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Sprout/sprout/random/poisson_distribution.hpp
2015-06-19 17:46:34 +09:00

417 lines
18 KiB
C++

/*=============================================================================
Copyright (c) 2011-2015 Bolero MURAKAMI
https://github.com/bolero-MURAKAMI/Sprout
Distributed under the Boost Software License, Version 1.0. (See accompanying
file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
=============================================================================*/
#ifndef SPROUT_RANDOM_POISSON_DISTRIBUTION_HPP
#define SPROUT_RANDOM_POISSON_DISTRIBUTION_HPP
#include <istream>
#include <ostream>
#include <sprout/config.hpp>
#include <sprout/limits.hpp>
#include <sprout/cstdlib/abs.hpp>
#include <sprout/math/abs.hpp>
#include <sprout/math/log.hpp>
#include <sprout/math/floor.hpp>
#include <sprout/random/random_result.hpp>
#include <sprout/random/uniform_01.hpp>
#include <sprout/random/results.hpp>
#include <sprout/assert.hpp>
#ifdef SPROUT_WORKAROUND_NOT_TERMINATE_RECURSIVE_CONSTEXPR_FUNCTION_TEMPLATE
# include <sprout/workaround/recursive_function_template.hpp>
#endif
namespace sprout {
namespace random {
namespace detail {
# define SPROUT_POISSON_TABLE_DEF \
{{ \
0.0, \
0.0, \
0.69314718055994529, \
1.7917594692280550, \
3.1780538303479458, \
4.7874917427820458, \
6.5792512120101012, \
8.5251613610654147, \
10.604602902745251, \
12.801827480081469 \
}}
template<typename RealType>
struct poisson_table {
public:
typedef sprout::array<RealType, 10> table_type;
public:
SPROUT_STATIC_CONSTEXPR table_type table
SPROUT_STATIC_CONSTEXPR_DATA_MEMBER_INNER(SPROUT_POISSON_TABLE_DEF)
;
};
template<typename RealType>
SPROUT_CONSTEXPR_OR_CONST typename sprout::random::detail::poisson_table<RealType>::table_type
sprout::random::detail::poisson_table<RealType>::table
SPROUT_STATIC_CONSTEXPR_DATA_MEMBER_OUTER(SPROUT_POISSON_TABLE_DEF)
;
# undef SPROUT_POISSON_TABLE_DEF
} // namespace detail
//
// poisson_distribution
//
template<typename IntType = int, typename RealType = double>
class poisson_distribution {
public:
typedef RealType input_type;
typedef IntType result_type;
public:
//
// param_type
//
class param_type {
public:
typedef poisson_distribution distribution_type;
private:
RealType mean_;
public:
SPROUT_CONSTEXPR param_type()
: mean_(RealType(1))
{}
param_type(param_type const&) = default;
explicit SPROUT_CONSTEXPR param_type(RealType mean_arg)
: mean_((SPROUT_ASSERT(RealType(0) < mean_arg), mean_arg))
{}
SPROUT_CONSTEXPR RealType mean() const SPROUT_NOEXCEPT {
return mean_;
}
template<typename Elem, typename Traits>
friend SPROUT_NON_CONSTEXPR std::basic_istream<Elem, Traits>& operator>>(
std::basic_istream<Elem, Traits>& lhs,
param_type& rhs
)
{
RealType mean;
if (lhs >> mean) {
if (RealType(0) < mean) {
rhs.mean_ = mean;
} else {
lhs.setstate(std::ios_base::failbit);
}
}
return lhs;
}
template<typename Elem, typename Traits>
friend SPROUT_NON_CONSTEXPR std::basic_ostream<Elem, Traits>& operator<<(
std::basic_ostream<Elem, Traits>& lhs,
param_type const& rhs
)
{
return lhs << rhs.mean_;
}
friend SPROUT_CONSTEXPR bool operator==(param_type const& lhs, param_type const& rhs) SPROUT_NOEXCEPT {
