#ifndef STAN_MATH_PRIM_SCAL_PROB_POISSON_LOG_LPMF_HPP
#define STAN_MATH_PRIM_SCAL_PROB_POISSON_LOG_LPMF_HPP

#include <stan/math/prim/scal/meta/is_constant_struct.hpp>
#include <stan/math/prim/scal/meta/partials_return_type.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_less.hpp>
#include <stan/math/prim/scal/err/check_nonnegative.hpp>
#include <stan/math/prim/scal/err/check_not_nan.hpp>
#include <stan/math/prim/scal/fun/constants.hpp>
#include <stan/math/prim/scal/fun/multiply_log.hpp>
#include <stan/math/prim/scal/fun/gamma_q.hpp>
#include <stan/math/prim/scal/fun/lgamma.hpp>
#include <stan/math/prim/scal/fun/value_of.hpp>
#include <stan/math/prim/scal/meta/include_summand.hpp>
#include <stan/math/prim/scal/meta/scalar_seq_view.hpp>
#include <stan/math/prim/scal/meta/VectorBuilder.hpp>
#include <boost/random/poisson_distribution.hpp>
#include <boost/random/variate_generator.hpp>
#include <cmath>
#include <limits>

namespace stan {
  namespace math {

    // PoissonLog(n|alpha)  [n >= 0]   = Poisson(n|exp(alpha))
    template <bool propto,
              typename T_n, typename T_log_rate>
    typename return_type<T_log_rate>::type
    poisson_log_lpmf(const T_n& n, const T_log_rate& alpha) {
      typedef typename stan::partials_return_type<T_n, T_log_rate>::type
        T_partials_return;

      static const char* function("poisson_log_lpmf");

      using std::exp;

      if (!(stan::length(n)
            && stan::length(alpha)))
        return 0.0;

      T_partials_return logp(0.0);

      check_nonnegative(function, "Random variable", n);
      check_not_nan(function, "Log rate parameter", alpha);
      check_consistent_sizes(function,
                             "Random variable", n,
                             "Log rate parameter", alpha);

      if (!include_summand<propto, T_log_rate>::value)
        return 0.0;

      scalar_seq_view<const T_n> n_vec(n);
      scalar_seq_view<const T_log_rate> alpha_vec(alpha);
      size_t size = max_size(n, alpha);

      // FIXME: first loop size of alpha_vec, second loop if-ed for size==1
      for (size_t i = 0; i < size; i++)
        if (std::numeric_limits<double>::infinity() == alpha_vec[i])
          return LOG_ZERO;
      for (size_t i = 0; i < size; i++)
        if (-std::numeric_limits<double>::infinity() == alpha_vec[i]
            && n_vec[i] != 0)
          return LOG_ZERO;

      OperandsAndPartials<T_log_rate> operands_and_partials(alpha);

      // FIXME: cache value_of for alpha_vec?  faster if only one?
      VectorBuilder<include_summand<propto, T_log_rate>::value,
                    T_partials_return, T_log_rate>
        exp_alpha(length(alpha));
      for (size_t i = 0; i < length(alpha); i++)
        if (include_summand<propto, T_log_rate>::value)
          exp_alpha[i] = exp(value_of(alpha_vec[i]));

      for (size_t i = 0; i < size; i++) {
        if (!(alpha_vec[i] == -std::numeric_limits<double>::infinity()
              && n_vec[i] == 0)) {
          if (include_summand<propto>::value)
            logp -= lgamma(n_vec[i] + 1.0);
          if (include_summand<propto, T_log_rate>::value)
            logp += n_vec[i] * value_of(alpha_vec[i]) - exp_alpha[i];
        }

        if (!is_constant_struct<T_log_rate>::value)
          operands_and_partials.d_x1[i] += n_vec[i] - exp_alpha[i];
      }
      return operands_and_partials.value(logp);
    }

    template <typename T_n,
              typename T_log_rate>
    inline
    typename return_type<T_log_rate>::type
    poisson_log_lpmf(const T_n& n, const T_log_rate& alpha) {
      return poisson_log_lpmf<false>(n, alpha);
    }

  }
}
#endif
