make StatisKit.Core Great Again with wrappers is better

src/py/statiskit/core/stl.py

@@ -0,0 +1,9 @@
+from statiskit.stl.vector import decorator as vector_decorator
+
+from . import _core
+from .__core.std import (_Vector)
+
+__all__ = []
+
+for _vector in _Vector:
+    vector_decorator(_vector)

src/py/wrapper/_core.h

@@ -0,0 +1,53 @@
+#pragma once
+
+#include <pybind11/pybind11.h>
+
+#include <memory>
+#include <statiskit/core/base.h>
+#include <statiskit/core/data.h>
+#include <statiskit/core/distribution.h>
+#include <statiskit/core/estimation.h>
+#include <statiskit/core/estimator.h>
+#include <statiskit/core/event.h>
+#include <statiskit/core/indicator.h>
+#include <statiskit/core/sample_space.h>
+#include <statiskit/core/singular.h>
+#include <statiskit/core/slope_heuristic.h>
+
+#define PYBIND11_OVERLOAD_UNIQUE_PTR_INT(ret_type, cname, name, ...) { \
+        pybind11::gil_scoped_acquire gil; \
+        pybind11::function overload = pybind11::get_overload(static_cast<const cname *>(this), name); \
+        if (overload) { \
+            auto o = overload(__VA_ARGS__); \
+            if (pybind11::detail::cast_is_temporary_value_reference<ret_type::pointer>::value) { \
+                static pybind11::detail::overload_caster_t<ret_type::pointer> caster; \
+                return std::unique_ptr< ret_type::element_type >(pybind11::detail::cast_ref<ret_type::pointer>(std::move(o), caster)); \
+            } \
+            else return std::unique_ptr< ret_type::element_type >(pybind11::detail::cast_safe<ret_type::pointer>(std::move(o))); \
+        } \
+    }
+
+#define PYBIND11_OVERLOAD_UNIQUE_PTR_NAME(ret_type, cname, name, fn, ...) \
+    PYBIND11_OVERLOAD_UNIQUE_PTR_INT(ret_type, cname, name, __VA_ARGS__) \
+    return cname::fn(__VA_ARGS__)
+
+#define PYBIND11_OVERLOAD_PURE_UNIQUE_PTR_NAME(ret_type, cname, name, fn, ...) \
+    PYBIND11_OVERLOAD_UNIQUE_PTR_INT(ret_type, cname, name, __VA_ARGS__) \
+    pybind11::pybind11_fail("Tried to call pure virtual function \"" #cname "::" name "\"");
+
+#define PYBIND11_OVERLOAD_UNIQUE_PTR(ret_type, cname, fn, ...) \
+    PYBIND11_OVERLOAD_UNIQUE_PTR_NAME(ret_type, cname, #fn, fn, __VA_ARGS__)
+
+#define PYBIND11_OVERLOAD_PURE_UNIQUE_PTR(ret_type, cname, fn, ...) \
+    PYBIND11_OVERLOAD_PURE_UNIQUE_PTR_NAME(ret_type, cname, #fn, fn, __VA_ARGS__)
+
+namespace autowig
+{
+    template<class T> struct HolderType {
+        typedef std::unique_ptr< T > Type;
+    };
+
+    template<class T> struct NoDeleteHolderType {
+        typedef std::unique_ptr< T, pybind11::nodelete > Type;
+    };
+}

