// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2010 Hauke Heibel // Copyright (C) 2015 Gael Guennebaud // // 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 void use_n_times(const XprType &xpr) { typename internal::nested_eval::type mat(xpr); typename XprType::PlainObject res(mat.rows(), mat.cols()); nb_temporaries--; // remove res res.setZero(); for(int i=0; i bool verify_eval_type(const XprType &, const ReferenceType&) { typedef typename internal::nested_eval::type EvalType; return internal::is_same::type, typename internal::remove_all::type>::value; } template void run_nesting_ops_1(const MatrixType& _m) { typename internal::nested_eval::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 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 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().solve(m1.col(0))), 1 ); VERIFY_EVALUATION_COUNT( use_n_times<10>(m1.template triangularView().solve(m1.col(0))), 1 ); VERIFY_EVALUATION_COUNT( use_n_times<1>(Scalar(2)*m1.template triangularView().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().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().solve(m1.col(0))), 2 ); } { VERIFY( verify_eval_type<10>(m1, m1) ); if(!NumTraits::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().solve(m1), m1) ); VERIFY( verify_eval_type<1>(m1+m1.template triangularView().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(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) }