Embed_in_Rd.h

/*    This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
 *    See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
 *    Author(s):       Siargey Kachanovich
 *
 *    Copyright (C) 2019 Inria
 *
 *    Modification(s):
 *      - YYYY/MM Author: Description of the modification
 */
 
#ifndef FUNCTIONS_EMBED_IN_RD_H_
#define FUNCTIONS_EMBED_IN_RD_H_
 
#include <cstdlib>  // for std::size_t
 
#include <Eigen/Dense>
 
namespace Gudhi {
 
namespace coxeter_triangulation {
 
template <class Function_>
struct Embed_in_Rd {
  Eigen::VectorXd operator()(const Eigen::VectorXd& p) const {
    Eigen::VectorXd x = p;
    Eigen::VectorXd x_k(fun_.amb_d()), x_rest(d_ - fun_.amb_d());
    for (std::size_t i = 0; i < fun_.amb_d(); ++i) x_k(i) = x(i);
    for (std::size_t i = fun_.amb_d(); i < d_; ++i) x_rest(i - fun_.amb_d()) = x(i);
    Eigen::VectorXd result = fun_(x_k);
    result.conservativeResize(this->cod_d());
    for (std::size_t i = fun_.cod_d(); i < this->cod_d(); ++i) result(i) = x_rest(i - fun_.cod_d());
    return result;
  }
 
  std::size_t amb_d() const { return d_; }
 
  std::size_t cod_d() const { return d_ - (fun_.amb_d() - fun_.cod_d()); }
 
  Eigen::VectorXd seed() const {
    Eigen::VectorXd result = fun_.seed();
    result.conservativeResize(d_);
    for (std::size_t l = fun_.amb_d(); l < d_; ++l) result(l) = 0;
    return result;
  }
 
  Embed_in_Rd(const Function_& function, std::size_t d) : fun_(function), d_(d) {}
 
 private:
  Function_ fun_;
  std::size_t d_;
};
 
template <class Function_>
Embed_in_Rd<Function_> make_embedding(const Function_& function, std::size_t d) {
  return Embed_in_Rd<Function_>(function, d);
}
 
}  // namespace coxeter_triangulation
 
}  // namespace Gudhi
 
#endif