weibull_lcdf.hpp

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#ifndef STAN_MATH_OPENCL_PRIM_WEIBULL_LCDF_HPP
#define STAN_MATH_OPENCL_PRIM_WEIBULL_LCDF_HPP
#ifdef STAN_OPENCL
 
#include <stan/math/prim/meta.hpp>
#include <stan/math/prim/err.hpp>
#include <stan/math/prim/fun/constants.hpp>
#include <stan/math/prim/fun/elt_divide.hpp>
#include <stan/math/prim/fun/elt_multiply.hpp>
#include <stan/math/opencl/kernel_generator.hpp>
#include <stan/math/prim/functor/partials_propagator.hpp>
 
namespace stan {
namespace math {
 
template <
    typename T_y_cl, typename T_shape_cl, typename T_scale_cl,
    require_all_prim_or_rev_kernel_expression_t<T_y_cl, T_shape_cl,
                                                T_scale_cl>* = nullptr,
    require_any_not_stan_scalar_t<T_y_cl, T_shape_cl, T_scale_cl>* = nullptr>
return_type_t<T_y_cl, T_shape_cl, T_scale_cl> weibull_lcdf(
    const T_y_cl& y, const T_shape_cl& alpha, const T_scale_cl& sigma) {
  static constexpr const char* function = "weibull_lcdf(OpenCL)";
  using T_partials_return = partials_return_t<T_y_cl, T_shape_cl, T_scale_cl>;
  using std::isfinite;
  using std::isnan;
 
  check_consistent_sizes(function, "Random variable", y, "Shape parameter",
                         alpha, "Scale parameter", sigma);
  const size_t N = max_size(y, alpha, sigma);
  if (N == 0) {
    return 1.0;
  }
 
  const auto& y_col = as_column_vector_or_scalar(y);
  const auto& alpha_col = as_column_vector_or_scalar(alpha);
  const auto& sigma_col = as_column_vector_or_scalar(sigma);
 
  const auto& y_val = value_of(y_col);
  const auto& alpha_val = value_of(alpha_col);
  const auto& sigma_val = value_of(sigma_col);
 
  auto check_y_nonnegative
      = check_cl(function, "Random variable", y_val, "not NaN");
  auto y_nonnegative = y_val >= 0.0;
  auto check_alpha_positive_finite
      = check_cl(function, "Shape parameter", alpha_val, "positive finite");
  auto alpha_positive_finite_expr = alpha_val > 0 && isfinite(alpha_val);
  auto check_sigma_positive_finite
      = check_cl(function, "Scale parameter", sigma_val, "positive finite");
  auto sigma_positive_finite_expr = 0 < sigma_val && isfinite(sigma_val);
 
  auto pow_n = pow(elt_divide(y_val, sigma_val), alpha_val);
  auto exp_n = exp(-pow_n);
  // TODO(Andrew) Further simplify derivatives and log1m_exp below
  auto lcdf_expr = colwise_sum(log1m(exp_n));
 
  auto rep_deriv = elt_divide(pow_n, elt_divide(1.0, exp_n) - 1.0);
  auto deriv_y_sigma = elt_multiply(rep_deriv, alpha_val);
  auto y_deriv = elt_divide(deriv_y_sigma, y_val);
  auto sigma_deriv = elt_divide(deriv_y_sigma, -sigma_val);
  auto alpha_deriv = elt_multiply(rep_deriv, log(elt_divide(y_val, sigma_val)));
 
  matrix_cl<double> lcdf_cl;
  matrix_cl<double> alpha_deriv_cl;
  matrix_cl<double> y_deriv_cl;
  matrix_cl<double> sigma_deriv_cl;
 
  results(check_y_nonnegative, check_alpha_positive_finite,
          check_sigma_positive_finite, lcdf_cl, y_deriv_cl, alpha_deriv_cl,
          sigma_deriv_cl)
      = expressions(y_nonnegative, alpha_positive_finite_expr,
                    sigma_positive_finite_expr, lcdf_expr,
                    calc_if<!is_constant<T_y_cl>::value>(y_deriv),
                    calc_if<!is_constant<T_shape_cl>::value>(alpha_deriv),
                    calc_if<!is_constant<T_scale_cl>::value>(sigma_deriv));
 
  T_partials_return lcdf = from_matrix_cl(lcdf_cl).sum();
 
  auto ops_partials = make_partials_propagator(y_col, alpha_col, sigma_col);
 
  if (!is_constant<T_y_cl>::value) {
    partials<0>(ops_partials) = std::move(y_deriv_cl);
  }
  if (!is_constant<T_shape_cl>::value) {
    partials<1>(ops_partials) = std::move(alpha_deriv_cl);
  }
  if (!is_constant<T_scale_cl>::value) {
    partials<2>(ops_partials) = std::move(sigma_deriv_cl);
  }
  return ops_partials.build(lcdf);
}
 
}  // namespace math
}  // namespace stan
#endif
#endif