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#include <Eigen/Sparse>
#include <bench/BenchTimer.h>
#include <set>
using namespace std;
using namespace Eigen;
using namespace Eigen;
#ifndef SIZE
#define SIZE 1024
#endif
#ifndef DENSITY
#define DENSITY 0.01
#endif
#ifndef SCALAR
#define SCALAR double
#endif
typedef SCALAR Scalar;
typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
typedef Matrix<Scalar,Dynamic,1> DenseVector;
typedef SparseMatrix<Scalar> EigenSparseMatrix;
void fillMatrix(float density, int rows, int cols, EigenSparseMatrix& dst)
{
dst.reserve(double(rows)*cols*density);
for(int j = 0; j < cols; j++)
{
for(int i = 0; i < rows; i++)
{
Scalar v = (internal::random<float>(0,1) < density) ? internal::random<Scalar>() : 0;
if (v!=0)
dst.insert(i,j) = v;
}
}
dst.finalize();
}
void fillMatrix2(int nnzPerCol, int rows, int cols, EigenSparseMatrix& dst)
{
// std::cout << "alloc " << nnzPerCol*cols << "\n";
dst.reserve(nnzPerCol*cols);
for(int j = 0; j < cols; j++)
{
std::set<int> aux;
for(int i = 0; i < nnzPerCol; i++)
{
int k = internal::random<int>(0,rows-1);
while (aux.find(k)!=aux.end())
k = internal::random<int>(0,rows-1);
aux.insert(k);
dst.insert(k,j) = internal::random<Scalar>();
}
}
dst.finalize();
}
void eiToDense(const EigenSparseMatrix& src, DenseMatrix& dst)
{
dst.setZero();
for (int j=0; j<src.cols(); ++j)
for (EigenSparseMatrix::InnerIterator it(src.derived(), j); it; ++it)
dst(it.index(),j) = it.value();
}
#ifndef NOGMM
#include "gmm/gmm.h"
typedef gmm::csc_matrix<Scalar> GmmSparse;
typedef gmm::col_matrix< gmm::wsvector<Scalar> > GmmDynSparse;
void eiToGmm(const EigenSparseMatrix& src, GmmSparse& dst)
{
GmmDynSparse tmp(src.rows(), src.cols());
for (int j=0; j<src.cols(); ++j)
for (EigenSparseMatrix::InnerIterator it(src.derived(), j); it; ++it)
tmp(it.index(),j) = it.value();
gmm::copy(tmp, dst);
}
#endif
#ifndef NOMTL
#include <boost/numeric/mtl/mtl.hpp>
typedef mtl::compressed2D<Scalar, mtl::matrix::parameters<mtl::tag::col_major> > MtlSparse;
typedef mtl::compressed2D<Scalar, mtl::matrix::parameters<mtl::tag::row_major> > MtlSparseRowMajor;
void eiToMtl(const EigenSparseMatrix& src, MtlSparse& dst)
{
mtl::matrix::inserter<MtlSparse> ins(dst);
for (int j=0; j<src.cols(); ++j)
for (EigenSparseMatrix::InnerIterator it(src.derived(), j); it; ++it)
ins[it.index()][j] = it.value();
}
#endif
#ifdef CSPARSE
extern "C" {
#include "cs.h"
}
void eiToCSparse(const EigenSparseMatrix& src, cs* &dst)
{
cs* aux = cs_spalloc (0, 0, 1, 1, 1);
for (int j=0; j<src.cols(); ++j)
for (EigenSparseMatrix::InnerIterator it(src.derived(), j); it; ++it)
if (!cs_entry(aux, it.index(), j, it.value()))
{
std::cout << "cs_entry error\n";
exit(2);
}
dst = cs_compress(aux);
// cs_spfree(aux);
}
#endif // CSPARSE
#ifndef NOUBLAS
#include <boost/numeric/ublas/vector.hpp>
#include <boost/numeric/ublas/matrix.hpp>
#include <boost/numeric/ublas/io.hpp>
#include <boost/numeric/ublas/triangular.hpp>
#include <boost/numeric/ublas/vector_sparse.hpp>
#include <boost/numeric/ublas/matrix_sparse.hpp>
#include <boost/numeric/ublas/vector_of_vector.hpp>
#include <boost/numeric/ublas/operation.hpp>
typedef boost::numeric::ublas::compressed_matrix<Scalar,boost::numeric::ublas::column_major> UBlasSparse;
void eiToUblas(const EigenSparseMatrix& src, UBlasSparse& dst)
{
dst.resize(src.rows(), src.cols(), false);
for (int j=0; j<src.cols(); ++j)
for (EigenSparseMatrix::InnerIterator it(src.derived(), j); it; ++it)
dst(it.index(),j) = it.value();
}
template <typename EigenType, typename UblasType>
void eiToUblasVec(const EigenType& src, UblasType& dst)
{
dst.resize(src.size());
for (int j=0; j<src.size(); ++j)
dst[j] = src.coeff(j);
}
#endif
#ifdef OSKI
extern "C" {
#include <oski/oski.h>
}
#endif