src/py/wrapper/wrapper_010dca8ca2e458db8505774b1f36db9a.cpp

@@ -0,0 +1,18 @@
+#include "_core.h"
+
+unsigned int const & (::statiskit::RegularUnivariateHistogramDistributionSlopeHeuristicSelection::Estimator::*method_pointer_8cc4d3f7e7a85290a6eac90ddb1b031c)()const= &::statiskit::RegularUnivariateHistogramDistributionSlopeHeuristicSelection::Estimator::get_maxbins;
+void  (::statiskit::RegularUnivariateHistogramDistributionSlopeHeuristicSelection::Estimator::*method_pointer_d93c3ccaf8e85e3fb977443d8d8f1b82)(unsigned int const &)= &::statiskit::RegularUnivariateHistogramDistributionSlopeHeuristicSelection::Estimator::set_maxbins;
+
+namespace autowig {
+}
+
+void wrapper_010dca8ca2e458db8505774b1f36db9a(pybind11::module& module)
+{
+
+    pybind11::class_<class ::statiskit::RegularUnivariateHistogramDistributionSlopeHeuristicSelection::Estimator, autowig::HolderType< class ::statiskit::RegularUnivariateHistogramDistributionSlopeHeuristicSelection::Estimator >::Type, struct ::statiskit::ContinuousUnivariateDistributionEstimation::Estimator > class_010dca8ca2e458db8505774b1f36db9a(module, "Estimator", "");
+    class_010dca8ca2e458db8505774b1f36db9a.def(pybind11::init<  >());
+    class_010dca8ca2e458db8505774b1f36db9a.def(pybind11::init< class ::statiskit::RegularUnivariateHistogramDistributionSlopeHeuristicSelection::Estimator const & >());
+    class_010dca8ca2e458db8505774b1f36db9a.def("get_maxbins", method_pointer_8cc4d3f7e7a85290a6eac90ddb1b031c, pybind11::return_value_policy::copy, "");
+    class_010dca8ca2e458db8505774b1f36db9a.def("set_maxbins", method_pointer_d93c3ccaf8e85e3fb977443d8d8f1b82, "");
+
+}

src/py/wrapper/wrapper_0159796d2beb51da9446e83d609342aa.cpp

@@ -0,0 +1,15 @@
+#include "_core.h"
+
+
+namespace autowig {
+}
+
+void wrapper_0159796d2beb51da9446e83d609342aa(pybind11::module& module)
+{
+
+    pybind11::class_<struct ::statiskit::UnivariateHistogramDistributionEstimation, autowig::HolderType< struct ::statiskit::UnivariateHistogramDistributionEstimation >::Type, class ::statiskit::ActiveEstimation< class ::statiskit::UnivariateHistogramDistribution, struct ::statiskit::ContinuousUnivariateDistributionEstimation > > class_0159796d2beb51da9446e83d609342aa(module, "UnivariateHistogramDistributionEstimation", "");
+    class_0159796d2beb51da9446e83d609342aa.def(pybind11::init<  >());
+    class_0159796d2beb51da9446e83d609342aa.def(pybind11::init< class ::statiskit::UnivariateHistogramDistribution const *, struct ::statiskit::UnivariateData const * >());
+    class_0159796d2beb51da9446e83d609342aa.def(pybind11::init< struct ::statiskit::UnivariateHistogramDistributionEstimation const & >());
+
+}

src/py/wrapper/wrapper_01ddd51bfe2a5d97b4620b9e2d14360e.cpp

@@ -0,0 +1,16 @@
+#include "_core.h"
+
+int const & (::statiskit::LeftCensoredEvent< ::statiskit::DiscreteEvent >::*method_pointer_7f2086559bba5548b25f5bb9bf3e9368)()const= &::statiskit::LeftCensoredEvent< struct ::statiskit::DiscreteEvent >::get_upper_bound;
+
+namespace autowig {
+}
+
+void wrapper_01ddd51bfe2a5d97b4620b9e2d14360e(pybind11::module& module)
+{
+
+    pybind11::class_<class ::statiskit::LeftCensoredEvent< struct ::statiskit::DiscreteEvent >, autowig::HolderType< class ::statiskit::LeftCensoredEvent< struct ::statiskit::DiscreteEvent > >::Type, struct ::statiskit::DiscreteEvent > class_01ddd51bfe2a5d97b4620b9e2d14360e(module, "_LeftCensoredEvent_01ddd51bfe2a5d97b4620b9e2d14360e", "");
+    class_01ddd51bfe2a5d97b4620b9e2d14360e.def(pybind11::init< int const & >());
+    class_01ddd51bfe2a5d97b4620b9e2d14360e.def(pybind11::init< class ::statiskit::LeftCensoredEvent< struct ::statiskit::DiscreteEvent > const & >());
+    class_01ddd51bfe2a5d97b4620b9e2d14360e.def("get_upper_bound", method_pointer_7f2086559bba5548b25f5bb9bf3e9368, pybind11::return_value_policy::copy, "");
+
+}