return lhs.mean_ == rhs.mean_;
}
friend SPROUT_CONSTEXPR bool operator!=(param_type const& lhs, param_type const& rhs) SPROUT_NOEXCEPT {
return !(lhs == rhs);
}
};
struct ptrd_type {
public:
RealType v_r;
RealType a;
RealType b;
RealType smu;
RealType inv_alpha;
};
private:
static SPROUT_CONSTEXPR bool use_inversion_check(RealType mean) {
return mean < 10;
}
static SPROUT_CONSTEXPR ptrd_type init_ptrd_2(RealType smu, RealType b) {
return ptrd_type{
0.9277 - 3.6224 / (b - 2),
-0.059 + 0.02483 * b,
b,
smu,
1.1239 + 1.1328 / (b - 3.4)
};
}
static SPROUT_CONSTEXPR ptrd_type init_ptrd_1(RealType smu) {
return init_ptrd_2(smu, 0.931 + 2.53 * smu);
}
static SPROUT_CONSTEXPR ptrd_type init_ptrd(RealType mean) {
return use_inversion_check(mean) ? ptrd_type()
: init_ptrd_1(sprout::sqrt(mean))
;
}
static SPROUT_CONSTEXPR RealType init_exp_mean(RealType mean) {
return !use_inversion_check(mean) ? RealType()
: sprout::exp(-mean)
;
}
static SPROUT_CONSTEXPR RealType log_factorial(IntType k) {
return sprout::random::detail::poisson_table<RealType>::table[k];
}
static SPROUT_CONSTEXPR RealType log_sqrt_2pi() {
return 0.91893853320467267;
}
static SPROUT_CONSTEXPR RealType generate_us(RealType u) {
return 0.5 - sprout::abs(u);
}
private:
RealType mean_;
ptrd_type ptrd_;
RealType exp_mean_;
private:
SPROUT_CONSTEXPR bool use_inversion() const {
return use_inversion_check(mean_);
}
template<typename Engine>
SPROUT_CXX14_CONSTEXPR result_type do_invert(Engine& eng) const {
RealType u = sprout::random::uniform_01<RealType>()(eng);
IntType x = 0;
RealType p = exp_mean_;
while (u > p) {
u -= p;
++x;
p = p * mean_ / x;
}
return x;
}
template<typename Engine, typename Random>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> invert_2(Random const& rnd, RealType u, IntType x, RealType p) const {
return !(u > p) ? sprout::random::random_result<Engine, poisson_distribution>(x, sprout::random::next(rnd).engine(), *this)
: invert_2<Engine>(rnd, u - p, x + 1, p * mean_ / (x + 1))
;
}
template<typename Engine, typename Random>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> invert_1(Random const& rnd, IntType x, RealType p) const {
return invert_2<Engine>(rnd, sprout::random::result(rnd), x, p);
}
template<typename Engine>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> invert(Engine const& eng) const {
return invert_1<Engine>(sprout::random::uniform_01<RealType>()(eng), 0, exp_mean_);
}
template<typename Engine>
SPROUT_CXX14_CONSTEXPR result_type do_generate(Engine& eng) const {
for (; ; ) {
RealType v = sprout::random::uniform_01<RealType>()(eng);
if (v <= 0.86 * ptrd_.v_r) {
RealType u = v / ptrd_.v_r - 0.43;
return static_cast<IntType>(sprout::floor((2 * ptrd_.a / (0.5 - sprout::abs(u)) + ptrd_.b) * u + mean_ + 0.445));
}
RealType u = RealType();
if (v >= ptrd_.v_r) {
u = sprout::random::uniform_01<RealType>()(eng) - 0.5;
} else {
u = v / ptrd_.v_r - 0.93;
u = ((u < 0) ? -0.5 : 0.5) - u;
v = sprout::random::uniform_01<RealType>()(eng) * ptrd_.v_r;
}
RealType us = 0.5 - sprout::abs(u);
if (us < 0.013 && v > us) {
continue;
}
RealType k = sprout::floor((2 * ptrd_.a / us + ptrd_.b) * u + mean_ + 0.445);
