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Random python binding
[SVN r2881]
This commit is contained in:
Daniel Wallin
243
python/random.cpp
Executable file
243
python/random.cpp
Executable file
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// Copyright Daniel Wallin 2006. Use, modification and distribution is
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// subject to the Boost Software License, Version 1.0. (See accompanying
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// file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
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#include <boost/preprocessor/iteration/local.hpp>
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#include <boost/preprocessor/repetition/enum_params.hpp>
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#include <boost/preprocessor/repetition/enum_trailing_params.hpp>
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#include <boost/preprocessor/repetition/enum_trailing_binary_params.hpp>
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#include <boost/preprocessor/seq/for_each.hpp>
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#include <boost/preprocessor/stringize.hpp>
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#include <boost/python.hpp>
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#include <boost/bind/apply.hpp>
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#include <vector> // missing include in sprng.hpp
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#include <boost/random/sprng.hpp>
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#include <boost/random/buffered_uniform_01.hpp>
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#include <boost/random/buffered_generator.hpp>
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// Generators
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#include <boost/random/linear_congruential.hpp>
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#include <boost/random/mersenne_twister.hpp>
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#include <boost/random/variate_generator.hpp>
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#include <boost/random.hpp>
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#include <boost/parameter/python.hpp>
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#include <boost/utility/base_from_member.hpp>
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using namespace boost::python;
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namespace mpl = boost::mpl;
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struct seed_fwd
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{
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#define BOOST_PP_LOCAL_MACRO(n) \
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template <class R, class T BOOST_PP_ENUM_TRAILING_PARAMS(n, class A)> \
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R operator()(boost::type<R>, T& self BOOST_PP_ENUM_TRAILING_BINARY_PARAMS(n, A, const& a)) \
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{ \
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return self.seed(BOOST_PP_ENUM_PARAMS(n, a)); \
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}
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#define BOOST_PP_LOCAL_LIMITS (0, 4)
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#include BOOST_PP_LOCAL_ITERATE()
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};
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struct sprng_visitor : def_visitor<sprng_visitor>
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{
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typedef mpl::vector4<
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boost::random::tag::stream_number*
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, boost::random::tag::total_streams*
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, boost::random::tag::global_seed*
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, boost::random::tag::parameter*
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> keywords;
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template <class C>
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void visit(C& cl) const
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{
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typedef typename C::wrapped_type rng;
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namespace py = boost::parameter::python;
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cl
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.def(
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py::init<
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keywords
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, mpl::vector4<int,int,int,int>
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>()
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)
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.def("seed",
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py::function<
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seed_fwd
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, keywords
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, mpl::vector5<void,int,int,int,int>
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>()
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);
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}
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};
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template <class Distribution>
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struct variate_generator_class
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: class_<
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boost::variate_generator<
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boost::buffered_uniform_01<>&, Distribution
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>
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>
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{
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typedef boost::variate_generator<
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boost::buffered_uniform_01<>&, Distribution
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> generator;
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typedef class_<generator> base;
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variate_generator_class(char const* name)
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: base(name, init<boost::buffered_uniform_01<>&, Distribution&>())
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{
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converter::registration const* r = converter::registry::query(type_id<Distribution>());
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assert(r);
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object distribution_class(handle<>(r->get_class_object()));
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dict current(scope().attr("__dict__"));
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if (!current.has_key("distribution_variate_map"))
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scope().attr("distribution_variate_map") = dict();
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scope().attr("distribution_variate_map")[distribution_class] = *this;
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this->def("__call__",
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make_function(
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boost::apply<typename generator::result_type>()
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, default_call_policies()
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, mpl::vector2<typename generator::result_type, generator&>()
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)
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);
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}
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};
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template <class Engine>
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struct rng_wrapper
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: boost::base_from_member<Engine>
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, boost::basic_buffered_uniform_01<Engine&>
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{
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typedef boost::base_from_member<Engine> member_base;
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typedef boost::basic_buffered_uniform_01<Engine&> buffered_base;
