// 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 #include #include #define SVD_DEFAULT(M) BDCSVD #define SVD_FOR_MIN_NORM(M) BDCSVD #include "svd_common.h" // Check all variants of JacobiSVD template void bdcsvd(const MatrixType& a = MatrixType(), bool pickrandom = true) { MatrixType m; if(pickrandom) { m.resizeLike(a); svd_fill_random(m); } else m = a; CALL_SUBTEST(( svd_test_all_computation_options >(m, false) )); } 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()); 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 void compare_bdc_jacobi(const MatrixType& a = MatrixType(), unsigned int computationOptions = 0) { MatrixType m = MatrixType::Random(a.rows(), a.cols()); BDCSVD bdc_svd(m); JacobiSVD 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 >(Matrix3f()) )); CALL_SUBTEST_4(( svd_verify_assert >(Matrix4d()) )); CALL_SUBTEST_7(( svd_verify_assert >(MatrixXf(10,12)) )); CALL_SUBTEST_8(( svd_verify_assert >(MatrixXcd(7,5)) )); CALL_SUBTEST_101(( svd_all_trivial_2x2(bdcsvd) )); CALL_SUBTEST_102(( svd_all_trivial_2x2(bdcsvd) )); for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_3(( bdcsvd() )); CALL_SUBTEST_4(( bdcsvd() )); CALL_SUBTEST_5(( bdcsvd >() )); 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_6(( bdcsvd(Matrix(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, MatrixXf>()) ); CALL_SUBTEST_10( (svd_inf_nan, MatrixXd>()) ); } // test matrixbase method CALL_SUBTEST_1(( bdcsvd_method() )); CALL_SUBTEST_3(( bdcsvd_method() )); // Test problem size constructors CALL_SUBTEST_7( BDCSVD(10,10) ); // Check that preallocation avoids subsequent mallocs // Disabled because not supported by BDCSVD // CALL_SUBTEST_9( svd_preallocate() ); CALL_SUBTEST_2( svd_underoverflow() ); }