| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2013 Gauthier Brun <brun.gauthier@gmail.com> |
| // Copyright (C) 2013 Nicolas Carre <nicolas.carre@ensimag.fr> |
| // Copyright (C) 2013 Jean Ceccato <jean.ceccato@ensimag.fr> |
| // Copyright (C) 2013 Pierre Zoppitelli <pierre.zoppitelli@ensimag.fr> |
| // |
| // 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 <Eigen/SVD> |
| |
| #define SVD_DEFAULT(M) BDCSVD<M> |
| #define SVD_FOR_MIN_NORM(M) BDCSVD<M> |
| #define SVD_STATIC_OPTIONS(M, O) BDCSVD<M, O> |
| #include "svd_common.h" |
| |
| template <typename MatrixType> |
| void bdcsvd_method() { |
| enum { Size = MatrixType::RowsAtCompileTime }; |
| typedef typename MatrixType::RealScalar RealScalar; |
| typedef Matrix<RealScalar, Size, 1> 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 <typename MatrixType> |
| 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<MatrixType> bdc_svd(m.rows(), m.cols()); |
| bdc_svd.setSwitchSize(algoswap); |
| bdc_svd.compute(m); |
| |
| JacobiSVD<MatrixType> 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 <typename MatrixType> |
| void bdcsvd_thin_options(const MatrixType& input = MatrixType()) { |
| svd_thin_option_checks<MatrixType, 0>(input); |
| } |
| |
| template <typename MatrixType> |
| void bdcsvd_full_options(const MatrixType& input = MatrixType()) { |
| svd_option_checks_full_only<MatrixType, 0>(input); |
| } |
| |
| template <typename MatrixType> |
| void bdcsvd_verify_assert(const MatrixType& input = MatrixType()) { |
| svd_verify_assert<MatrixType>(input); |
| svd_verify_constructor_options_assert<BDCSVD<MatrixType>>(input); |
| } |
| |
| template <typename MatrixType> |
| void bdcsvd_check_convergence(const MatrixType& input) { |
| BDCSVD<MatrixType, Eigen::ComputeThinU | Eigen::ComputeThinV> 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<Matrix3f>())); |
| CALL_SUBTEST_2((bdcsvd_verify_assert<Matrix4d>())); |
| CALL_SUBTEST_3((bdcsvd_verify_assert<Matrix<float, 10, 7>>())); |
| CALL_SUBTEST_4((bdcsvd_verify_assert<Matrix<float, 7, 10>>())); |
| CALL_SUBTEST_5((bdcsvd_verify_assert<Matrix<std::complex<double>, 6, 9>>())); |
| |
| CALL_SUBTEST_6((svd_all_trivial_2x2(bdcsvd_thin_options<Matrix2cd>))); |
| CALL_SUBTEST_7((svd_all_trivial_2x2(bdcsvd_full_options<Matrix2cd>))); |
| CALL_SUBTEST_8((svd_all_trivial_2x2(bdcsvd_thin_options<Matrix2d>))); |
| CALL_SUBTEST_9((svd_all_trivial_2x2(bdcsvd_full_options<Matrix2d>))); |
| |
| for (int i = 0; i < g_repeat; i++) { |
| int r = internal::random<int>(1, EIGEN_TEST_MAX_SIZE / 2), c = internal::random<int>(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>(MatrixXf(r, c)))); |
| CALL_SUBTEST_11((compare_bdc_jacobi<MatrixXd>(MatrixXd(r, c)))); |
| CALL_SUBTEST_12((compare_bdc_jacobi<MatrixXcd>(MatrixXcd(r, c)))); |
| // Test on inf/nan matrix |
| CALL_SUBTEST_13((svd_inf_nan<MatrixXf>())); |
| CALL_SUBTEST_14((svd_inf_nan<MatrixXd>())); |
| |
| // Verify some computations using all combinations of the Options template parameter. |
| CALL_SUBTEST_15((bdcsvd_thin_options<Matrix3f>())); |
