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// 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 Daniel Gomez Ferro <dgomezferro@gmail.com>
//
// 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"
#include <Eigen/Sparse>
template<typename Scalar> void sparse()
{
int rows = 8, cols = 8;
double density = std::max(8./(rows*cols), 0.01);
typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
Scalar eps = 1e-6;
SparseMatrix<Scalar> m(rows, cols);
DenseMatrix refMat = DenseMatrix::Zero(rows, cols);
std::vector<Vector2i> zeroCoords;
std::vector<Vector2i> nonzeroCoords;
m.startFill(rows*cols*density);
for(int j=0; j<cols; j++)
{
for(int i=0; i<rows; i++)
{
Scalar v = (ei_random<Scalar>(0,1) < density) ? ei_random<Scalar>() : 0;
if (v!=0)
{
m.fill(i,j) = v;
nonzeroCoords.push_back(Vector2i(i,j));
}
else
{
zeroCoords.push_back(Vector2i(i,j));
}
refMat(i,j) = v;
}
}
m.endFill();
VERIFY(zeroCoords.size()>0 && "re-run the test");
VERIFY(nonzeroCoords.size()>0 && "re-run the test");
// test coeff and coeffRef
for (int i=0; i<(int)zeroCoords.size(); ++i)
{
VERIFY_IS_MUCH_SMALLER_THAN( m.coeff(zeroCoords[i].x(),zeroCoords[i].y()), eps );
VERIFY_RAISES_ASSERT( m.coeffRef(zeroCoords[0].x(),zeroCoords[0].y()) = 5 );
}
VERIFY_IS_APPROX(m, refMat);
m.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
refMat.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
VERIFY_IS_APPROX(m, refMat);
// test SparseSetters
// coherent setter
// TODO extend the MatrixSetter
// {
// m.setZero();
// VERIFY_IS_NOT_APPROX(m, refMat);
// SparseSetter<SparseMatrix<Scalar>, FullyCoherentAccessPattern> w(m);
// for (int i=0; i<nonzeroCoords.size(); ++i)
// {
// w->coeffRef(nonzeroCoords[i].x(),nonzeroCoords[i].y()) = refMat.coeff(nonzeroCoords[i].x(),nonzeroCoords[i].y());
// }
// }
// VERIFY_IS_APPROX(m, refMat);
// random setter
{
m.setZero();
VERIFY_IS_NOT_APPROX(m, refMat);
SparseSetter<SparseMatrix<Scalar>, RandomAccessPattern> w(m);
std::vector<Vector2i> remaining = nonzeroCoords;
while(!remaining.empty())
{
int i = ei_random<int>(0,remaining.size()-1);
w->coeffRef(remaining[i].x(),remaining[i].y()) = refMat.coeff(remaining[i].x(),remaining[i].y());
remaining[i] = remaining.back();
remaining.pop_back();
}
}
VERIFY_IS_APPROX(m, refMat);
}
void test_sparse()
{
sparse<double>();
}
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