v = v * ptrd_.inv_alpha / (ptrd_.a / (us * us) + ptrd_.b);
if ((k >= 10 && sprout::log(v * ptrd_.smu) <= (k + 0.5) * sprout::log(mean_ / k) - mean_ - log_sqrt_2pi() + k - (1 / 12. - (1 / 360. - 1 / (1260. * k * k)) / (k * k)) / k)
|| (k >= 0 && sprout::log(v) <= k * sprout::log(mean_) - mean_ - log_factorial(static_cast<IntType>(k)))
)
{
return static_cast<IntType>(k);
}
}
}
template<typename Engine, typename Random>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> generate_4(Random const& rnd, RealType u) const {
return sprout::random::random_result<Engine, poisson_distribution>(
static_cast<IntType>(sprout::floor((2 * ptrd_.a / (0.5 - sprout::abs(u)) + ptrd_.b) * u + mean_ + 0.445)),
sprout::random::next(rnd).engine(),
*this
);
}
#ifdef SPROUT_WORKAROUND_NOT_TERMINATE_RECURSIVE_CONSTEXPR_FUNCTION_TEMPLATE
template<typename Engine, int D, typename Random, SPROUT_RECURSIVE_FUNCTION_TEMPLATE_CONTINUE(D)>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> generate_3(Random const& rnd, RealType k, RealType v) const {
return (k >= 10 && sprout::log(v * ptrd_.smu) <= (k + 0.5) * sprout::log(mean_ / k) - mean_ - log_sqrt_2pi() + k - (1 / 12. - (1 / 360. - 1 / (1260. * k * k)) / (k * k)) / k)
|| (k >= 0 && sprout::log(v) <= k * sprout::log(mean_) - mean_ - log_factorial(static_cast<IntType>(k)))
? sprout::random::random_result<Engine, poisson_distribution>(static_cast<IntType>(k), sprout::random::next(rnd).engine(), *this)
: generate_1<Engine, D + 1>(rnd())
;
}
template<typename Engine, int D, typename Random, SPROUT_RECURSIVE_FUNCTION_TEMPLATE_BREAK(D)>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> generate_3(Random const&, RealType, RealType) const {
return sprout::throw_recursive_function_template_instantiation_exeeded();
}
template<typename Engine, int D, typename Random, SPROUT_RECURSIVE_FUNCTION_TEMPLATE_CONTINUE(D)>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> generate_2(Random const& rnd, RealType v, RealType u, RealType us) const {
return us < 0.013 && v > us ? generate_1<Engine, D + 1>(rnd())
: generate_3<Engine, D + 1>(
rnd,
sprout::floor((2 * ptrd_.a / us + ptrd_.b) * u + mean_ + 0.445),
v * ptrd_.inv_alpha / (ptrd_.a / (us * us) + ptrd_.b)
)
;
}
template<typename Engine, int D, typename Random, SPROUT_RECURSIVE_FUNCTION_TEMPLATE_BREAK(D)>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> generate_2(Random const&, RealType, RealType, RealType) const {
return sprout::throw_recursive_function_template_instantiation_exeeded();
}
template<typename Engine, int D, typename Random, SPROUT_RECURSIVE_FUNCTION_TEMPLATE_CONTINUE(D)>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> generate_1_3(Random const& rnd, RealType, RealType u) const {
return generate_2<Engine, D + 1>(rnd, sprout::random::result(rnd), ((u < 0) ? -0.5 : 0.5) - u, generate_us(((u < 0) ? -0.5 : 0.5) - u));
}
template<typename Engine, int D, typename Random, SPROUT_RECURSIVE_FUNCTION_TEMPLATE_BREAK(D)>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> generate_1_3(Random const&, RealType, RealType) const {
return sprout::throw_recursive_function_template_instantiation_exeeded();
}
