標準ライブラリヘッダ <random>

 

C++

言語

標準ライブラリヘッダ

フリースタンディング処理系とホスト処理系

名前付き要件

言語サポートライブラリ

コンセプトライブラリ (C++20)

診断ライブラリ

ユーティリティライブラリ

文字列ライブラリ

コンテナライブラリ

イテレータライブラリ

範囲ライブラリ (C++20)

アルゴリズムライブラリ

数値演算ライブラリ

ローカライゼーションライブラリ

入出力ライブラリ

ファイルシステムライブラリ (C++17)

正規表現ライブラリ (C++11)

アトミック操作ライブラリ (C++11)

スレッドサポートライブラリ (C++11)

技術仕様書

 

標準ライブラリヘッダ

言語サポート
<cstddef> <cstdlib> <version> <limits> <climits>	<cfloat> <cstdint> <new> <typeinfo>	<source_location> <exception> <initializer_list> <compare>	<coroutine> <csignal> <csetjmp> <cstdarg>
コンセプト
<concepts>
診断
<stdexcept>	<cassert>	<cerrno>	<system_error>
汎用ユーティリティ
<utility> <memory> <memory_resource> <scoped_allocator>	<bitset> <tuple> <optional> <any>	<variant> <type_traits> <ratio> <chrono>	<typeindex> <functional> <ctime>
文字列
<string> <string_view> <cstring>	<charconv> <format>	<cctype> <cwctype>	<cwchar> <cuchar>
ローカライゼーション
<locale>	<codecvt>	<clocale>
コンテナ
<span> <array> <vector>	<deque> <forward_list> <list>	<map> <set> <queue>	<unordered_map> <unordered_set> <stack>
イテレータ
<iterator>
範囲
<ranges>
アルゴリズム
<algorithm>	<execution>
数値演算
<complex> <random>	<valarray> <numeric>	<bit> <numbers>	<cfenv> <cmath>
入出力
<iosfwd> <ios> <iomanip> <streambuf>	<istream> <ostream> <iostream>	<sstream> <spanstream> <fstream> <syncstream>	<cstdio> <cinttypes> <strstream>
正規表現
<regex>
ファイルシステムサポート
<filesystem>
スレッドサポート
<thread> <atomic> <mutex>	<shared_mutex> <condition_variable> <future>	<stop_token> <semaphore>	<latch> <barrier>
C互換
<ciso646> <cstdalign>	<cstdbool> <ccomplex>	<ctgmath> <stdatomic.h>

 