src/py/wrapper/wrapper_0281a28ebbe655cabfc3d1baabb16b6c.cpp

@@ -0,0 +1,37 @@
+#include "_core.h"
+
+namespace autowig
+{
+    typedef ::statiskit::PolymorphicCopy< struct ::statiskit::SingularDistribution, ::statiskit::DirichletMultinomialSingularDistribution, struct ::statiskit::SingularDistribution > class_type;
+
+    class Trampoline : public class_type
+    {
+        public:
+            using ::statiskit::PolymorphicCopy< struct ::statiskit::SingularDistribution, ::statiskit::DirichletMultinomialSingularDistribution, struct ::statiskit::SingularDistribution >::PolymorphicCopy;
+
+            typedef class ::std::unique_ptr< struct ::statiskit::SingularDistribution, struct ::std::default_delete< struct ::statiskit::SingularDistribution > >  return_type_d1b9702be8e75e50b289d463019d92e6;
+            virtual return_type_d1b9702be8e75e50b289d463019d92e6 copy() const override { PYBIND11_OVERLOAD_UNIQUE_PTR(return_type_d1b9702be8e75e50b289d463019d92e6, class_type, copy, ); };
+            typedef class ::std::unique_ptr< struct ::statiskit::MultivariateEvent, struct ::std::default_delete< struct ::statiskit::MultivariateEvent > >  return_type_48a21906343659d38a01df937deeb28c;
+            typedef unsigned int  param_48a21906343659d38a01df937deeb28c_0_type;
+            virtual return_type_48a21906343659d38a01df937deeb28c simulate(param_48a21906343659d38a01df937deeb28c_0_type param_0) const override { PYBIND11_OVERLOAD_PURE_UNIQUE_PTR(return_type_48a21906343659d38a01df937deeb28c, class_type, simulate, param_0); };
+            typedef double  return_type_acdea368f48f572bb000ce0a3e887539;
+            typedef struct ::statiskit::MultivariateEvent const * param_acdea368f48f572bb000ce0a3e887539_0_type;
+            typedef bool const & param_acdea368f48f572bb000ce0a3e887539_1_type;
+            virtual return_type_acdea368f48f572bb000ce0a3e887539 probability(param_acdea368f48f572bb000ce0a3e887539_0_type param_0, param_acdea368f48f572bb000ce0a3e887539_1_type param_1) const override { PYBIND11_OVERLOAD_PURE(return_type_acdea368f48f572bb000ce0a3e887539, class_type, probability, param_0, param_1); };
+            typedef unsigned int  return_type_2c1d7ed64e3e5d1aa53e91bf74bfffd9;
+            virtual return_type_2c1d7ed64e3e5d1aa53e91bf74bfffd9 get_nb_parameters() const override { PYBIND11_OVERLOAD_PURE(return_type_2c1d7ed64e3e5d1aa53e91bf74bfffd9, class_type, get_nb_parameters, ); };
+            typedef ::statiskit::Index  return_type_0d6cc8e9b1fb50da9e07aa24ca7b9901;
+            virtual return_type_0d6cc8e9b1fb50da9e07aa24ca7b9901 get_nb_components() const override { PYBIND11_OVERLOAD_PURE(return_type_0d6cc8e9b1fb50da9e07aa24ca7b9901, class_type, get_nb_components, ); };
+    };
+}
+
+
+namespace autowig {
+}
+
+void wrapper_0281a28ebbe655cabfc3d1baabb16b6c(pybind11::module& module)
+{
+
+    pybind11::class_<struct ::statiskit::PolymorphicCopy< struct ::statiskit::SingularDistribution, class ::statiskit::DirichletMultinomialSingularDistribution, struct ::statiskit::SingularDistribution >, autowig::Trampoline, autowig::HolderType< struct ::statiskit::PolymorphicCopy< struct ::statiskit::SingularDistribution, class ::statiskit::DirichletMultinomialSingularDistribution, struct ::statiskit::SingularDistribution > >::Type, struct ::statiskit::SingularDistribution > class_0281a28ebbe655cabfc3d1baabb16b6c(module, "_PolymorphicCopy_0281a28ebbe655cabfc3d1baabb16b6c", "");
+
+}

