eigen-matrix.hpp

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/*
 Code adapted from:
 https://gist.githubusercontent.com/mtao/5798888/raw/5be9fa9b66336c166dba3a92c0e5b69ffdb81501/eigen_boost_serialization.hpp
 Copyright (c) 2015 Michael Tao
 
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#ifndef __parameteric_curves_serialization_eigen_matrix_hpp__
#define __parameteric_curves_serialization_eigen_matrix_hpp__
 
#include <Eigen/Dense>
#include <boost/serialization/split_free.hpp>
#include <boost/serialization/vector.hpp>
 
namespace boost {
 
namespace serialization {
 
template <class Archive, typename _Scalar, int _Rows, int _Cols, int _Options,
          int _MaxRows, int _MaxCols>
void save(
    Archive& ar,
    const Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& m,
    const unsigned int /*version*/) {
  Eigen::DenseIndex rows(m.rows()), cols(m.cols());
  ar& BOOST_SERIALIZATION_NVP(rows);
  ar& BOOST_SERIALIZATION_NVP(cols);
  ar& make_nvp("data", make_array(m.data(), (size_t)m.size()));
}
 
template <class Archive, typename _Scalar, int _Rows, int _Cols, int _Options,
          int _MaxRows, int _MaxCols>
void load(Archive& ar,
          Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& m,
          const unsigned int /*version*/) {
  Eigen::DenseIndex rows, cols;
  ar >> BOOST_SERIALIZATION_NVP(rows);
  ar >> BOOST_SERIALIZATION_NVP(cols);
  m.resize(rows, cols);
  ar >> make_nvp("data", make_array(m.data(), (size_t)m.size()));
}
 
template <class Archive, typename _Scalar, int _Rows, int _Cols, int _Options,
          int _MaxRows, int _MaxCols>
void serialize(
    Archive& ar,
    Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& m,
    const unsigned int version) {
  split_free(ar, m, version);
}
 
}  // namespace serialization
}  // namespace boost
 
#endif  // ifndef __parametric_curves_serialization_eigen_matrix_hpp__