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111 lines
3.5 KiB
C++
111 lines
3.5 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra. Eigen itself is part of the KDE project.
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//
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// Copyright (C) 2008 Daniel Gomez Ferro <dgomezferro@gmail.com>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#include "main.h"
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#include <Eigen/Sparse>
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template<typename Scalar> void sparse()
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{
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int rows = 8, cols = 8;
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double density = std::max(8./(rows*cols), 0.01);
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typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
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Scalar eps = 1e-6;
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SparseMatrix<Scalar> m(rows, cols);
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DenseMatrix refMat = DenseMatrix::Zero(rows, cols);
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std::vector<Vector2i> zeroCoords;
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std::vector<Vector2i> nonzeroCoords;
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m.startFill(rows*cols*density);
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for(int j=0; j<cols; j++)
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{
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for(int i=0; i<rows; i++)
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{
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Scalar v = (ei_random<Scalar>(0,1) < density) ? ei_random<Scalar>() : 0;
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if (v!=0)
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{
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m.fill(i,j) = v;
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nonzeroCoords.push_back(Vector2i(i,j));
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}
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else
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{
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zeroCoords.push_back(Vector2i(i,j));
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}
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refMat(i,j) = v;
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}
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}
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m.endFill();
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VERIFY(zeroCoords.size()>0 && "re-run the test");
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VERIFY(nonzeroCoords.size()>0 && "re-run the test");
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// test coeff and coeffRef
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for (int i=0; i<(int)zeroCoords.size(); ++i)
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{
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VERIFY_IS_MUCH_SMALLER_THAN( m.coeff(zeroCoords[i].x(),zeroCoords[i].y()), eps );
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VERIFY_RAISES_ASSERT( m.coeffRef(zeroCoords[0].x(),zeroCoords[0].y()) = 5 );
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}
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VERIFY_IS_APPROX(m, refMat);
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m.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
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refMat.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
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VERIFY_IS_APPROX(m, refMat);
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// test SparseSetters
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// coherent setter
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// TODO extend the MatrixSetter
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// {
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// m.setZero();
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// VERIFY_IS_NOT_APPROX(m, refMat);
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// SparseSetter<SparseMatrix<Scalar>, FullyCoherentAccessPattern> w(m);
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// for (int i=0; i<nonzeroCoords.size(); ++i)
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// {
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// w->coeffRef(nonzeroCoords[i].x(),nonzeroCoords[i].y()) = refMat.coeff(nonzeroCoords[i].x(),nonzeroCoords[i].y());
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// }
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// }
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// VERIFY_IS_APPROX(m, refMat);
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// random setter
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{
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m.setZero();
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VERIFY_IS_NOT_APPROX(m, refMat);
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SparseSetter<SparseMatrix<Scalar>, RandomAccessPattern> w(m);
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std::vector<Vector2i> remaining = nonzeroCoords;
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while(!remaining.empty())
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{
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int i = ei_random<int>(0,remaining.size()-1);
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w->coeffRef(remaining[i].x(),remaining[i].y()) = refMat.coeff(remaining[i].x(),remaining[i].y());
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remaining[i] = remaining.back();
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remaining.pop_back();
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}
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}
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VERIFY_IS_APPROX(m, refMat);
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}
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void test_sparse()
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{
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sparse<double>();
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}
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