corr_matrix_constrain.hpp

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#ifndef STAN_MATH_PRIM_FUN_CORR_MATRIX_CONSTRAIN_HPP
#define STAN_MATH_PRIM_FUN_CORR_MATRIX_CONSTRAIN_HPP
 
#include <stan/math/prim/meta.hpp>
#include <stan/math/prim/err.hpp>
#include <stan/math/prim/fun/Eigen.hpp>
#include <stan/math/prim/fun/corr_constrain.hpp>
#include <stan/math/prim/fun/read_corr_matrix.hpp>
#include <stdexcept>
 
namespace stan {
namespace math {
 
template <typename T, require_eigen_col_vector_t<T>* = nullptr>
inline Eigen::Matrix<value_type_t<T>, Eigen::Dynamic, Eigen::Dynamic>
corr_matrix_constrain(const T& x, Eigen::Index k) {
  Eigen::Index k_choose_2 = (k * (k - 1)) / 2;
  check_size_match("cov_matrix_constrain", "x.size()", x.size(), "k_choose_2",
                   k_choose_2);
  return read_corr_matrix(corr_constrain(x), k);
}
 
template <typename T, require_eigen_col_vector_t<T>* = nullptr>
inline Eigen::Matrix<value_type_t<T>, Eigen::Dynamic, Eigen::Dynamic>
corr_matrix_constrain(const T& x, Eigen::Index k, return_type_t<T>& lp) {
  Eigen::Index k_choose_2 = (k * (k - 1)) / 2;
  check_size_match("cov_matrix_constrain", "x.size()", x.size(), "k_choose_2",
                   k_choose_2);
  return read_corr_matrix(corr_constrain(x, lp), k, lp);
}
 
template <bool Jacobian, typename T, require_not_std_vector_t<T>* = nullptr>
inline auto corr_matrix_constrain(const T& x, Eigen::Index k,
                                  return_type_t<T>& lp) {
  if (Jacobian) {
    return corr_matrix_constrain(x, k, lp);
  } else {
    return corr_matrix_constrain(x, k);
  }
}
 
template <bool Jacobian, typename T, require_std_vector_t<T>* = nullptr>
inline auto corr_matrix_constrain(const T& y, int K, return_type_t<T>& lp) {
  return apply_vector_unary<T>::apply(y, [&lp, K](auto&& v) {
    return corr_matrix_constrain<Jacobian>(v, K, lp);
  });
}
 
}  // namespace math
}  // namespace stan
 
#endif