| CALL_SUBTEST_16((bdcsvd_full_options<Matrix3f>())); |
| CALL_SUBTEST_17((bdcsvd_thin_options<Matrix<float, 2, 3>>())); |
| CALL_SUBTEST_18((bdcsvd_full_options<Matrix<float, 2, 3>>())); |
| CALL_SUBTEST_19((bdcsvd_thin_options<MatrixXd>(MatrixXd(20, 17)))); |
| CALL_SUBTEST_20((bdcsvd_full_options<MatrixXd>(MatrixXd(20, 17)))); |
| CALL_SUBTEST_21((bdcsvd_thin_options<MatrixXd>(MatrixXd(17, 20)))); |
| CALL_SUBTEST_22((bdcsvd_full_options<MatrixXd>(MatrixXd(17, 20)))); |
| CALL_SUBTEST_23((bdcsvd_thin_options<Matrix<double, Dynamic, 15>>(Matrix<double, Dynamic, 15>(r, 15)))); |
| CALL_SUBTEST_24((bdcsvd_full_options<Matrix<double, Dynamic, 15>>(Matrix<double, Dynamic, 15>(r, 15)))); |
| CALL_SUBTEST_25((bdcsvd_thin_options<Matrix<double, 13, Dynamic>>(Matrix<double, 13, Dynamic>(13, c)))); |
| CALL_SUBTEST_26((bdcsvd_full_options<Matrix<double, 13, Dynamic>>(Matrix<double, 13, Dynamic>(13, c)))); |
| CALL_SUBTEST_27((bdcsvd_thin_options<MatrixXf>(MatrixXf(r, c)))); |
| CALL_SUBTEST_28((bdcsvd_full_options<MatrixXf>(MatrixXf(r, c)))); |
| CALL_SUBTEST_29((bdcsvd_thin_options<MatrixXcd>(MatrixXcd(r, c)))); |
| CALL_SUBTEST_30((bdcsvd_full_options<MatrixXcd>(MatrixXcd(r, c)))); |
| CALL_SUBTEST_31((bdcsvd_thin_options<MatrixXd>(MatrixXd(r, c)))); |
| CALL_SUBTEST_32((bdcsvd_full_options<MatrixXd>(MatrixXd(r, c)))); |
| CALL_SUBTEST_33((bdcsvd_thin_options<Matrix<double, Dynamic, Dynamic, RowMajor>>( |
| Matrix<double, Dynamic, Dynamic, RowMajor>(20, 27)))); |
| CALL_SUBTEST_34((bdcsvd_full_options<Matrix<double, Dynamic, Dynamic, RowMajor>>( |
| Matrix<double, Dynamic, Dynamic, RowMajor>(20, 27)))); |
| CALL_SUBTEST_35((bdcsvd_thin_options<Matrix<double, Dynamic, Dynamic, RowMajor>>( |
| Matrix<double, Dynamic, Dynamic, RowMajor>(27, 20)))); |
| CALL_SUBTEST_36((bdcsvd_full_options<Matrix<double, Dynamic, Dynamic, RowMajor>>( |
| Matrix<double, Dynamic, Dynamic, RowMajor>(27, 20)))); |
| CALL_SUBTEST_37(( |
| svd_check_max_size_matrix<Matrix<float, Dynamic, Dynamic, ColMajor, 20, 35>, ColPivHouseholderQRPreconditioner>( |
| r, c))); |
| CALL_SUBTEST_38( |
| (svd_check_max_size_matrix<Matrix<float, Dynamic, Dynamic, ColMajor, 35, 20>, HouseholderQRPreconditioner>(r, |
| c))); |
| CALL_SUBTEST_39(( |
| svd_check_max_size_matrix<Matrix<float, Dynamic, Dynamic, RowMajor, 20, 35>, ColPivHouseholderQRPreconditioner>( |
| r, c))); |
| CALL_SUBTEST_40( |
| (svd_check_max_size_matrix<Matrix<float, Dynamic, Dynamic, RowMajor, 35, 20>, HouseholderQRPreconditioner>(r, |
| c))); |
| } |
| |
| // test matrixbase method |
| CALL_SUBTEST_41((bdcsvd_method<Matrix2cd>())); |
| CALL_SUBTEST_42((bdcsvd_method<Matrix3f>())); |
| |
| // Test problem size constructors |
| CALL_SUBTEST_43(BDCSVD<MatrixXf>(10, 10)); |
| |
| // Check that preallocation avoids subsequent mallocs |
| // Disabled because not supported by BDCSVD |
| // CALL_SUBTEST_9( svd_preallocate<void>() ); |
| |
| CALL_SUBTEST_44(svd_underoverflow<void>()); |
| |
| // 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>(MatrixXf::Constant(500, 500, 1))); |
| } |