nesting_ops.cpp

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// 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)
{
  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)
}