template<typename Engine, int D, typename Random, SPROUT_RECURSIVE_FUNCTION_TEMPLATE_CONTINUE(D)>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> generate_1_2(Random const& rnd, RealType v) const {
return generate_2<Engine, D + 1>(rnd, v, sprout::random::result(rnd) - 0.5, generate_us(sprout::random::result(rnd) - 0.5));
}
template<typename Engine, int D, typename Random, SPROUT_RECURSIVE_FUNCTION_TEMPLATE_BREAK(D)>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> generate_1_2(Random const&, RealType) const {
return sprout::throw_recursive_function_template_instantiation_exeeded();
}
template<typename Engine, int D = 16, typename Random, SPROUT_RECURSIVE_FUNCTION_TEMPLATE_CONTINUE(D)>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> generate_1(Random const& rnd) const {
return sprout::random::result(rnd) <= 0.86 * ptrd_.v_r ? generate_4<Engine>(rnd, sprout::random::result(rnd) / ptrd_.v_r - 0.43)
: sprout::random::result(rnd) >= ptrd_.v_r
? generate_1_2<Engine, D + 1>(rnd(), sprout::random::result(rnd))
: generate_1_3<Engine, D + 1>(rnd(), sprout::random::result(rnd), sprout::random::result(rnd) / ptrd_.v_r - 0.93)
;
}
template<typename Engine, int D = 16, typename Random, SPROUT_RECURSIVE_FUNCTION_TEMPLATE_BREAK(D)>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> generate_1(Random const&) const {
return sprout::throw_recursive_function_template_instantiation_exeeded();
}
#else
template<typename Engine, typename Random>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> generate_3(Random const& rnd, RealType k, RealType v) const {
return (k >= 10 && sprout::log(v * ptrd_.smu) <= (k + 0.5) * sprout::log(mean_ / k) - mean_ - log_sqrt_2pi() + k - (1 / 12. - (1 / 360. - 1 / (1260. * k * k)) / (k * k)) / k)
|| (k >= 0 && sprout::log(v) <= k * sprout::log(mean_) - mean_ - log_factorial(static_cast<IntType>(k)))
? sprout::random::random_result<Engine, poisson_distribution>(static_cast<IntType>(k), sprout::random::next(rnd).engine(), *this)
: generate_1<Engine>(rnd())
;
}
template<typename Engine, typename Random>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> generate_2(Random const& rnd, RealType v, RealType u, RealType us) const {
return us < 0.013 && v > us ? generate_1<Engine>(rnd())
: generate_3<Engine>(
rnd,
sprout::floor((2 * ptrd_.a / us + ptrd_.b) * u + mean_ + 0.445),
v * ptrd_.inv_alpha / (ptrd_.a / (us * us) + ptrd_.b)
)
;
}
template<typename Engine, typename Random>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> generate_1_3(Random const& rnd, RealType v, RealType u) const {
return generate_2<Engine>(rnd, sprout::random::result(rnd), ((u < 0) ? -0.5 : 0.5) - u, generate_us(((u < 0) ? -0.5 : 0.5) - u));
}
template<typename Engine, typename Random>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> generate_1_2(Random const& rnd, RealType v) const {
return generate_2<Engine>(rnd, v, sprout::random::result(rnd) - 0.5, generate_us(sprout::random::result(rnd) - 0.5));
}
template<typename Engine, typename Random>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> generate_1(Random const& rnd) const {
return sprout::random::result(rnd) <= 0.86 * ptrd_.v_r ? generate_4<Engine>(rnd, sprout::random::result(rnd) / ptrd_.v_r - 0.43)
