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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>
//
// 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/.
#ifndef EIGEN_TESTSPARSE_H
#include "main.h"
#if EIGEN_GNUC_AT_LEAST(4,0) && !defined __ICC
#include <tr1/unordered_map>
#define EIGEN_UNORDERED_MAP_SUPPORT
namespace std {
using std::tr1::unordered_map;
}
#endif
#ifdef EIGEN_GOOGLEHASH_SUPPORT
#include <google/sparse_hash_map>
#endif
#include <Eigen/Cholesky>
#include <Eigen/LU>
#include <Eigen/Sparse>
enum {
ForceNonZeroDiag = 1,
MakeLowerTriangular = 2,
MakeUpperTriangular = 4,
ForceRealDiag = 8
};
/* Initializes both a sparse and dense matrix with same random values,
* and a ratio of \a density non zero entries.
* \param flags is a union of ForceNonZeroDiag, MakeLowerTriangular and MakeUpperTriangular
* allowing to control the shape of the matrix.
* \param zeroCoords and nonzeroCoords allows to get the coordinate lists of the non zero,
* and zero coefficients respectively.
*/
template<typename Scalar> void
initSparse(double density,
Matrix<Scalar,Dynamic,Dynamic>& refMat,
SparseMatrix<Scalar>& sparseMat,
int flags = 0,
std::vector<Vector2i>* zeroCoords = 0,
std::vector<Vector2i>* nonzeroCoords = 0)
{
sparseMat.startFill(int(refMat.rows()*refMat.cols()*density));
for(int j=0; j<refMat.cols(); j++)
{
for(int i=0; i<refMat.rows(); i++)
{
Scalar v = (ei_random<double>(0,1) < density) ? ei_random<Scalar>() : Scalar(0);
if ((flags&ForceNonZeroDiag) && (i==j))
{
v = ei_random<Scalar>()*Scalar(3.);
v = v*v + Scalar(5.);
}
if ((flags & MakeLowerTriangular) && j>i)
v = Scalar(0);
else if ((flags & MakeUpperTriangular) && j<i)
v = Scalar(0);
if ((flags&ForceRealDiag) && (i==j))
v = ei_real(v);
if (v!=Scalar(0))
{
sparseMat.fill(i,j) = v;
if (nonzeroCoords)
nonzeroCoords->push_back(Vector2i(i,j));
}
else if (zeroCoords)
{
zeroCoords->push_back(Vector2i(i,j));
}
refMat(i,j) = v;
}
}
sparseMat.endFill();
}
template<typename Scalar> void
initSparse(double density,
Matrix<Scalar,Dynamic,Dynamic>& refMat,
DynamicSparseMatrix<Scalar>& sparseMat,
int flags = 0,
std::vector<Vector2i>* zeroCoords = 0,
std::vector<Vector2i>* nonzeroCoords = 0)
{
sparseMat.startFill(int(refMat.rows()*refMat.cols()*density));
for(int j=0; j<refMat.cols(); j++)
{
for(int i=0; i<refMat.rows(); i++)
{
Scalar v = (ei_random<double>(0,1) < density) ? ei_random<Scalar>() : Scalar(0);
if ((flags&ForceNonZeroDiag) && (i==j))
{
v = ei_random<Scalar>()*Scalar(3.);
v = v*v + Scalar(5.);
}
if ((flags & MakeLowerTriangular) && j>i)
v = Scalar(0);
else if ((flags & MakeUpperTriangular) && j<i)
v = Scalar(0);
if ((flags&ForceRealDiag) && (i==j))
v = ei_real(v);
if (v!=Scalar(0))
{
sparseMat.fill(i,j) = v;
if (nonzeroCoords)
nonzeroCoords->push_back(Vector2i(i,j));
}
else if (zeroCoords)
{
zeroCoords->push_back(Vector2i(i,j));
}
refMat(i,j) = v;
}
}
sparseMat.endFill();
}
template<typename Scalar> void
initSparse(double density,
Matrix<Scalar,Dynamic,1>& refVec,
SparseVector<Scalar>& sparseVec,
std::vector<int>* zeroCoords = 0,
std::vector<int>* nonzeroCoords = 0)
{
sparseVec.reserve(int(refVec.size()*density));
sparseVec.setZero();
for(int i=0; i<refVec.size(); i++)
{
Scalar v = (ei_random<double>(0,1) < density) ? ei_random<Scalar>() : Scalar(0);
if (v!=Scalar(0))
{
sparseVec.fill(i) = v;
if (nonzeroCoords)
nonzeroCoords->push_back(i);
}
else if (zeroCoords)
zeroCoords->push_back(i);
refVec[i] = v;
}
}
#endif // EIGEN_TESTSPARSE_H
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