// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2013 Gauthier Brun // Copyright (C) 2013 Nicolas Carre // Copyright (C) 2013 Jean Ceccato // Copyright (C) 2013 Pierre Zoppitelli // // This Source Code Form is subject to the terms of the Mozilla // Public License v. 2.0. If a copy of the MPL was not distributed // with this file, You can obtain one at http://mozilla.org/MPL/2.0/ // discard stack allocation as that too bypasses malloc #define EIGEN_STACK_ALLOCATION_LIMIT 0 #define EIGEN_RUNTIME_NO_MALLOC #include "main.h" #include #define SVD_DEFAULT(M) BDCSVD #define SVD_FOR_MIN_NORM(M) BDCSVD #define SVD_STATIC_OPTIONS(M, O) BDCSVD #include "svd_common.h" template void bdcsvd_method() { enum { Size = MatrixType::RowsAtCompileTime }; typedef typename MatrixType::RealScalar RealScalar; typedef Matrix RealVecType; MatrixType m = MatrixType::Identity(); VERIFY_IS_APPROX(m.bdcSvd().singularValues(), RealVecType::Ones()); VERIFY_RAISES_ASSERT(m.bdcSvd().matrixU()); VERIFY_RAISES_ASSERT(m.bdcSvd().matrixV()); } // compare the Singular values returned with Jacobi and Bdc template void compare_bdc_jacobi(const MatrixType& a = MatrixType(), int algoswap = 16, bool random = true) { MatrixType m = random ? MatrixType::Random(a.rows(), a.cols()) : a; BDCSVD bdc_svd(m.rows(), m.cols()); bdc_svd.setSwitchSize(algoswap); bdc_svd.compute(m); JacobiSVD jacobi_svd(m); VERIFY_IS_APPROX(bdc_svd.singularValues(), jacobi_svd.singularValues()); } // Verifies total deflation is **not** triggered. void compare_bdc_jacobi_instance(bool structure_as_m, int algoswap = 16) { MatrixXd m(4, 3); if (structure_as_m) { // The first 3 rows are the reduced form of Matrix 1 as shown below, and it // has nonzero elements in the first column and diagonals only. m << 1.056293, 0, 0, -0.336468, 0.907359, 0, -1.566245, 0, 0.149150, -0.1, 0, 0; } else { // Matrix 1. m << 0.882336, 18.3914, -26.7921, -5.58135, 17.1931, -24.0892, -20.794, 8.68496, -4.83103, -8.4981, -10.5451, 23.9072; } compare_bdc_jacobi(m, algoswap, false); } template void bdcsvd_thin_options(const MatrixType& input = MatrixType()) { svd_thin_option_checks(input); } template void bdcsvd_full_options(const MatrixType& input = MatrixType()) { svd_option_checks_full_only(input); } template void bdcsvd_verify_assert(const MatrixType& input = MatrixType()) { svd_verify_assert(input); svd_verify_constructor_options_assert>(input); } template void bdcsvd_check_convergence(const MatrixType& input) { BDCSVD svd(input); VERIFY(svd.info() == Eigen::Success); MatrixType D = svd.matrixU() * svd.singularValues().asDiagonal() * svd.matrixV().transpose(); VERIFY_IS_APPROX(input, D); } EIGEN_DECLARE_TEST(bdcsvd) { CALL_SUBTEST_1((bdcsvd_verify_assert())); CALL_SUBTEST_2((bdcsvd_verify_assert())); CALL_SUBTEST_3((bdcsvd_verify_assert>())); CALL_SUBTEST_4((bdcsvd_verify_assert>())); CALL_SUBTEST_5((bdcsvd_verify_assert, 6, 9>>())); CALL_SUBTEST_6((svd_all_trivial_2x2(bdcsvd_thin_options))); CALL_SUBTEST_7((svd_all_trivial_2x2(bdcsvd_full_options))); CALL_SUBTEST_8((svd_all_trivial_2x2(bdcsvd_thin_options))); CALL_SUBTEST_9((svd_all_trivial_2x2(bdcsvd_full_options))); for (int i = 0; i < g_repeat; i++) { int r = internal::random(1, EIGEN_TEST_MAX_SIZE / 2), c = internal::random(1, EIGEN_TEST_MAX_SIZE / 2); TEST_SET_BUT_UNUSED_VARIABLE(r) TEST_SET_BUT_UNUSED_VARIABLE(c) CALL_SUBTEST_10((compare_bdc_jacobi(MatrixXf(r, c)))); CALL_SUBTEST_11((compare_bdc_jacobi(MatrixXd(r, c)))); CALL_SUBTEST_12((compare_bdc_jacobi(MatrixXcd(r, c)))); // Test on inf/nan matrix CALL_SUBTEST_13((svd_inf_nan())); CALL_SUBTEST_14((svd_inf_nan())); // Verify some computations using all combinations of the Options template parameter. CALL_SUBTEST_15((bdcsvd_thin_options())); CALL_SUBTEST_16((bdcsvd_full_options())); CALL_SUBTEST_17((bdcsvd_thin_options>())); CALL_SUBTEST_18((bdcsvd_full_options>())); CALL_SUBTEST_19((bdcsvd_thin_options(MatrixXd(20, 17)))); CALL_SUBTEST_20((bdcsvd_full_options(MatrixXd(20, 17)))); CALL_SUBTEST_21((bdcsvd_thin_options(MatrixXd(17, 20)))); CALL_SUBTEST_22((bdcsvd_full_options(MatrixXd(17, 20)))); CALL_SUBTEST_23((bdcsvd_thin_options>(Matrix(r, 15)))); CALL_SUBTEST_24((bdcsvd_full_options>(Matrix(r, 15)))); CALL_SUBTEST_25((bdcsvd_thin_options>(Matrix(13, c)))); CALL_SUBTEST_26((bdcsvd_full_options>(Matrix(13, c)))); CALL_SUBTEST_27((bdcsvd_thin_options(MatrixXf(r, c)))); CALL_SUBTEST_28((bdcsvd_full_options(MatrixXf(r, c)))); CALL_SUBTEST_29((bdcsvd_thin_options(MatrixXcd(r, c)))); CALL_SUBTEST_30((bdcsvd_full_options(MatrixXcd(r, c)))); CALL_SUBTEST_31((bdcsvd_thin_options(MatrixXd(r, c)))); CALL_SUBTEST_32((bdcsvd_full_options(MatrixXd(r, c)))); CALL_SUBTEST_33((bdcsvd_thin_options>( Matrix(20, 27)))); CALL_SUBTEST_34((bdcsvd_full_options>( Matrix(20, 27)))); CALL_SUBTEST_35((bdcsvd_thin_options>( Matrix(27, 20)))); CALL_SUBTEST_36((bdcsvd_full_options>( Matrix(27, 20)))); CALL_SUBTEST_37(( svd_check_max_size_matrix, ColPivHouseholderQRPreconditioner>( r, c))); CALL_SUBTEST_38( (svd_check_max_size_matrix, HouseholderQRPreconditioner>(r, c))); CALL_SUBTEST_39(( svd_check_max_size_matrix, ColPivHouseholderQRPreconditioner>( r, c))); CALL_SUBTEST_40( (svd_check_max_size_matrix, HouseholderQRPreconditioner>(r, c))); } // test matrixbase method CALL_SUBTEST_41((bdcsvd_method())); CALL_SUBTEST_42((bdcsvd_method())); // Test problem size constructors CALL_SUBTEST_43(BDCSVD(10, 10)); // Check that preallocation avoids subsequent mallocs // Disabled because not supported by BDCSVD // CALL_SUBTEST_9( svd_preallocate() ); CALL_SUBTEST_44(svd_underoverflow()); // Without total deflation issues. CALL_SUBTEST_45((compare_bdc_jacobi_instance(true))); CALL_SUBTEST_46((compare_bdc_jacobi_instance(false))); // With total deflation issues before, when it shouldn't be triggered. CALL_SUBTEST_47((compare_bdc_jacobi_instance(true, 3))); CALL_SUBTEST_48((compare_bdc_jacobi_instance(false, 3))); // Convergence for large constant matrix (https://gitlab.com/libeigen/eigen/-/issues/2491) CALL_SUBTEST_49(bdcsvd_check_convergence(MatrixXf::Constant(500, 500, 1))); }