LeastSquaresConjugateGradient.hpp

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/*
 * Copyright 2017-2018 CNRS
 */
 
#ifndef __eigenpy_least_square_conjugate_gradient_hpp__
#define __eigenpy_least_square_conjugate_gradient_hpp__
 
#include <Eigen/IterativeLinearSolvers>
 
#include "eigenpy/fwd.hpp"
#include "eigenpy/solvers/IterativeSolverBase.hpp"
 
namespace eigenpy {
 
template <typename LeastSquaresConjugateGradient>
struct LeastSquaresConjugateGradientVisitor
    : public boost::python::def_visitor<LeastSquaresConjugateGradientVisitor<
          LeastSquaresConjugateGradient> > {
  typedef Eigen::MatrixXd MatrixType;
 
  template <class PyClass>
  void visit(PyClass& cl) const {
    cl.def(bp::init<>("Default constructor"))
        .def(bp::init<MatrixType>(
            bp::arg("A"),
            "Initialize the solver with matrix A for further || Ax - b || "
            "solving.\n"
            "This constructor is a shortcut for the default constructor "
            "followed by a call to compute()."));
  }
 
  static void expose() {
    bp::class_<LeastSquaresConjugateGradient, boost::noncopyable>(
        "LeastSquaresConjugateGradient", bp::no_init)
        .def(IterativeSolverVisitor<LeastSquaresConjugateGradient>())
        .def(LeastSquaresConjugateGradientVisitor<
             LeastSquaresConjugateGradient>())
        .def(IdVisitor<LeastSquaresConjugateGradient>());
  }
};
 
}  // namespace eigenpy
 
#endif  // ifndef __eigenpy_least_square_conjugate_gradient_hpp__