#ifndef STAN_MATH_PRIM_MAT_FUN_UNIT_VECTOR_CONSTRAIN_HPP
#define STAN_MATH_PRIM_MAT_FUN_UNIT_VECTOR_CONSTRAIN_HPP

#include <stan/math/prim/arr/err/check_nonzero_size.hpp>
#include <stan/math/prim/mat/err/check_vector.hpp>
#include <stan/math/prim/mat/fun/Eigen.hpp>
#include <stan/math/prim/mat/fun/dot_self.hpp>
#include <stan/math/prim/scal/err/check_positive.hpp>
#include <stan/math/prim/scal/err/check_positive_finite.hpp>
#include <cmath>

namespace stan {
  namespace math {

    /**
     * Return the unit length vector corresponding to the free vector y.
     * See https://en.wikipedia.org/wiki/N-sphere#Generating_random_points
     *
     * @param y vector of K unrestricted variables
     * @return Unit length vector of dimension K
     * @tparam T Scalar type.
     **/
    template <typename T, int R, int C>
    Eigen::Matrix<T, R, C>
    unit_vector_constrain(const Eigen::Matrix<T, R, C>& y) {
      using std::sqrt;
      check_vector("unit_vector_constrain", "y", y);
      check_nonzero_size("unit_vector_constrain", "y", y);
      const T SN = dot_self(y);
      check_positive_finite("unit_vector_constrain", "norm", SN);
      return y / sqrt(SN);
    }

    /**
     * Return the unit length vector corresponding to the free vector y.
     * See https://en.wikipedia.org/wiki/N-sphere#Generating_random_points
     *
     * @param y vector of K unrestricted variables
     * @return Unit length vector of dimension K
     * @param lp Log probability reference to increment.
     * @tparam T Scalar type.
     **/
    template <typename T, int R, int C>
    Eigen::Matrix<T, R, C>
    unit_vector_constrain(const Eigen::Matrix<T, R, C>& y, T& lp) {
      using std::sqrt;
      check_vector("unit_vector_constrain", "y", y);
      check_nonzero_size("unit_vector_constrain", "y", y);
      const T SN = dot_self(y);
      check_positive_finite("unit_vector_constrain", "norm", SN);
      lp -= 0.5 * SN;
      return y / sqrt(SN);
    }

  }

}

#endif