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rng_wrapper()
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: buffered_base(this->member)
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{}
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#define BOOST_PP_LOCAL_MACRO(n) \
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template <BOOST_PP_ENUM_PARAMS(n, class A)> \
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rng_wrapper(BOOST_PP_ENUM_BINARY_PARAMS(n, A, a)) \
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: member_base(BOOST_PP_ENUM_PARAMS(n, a)) \
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, buffered_base(this->member) \
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{}
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#define BOOST_PP_LOCAL_LIMITS (1, 5)
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#include BOOST_PP_LOCAL_ITERATE()
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void seed()
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{
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this->member.seed();
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this->reset();
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}
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#define BOOST_PP_LOCAL_MACRO(n) \
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template <BOOST_PP_ENUM_PARAMS(n, class A)> \
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void seed(BOOST_PP_ENUM_BINARY_PARAMS(n, A, a)) \
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{ \
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this->member.seed(BOOST_PP_ENUM_PARAMS(n, a)); \
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this->reset(); \
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}
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#define BOOST_PP_LOCAL_LIMITS (1, 5)
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#include BOOST_PP_LOCAL_ITERATE()
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};
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template <class Rng>
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struct buffered_uniform_01_class
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: class_<
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rng_wrapper<Rng>, bases<boost::buffered_uniform_01<> >
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>
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{
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typedef class_<
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rng_wrapper<Rng>, bases<boost::buffered_uniform_01<> >
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> base;
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buffered_uniform_01_class(char const* name)
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: base(name)
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{
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this->def("seed", (void(rng_wrapper<Rng>::*)())&rng_wrapper<Rng>::seed);
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}
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};
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BOOST_PYTHON_MODULE(_random)
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{
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typedef boost::buffered_uniform_01<boost::mt11213b> rng;
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class_<boost::buffered_generator<double>, boost::noncopyable>("buffered_generator", no_init)
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.def("__call__",
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make_function(
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boost::apply<boost::buffered_generator<double>::result_type>()
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, default_call_policies()
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, mpl::vector2<boost::buffered_generator<double>::result_type, boost::buffered_generator<double>&>()
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)
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);
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class_<
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boost::buffered_uniform_01<>, bases<boost::buffered_generator<double> >, boost::noncopyable
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>("buffered_uniform_01", no_init);
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#define RNG_CLASSES \
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(minstd_rand0)(minstd_rand) \
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(rand48) \
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(ecuyer1988) \
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(kreutzer1986) \
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(hellekalek1995) \
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(mt11213b)(mt19937) \
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(lagged_fibonacci607)(lagged_fibonacci1279)(lagged_fibonacci2281) \
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(lagged_fibonacci3217)(lagged_fibonacci4423)(lagged_fibonacci9689) \
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(lagged_fibonacci19937)(lagged_fibonacci23209)(lagged_fibonacci44497)
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#define MAKE_PYTHON_CLASS(r, _, rng) \
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buffered_uniform_01_class<boost::rng>(BOOST_PP_STRINGIZE(rng) "_01");
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BOOST_PP_SEQ_FOR_EACH(MAKE_PYTHON_CLASS, ~, RNG_CLASSES)
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#undef MAKE_PYTHON_CLASS
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#undef RNG_CLASSES
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class_<boost::uniform_int<> >("uniform_int", init<optional<int,int> >());
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class_<boost::bernoulli_distribution<> >("bernoulli_distribution", init<optional<double> >());
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class_<boost::geometric_distribution<> >("geometric_distribution", init<optional<double> >());
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class_<boost::triangle_distribution<> >("triangle_distribution", init<optional<double,double,double> >());
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class_<boost::exponential_distribution<> >("exponential_distribution", init<optional<double> >());
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class_<boost::normal_distribution<> >("normal_distribution", init<optional<double,double> >());
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class_<boost::lognormal_distribution<> >("lognormal_distribution", init<optional<double,double> >());
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variate_generator_class<boost::uniform_int<> >("uniform_int_variate");
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variate_generator_class<boost::bernoulli_distribution<> >("bernoulli_distribution_variate");
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variate_generator_class<boost::geometric_distribution<> >("geometric_distribution_variate");
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variate_generator_class<boost::triangle_distribution<> >("triangle_distribution_variate");
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variate_generator_class<boost::exponential_distribution<> >("exponential_distribution_variate");
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variate_generator_class<boost::normal_distribution<> >("normal_distribution_variate");
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variate_generator_class<boost::lognormal_distribution<> >("lognormal_distribution_variate");
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#define SPRNG_CLASSES \
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(cmrg)(lcg)(lcg64)(lfg)(mlfg)
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//(pmlcg)
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#define MAKE_PYTHON_CLASS(r, _, rng) \
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buffered_uniform_01_class<boost::random::sprng::rng>(BOOST_PP_STRINGIZE(rng) "_01") \
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.def(sprng_visitor());
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BOOST_PP_SEQ_FOR_EACH(MAKE_PYTHON_CLASS, ~, SPRNG_CLASSES)
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#undef MAKE_PYTHON_CLASS
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#undef SPRNG_CLASSES
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}
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