source: pacpussensors/trunk/Vislab/lib3dv/eigen/test/eigen2/eigen2_sum.cpp@ 136

// This file is part of Eigen, a lightweight C++ template library
// for linear algebra. Eigen itself is part of the KDE project.
//
// Copyright (C) 2008 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/.

#include "main.h"

template<typename MatrixType> void matrixSum(const MatrixType& m)
{
  typedef typename MatrixType::Scalar Scalar;

  int rows = m.rows();
  int cols = m.cols();

  MatrixType m1 = MatrixType::Random(rows, cols);

  VERIFY_IS_MUCH_SMALLER_THAN(MatrixType::Zero(rows, cols).sum(), Scalar(1));
  VERIFY_IS_APPROX(MatrixType::Ones(rows, cols).sum(), Scalar(float(rows*cols))); // the float() here to shut up excessive MSVC warning about int->complex conversion being lossy
  Scalar x = Scalar(0);
  for(int i = 0; i < rows; i++) for(int j = 0; j < cols; j++) x += m1(i,j);
  VERIFY_IS_APPROX(m1.sum(), x);
}

template<typename VectorType> void vectorSum(const VectorType& w)
{
  typedef typename VectorType::Scalar Scalar;
  int size = w.size();

  VectorType v = VectorType::Random(size);
  for(int i = 1; i < size; i++)
  {
    Scalar s = Scalar(0);
    for(int j = 0; j < i; j++) s += v[j];
    VERIFY_IS_APPROX(s, v.start(i).sum());
  }

  for(int i = 0; i < size-1; i++)
  {
    Scalar s = Scalar(0);
    for(int j = i; j < size; j++) s += v[j];
    VERIFY_IS_APPROX(s, v.end(size-i).sum());
  }

  for(int i = 0; i < size/2; i++)
  {
    Scalar s = Scalar(0);
    for(int j = i; j < size-i; j++) s += v[j];
    VERIFY_IS_APPROX(s, v.segment(i, size-2*i).sum());
  }
}

void test_eigen2_sum()
{
  for(int i = 0; i < g_repeat; i++) {
    CALL_SUBTEST_1( matrixSum(Matrix<float, 1, 1>()) );
    CALL_SUBTEST_2( matrixSum(Matrix2f()) );
    CALL_SUBTEST_3( matrixSum(Matrix4d()) );
    CALL_SUBTEST_4( matrixSum(MatrixXcf(3, 3)) );
    CALL_SUBTEST_5( matrixSum(MatrixXf(8, 12)) );
    CALL_SUBTEST_6( matrixSum(MatrixXi(8, 12)) );
  }
  for(int i = 0; i < g_repeat; i++) {
    CALL_SUBTEST_5( vectorSum(VectorXf(5)) );
    CALL_SUBTEST_7( vectorSum(VectorXd(10)) );
    CALL_SUBTEST_5( vectorSum(VectorXf(33)) );
  }
}