このヘッダは擬似乱数生成ライブラリの一部です。

インクルード
<initializer_list> (C++11)	std::initializer_list クラステンプレート
コンセプト
一様ランダムビットジェネレータの要件
uniform_random_bit_generator (C++20)	型が一様ランダムビットジェネレータとして適格であることを指定します (コンセプト)
クラス
乱数エンジン
linear_congruential_engine (C++11)	線形合同法のアルゴリズムを実装します (クラステンプレート)
mersenne_twister_engine (C++11)	メルセンヌ・ツイスタのアルゴリズムを実装します (クラステンプレート)
subtract_with_carry_engine (C++11)	キャリー付き減算 (ラグ付きフィボナッチ法) のアルゴリズムを実装します (クラステンプレート)
乱数エンジンアダプタ
discard_block_engine (C++11)	乱数エンジンの出力をいくらか破棄します (クラステンプレート)
independent_bits_engine (C++11)	指定されたビット数のブロックに乱数の出力をパックします (クラステンプレート)
shuffle_order_engine (C++11)	乱数エンジンの出力を異なる順序に並び替えます (クラステンプレート)
定義済みのジェネレータ
minstd_rand0(C++11)	std::linear_congruential_engine<std::uint_fast32_t, 16807, 0, 2147483647> Lewis、 Goodman および Miller によって1969年に発見され、 Park と Miller によって1988年に「最低基準」として選定されたもの
minstd_rand(C++11)	std::linear_congruential_engine<std::uint_fast32_t, 48271, 0, 2147483647> Park、 Miller および Stockmeyer によって1993年に推奨された新たな「最低基準」
mt19937(C++11)	std::mersenne_twister_engine<std::uint_fast32_t, 32, 624, 397, 31, 0x9908b0df, 11, 0xffffffff, 7, 0x9d2c5680, 15, 0xefc60000, 18, 1812433253> 松本と西村による32ビットのメルセンヌ・ツイスタ (1998年)
mt19937_64(C++11)	std::mersenne_twister_engine<std::uint_fast64_t, 64, 312, 156, 31, 0xb5026f5aa96619e9, 29, 0x5555555555555555, 17, 0x71d67fffeda60000, 37, 0xfff7eee000000000, 43, 6364136223846793005> 松本と西村による64ビットのメルセンヌ・ツイスタ (2000年)
ranlux24_base(C++11)	std::subtract_with_carry_engine<std::uint_fast32_t, 24, 10, 24>
ranlux48_base(C++11)	std::subtract_with_carry_engine<std::uint_fast64_t, 48, 5, 12>
ranlux24(C++11)	std::discard_block_engine<std::ranlux24_base, 223, 23> Martin Lüscher と Fred James による24ビットの RANLUX ジェネレータ (1994年)
ranlux48(C++11)	std::discard_block_engine<std::ranlux48_base, 389, 11> Martin Lüscher と Fred James による48ビットの RANLUX ジェネレータ (1994年)
knuth_b(C++11)	std::shuffle_order_engine<std::minstd_rand0, 256>
default_random_engine(C++11)	処理系定義
非決定的な乱数
random_device (C++11)	ハードウェアエントロピーソースを使用する非決定的な乱数生成器 (クラス)
一様分布
uniform_int_distribution (C++11)	範囲内に一様に分布した整数値を生成します (クラステンプレート)
uniform_real_distribution (C++11)	範囲内に一様に分布した実数値を生成します (クラステンプレート)
ベルヌーイ分布
bernoulli_distribution (C++11)	ベルヌーイ分布に従った bool 値を生成します (クラス)
binomial_distribution (C++11)	二項分布に従った整数値を生成します (クラステンプレート)
negative_binomial_distribution (C++11)	負の二項分布に従った整数値を生成します (クラステンプレート)
geometric_distribution (C++11)	幾何分布に従った整数値を生成します (クラステンプレート)
ポアソン分布
poisson_distribution (C++11)	ポアソン分布に従った整数値を生成します (クラステンプレート)
exponential_distribution (C++11)	指数分布に従った実数値を生成します (クラステンプレート)
gamma_distribution (C++11)	ガンマ分布に従った実数値を生成します (クラステンプレート)
weibull_distribution (C++11)	ワイブル分布に従った実数値を生成します (クラステンプレート)
extreme_value_distribution (C++11)	極値分布に従った実数値を生成します (クラステンプレート)
正規分布
normal_distribution (C++11)	標準正規 (ガウス) 分布に従った実数値を生成します (クラステンプレート)
lognormal_distribution (C++11)	対数正規分布に従った実数値を生成します (クラステンプレート)
chi_squared_distribution (C++11)	カイ二乗分布に従った実数値を生成します (クラステンプレート)
cauchy_distribution (C++11)	コーシー分布に従った実数値を生成します (クラステンプレート)
fisher_f_distribution (C++11)	フィッシャーのF分布に従った実数値を生成します (クラステンプレート)
student_t_distribution (C++11)	スチューデントのt分布に従った実数値を生成します (クラステンプレート)
標本分布
discrete_distribution (C++11)	指定された離散分布に従ったランダムな整数を生成します (クラステンプレート)
piecewise_constant_distribution (C++11)	一定の区間に分布する実数値を生成します (クラステンプレート)
piecewise_linear_distribution (C++11)	定義された区間に分布する実数値を生成します (クラステンプレート)
ユーティリティ
seed_seq (C++11)	汎用のバイアス除去付きのスクランブルされたシードシーケンス生成器 (クラス)
関数
generate_canonical (C++11)	[0, 1) 内に一様に分布した、与えられた精度における実数値 (関数テンプレート)

概要

#include <initializer_list>

namespace std {
  // uniform random bit generator requirements
  template<class G>
    concept uniform_random_bit_generator = /* see description */;

  // class template linear_congruential_engine
  template<class UIntType, UIntType a, UIntType c, UIntType m>
    class linear_congruential_engine;

  // class template mersenne_twister_engine
  template<class UIntType, size_t w, size_t n, size_t m, size_t r,
           UIntType a, size_t u, UIntType d, size_t s,
           UIntType b, size_t t,
           UIntType c, size_t l, UIntType f>
    class mersenne_twister_engine;

  // class template subtract_with_carry_engine
  template<class UIntType, size_t w, size_t s, size_t r>
    class subtract_with_carry_engine;

  // class template discard_block_engine
  template<class Engine, size_t p, size_t r>
    class discard_block_engine;

  // class template independent_bits_engine
  template<class Engine, size_t w, class UIntType>
    class independent_bits_engine;