src/py/wrapper/wrapper_02cb27a2f5305d6eaf2fc0d0977b5565.cpp

@@ -0,0 +1,63 @@
+#include "_core.h"
+
+namespace autowig
+{
+    typedef ::statiskit::DiscreteUnivariateDistribution class_type;
+
+    class Trampoline : public class_type
+    {
+        public:
+            using ::statiskit::DiscreteUnivariateDistribution::DiscreteUnivariateDistribution;
+
+            typedef double  return_type_c6a8fd2e5dc454c89e463671fdf91f3e;
+            virtual return_type_c6a8fd2e5dc454c89e463671fdf91f3e get_variance() const override { PYBIND11_OVERLOAD_PURE(return_type_c6a8fd2e5dc454c89e463671fdf91f3e, class_type, get_variance, ); };
+            typedef double  return_type_9fdf92df3e8c5e0e85306b85eb662025;
+            virtual return_type_9fdf92df3e8c5e0e85306b85eb662025 get_mean() const override { PYBIND11_OVERLOAD_PURE(return_type_9fdf92df3e8c5e0e85306b85eb662025, class_type, get_mean, ); };
+            typedef class ::std::unique_ptr< struct ::statiskit::UnivariateEvent, struct ::std::default_delete< struct ::statiskit::UnivariateEvent > >  return_type_9b1e41d78cb15fb485b076a8136faf6b;
+            virtual return_type_9b1e41d78cb15fb485b076a8136faf6b simulate() const override { PYBIND11_OVERLOAD_UNIQUE_PTR(return_type_9b1e41d78cb15fb485b076a8136faf6b, class_type, simulate, ); };
+            typedef int  return_type_0f752a27239a55e4a5244da5bea67286;
+            typedef double const & param_0f752a27239a55e4a5244da5bea67286_0_type;
+            virtual return_type_0f752a27239a55e4a5244da5bea67286 quantile(param_0f752a27239a55e4a5244da5bea67286_0_type param_0) const override { PYBIND11_OVERLOAD(return_type_0f752a27239a55e4a5244da5bea67286, class_type, quantile, param_0); };
+            typedef double  return_type_b8cb3c3bef9a57b0b9e80ef518f215b7;
+            typedef int const & param_b8cb3c3bef9a57b0b9e80ef518f215b7_0_type;
+            virtual return_type_b8cb3c3bef9a57b0b9e80ef518f215b7 cdf(param_b8cb3c3bef9a57b0b9e80ef518f215b7_0_type param_0) const override { PYBIND11_OVERLOAD(return_type_b8cb3c3bef9a57b0b9e80ef518f215b7, class_type, cdf, param_0); };
+            typedef double  return_type_e743676180d85397828cc79f44d4d185;
+            typedef int const & param_e743676180d85397828cc79f44d4d185_0_type;
+            virtual return_type_e743676180d85397828cc79f44d4d185 pdf(param_e743676180d85397828cc79f44d4d185_0_type param_0) const override { PYBIND11_OVERLOAD(return_type_e743676180d85397828cc79f44d4d185, class_type, pdf, param_0); };
+            typedef double  return_type_e31fb7a7a5b852af9574d7d8bac3da21;
+            typedef int const & param_e31fb7a7a5b852af9574d7d8bac3da21_0_type;
+            virtual return_type_e31fb7a7a5b852af9574d7d8bac3da21 ldf(param_e31fb7a7a5b852af9574d7d8bac3da21_0_type param_0) const override { PYBIND11_OVERLOAD(return_type_e31fb7a7a5b852af9574d7d8bac3da21, class_type, ldf, param_0); };
+            typedef double  return_type_c3377d2e9b535f76985d786c2f3a6fe0;
+            typedef struct ::statiskit::UnivariateEvent const * param_c3377d2e9b535f76985d786c2f3a6fe0_0_type;
+            typedef bool const & param_c3377d2e9b535f76985d786c2f3a6fe0_1_type;
+            virtual return_type_c3377d2e9b535f76985d786c2f3a6fe0 probability(param_c3377d2e9b535f76985d786c2f3a6fe0_0_type param_0, param_c3377d2e9b535f76985d786c2f3a6fe0_1_type param_1) const override { PYBIND11_OVERLOAD(return_type_c3377d2e9b535f76985d786c2f3a6fe0, class_type, probability, param_0, param_1); };
+            typedef class ::std::unique_ptr< struct ::statiskit::UnivariateDistribution, struct ::std::default_delete< struct ::statiskit::UnivariateDistribution > >  return_type_7043746e82585022aaf3d0d72cbf150b;
+            virtual return_type_7043746e82585022aaf3d0d72cbf150b copy() const override { PYBIND11_OVERLOAD_PURE_UNIQUE_PTR(return_type_7043746e82585022aaf3d0d72cbf150b, class_type, copy, ); };
+            typedef unsigned int  return_type_0826ef63abcb5a8d83b7e3e2df48a620;
+            virtual return_type_0826ef63abcb5a8d83b7e3e2df48a620 get_nb_parameters() const override { PYBIND11_OVERLOAD_PURE(return_type_0826ef63abcb5a8d83b7e3e2df48a620, class_type, get_nb_parameters, ); };
