eigen/test/sum.cpp
Gael Guennebaud f0394edfa7 * bugfix in SolveTriangular found by Timothy Hunter (did not compiled for very small fixed size matrices)
* bugfix in Dot unroller
* added special random generator for the unit tests and reduced the tolerance threshold by an order of magnitude
  this fixes issues with sum.cpp but other tests still failed sometimes, this have to be carefully checked...
2008-08-22 17:48:36 +00:00

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C++

// 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@math.jussieu.fr>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#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 = test_random_matrix<MatrixType>(rows, cols);
VERIFY_IS_MUCH_SMALLER_THAN(MatrixType::Zero(rows, cols).sum(), Scalar(1));
VERIFY_IS_APPROX(MatrixType::Ones(rows, cols).sum(), Scalar(rows*cols));
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 = test_random_matrix<VectorType>(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.block(i, size-2*i).sum());
}
}
void test_sum()
{
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST( matrixSum(Matrix<float, 1, 1>()) );
CALL_SUBTEST( matrixSum(Matrix2f()) );
CALL_SUBTEST( matrixSum(Matrix4d()) );
CALL_SUBTEST( matrixSum(MatrixXcf(3, 3)) );
CALL_SUBTEST( matrixSum(MatrixXf(8, 12)) );
CALL_SUBTEST( matrixSum(MatrixXi(8, 12)) );
}
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST( vectorSum(VectorXf(5)) );
CALL_SUBTEST( vectorSum(VectorXd(10)) );
CALL_SUBTEST( vectorSum(VectorXf(33)) );
}
}