  // class template shuffle_order_engine
  template<class Engine, size_t k>
    class shuffle_order_engine;

  // engines and engine adaptors with predefined parameters
  using minstd_rand0  = /* see description */;
  using minstd_rand   = /* see description */;
  using mt19937       = /* see description */;
  using mt19937_64    = /* see description */;
  using ranlux24_base = /* see description */;
  using ranlux48_base = /* see description */;
  using ranlux24      = /* see description */;
  using ranlux48      = /* see description */;
  using knuth_b       = /* see description */;

  using default_random_engine = /* see description */;

  // class random_device
  class random_device;

  // class seed_seq
  class seed_seq;

  // function template generate_canonical
  template<class RealType, size_t bits, class URBG>
    RealType generate_canonical(URBG& g);

  // class template uniform_int_distribution
  template<class IntType = int>
    class uniform_int_distribution;

  // class template uniform_real_distribution
  template<class RealType = double>
    class uniform_real_distribution;

  // class bernoulli_distribution
  class bernoulli_distribution;

  // class template binomial_distribution
  template<class IntType = int>
    class binomial_distribution;

  // class template geometric_distribution
  template<class IntType = int>
    class geometric_distribution;

  // class template negative_binomial_distribution
  template<class IntType = int>
    class negative_binomial_distribution;

  // class template poisson_distribution
  template<class IntType = int>
    class poisson_distribution;

  // class template exponential_distribution
  template<class RealType = double>
    class exponential_distribution;

  // class template gamma_distribution
  template<class RealType = double>
    class gamma_distribution;

  // class template weibull_distribution
  template<class RealType = double>
    class weibull_distribution;

  // class template extreme_value_distribution
  template<class RealType = double>
    class extreme_value_distribution;

  // class template normal_distribution
  template<class RealType = double>
    class normal_distribution;

  // class template lognormal_distribution
  template<class RealType = double>
    class lognormal_distribution;

  // class template chi_squared_distribution
  template<class RealType = double>
    class chi_squared_distribution;

  // class template cauchy_distribution
  template<class RealType = double>
    class cauchy_distribution;

  // class template fisher_f_distribution
  template<class RealType = double>
    class fisher_f_distribution;

  // class template student_t_distribution
  template<class RealType = double>
    class student_t_distribution;

  // class template discrete_distribution
  template<class IntType = int>
    class discrete_distribution;

  // class template piecewise_constant_distribution
  template<class RealType = double>
    class piecewise_constant_distribution;

  // class template piecewise_linear_distribution
  template<class RealType = double>
    class piecewise_linear_distribution;
}

コンセプト uniform_random_bit_generator

namespace std {
  template<class G>
    concept uniform_random_bit_generator =
      invocable<G&> && unsigned_integral<invoke_result_t<G&>> &&
      requires {
        { G::min() } -> same_as<invoke_result_t<G&>>;
        { G::max() } -> same_as<invoke_result_t<G&>>;
        requires bool_constant<(G::min() < G::max())>::value;
      };
}

クラステンプレート std::linear_congruential_engine

namespace std {
  template<class UIntType, UIntType a, UIntType c, UIntType m>
    class linear_congruential_engine {
    public:
      // types
      using result_type = UIntType;

      // engine characteristics
      static constexpr result_type multiplier = a;
      static constexpr result_type increment = c;
      static constexpr result_type modulus = m;
      static constexpr result_type min() { return c == 0u ? 1u: 0u; }
      static constexpr result_type max() { return m - 1u; }
      static constexpr result_type default_seed = 1u;

      // constructors and seeding functions
      linear_congruential_engine() : linear_congruential_engine(default_seed) {}
      explicit linear_congruential_engine(result_type s);
      template<class Sseq> explicit linear_congruential_engine(Sseq& q);
      void seed(result_type s = default_seed);
      template<class Sseq> void seed(Sseq& q);

      // generating functions
      result_type operator()();
      void discard(unsigned long long z);
    };
}

クラステンプレート std::mersenne_twister_engine

namespace std {
  template<class UIntType, size_t w, size_t n, size_t m, size_t r,
           UIntType a, size_t u, UIntType d, size_t s,
           UIntType b, size_t t,
           UIntType c, size_t l, UIntType f>
    class mersenne_twister_engine {
    public:
      // types
      using result_type = UIntType;

