| // 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> | |
| #include <iostream> | |
| #include <Eigen/LU> | |
| #define SVD_DEFAULT(M) BDCSVD<M> | |
| #define SVD_FOR_MIN_NORM(M) BDCSVD<M> | |
| #include "svd_common.h" | |
| // Check all variants of JacobiSVD | |
| template<typename MatrixType> | |
| void bdcsvd(const MatrixType& a = MatrixType(), bool pickrandom = true) | |
| { | |
| MatrixType m = a; | |
| if(pickrandom) | |
| svd_fill_random(m); | |
| CALL_SUBTEST(( svd_test_all_computation_options<BDCSVD<MatrixType> >(m, false) )); | |
| } | |
| 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()); | |
| VERIFY_IS_APPROX(m.bdcSvd(ComputeFullU|ComputeFullV).solve(m), m); | |
| VERIFY_IS_APPROX(m.bdcSvd(ComputeFullU|ComputeFullV).transpose().solve(m), m); | |
| VERIFY_IS_APPROX(m.bdcSvd(ComputeFullU|ComputeFullV).adjoint().solve(m), m); | |
| } | |
| // compare the Singular values returned with Jacobi and Bdc | |
| template<typename MatrixType> | |
| void compare_bdc_jacobi(const MatrixType& a = MatrixType(), unsigned int computationOptions = 0) | |
| { | |
| MatrixType m = MatrixType::Random(a.rows(), a.cols()); | |
| BDCSVD<MatrixType> bdc_svd(m); | |
| JacobiSVD<MatrixType> jacobi_svd(m); | |
| VERIFY_IS_APPROX(bdc_svd.singularValues(), jacobi_svd.singularValues()); | |
| if(computationOptions & ComputeFullU) VERIFY_IS_APPROX(bdc_svd.matrixU(), jacobi_svd.matrixU()); | |
| if(computationOptions & ComputeThinU) VERIFY_IS_APPROX(bdc_svd.matrixU(), jacobi_svd.matrixU()); | |
| if(computationOptions & ComputeFullV) VERIFY_IS_APPROX(bdc_svd.matrixV(), jacobi_svd.matrixV()); | |
| if(computationOptions & ComputeThinV) VERIFY_IS_APPROX(bdc_svd.matrixV(), jacobi_svd.matrixV()); | |
| } | |
| EIGEN_DECLARE_TEST(bdcsvd) | |
| { | |
| CALL_SUBTEST_3(( svd_verify_assert<BDCSVD<Matrix3f> >(Matrix3f()) )); | |
| CALL_SUBTEST_4(( svd_verify_assert<BDCSVD<Matrix4d> >(Matrix4d()) )); | |
| CALL_SUBTEST_7(( svd_verify_assert<BDCSVD<MatrixXf> >(MatrixXf(10,12)) )); | |
| CALL_SUBTEST_8(( svd_verify_assert<BDCSVD<MatrixXcd> >(MatrixXcd(7,5)) )); | |
| CALL_SUBTEST_101(( svd_all_trivial_2x2(bdcsvd<Matrix2cd>) )); | |
| CALL_SUBTEST_102(( svd_all_trivial_2x2(bdcsvd<Matrix2d>) )); | |
| for(int i = 0; i < g_repeat; i++) { | |
| CALL_SUBTEST_3(( bdcsvd<Matrix3f>() )); | |
| CALL_SUBTEST_4(( bdcsvd<Matrix4d>() )); | |
| CALL_SUBTEST_5(( bdcsvd<Matrix<float,3,5> >() )); | |
| 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_6(( bdcsvd(Matrix<double,Dynamic,2>(r,2)) )); | |
| CALL_SUBTEST_7(( bdcsvd(MatrixXf(r,c)) )); | |
| CALL_SUBTEST_7(( compare_bdc_jacobi(MatrixXf(r,c)) )); | |
| CALL_SUBTEST_10(( bdcsvd(MatrixXd(r,c)) )); | |
| CALL_SUBTEST_10(( compare_bdc_jacobi(MatrixXd(r,c)) )); | |
| CALL_SUBTEST_8(( bdcsvd(MatrixXcd(r,c)) )); | |
| CALL_SUBTEST_8(( compare_bdc_jacobi(MatrixXcd(r,c)) )); | |
| // Test on inf/nan matrix | |
| CALL_SUBTEST_7( (svd_inf_nan<BDCSVD<MatrixXf>, MatrixXf>()) ); | |
| CALL_SUBTEST_10( (svd_inf_nan<BDCSVD<MatrixXd>, MatrixXd>()) ); | |
| } | |
| // test matrixbase method | |
| CALL_SUBTEST_1(( bdcsvd_method<Matrix2cd>() )); | |
| CALL_SUBTEST_3(( bdcsvd_method<Matrix3f>() )); | |
| // Test problem size constructors | |
| CALL_SUBTEST_7( BDCSVD<MatrixXf>(10,10) ); | |
| // Check that preallocation avoids subsequent mallocs | |
| // Disabled because not supported by BDCSVD | |
| // CALL_SUBTEST_9( svd_preallocate<void>() ); | |
| CALL_SUBTEST_2( svd_underoverflow<void>() ); | |
| } | |