|  | // This file is part of Eigen, a lightweight C++ template library | 
|  | // for linear algebra. | 
|  | // | 
|  | // Copyright (C) 2010 Hauke Heibel <hauke.heibel@gmail.com> | 
|  | // Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.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/. | 
|  |  | 
|  | #define TEST_ENABLE_TEMPORARY_TRACKING | 
|  |  | 
|  | #include "main.h" | 
|  |  | 
|  | template <int N, typename XprType> | 
|  | void use_n_times(const XprType& xpr) { | 
|  | typename internal::nested_eval<XprType, N>::type mat(xpr); | 
|  | typename XprType::PlainObject res(mat.rows(), mat.cols()); | 
|  | nb_temporaries--;  // remove res | 
|  | res.setZero(); | 
|  | for (int i = 0; i < N; ++i) res += mat; | 
|  | } | 
|  |  | 
|  | template <int N, typename ReferenceType, typename XprType> | 
|  | bool verify_eval_type(const XprType&, const ReferenceType&) { | 
|  | typedef typename internal::nested_eval<XprType, N>::type EvalType; | 
|  | return internal::is_same<internal::remove_all_t<EvalType>, internal::remove_all_t<ReferenceType>>::value; | 
|  | } | 
|  |  | 
|  | template <typename MatrixType> | 
|  | void run_nesting_ops_1(const MatrixType& _m) { | 
|  | typename internal::nested_eval<MatrixType, 2>::type m(_m); | 
|  |  | 
|  | // Make really sure that we are in debug mode! | 
|  | VERIFY_RAISES_ASSERT(eigen_assert(false)); | 
|  |  | 
|  | // The only intention of these tests is to ensure that this code does | 
|  | // not trigger any asserts or segmentation faults... more to come. | 
|  | VERIFY_IS_APPROX((m.transpose() * m).diagonal().sum(), (m.transpose() * m).diagonal().sum()); | 
|  | VERIFY_IS_APPROX((m.transpose() * m).diagonal().array().abs().sum(), | 
|  | (m.transpose() * m).diagonal().array().abs().sum()); | 
|  |  | 
|  | VERIFY_IS_APPROX((m.transpose() * m).array().abs().sum(), (m.transpose() * m).array().abs().sum()); | 
|  | } | 
|  |  | 
|  | template <typename MatrixType> | 
|  | void run_nesting_ops_2(const MatrixType& _m) { | 
|  | typedef typename MatrixType::Scalar Scalar; | 
|  | Index rows = _m.rows(); | 
|  | Index cols = _m.cols(); | 
|  | MatrixType m1 = MatrixType::Random(rows, cols); | 
|  | Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime, ColMajor> m2; | 
|  |  | 
|  | if ((MatrixType::SizeAtCompileTime == Dynamic)) { | 
|  | VERIFY_EVALUATION_COUNT(use_n_times<1>(m1 + m1 * m1), 1); | 
|  | VERIFY_EVALUATION_COUNT(use_n_times<10>(m1 + m1 * m1), 1); | 
|  |  | 
|  | VERIFY_EVALUATION_COUNT(use_n_times<1>(m1.template triangularView<Lower>().solve(m1.col(0))), 1); | 
|  | VERIFY_EVALUATION_COUNT(use_n_times<10>(m1.template triangularView<Lower>().solve(m1.col(0))), 1); | 
|  |  | 
|  | VERIFY_EVALUATION_COUNT(use_n_times<1>(Scalar(2) * m1.template triangularView<Lower>().solve(m1.col(0))), | 
|  | 2);  // FIXME could be one by applying the scaling in-place on the solve result | 
|  | VERIFY_EVALUATION_COUNT(use_n_times<1>(m1.col(0) + m1.template triangularView<Lower>().solve(m1.col(0))), | 
|  | 2);  // FIXME could be one by adding m1.col() inplace | 
|  | VERIFY_EVALUATION_COUNT(use_n_times<10>(m1.col(0) + m1.template triangularView<Lower>().solve(m1.col(0))), 2); | 
|  | } | 
|  |  | 
|  | { | 
|  | VERIFY(verify_eval_type<10>(m1, m1)); | 
|  | if (!NumTraits<Scalar>::IsComplex) { | 
|  | VERIFY(verify_eval_type<3>(2 * m1, 2 * m1)); | 
|  | VERIFY(verify_eval_type<4>(2 * m1, m1)); | 
|  | } else { | 
|  | VERIFY(verify_eval_type<2>(2 * m1, 2 * m1)); | 
|  | VERIFY(verify_eval_type<3>(2 * m1, m1)); | 
|  | } | 
|  | VERIFY(verify_eval_type<2>(m1 + m1, m1 + m1)); | 
|  | VERIFY(verify_eval_type<3>(m1 + m1, m1)); | 
|  | VERIFY(verify_eval_type<1>(m1 * m1.transpose(), m2)); | 
|  | VERIFY(verify_eval_type<1>(m1 * (m1 + m1).transpose(), m2)); | 
|  | VERIFY(verify_eval_type<2>(m1 * m1.transpose(), m2)); | 
|  | VERIFY(verify_eval_type<1>(m1 + m1 * m1, m1)); | 
|  |  | 
|  | VERIFY(verify_eval_type<1>(m1.template triangularView<Lower>().solve(m1), m1)); | 
|  | VERIFY(verify_eval_type<1>(m1 + m1.template triangularView<Lower>().solve(m1), m1)); | 
|  | } | 
|  | } | 
|  |  | 
|  | EIGEN_DECLARE_TEST(nesting_ops) { | 
|  | CALL_SUBTEST_1(run_nesting_ops_1(MatrixXf::Random(25, 25))); | 
|  | CALL_SUBTEST_2(run_nesting_ops_1(MatrixXcd::Random(25, 25))); | 
|  | CALL_SUBTEST_3(run_nesting_ops_1(Matrix4f::Random())); | 
|  | CALL_SUBTEST_4(run_nesting_ops_1(Matrix2d::Random())); | 
|  |  | 
|  | Index s = internal::random<int>(1, EIGEN_TEST_MAX_SIZE); | 
|  | CALL_SUBTEST_1(run_nesting_ops_2(MatrixXf(s, s))); | 
|  | CALL_SUBTEST_2(run_nesting_ops_2(MatrixXcd(s, s))); | 
|  | CALL_SUBTEST_3(run_nesting_ops_2(Matrix4f())); | 
|  | CALL_SUBTEST_4(run_nesting_ops_2(Matrix2d())); | 
|  | TEST_SET_BUT_UNUSED_VARIABLE(s) | 
|  | } |