#ifndef STAN__MATH__PRIM__SCAL__PROB__CAUCHY_CDF_LOG_HPP
#define STAN__MATH__PRIM__SCAL__PROB__CAUCHY_CDF_LOG_HPP

#include <boost/random/cauchy_distribution.hpp>
#include <boost/random/variate_generator.hpp>
#include <stan/math/prim/scal/meta/OperandsAndPartials.hpp>
#include <stan/math/prim/scal/err/check_consistent_sizes.hpp>
#include <stan/math/prim/scal/err/check_finite.hpp>
#include <stan/math/prim/scal/err/check_not_nan.hpp>
#include <stan/math/prim/scal/err/check_positive_finite.hpp>
#include <stan/math/prim/scal/fun/constants.hpp>
#include <stan/math/prim/scal/fun/log1p.hpp>
#include <stan/math/prim/scal/fun/square.hpp>
#include <stan/math/prim/scal/fun/value_of.hpp>
#include <stan/math/prim/scal/fun/log1p.hpp>
#include <stan/math/prim/scal/meta/constants.hpp>
#include <stan/math/prim/scal/meta/include_summand.hpp>

namespace stan {

  namespace prob {

    template <typename T_y, typename T_loc, typename T_scale>
    typename return_type<T_y,T_loc,T_scale>::type
    cauchy_cdf_log(const T_y& y, const T_loc& mu, const T_scale& sigma) {
      typedef typename stan::partials_return_type<T_y,T_loc,T_scale>::type
        T_partials_return;
              
      // Size checks
      if ( !( stan::length(y) && stan::length(mu) 
              && stan::length(sigma) ) ) 
        return 0.0;
        
      static const char* function("stan::prob::cauchy_cdf");
      
      using stan::math::check_positive_finite;
      using stan::math::check_finite;
      using stan::math::check_not_nan;
      using stan::math::check_consistent_sizes;
      using boost::math::tools::promote_args;
      using stan::math::value_of;

      T_partials_return cdf_log(0.0);
        
      check_not_nan(function, "Random variable", y);
      check_finite(function, "Location parameter", mu);
      check_positive_finite(function, "Scale parameter", sigma);
      check_consistent_sizes(function, 
                             "Random variable", y, 
                             "Location parameter", mu, 
                             "Scale Parameter", sigma);
        
      // Wrap arguments in vectors
      VectorView<const T_y> y_vec(y);
      VectorView<const T_loc> mu_vec(mu);
      VectorView<const T_scale> sigma_vec(sigma);
      size_t N = max_size(y, mu, sigma);
        
      agrad::OperandsAndPartials<T_y, T_loc, T_scale> 
        operands_and_partials(y, mu, sigma);
        
      // Compute CDFLog and its gradients
      using std::atan;
      using stan::math::pi;

      // Compute vectorized CDF and gradient
      for (size_t n = 0; n < N; n++) {
            
        // Pull out values
        const T_partials_return y_dbl = value_of(y_vec[n]);
        const T_partials_return mu_dbl = value_of(mu_vec[n]);
        const T_partials_return sigma_inv_dbl = 1.0 / value_of(sigma_vec[n]);
        const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
            
        const T_partials_return z = (y_dbl - mu_dbl) * sigma_inv_dbl;
          
        // Compute
        const T_partials_return Pn = atan(z) / pi() + 0.5;
        cdf_log += log(Pn);
            
        const T_partials_return rep_deriv = 1.0 / (pi() * Pn 
                                                   * (z * z * sigma_dbl + sigma_dbl));
        if (!is_constant_struct<T_y>::value)
          operands_and_partials.d_x1[n] += rep_deriv;
        if (!is_constant_struct<T_loc>::value)
          operands_and_partials.d_x2[n] -= rep_deriv;
        if (!is_constant_struct<T_scale>::value)
          operands_and_partials.d_x3[n] -= rep_deriv * z;
      }
      return operands_and_partials.to_var(cdf_log,y,mu,sigma);
    }

  }
}
#endif
