You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
182 lines
5.3 KiB
182 lines
5.3 KiB
// This file is part of Eigen, a lightweight C++ template library
|
|
// for linear algebra.
|
|
//
|
|
// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
|
|
//
|
|
// 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
|
|
#define EIGEN_TESTSPARSE_H
|
|
|
|
#define EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET
|
|
|
|
#include "main.h"
|
|
|
|
#if EIGEN_GNUC_AT_LEAST(4,0) && !defined __ICC && !defined(__clang__)
|
|
|
|
#ifdef min
|
|
#undef min
|
|
#endif
|
|
|
|
#ifdef max
|
|
#undef max
|
|
#endif
|
|
|
|
#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,int Opt1,int Opt2,typename Index> void
|
|
initSparse(double density,
|
|
Matrix<Scalar,Dynamic,Dynamic,Opt1>& refMat,
|
|
SparseMatrix<Scalar,Opt2,Index>& sparseMat,
|
|
int flags = 0,
|
|
std::vector<Vector2i>* zeroCoords = 0,
|
|
std::vector<Vector2i>* nonzeroCoords = 0)
|
|
{
|
|
enum { IsRowMajor = SparseMatrix<Scalar,Opt2,Index>::IsRowMajor };
|
|
sparseMat.setZero();
|
|
//sparseMat.reserve(int(refMat.rows()*refMat.cols()*density));
|
|
sparseMat.reserve(VectorXi::Constant(IsRowMajor ? refMat.rows() : refMat.cols(), int((1.5*density)*(IsRowMajor?refMat.cols():refMat.rows()))));
|
|
|
|
for(int j=0; j<sparseMat.outerSize(); j++)
|
|
{
|
|
//sparseMat.startVec(j);
|
|
for(int i=0; i<sparseMat.innerSize(); i++)
|
|
{
|
|
int ai(i), aj(j);
|
|
if(IsRowMajor)
|
|
std::swap(ai,aj);
|
|
Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0);
|
|
if ((flags&ForceNonZeroDiag) && (i==j))
|
|
{
|
|
v = internal::random<Scalar>()*Scalar(3.);
|
|
v = v*v + Scalar(5.);
|
|
}
|
|
if ((flags & MakeLowerTriangular) && aj>ai)
|
|
v = Scalar(0);
|
|
else if ((flags & MakeUpperTriangular) && aj<ai)
|
|
v = Scalar(0);
|
|
|
|
if ((flags&ForceRealDiag) && (i==j))
|
|
v = internal::real(v);
|
|
|
|
if (v!=Scalar(0))
|
|
{
|
|
//sparseMat.insertBackByOuterInner(j,i) = v;
|
|
sparseMat.insertByOuterInner(j,i) = v;
|
|
if (nonzeroCoords)
|
|
nonzeroCoords->push_back(Vector2i(ai,aj));
|
|
}
|
|
else if (zeroCoords)
|
|
{
|
|
zeroCoords->push_back(Vector2i(ai,aj));
|
|
}
|
|
refMat(ai,aj) = v;
|
|
}
|
|
}
|
|
//sparseMat.finalize();
|
|
}
|
|
|
|
template<typename Scalar,int Opt1,int Opt2,typename Index> void
|
|
initSparse(double density,
|
|
Matrix<Scalar,Dynamic,Dynamic, Opt1>& refMat,
|
|
DynamicSparseMatrix<Scalar, Opt2, Index>& sparseMat,
|
|
int flags = 0,
|
|
std::vector<Vector2i>* zeroCoords = 0,
|
|
std::vector<Vector2i>* nonzeroCoords = 0)
|
|
{
|
|
enum { IsRowMajor = DynamicSparseMatrix<Scalar,Opt2,Index>::IsRowMajor };
|
|
sparseMat.setZero();
|
|
sparseMat.reserve(int(refMat.rows()*refMat.cols()*density));
|
|
for(int j=0; j<sparseMat.outerSize(); j++)
|
|
{
|
|
sparseMat.startVec(j); // not needed for DynamicSparseMatrix
|
|
for(int i=0; i<sparseMat.innerSize(); i++)
|
|
{
|
|
int ai(i), aj(j);
|
|
if(IsRowMajor)
|
|
std::swap(ai,aj);
|
|
Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0);
|
|
if ((flags&ForceNonZeroDiag) && (i==j))
|
|
{
|
|
v = internal::random<Scalar>()*Scalar(3.);
|
|
v = v*v + Scalar(5.);
|
|
}
|
|
if ((flags & MakeLowerTriangular) && aj>ai)
|
|
v = Scalar(0);
|
|
else if ((flags & MakeUpperTriangular) && aj<ai)
|
|
v = Scalar(0);
|
|
|
|
if ((flags&ForceRealDiag) && (i==j))
|
|
v = internal::real(v);
|
|
|
|
if (v!=Scalar(0))
|
|
{
|
|
sparseMat.insertBackByOuterInner(j,i) = v;
|
|
if (nonzeroCoords)
|
|
nonzeroCoords->push_back(Vector2i(ai,aj));
|
|
}
|
|
else if (zeroCoords)
|
|
{
|
|
zeroCoords->push_back(Vector2i(ai,aj));
|
|
}
|
|
refMat(ai,aj) = v;
|
|
}
|
|
}
|
|
sparseMat.finalize();
|
|
}
|
|
|
|
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 = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0);
|
|
if (v!=Scalar(0))
|
|
{
|
|
sparseVec.insertBack(i) = v;
|
|
if (nonzeroCoords)
|
|
nonzeroCoords->push_back(i);
|
|
}
|
|
else if (zeroCoords)
|
|
zeroCoords->push_back(i);
|
|
refVec[i] = v;
|
|
}
|
|
}
|
|
|
|
#include <unsupported/Eigen/SparseExtra>
|
|
#endif // EIGEN_TESTSPARSE_H
|