Automatic Differentiation
 
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rayleigh_lcdf.hpp
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1#ifndef STAN_MATH_OPENCL_PRIM_RAYLEIGH_LCDF_HPP
2#define STAN_MATH_OPENCL_PRIM_RAYLEIGH_LCDF_HPP
3#ifdef STAN_OPENCL
4
12
13namespace stan {
14namespace math {
15
27template <
28 typename T_y_cl, typename T_scale_cl,
29 require_all_prim_or_rev_kernel_expression_t<T_y_cl, T_scale_cl>* = nullptr,
30 require_any_not_stan_scalar_t<T_y_cl, T_scale_cl>* = nullptr>
32 const T_scale_cl& sigma) {
33 static constexpr const char* function = "rayleigh_lcdf(OpenCL)";
34 using T_partials_return = partials_return_t<T_y_cl, T_scale_cl>;
35 using std::isfinite;
36 using std::isnan;
37
38 check_consistent_sizes(function, "Random variable", y, "Scale parameter",
39 sigma);
40 const size_t N = max_size(y, sigma);
41 if (N == 0) {
42 return 0.0;
43 }
44
45 const auto& y_col = as_column_vector_or_scalar(y);
46 const auto& sigma_col = as_column_vector_or_scalar(sigma);
47
48 const auto& y_val = value_of(y_col);
49 const auto& sigma_val = value_of(sigma_col);
50
51 auto check_y_nonnegative
52 = check_cl(function, "Random variable", y_val, "nonnegative");
53 auto y_nonnegative_expr = 0.0 <= y_val;
54 auto check_sigma_positive
55 = check_cl(function, "Scale parameter", sigma_val, "positive");
56 auto sigma_positive_expr = 0 < sigma_val;
57
58 auto inv_sigma = elt_divide(1.0, sigma_val);
59 auto y_div_sigma_square = elt_multiply(y_val, square(inv_sigma));
60 auto exp_val = exp(elt_multiply(-0.5 * y_val, y_div_sigma_square));
61 auto lcdf_expr = colwise_sum(log1m(exp_val));
62
63 auto y_deriv
64 = elt_divide(elt_multiply(y_div_sigma_square, exp_val), 1.0 - exp_val);
65 auto sigma_deriv = elt_multiply(elt_multiply(y_val, -inv_sigma), y_deriv);
66
67 matrix_cl<double> lcdf_cl;
68 matrix_cl<double> y_deriv_cl;
69 matrix_cl<double> sigma_deriv_cl;
70
71 results(check_y_nonnegative, check_sigma_positive, lcdf_cl, y_deriv_cl,
72 sigma_deriv_cl)
73 = expressions(y_nonnegative_expr, sigma_positive_expr, lcdf_expr,
76
77 T_partials_return lcdf = from_matrix_cl(lcdf_cl).sum();
78
79 auto ops_partials = make_partials_propagator(y_col, sigma_col);
80
82 partials<0>(ops_partials) = std::move(y_deriv_cl);
83 }
85 partials<1>(ops_partials) = std::move(sigma_deriv_cl);
86 }
87
88 return ops_partials.build(lcdf);
89}
90
91} // namespace math
92} // namespace stan
93#endif
94#endif
Represents an arithmetic matrix on the OpenCL device.
Definition matrix_cl.hpp:47
elt_multiply_< as_operation_cl_t< T_a >, as_operation_cl_t< T_b > > elt_multiply(T_a &&a, T_b &&b)
auto check_cl(const char *function, const char *var_name, T &&y, const char *must_be)
Constructs a check on opencl matrix or expression.
Definition check_cl.hpp:219
results_cl< T_results... > results(T_results &&... results)
Deduces types for constructing results_cl object.
auto as_column_vector_or_scalar(T &&a)
as_column_vector_or_scalar of a kernel generator expression.
elt_divide_< as_operation_cl_t< T_a >, as_operation_cl_t< T_b > > elt_divide(T_a &&a, T_b &&b)
calc_if_< true, as_operation_cl_t< T > > calc_if(T &&a)
Definition calc_if.hpp:121
auto colwise_sum(T &&a)
Column wise sum - reduction of a kernel generator expression.
expressions_cl< T_expressions... > expressions(T_expressions &&... expressions)
Deduces types for constructing expressions_cl object.
return_type_t< T_y_cl, T_scale_cl > rayleigh_lcdf(const T_y_cl &y, const T_scale_cl &sigma)
Returns the Rayleigh log cumulative distribution function for the given location, and scale.
auto from_matrix_cl(const T &src)
Copies the source matrix that is stored on the OpenCL device to the destination Eigen matrix.
Definition copy.hpp:61
typename return_type< Ts... >::type return_type_t
Convenience type for the return type of the specified template parameters.
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition value_of.hpp:18
void check_consistent_sizes(const char *)
Trivial no input case, this function is a no-op.
int64_t max_size(const T1 &x1, const Ts &... xs)
Calculate the size of the largest input.
Definition max_size.hpp:20
fvar< T > log1m(const fvar< T > &x)
Definition log1m.hpp:12
auto make_partials_propagator(Ops &&... ops)
Construct an partials_propagator.
fvar< T > square(const fvar< T > &x)
Definition square.hpp:12
fvar< T > exp(const fvar< T > &x)
Definition exp.hpp:13
typename partials_return_type< Args... >::type partials_return_t
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...
bool isnan(const stan::math::var &a)
Checks if the given number is NaN.
Definition std_isnan.hpp:18
Metaprogramming struct to detect whether a given type is constant in the mathematical sense (not the ...