diff options
author | Gael Guennebaud <g.gael@free.fr> | 2014-07-17 17:09:15 +0200 |
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committer | Gael Guennebaud <g.gael@free.fr> | 2014-07-17 17:09:15 +0200 |
commit | da62eb22e497d864ccaed93907818a384bad8e2a (patch) | |
tree | b37ecb524f1bad26050c2501af08b6ff66327189 /test/jacobisvd.cpp | |
parent | 77af4cc3c9fac237d8fcf32379137b14c203033f (diff) |
bug #843: fix jacobisvd for complexes and extend respective unit test to chack with random tricky matrices
Diffstat (limited to 'test/jacobisvd.cpp')
-rw-r--r-- | test/jacobisvd.cpp | 88 |
1 files changed, 67 insertions, 21 deletions
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<typename MatrixType, int QRPreconditioner> 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<Index>(1, cols)); JacobiSVD<MatrixType, QRPreconditioner> svd(m, computationOptions); + + if(internal::is_same<RealScalar,double>::value) svd.setThreshold(1e-8); + else if(internal::is_same<RealScalar,float>::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<x.rows();++k) + { + SolutionType y(x); + y.row(k).array() += 2*NumTraits<RealScalar>::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<RealScalar>::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<RealScalar,double>::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<MatrixType, QRPreconditioner> fullSvd(m, ComputeFullU|ComputeFullV); - - jacobisvd_check_full(m, fullSvd); - jacobisvd_solve<MatrixType, QRPreconditioner>(m, ComputeFullU | ComputeFullV); - + CALL_SUBTEST(( jacobisvd_check_full(m, fullSvd) )); + CALL_SUBTEST(( jacobisvd_solve<MatrixType, QRPreconditioner>(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<MatrixType, QRPreconditioner>(m, ComputeFullU | ComputeThinV); - jacobisvd_solve<MatrixType, QRPreconditioner>(m, ComputeThinU | ComputeFullV); - jacobisvd_solve<MatrixType, QRPreconditioner>(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<MatrixType, QRPreconditioner>(m, ComputeFullU | ComputeThinV) )); + CALL_SUBTEST(( jacobisvd_solve<MatrixType, QRPreconditioner>(m, ComputeThinU | ComputeFullV) )); + CALL_SUBTEST(( jacobisvd_solve<MatrixType, QRPreconditioner>(m, ComputeThinU | ComputeThinV) )); // test reconstruction typedef typename MatrixType::Index Index; @@ -176,12 +204,29 @@ void jacobisvd_test_all_computation_options(const MatrixType& m) template<typename MatrixType> 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<RealScalar>::max_exponent10/4; + s = internal::random<RealScalar>(1,s); + Matrix<RealScalar,Dynamic,1> d = Matrix<RealScalar,Dynamic,1>::Random(diagSize); + for(Index k=0; k<diagSize; ++k) + d(k) = d(k)*std::pow(RealScalar(10),internal::random<RealScalar>(-s,s)); + m = Matrix<Scalar,Dynamic,Dynamic>::Random(a.rows(),diagSize) * d.asDiagonal() * Matrix<Scalar,Dynamic,Dynamic>::Random(diagSize,a.cols()); + // cancel some coeffs + Index n = internal::random<Index>(0,m.size()-1); + for(Index i=0; i<n; ++i) + m(internal::random<Index>(0,m.rows()-1), internal::random<Index>(0,m.cols()-1)) = Scalar(0); + } - jacobisvd_test_all_computation_options<MatrixType, FullPivHouseholderQRPreconditioner>(m); - jacobisvd_test_all_computation_options<MatrixType, ColPivHouseholderQRPreconditioner>(m); - jacobisvd_test_all_computation_options<MatrixType, HouseholderQRPreconditioner>(m); - jacobisvd_test_all_computation_options<MatrixType, NoQRPreconditioner>(m); + CALL_SUBTEST(( jacobisvd_test_all_computation_options<MatrixType, FullPivHouseholderQRPreconditioner>(m) )); + CALL_SUBTEST(( jacobisvd_test_all_computation_options<MatrixType, ColPivHouseholderQRPreconditioner>(m) )); + CALL_SUBTEST(( jacobisvd_test_all_computation_options<MatrixType, HouseholderQRPreconditioner>(m) )); + CALL_SUBTEST(( jacobisvd_test_all_computation_options<MatrixType, NoQRPreconditioner>(m) )); } template<typename MatrixType> 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>(MatrixXd(r,c)) )); CALL_SUBTEST_7(( jacobisvd<MatrixXf>(MatrixXf(r,c)) )); CALL_SUBTEST_8(( jacobisvd<MatrixXcd>(MatrixXcd(r,c)) )); (void) r; |