uniform_cdf.hpp

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#ifndef STAN_MATH_PRIM_PROB_UNIFORM_CDF_HPP
#define STAN_MATH_PRIM_PROB_UNIFORM_CDF_HPP
 
#include <stan/math/prim/meta.hpp>
#include <stan/math/prim/err.hpp>
#include <stan/math/prim/fun/as_column_vector_or_scalar.hpp>
#include <stan/math/prim/fun/as_array_or_scalar.hpp>
#include <stan/math/prim/fun/as_value_column_array_or_scalar.hpp>
#include <stan/math/prim/fun/max_size.hpp>
#include <stan/math/prim/fun/promote_scalar.hpp>
#include <stan/math/prim/fun/size.hpp>
#include <stan/math/prim/fun/size_zero.hpp>
#include <stan/math/prim/fun/to_ref.hpp>
#include <stan/math/prim/fun/value_of.hpp>
#include <stan/math/prim/functor/partials_propagator.hpp>
 
namespace stan {
namespace math {
 
template <typename T_y, typename T_low, typename T_high,
          require_all_not_nonscalar_prim_or_rev_kernel_expression_t<
              T_y, T_low, T_high>* = nullptr>
return_type_t<T_y, T_low, T_high> uniform_cdf(const T_y& y, const T_low& alpha,
                                              const T_high& beta) {
  using T_partials_return = partials_return_t<T_y, T_low, T_high>;
  using T_y_ref = ref_type_if_not_constant_t<T_y>;
  using T_alpha_ref = ref_type_if_not_constant_t<T_low>;
  using T_beta_ref = ref_type_if_not_constant_t<T_high>;
  static constexpr const char* function = "uniform_cdf";
  check_consistent_sizes(function, "Random variable", y,
                         "Lower bound parameter", alpha,
                         "Upper bound parameter", beta);
 
  T_y_ref y_ref = y;
  T_alpha_ref alpha_ref = alpha;
  T_beta_ref beta_ref = beta;
 
  decltype(auto) y_val = to_ref(as_value_column_array_or_scalar(y_ref));
  decltype(auto) alpha_val = to_ref(as_value_column_array_or_scalar(alpha_ref));
  decltype(auto) beta_val = to_ref(as_value_column_array_or_scalar(beta_ref));
 
  check_not_nan(function, "Random variable", y_val);
  check_finite(function, "Lower bound parameter", alpha_val);
  check_finite(function, "Upper bound parameter", beta_val);
  check_greater(function, "Upper bound parameter", beta_val, alpha_val);
 
  if (size_zero(y, alpha, beta)) {
    return 1.0;
  }
 
  if (sum(promote_scalar<int>(y_val < alpha_val))
      || sum(promote_scalar<int>(beta_val < y_val))) {
    return 0;
  }
 
  auto ops_partials = make_partials_propagator(y_ref, alpha_ref, beta_ref);
 
  const auto& b_minus_a
      = to_ref_if<!is_constant_all<T_y, T_low, T_high>::value>(beta_val
                                                               - alpha_val);
  const auto& cdf_n = to_ref_if<!is_constant_all<T_y, T_low>::value>(
      (y_val - alpha_val) / b_minus_a);
 
  T_partials_return cdf = prod(cdf_n);
 
  if (!is_constant_all<T_y, T_low, T_high>::value) {
    const auto& rep_deriv
        = to_ref_if<(!is_constant_all<T_y, T_low>::value
                     && !is_constant_all<T_high>::value)>(cdf / b_minus_a);
    if (!is_constant_all<T_y, T_low>::value) {
      auto deriv_y
          = to_ref_if<(!is_constant_all<T_low>::value
                       && !is_constant_all<T_y>::value)>(rep_deriv / cdf_n);
      if (!is_constant_all<T_low>::value) {
        edge<1>(ops_partials).partials_
            = (y_val - beta_val) * deriv_y / b_minus_a;
      }
      if (!is_constant_all<T_y>::value) {
        partials<0>(ops_partials) = std::move(deriv_y);
      }
    }
    if (!is_constant_all<T_high>::value) {
      if (is_vector<T_y>::value && !is_vector<T_low>::value
          && !is_vector<T_high>::value) {
        edge<2>(ops_partials).partials_
            = -rep_deriv * max_size(y, alpha, beta) / max_size(alpha, beta);
      } else {
        partials<2>(ops_partials) = -rep_deriv;
      }
    }
  }
 
  return ops_partials.build(cdf);
}
 
}  // namespace math
}  // namespace stan
#endif