|  | // 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); | 
|  | typedef typename MatrixType::Index Index; | 
|  | 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); | 
|  | } | 
|  |  | 
|  | void 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>()) ); | 
|  | } | 
|  |  | 
|  | 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>() ); | 
|  | } |