+    };
+}
+
+double  (::statiskit::DiscreteUnivariateDistribution::*method_pointer_e31fb7a7a5b852af9574d7d8bac3da21)(int const &)const= &::statiskit::DiscreteUnivariateDistribution::ldf;
+double  (::statiskit::DiscreteUnivariateDistribution::*method_pointer_e743676180d85397828cc79f44d4d185)(int const &)const= &::statiskit::DiscreteUnivariateDistribution::pdf;
+double  (::statiskit::DiscreteUnivariateDistribution::*method_pointer_b8cb3c3bef9a57b0b9e80ef518f215b7)(int const &)const= &::statiskit::DiscreteUnivariateDistribution::cdf;
+int  (::statiskit::DiscreteUnivariateDistribution::*method_pointer_0f752a27239a55e4a5244da5bea67286)(double const &)const= &::statiskit::DiscreteUnivariateDistribution::quantile;
+double  (::statiskit::DiscreteUnivariateDistribution::*method_pointer_9fdf92df3e8c5e0e85306b85eb662025)()const= &::statiskit::DiscreteUnivariateDistribution::get_mean;
+double  (::statiskit::DiscreteUnivariateDistribution::*method_pointer_c6a8fd2e5dc454c89e463671fdf91f3e)()const= &::statiskit::DiscreteUnivariateDistribution::get_variance;
+
+namespace autowig {
+}
+
+void wrapper_02cb27a2f5305d6eaf2fc0d0977b5565(pybind11::module& module)
+{
+
+    pybind11::class_<struct ::statiskit::DiscreteUnivariateDistribution, autowig::Trampoline, autowig::HolderType< struct ::statiskit::DiscreteUnivariateDistribution >::Type, struct ::statiskit::UnivariateDistribution > class_02cb27a2f5305d6eaf2fc0d0977b5565(module, "DiscreteUnivariateDistribution", "This virtual class DiscreteUnivariateDistribution represents the\ndistribution of a random discrete component $ N$. The support is $\n:raw-latex:`\\mathbb{Z}` $ and we have $\n:raw-latex:`\\sum`\\_{n:raw-latex:`\\in `:raw-latex:`\\mathbb{Z}`} P(N=n) =\n1$.\n\n");
+    class_02cb27a2f5305d6eaf2fc0d0977b5565.def(pybind11::init<  >());
+    class_02cb27a2f5305d6eaf2fc0d0977b5565.def("ldf", method_pointer_e31fb7a7a5b852af9574d7d8bac3da21, "Compute the log-probability of a value.\n\nLet $n :raw-latex:`\\in `:raw-latex:`\\mathbb{Z}` $ denote the value, $\n:raw-latex:`\\ln `P:raw-latex:`\\left`(N = n:raw-latex:`\\right`) $.\n\n:Parameter:\n    `value` (:cpp:any:`int`) - The considered value.\n\n:Return Type:\n    :cpp:any:`double`\n\n");
+    class_02cb27a2f5305d6eaf2fc0d0977b5565.def("pdf", method_pointer_e743676180d85397828cc79f44d4d185, "Compute the probability of a value\n\nLet $n :raw-latex:`\\in `:raw-latex:`\\mathbb{Z}` $ denote the value, $\nP:raw-latex:`\\left`(N = n:raw-latex:`\\right`) $.\n\n:Parameter:\n    `value` (:cpp:any:`int`) - The considered value.\n\n:Return Type:\n    :cpp:any:`double`\n\n");
+    class_02cb27a2f5305d6eaf2fc0d0977b5565.def("cdf", method_pointer_b8cb3c3bef9a57b0b9e80ef518f215b7, "Compute the cumulative probability of a value\n\nLet $n :raw-latex:`\\in `:raw-latex:`\\mathbb{Z}` $ denote the value\n\n.. math::\n\n\n   P\\left(N \\leq n\\right)  =   \\sum_{k \\leq n} P\\left(N = k\\right).\n\n:Parameter:\n    `value` (:cpp:any:`int`) - The considered value.\n\n:Return Type:\n    :cpp:any:`double`\n\n");
+    class_02cb27a2f5305d6eaf2fc0d0977b5565.def("quantile", method_pointer_0f752a27239a55e4a5244da5bea67286, "Compute the quantile of a probability. This is the value $ n\n:raw-latex:`\\in `:raw-latex:`\\mathbb{Z}` $ such that $ P(N\n:raw-latex:`\\leq `n) :raw-latex:`\\leq `p < P(N :raw-latex:`\\leq `n+1) $.\n\n:Parameter:\n    `p` (:cpp:any:`double`) - Undocumented\n\n:Return Type:\n    :cpp:any:`int`\n\n");
+    class_02cb27a2f5305d6eaf2fc0d0977b5565.def("get_mean", method_pointer_9fdf92df3e8c5e0e85306b85eb662025, "Get mean of a discrete random component $ E(N) =\n:raw-latex:`\\sum`\\_{n:raw-latex:`\\in`:raw-latex:`\\mathbb{Z}`} n P(N=n)\n$.\n\n:Return Type:\n    :cpp:any:`double`\n\n");
+    class_02cb27a2f5305d6eaf2fc0d0977b5565.def("get_variance", method_pointer_c6a8fd2e5dc454c89e463671fdf91f3e, "Get variance of a discrete random component $ V(N) =\n:raw-latex:`\\sum`\\_{n:raw-latex:`\\in`:raw-latex:`\\mathbb{Z}`}\n:raw-latex:`\\lbrace `n-E(n) :raw-latex:`\\rbrace`^2 P(N=n) $ $\n:raw-latex:`\\mathbb{N}` $.\n\n:Return Type:\n    :cpp:any:`double`\n\n");
+
+}

