| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr> |
| // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com> |
| // |
| // 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) JacobiSVD<M> |
| #define SVD_FOR_MIN_NORM(M) JacobiSVD<M,ColPivHouseholderQRPreconditioner> |
| #include "svd_common.h" |
| |
| // Check all variants of JacobiSVD |
| template<typename MatrixType> |
| void jacobisvd(const MatrixType& a = MatrixType(), bool pickrandom = true) |
| { |
| MatrixType m = a; |
| if(pickrandom) |
| svd_fill_random(m); |
| |
| CALL_SUBTEST(( svd_test_all_computation_options<JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner> >(m, true) )); // check full only |
| CALL_SUBTEST(( svd_test_all_computation_options<JacobiSVD<MatrixType, ColPivHouseholderQRPreconditioner> >(m, false) )); |
| CALL_SUBTEST(( svd_test_all_computation_options<JacobiSVD<MatrixType, HouseholderQRPreconditioner> >(m, false) )); |
| if(m.rows()==m.cols()) |
| CALL_SUBTEST(( svd_test_all_computation_options<JacobiSVD<MatrixType, NoQRPreconditioner> >(m, false) )); |
| } |
| |
| template<typename MatrixType> void jacobisvd_verify_assert(const MatrixType& m) |
| { |
| svd_verify_assert<JacobiSVD<MatrixType> >(m); |
| Index rows = m.rows(); |
| Index cols = m.cols(); |
| |
| enum { |
| ColsAtCompileTime = MatrixType::ColsAtCompileTime |
| }; |
| |
| |
| MatrixType a = MatrixType::Zero(rows, cols); |
| a.setZero(); |
| |
| if (ColsAtCompileTime == Dynamic) |
| { |
| JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner> svd_fullqr; |
| VERIFY_RAISES_ASSERT(svd_fullqr.compute(a, ComputeFullU|ComputeThinV)) |
| VERIFY_RAISES_ASSERT(svd_fullqr.compute(a, ComputeThinU|ComputeThinV)) |
| VERIFY_RAISES_ASSERT(svd_fullqr.compute(a, ComputeThinU|ComputeFullV)) |
| } |
| } |
| |
| template<typename MatrixType> |
| void jacobisvd_method() |
| { |
| enum { Size = MatrixType::RowsAtCompileTime }; |
| typedef typename MatrixType::RealScalar RealScalar; |
| typedef Matrix<RealScalar, Size, 1> RealVecType; |
| MatrixType m = MatrixType::Identity(); |
| VERIFY_IS_APPROX(m.jacobiSvd().singularValues(), RealVecType::Ones()); |
| VERIFY_RAISES_ASSERT(m.jacobiSvd().matrixU()); |
| VERIFY_RAISES_ASSERT(m.jacobiSvd().matrixV()); |
| VERIFY_IS_APPROX(m.jacobiSvd(ComputeFullU|ComputeFullV).solve(m), m); |
| VERIFY_IS_APPROX(m.jacobiSvd(ComputeFullU|ComputeFullV).transpose().solve(m), m); |
| VERIFY_IS_APPROX(m.jacobiSvd(ComputeFullU|ComputeFullV).adjoint().solve(m), m); |
| } |
| |
| namespace Foo { |
| // older compiler require a default constructor for Bar |
| // cf: https://stackoverflow.com/questions/7411515/ |
| class Bar {public: Bar() {}}; |
| bool operator<(const Bar&, const Bar&) { return true; } |
| } |
| // regression test for a very strange MSVC issue for which simply |
| // including SVDBase.h messes up with std::max and custom scalar type |
| void msvc_workaround() |
| { |
| const Foo::Bar a; |
| const Foo::Bar b; |
| std::max EIGEN_NOT_A_MACRO (a,b); |
| } |
| |
| EIGEN_DECLARE_TEST(jacobisvd) |
| { |
| CALL_SUBTEST_3(( jacobisvd_verify_assert(Matrix3f()) )); |
| CALL_SUBTEST_4(( jacobisvd_verify_assert(Matrix4d()) )); |
| CALL_SUBTEST_7(( jacobisvd_verify_assert(MatrixXf(10,12)) )); |
| CALL_SUBTEST_8(( jacobisvd_verify_assert(MatrixXcd(7,5)) )); |
| |
| CALL_SUBTEST_11(svd_all_trivial_2x2(jacobisvd<Matrix2cd>)); |
| CALL_SUBTEST_12(svd_all_trivial_2x2(jacobisvd<Matrix2d>)); |
| |
| for(int i = 0; i < g_repeat; i++) { |
| CALL_SUBTEST_3(( jacobisvd<Matrix3f>() )); |
| CALL_SUBTEST_4(( jacobisvd<Matrix4d>() )); |
| CALL_SUBTEST_5(( jacobisvd<Matrix<float,3,5> >() )); |
| CALL_SUBTEST_6(( jacobisvd<Matrix<double,Dynamic,2> >(Matrix<double,Dynamic,2>(10,2)) )); |
| |
| int r = internal::random<int>(1, 30), |
| c = internal::random<int>(1, 30); |
| |
| 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; |
| (void) c; |
| |
| // Test on inf/nan matrix |
| CALL_SUBTEST_7( (svd_inf_nan<JacobiSVD<MatrixXf>, MatrixXf>()) ); |
| CALL_SUBTEST_10( (svd_inf_nan<JacobiSVD<MatrixXd>, MatrixXd>()) ); |
| |
| // bug1395 test compile-time vectors as input |
| CALL_SUBTEST_13(( jacobisvd_verify_assert(Matrix<double,6,1>()) )); |
| CALL_SUBTEST_13(( jacobisvd_verify_assert(Matrix<double,1,6>()) )); |
| CALL_SUBTEST_13(( jacobisvd_verify_assert(Matrix<double,Dynamic,1>(r)) )); |
| CALL_SUBTEST_13(( jacobisvd_verify_assert(Matrix<double,1,Dynamic>(c)) )); |
| } |
| |
| CALL_SUBTEST_7(( jacobisvd<MatrixXf>(MatrixXf(internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/2), internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/2))) )); |
| CALL_SUBTEST_8(( jacobisvd<MatrixXcd>(MatrixXcd(internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/3), internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/3))) )); |
| |
| // test matrixbase method |
| CALL_SUBTEST_1(( jacobisvd_method<Matrix2cd>() )); |
| CALL_SUBTEST_3(( jacobisvd_method<Matrix3f>() )); |
| |
| // Test problem size constructors |
| CALL_SUBTEST_7( JacobiSVD<MatrixXf>(10,10) ); |
| |
| // Check that preallocation avoids subsequent mallocs |
| CALL_SUBTEST_9( svd_preallocate<void>() ); |
| |
| CALL_SUBTEST_2( svd_underoverflow<void>() ); |
| |
| msvc_workaround(); |
| } |