eigen3.cpp

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/*
 * This program is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation; either version 3 of the License, or
 * (at your option) any later version.
 *
 * Written (W) 2013 Soumyajit De
 */

#include <shogun/lib/common.h>

#include <shogun/lib/SGSparseMatrix.h>
#include <shogun/lib/SGSparseVector.h>
#include <shogun/mathematics/eigen3.h>

using namespace Eigen;

namespace shogun
{

template<typename T>
SparseMatrix<T> EigenSparseUtil<T>::toEigenSparse(SGSparseMatrix<T> sg_matrix)
    {
        REQUIRE(sg_matrix.num_vectors>0,
            "EigenSparseUtil::toEigenSparse(): \
            Number of rows must be positive!\n");
        REQUIRE(sg_matrix.num_features>0,
            "EigenSparseUtil::toEigenSparse(): \
            Number of cols must be positive!\n");
        REQUIRE(sg_matrix.sparse_matrix,
            "EigenSparseUtil::toEigenSparse(): \
            sg_matrix is not initialized!\n");

        index_t num_rows=sg_matrix.num_vectors;
        index_t num_cols=sg_matrix.num_features;

        typedef Eigen::Triplet<T> SparseTriplet;

        std::vector<SparseTriplet> tripletList;
        for (index_t i=0; i<num_rows; ++i)
        {
            for (index_t k=0; k<sg_matrix[i].num_feat_entries; ++k)
            {
                index_t &index_i=i;
                index_t &index_j=sg_matrix[i].features[k].feat_index;
                T &val=sg_matrix[i].features[k].entry;
                tripletList.push_back(SparseTriplet(index_i, index_j, val));
            }
        }

#ifdef EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET
        DynamicSparseMatrix<T> dM(num_rows, num_cols);
        dM.reserve(tripletList.size());

        for (typename std::vector<SparseTriplet>::iterator it=tripletList.begin();
            it!=tripletList.end(); ++it )
            dM.coeffRef(it->row(), it->col())+=it->value();

        SparseMatrix<T> M(dM);
#else // EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET
        SparseMatrix<T> M(num_rows, num_cols);
        M.setFromTriplets(tripletList.begin(), tripletList.end());
#endif // EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET

        return M;
    }

template class EigenSparseUtil<bool>;
template class EigenSparseUtil<float64_t>;
template class EigenSparseUtil<complex128_t>;
}