/usr/include/shark/LinAlg/BlockMatrix2x2.h is in libshark-dev 3.0.1+ds1-2ubuntu1.
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/*!
*
*
* \brief Precomputed version of a matrix for quadratic programming
*
*
* \par
*
*
*
* \author T. Glasmachers
* \date 2007-2012
*
*
* \par Copyright 1995-2015 Shark Development Team
*
* <BR><HR>
* This file is part of Shark.
* <http://image.diku.dk/shark/>
*
* Shark 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.
*
* Shark 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 for more details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with Shark. If not, see <http://www.gnu.org/licenses/>.
*
*/
//===========================================================================
#ifndef SHARK_LINALG_BLOCKMATRIX2X2_H
#define SHARK_LINALG_BLOCKMATRIX2X2_H
#include <shark/Data/Dataset.h>
#include <shark/LinAlg/Base.h>
#include <vector>
#include <cmath>
namespace shark {
///
/// \brief SVM regression matrix
///
/// \par
/// The BlockMatrix2x2 class is a \f$ 2n \times 2n \f$ block matrix of the form<br>
/// \f$ \left( \begin{array}{lr} M & M \\ M & M \end{array} \right) \f$ <br>
/// where M is an \f$ n \times n \f$ matrix.
/// This matrix form is needed in SVM regression problems.
///
template <class Matrix>
class BlockMatrix2x2
{
public:
typedef typename Matrix::QpFloatType QpFloatType;
/// Constructor.
/// \param base underlying matrix M, see class description of BlockMatrix2x2.
BlockMatrix2x2(Matrix* base)
{
m_base = base;
m_mapping.resize(size());
std::size_t ic = m_base->size();
for (std::size_t i = 0; i < ic; i++)
{
m_mapping[i] = i;
m_mapping[i + ic] = i;
}
}
/// return a single matrix entry
QpFloatType operator () (std::size_t i, std::size_t j) const
{ return entry(i, j); }
/// return a single matrix entry
QpFloatType entry(std::size_t i, std::size_t j) const
{
return m_base->entry(m_mapping[i], m_mapping[j]);
}
/// \brief Computes the i-th row of the kernel matrix.
///
///The entries start,...,end of the i-th row are computed and stored in storage.
///There must be enough room for this operation preallocated.
void row(std::size_t i, std::size_t start,std::size_t end, QpFloatType* storage) const{
for(std::size_t j = start; j < end; j++){
storage[j-start] = m_base->entry(m_mapping[i], m_mapping[j]);
}
}
/// \brief Computes the kernel-matrix
template<class M>
void matrix(
blas::matrix_expression<M> & storage
) const{
for(std::size_t i = 0; i != size(); ++i){
for(std::size_t j = 0; j != size(); ++j){
storage()(i,j) = entry(i,j);
}
}
}
/// swap two variables
void flipColumnsAndRows(std::size_t i, std::size_t j)
{
std::swap(m_mapping[i], m_mapping[j]);
}
/// return the size of the quadratic matrix
std::size_t size() const
{ return 2 * m_base->size(); }
protected:
/// underlying KernelMatrix object
Matrix* m_base;
/// coordinate permutation
std::vector<std::size_t> m_mapping;
};
}
#endif
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