row(k).array() - 2*NumTraits::epsilon(); + residual_y = (m*y-rhs).norm(); + VERIFY( test_isApprox(residual_y,residual) || residual < residual_y ); + } + } + // evaluate normal equation which works also for least-squares solutions - VERIFY_IS_APPROX(m.adjoint()*m*x,m.adjoint()*rhs); + if(internal::is_same::value) + { + // This test is not stable with single precision. + // This is probably because squaring m signicantly affects the precision. + VERIFY_IS_APPROX(m.adjoint()*m*x,m.adjoint()*rhs); + } // check minimal norm solutions { @@ -139,10 +168,9 @@ void jacobisvd_test_all_computation_options(const MatrixType& m) if (QRPreconditioner == NoQRPreconditioner && m.rows() != m.cols()) return; JacobiSVD fullSvd(m, ComputeFullU|ComputeFullV); - - jacobisvd_check_full(m, fullSvd); - jacobisvd_solve(m, ComputeFullU | ComputeFullV); - + CALL_SUBTEST(( jacobisvd_check_full(m, fullSvd) )); + CALL_SUBTEST(( jacobisvd_solve(m, ComputeFullU | ComputeFullV) )); + #if defined __INTEL_COMPILER // remark #111: statement is unreachable #pragma warning disable 111 @@ -150,20 +178,20 @@ void jacobisvd_test_all_computation_options(const MatrixType& m) if(QRPreconditioner == FullPivHouseholderQRPreconditioner) return; - jacobisvd_compare_to_full(m, ComputeFullU, fullSvd); - jacobisvd_compare_to_full(m, ComputeFullV, fullSvd); - jacobisvd_compare_to_full(m, 0, fullSvd); + CALL_SUBTEST(( jacobisvd_compare_to_full(m, ComputeFullU, fullSvd) )); + CALL_SUBTEST(( jacobisvd_compare_to_full(m, ComputeFullV, fullSvd) )); + CALL_SUBTEST(( jacobisvd_compare_to_full(m, 0, fullSvd) )); if (MatrixType::ColsAtCompileTime == Dynamic) { // thin U/V are only available with dynamic number of columns - jacobisvd_compare_to_full(m, ComputeFullU|ComputeThinV, fullSvd); - jacobisvd_compare_to_full(m, ComputeThinV, fullSvd); - jacobisvd_compare_to_full(m, ComputeThinU|ComputeFullV, fullSvd); - jacobisvd_compare_to_full(m, ComputeThinU , fullSvd); - jacobisvd_compare_to_full(m, ComputeThinU|ComputeThinV, fullSvd); - jacobisvd_solve(m, ComputeFullU | ComputeThinV); - jacobisvd_solve(m, ComputeThinU | ComputeFullV); - jacobisvd_solve(m, ComputeThinU | ComputeThinV); + CALL_SUBTEST(( jacobisvd_compare_to_full(m, ComputeFullU|ComputeThinV, fullSvd) )); + CALL_SUBTEST(( jacobisvd_compare_to_full(m, ComputeThinV, fullSvd) )); + CALL_SUBTEST(( jacobisvd_compare_to_full(m, ComputeThinU|ComputeFullV, fullSvd) )); + CALL_SUBTEST(( jacobisvd_compare_to_full(m, ComputeThinU , fullSvd) )); + CALL_SUBTEST(( jacobisvd_compare_to_full(m, ComputeThinU|ComputeThinV, fullSvd) )); + CALL_SUBTEST(( jacobisvd_solve(m, ComputeFullU | ComputeThinV) )); + CALL_SUBTEST(( jacobisvd_solve(m, ComputeThinU | ComputeFullV) )); + CALL_SUBTEST(( jacobisvd_solve(m, ComputeThinU | ComputeThinV) )); // test reconstruction typedef typename MatrixType::Index Index; @@ -176,12 +204,29 @@ void jacobisvd_test_all_computation_options(const MatrixType& m) template void jacobisvd(const MatrixType& a = MatrixType(), bool pickrandom = true) { - MatrixType m = pickrandom ? MatrixType::Random(a.rows(), a.cols()) : a; + MatrixType m = a; + if(pickrandom) + { + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::RealScalar RealScalar; + typedef typename MatrixType::Index Index; + Index diagSize = (std::min)(a.rows(), a.cols()); + RealScalar s = std::numeric_limits::max_exponent10/4; + s = internal::random(1,s); + Matrix d = Matrix::Random(diagSize); + for(Index k=0; k(-s,s)); + m = Matrix::Random(a.rows(),diagSize) * d.asDiagonal() * Matrix::Random(diagSize,a.cols()); + // cancel some coeffs + Index n = internal::random(0,m.size()-1); + for(Index i=0; i(0,m.rows()-1), internal::random(0,m.cols()-1)) = Scalar(0); + } - jacobisvd_test_all_computation_options(m); - jacobisvd_test_all_computation_options(m); - jacobisvd_test_all_computation_options(m); - jacobisvd_test_all_computation_options(m); + CALL_SUBTEST(( jacobisvd_test_all_computation_options(m) )); + CALL_SUBTEST(( jacobisvd_test_all_computation_options(m) )); + CALL_SUBTEST(( jacobisvd_test_all_computation_options(m) )); + CALL_SUBTEST(( jacobisvd_test_all_computation_options(m) )); } template void jacobisvd_verify_assert(const MatrixType& m) @@ -384,6 +429,7 @@ void test_jacobisvd() TEST_SET_BUT_UNUSED_VARIABLE(r) TEST_SET_BUT_UNUSED_VARIABLE(c) + CALL_SUBTEST_10(( jacobisvd(MatrixXd(r,c)) )); CALL_SUBTEST_7(( jacobisvd(MatrixXf(r,c)) )); CALL_SUBTEST_8(( jacobisvd(MatrixXcd(r,c)) )); (void) r;