// Arguments: Doubles, Doubles, Doubles
#include <stan/math/prim/prob/double_exponential_lpdf.hpp>
#include <stan/math/prim/fun/constants.hpp>

using stan::math::var;
using std::numeric_limits;
using std::vector;

class AgradDistributionsDoubleExponential : public AgradDistributionTest {
 public:
  void valid_values(vector<vector<double> >& parameters,
                    vector<double>& log_prob) {
    vector<double> param(3);

    param[0] = 1.0;  // y
    param[1] = 1.0;  // mu
    param[2] = 1.0;  // sigma
    parameters.push_back(param);
    log_prob.push_back(
        -0.6931471805599453094172321214581765680755001343602552541206800094933936219696947156058633269964186875);  // expected log_prob

    param[0] = 2.0;  // y
    param[1] = 1.0;  // mu
    param[2] = 1.0;  // sigma
    parameters.push_back(param);
    log_prob.push_back(
        -1.693147180559945309417232121458176568075500134360255254120680009493393621969694715605863326996418688);  // expected log_prob

    param[0] = -3.0;  // y
    param[1] = 2.0;   // mu
    param[2] = 1.0;   // sigma
    parameters.push_back(param);
    log_prob.push_back(
        -5.693147180559945309417232121458176568075500134360255254120680009493393621969694715605863326996418688);  // expected log_prob

    param[0] = 1.0;  // y
    param[1] = 0.0;  // mu
    param[2] = 2.0;  // sigma
    parameters.push_back(param);
    log_prob.push_back(
        -1.8862943611198906188344642429163531361510002687205105082413600189867872439393894312117266539928373751);  // expected log_prob

    param[0] = 1.9;  // y
    param[1] = 2.3;  // mu
    param[2] = 0.5;  // sigma
    parameters.push_back(param);
    log_prob.push_back(-0.8);  // expected log_prob

    param[0] = 1.9;   // y
    param[1] = 2.3;   // mu
    param[2] = 0.25;  // sigma
    parameters.push_back(param);
    log_prob.push_back(-0.90685281944005469058276788);  // expected log_prob
  }

  void invalid_values(vector<size_t>& index, vector<double>& value) {
    // y
    index.push_back(0U);
    value.push_back(numeric_limits<double>::infinity());

    index.push_back(0U);
    value.push_back(-numeric_limits<double>::infinity());

    // mu
    index.push_back(1U);
    value.push_back(numeric_limits<double>::infinity());

    index.push_back(1U);
    value.push_back(-numeric_limits<double>::infinity());

    // sigma
    index.push_back(2U);
    value.push_back(0.0);

    index.push_back(2U);
    value.push_back(-1.0);

    index.push_back(2U);
    value.push_back(numeric_limits<double>::infinity());

    index.push_back(2U);
    value.push_back(-numeric_limits<double>::infinity());
  }

  template <typename T_y, typename T_loc, typename T_scale, typename T3,
            typename T4, typename T5>
  stan::return_type_t<T_y, T_loc, T_scale> log_prob(const T_y& y,
                                                    const T_loc& mu,
                                                    const T_scale& sigma,
                                                    const T3&, const T4&,
                                                    const T5&) {
    return stan::math::double_exponential_lpdf(y, mu, sigma);
  }

  template <bool propto, typename T_y, typename T_loc, typename T_scale,
            typename T3, typename T4, typename T5>
  stan::return_type_t<T_y, T_loc, T_scale> log_prob(const T_y& y,
                                                    const T_loc& mu,
                                                    const T_scale& sigma,
                                                    const T3&, const T4&,
                                                    const T5&) {
    return stan::math::double_exponential_lpdf<propto>(y, mu, sigma);
  }

  template <typename T_y, typename T_loc, typename T_scale, typename T3,
            typename T4, typename T5>
  stan::return_type_t<T_y, T_loc, T_scale> log_prob_function(
      const T_y& y, const T_loc& mu, const T_scale& sigma, const T3&, const T4&,
      const T5&) {
    using stan::math::LOG_TWO;
    using std::fabs;
    using std::log;

    return -LOG_TWO - log(sigma) - fabs(y - mu) / sigma;
  }
};

TEST(ProbDistributionsDoubleExponential, Cumulative) {
  EXPECT_FLOAT_EQ(0.5, stan::math::double_exponential_cdf(1.0, 1.0, 1.0));
  EXPECT_FLOAT_EQ(0.8160603, stan::math::double_exponential_cdf(2.0, 1.0, 1.0));
  EXPECT_FLOAT_EQ(0.003368973,
                  stan::math::double_exponential_cdf(-3.0, 2.0, 1.0));
  EXPECT_FLOAT_EQ(0.6967347, stan::math::double_exponential_cdf(1.0, 0.0, 2.0));
  EXPECT_FLOAT_EQ(0.2246645, stan::math::double_exponential_cdf(1.9, 2.3, 0.5));
  EXPECT_FLOAT_EQ(0.10094826,
                  stan::math::double_exponential_cdf(1.9, 2.3, 0.25));
}
