eigen/test/nesting_ops.cpp
2015-10-09 14:29:46 +02:00

108 lines
3.8 KiB
C++

// 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<typename internal::remove_all<EvalType>::type, typename internal::remove_all<ReferenceType>::type>::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)
{
Index rows = _m.rows();
Index cols = _m.cols();
MatrixType m1 = MatrixType::Random(rows,cols);
if((MatrixType::SizeAtCompileTime==Dynamic))
{
VERIFY_EVALUATION_COUNT( use_n_times<10>(m1), 0 );
if(!NumTraits<typename MatrixType::Scalar>::IsComplex)
{
VERIFY_EVALUATION_COUNT( use_n_times<3>(2*m1), 0 );
VERIFY_EVALUATION_COUNT( use_n_times<4>(2*m1), 1 );
}
else
{
VERIFY_EVALUATION_COUNT( use_n_times<1>(2*m1), 0 );
VERIFY_EVALUATION_COUNT( use_n_times<2>(2*m1), 1 );
}
VERIFY_EVALUATION_COUNT( use_n_times<2>(m1+m1), 0 );
VERIFY_EVALUATION_COUNT( use_n_times<3>(m1+m1), 1 );
VERIFY_EVALUATION_COUNT( use_n_times<1>(m1*m1.transpose()), 1 );
VERIFY_EVALUATION_COUNT( use_n_times<2>(m1*m1.transpose()), 1 );
}
{
VERIFY( verify_eval_type<10>(m1, m1) );
if(!NumTraits<typename MatrixType::Scalar>::IsComplex)
{
VERIFY( verify_eval_type<3>(2*m1, 2*m1) );
VERIFY( verify_eval_type<4>(2*m1, m1) );
}
else
{
VERIFY( verify_eval_type<1>(2*m1, 2*m1) );
VERIFY( verify_eval_type<2>(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(), m1) );
VERIFY( verify_eval_type<1>(m1*(m1+m1).transpose(), m1) );
VERIFY( verify_eval_type<2>(m1*m1.transpose(), m1) );
}
}
void 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()));
CALL_SUBTEST_1( run_nesting_ops_2(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
CALL_SUBTEST_2( run_nesting_ops_2(MatrixXcd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
CALL_SUBTEST_3( run_nesting_ops_2(Matrix4f()) );
CALL_SUBTEST_4( run_nesting_ops_2(Matrix2d()) );
}