src/py/wrapper/wrapper_033df89396b35855a50192cdc7f16be3.cpp

@@ -0,0 +1,19 @@
+#include "_core.h"
+
+double const & (::statiskit::PoissonDistribution::*method_pointer_e1c5d61243a2516d8cca503eee6d4b6d)()const= &::statiskit::PoissonDistribution::get_theta;
+void  (::statiskit::PoissonDistribution::*method_pointer_f1f3fd67865756958164089e5a85911b)(double const &)= &::statiskit::PoissonDistribution::set_theta;
+
+namespace autowig {
+}
+
+void wrapper_033df89396b35855a50192cdc7f16be3(pybind11::module& module)
+{
+
+    pybind11::class_<class ::statiskit::PoissonDistribution, autowig::HolderType< class ::statiskit::PoissonDistribution >::Type, struct ::statiskit::PolymorphicCopy< struct ::statiskit::UnivariateDistribution, class ::statiskit::PoissonDistribution, struct ::statiskit::DiscreteUnivariateDistribution > > class_033df89396b35855a50192cdc7f16be3(module, "PoissonDistribution", "This class PoissonDistribution represents a `Poisson\ndistribution <https://en.wikipedia.org/wiki/Poisson_distribution>`__\n\nThe Poisson distribution is an univariate discrete distribution that\nexpresses the probability of a given number of events occurring in a\nfixed interval of time and/or space if these events occur with a known\naverage rate\n$:raw-latex:`\\theta  `:raw-latex:`\\in `:raw-latex:`\\mathbb{R}`\\_+^\\* $\nand independently of the time since the last event. The support of the\nPoisson distribution is the set of non-negative integer $\n:raw-latex:`\\mathbb{N}` $.\n\n");
+    class_033df89396b35855a50192cdc7f16be3.def(pybind11::init<  >());
+    class_033df89396b35855a50192cdc7f16be3.def(pybind11::init< double const & >());
+    class_033df89396b35855a50192cdc7f16be3.def(pybind11::init< class ::statiskit::PoissonDistribution const & >());
+    class_033df89396b35855a50192cdc7f16be3.def("get_theta", method_pointer_e1c5d61243a2516d8cca503eee6d4b6d, pybind11::return_value_policy::copy, "Get the value of theta.\n\n:Return Type:\n    :cpp:any:`double`\n\n");
+    class_033df89396b35855a50192cdc7f16be3.def("set_theta", method_pointer_f1f3fd67865756958164089e5a85911b, "Set the value of theta.\n\n:Parameter:\n    `theta` (:cpp:any:`double`) - Undocumented\n\n:Return Type:\n    :cpp:any:`void`\n\n");
+
+}