: sprout::random::result(rnd) >= ptrd_.v_r
? generate_1_2<Engine>(rnd(), sprout::random::result(rnd))
: generate_1_3<Engine>(rnd(), sprout::random::result(rnd), sprout::random::result(rnd) / ptrd_.v_r - 0.93)
;
}
#endif
template<typename Engine>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> generate(Engine const& eng) const {
return generate_1<Engine>(sprout::random::uniform_01<RealType>()(eng));
}
public:
SPROUT_CONSTEXPR poisson_distribution()
: mean_(RealType(1))
, ptrd_(init_ptrd(RealType(1)))
, exp_mean_(init_exp_mean(RealType(1)))
{}
poisson_distribution(poisson_distribution const&) = default;
explicit SPROUT_CONSTEXPR poisson_distribution(RealType mean_arg)
: mean_((SPROUT_ASSERT(RealType(0) < mean_arg), mean_arg))
, ptrd_(init_ptrd(mean_arg))
, exp_mean_(init_exp_mean(mean_arg))
{}
explicit SPROUT_CONSTEXPR poisson_distribution(param_type const& parm)
: mean_(parm.mean())
, ptrd_(init_ptrd(parm.mean()))
, exp_mean_(init_exp_mean(parm.mean()))
{}
SPROUT_CONSTEXPR result_type mean() const SPROUT_NOEXCEPT {
return mean_;
}
SPROUT_CONSTEXPR result_type min() const SPROUT_NOEXCEPT {
return 0;
}
SPROUT_CONSTEXPR result_type max() const SPROUT_NOEXCEPT {
return sprout::numeric_limits<result_type>::max();
}
SPROUT_CXX14_CONSTEXPR void reset() SPROUT_NOEXCEPT {}
SPROUT_CONSTEXPR param_type param() const SPROUT_NOEXCEPT {
return param_type(mean_);
}
SPROUT_CXX14_CONSTEXPR void param(param_type const& parm) {
mean_ = parm.mean();
ptrd_ = init_ptrd(mean_);
exp_mean_ = init_exp_mean(mean_);
}
template<typename Engine>
SPROUT_CXX14_CONSTEXPR result_type operator()(Engine& eng) const {
return use_inversion() ? do_invert(eng)
: do_generate(eng)
;
}
template<typename Engine>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> const operator()(Engine const& eng) const {
return use_inversion() ? invert(eng)
: generate(eng)
;
}
template<typename Engine>
SPROUT_CXX14_CONSTEXPR result_type operator()(Engine& eng, param_type const& parm) const {
return poisson_distribution(parm)(eng);
}
template<typename Engine>
SPROUT_CONSTEXPR sprout::random::random_result<Engine, poisson_distribution> const operator()(Engine const& eng, param_type const& parm) const {
return poisson_distribution(parm)(eng);
}
template<typename Elem, typename Traits>
friend SPROUT_NON_CONSTEXPR std::basic_istream<Elem, Traits>& operator>>(
std::basic_istream<Elem, Traits>& lhs,
poisson_distribution& rhs
)
{
param_type parm;
if (lhs >> parm) {
rhs.param(parm);
}
return lhs;
}
template<typename Elem, typename Traits>
friend SPROUT_NON_CONSTEXPR std::basic_ostream<Elem, Traits>& operator<<(
std::basic_ostream<Elem, Traits>& lhs,
poisson_distribution const& rhs
)
{
return lhs << rhs.param();
}
friend SPROUT_CONSTEXPR bool operator==(poisson_distribution const& lhs, poisson_distribution const& rhs) SPROUT_NOEXCEPT {
return lhs.param() == rhs.param();
}
friend SPROUT_CONSTEXPR bool operator!=(poisson_distribution const& lhs, poisson_distribution const& rhs) SPROUT_NOEXCEPT {
return !(lhs == rhs);
}
};
} // namespace random
using sprout::random::poisson_distribution;
} // namespace sprout
#endif // #ifndef SPROUT_RANDOM_POISSON_DISTRIBUTION_HPP