      // engine characteristics
      static constexpr size_t word_size = w;
      static constexpr size_t state_size = n;
      static constexpr size_t shift_size = m;
      static constexpr size_t mask_bits = r;
      static constexpr UIntType xor_mask = a;
      static constexpr size_t tempering_u = u;
      static constexpr UIntType tempering_d = d;
      static constexpr size_t tempering_s = s;
      static constexpr UIntType tempering_b = b;
      static constexpr size_t tempering_t = t;
      static constexpr UIntType tempering_c = c;
      static constexpr size_t tempering_l = l;
      static constexpr UIntType initialization_multiplier = f;
      static constexpr result_type min() { return 0; }
      static constexpr result_type max() { return /* pow(2, w) - 1 */; }
      static constexpr result_type default_seed = 5489u;

      // constructors and seeding functions
      mersenne_twister_engine() : mersenne_twister_engine(default_seed) {}
      explicit mersenne_twister_engine(result_type value);
      template<class Sseq> explicit mersenne_twister_engine(Sseq& q);
      void seed(result_type value = default_seed);
      template<class Sseq> void seed(Sseq& q);

      // generating functions
      result_type operator()();
      void discard(unsigned long long z);
    };
}

クラステンプレート std::subtract_with_carry_engine

namespace std {
  template<class UIntType, size_t w, size_t s, size_t r>
    class subtract_with_carry_engine {
    public:
      // types
      using result_type = UIntType;

      // engine characteristics
      static constexpr size_t word_size = w;
      static constexpr size_t short_lag = s;
      static constexpr size_t long_lag = r;
      static constexpr result_type min() { return 0; }
      static constexpr result_type max() { return /* pow(2, w) - 1 */; }
      static constexpr result_type default_seed = 19780503u;

      // constructors and seeding functions
      subtract_with_carry_engine() : subtract_with_carry_engine(default_seed) {}
      explicit subtract_with_carry_engine(result_type value);
      template<class Sseq> explicit subtract_with_carry_engine(Sseq& q);
      void seed(result_type value = default_seed);
      template<class Sseq> void seed(Sseq& q);

      // generating functions
      result_type operator()();
      void discard(unsigned long long z);
    };
}

クラステンプレート std::discard_block_engine

namespace std {
  template<class Engine, size_t p, size_t r>
    class discard_block_engine {
    public:
      // types
      using result_type = typename Engine::result_type;

      // engine characteristics
      static constexpr size_t block_size = p;
      static constexpr size_t used_block = r;
      static constexpr result_type min() { return Engine::min(); }
      static constexpr result_type max() { return Engine::max(); }

      // constructors and seeding functions
      discard_block_engine();
      explicit discard_block_engine(const Engine& e);
      explicit discard_block_engine(Engine&& e);
      explicit discard_block_engine(result_type s);
      template<class Sseq> explicit discard_block_engine(Sseq& q);
      void seed();
      void seed(result_type s);
      template<class Sseq> void seed(Sseq& q);

      // generating functions
      result_type operator()();
      void discard(unsigned long long z);

      // property functions
      const Engine& base() const noexcept { return e; };

    private:
      Engine e;   // exposition only
      int n;      // exposition only
    };
}

クラステンプレート std::independent_bits_engine

namespace std {
  template<class Engine, size_t w, class UIntType>
    class independent_bits_engine {
    public:
      // types
      using result_type = UIntType;

      // engine characteristics
      static constexpr result_type min() { return 0; }
      static constexpr result_type max() { return /* pow(2, w) - 1 */; }

      // constructors and seeding functions
      independent_bits_engine();
      explicit independent_bits_engine(const Engine& e);
      explicit independent_bits_engine(Engine&& e);
      explicit independent_bits_engine(result_type s);
      template<class Sseq> explicit independent_bits_engine(Sseq& q);
      void seed();
      void seed(result_type s);
      template<class Sseq> void seed(Sseq& q);

      // generating functions
      result_type operator()();
      void discard(unsigned long long z);

      // property functions
      const Engine& base() const noexcept { return e; };

    private:
      Engine e;   // exposition only
    };
}

クラステンプレート std::shuffle_order_engine

namespace std {
  template<class Engine, size_t k>
    class shuffle_order_engine {
    public:
      // types
      using result_type = typename Engine::result_type;

      // engine characteristics
      static constexpr size_t table_size = k;
      static constexpr result_type min() { return Engine::min(); }
      static constexpr result_type max() { return Engine::max(); }

      // constructors and seeding functions
      shuffle_order_engine();
      explicit shuffle_order_engine(const Engine& e);
      explicit shuffle_order_engine(Engine&& e);
      explicit shuffle_order_engine(result_type s);
      template<class Sseq> explicit shuffle_order_engine(Sseq& q);
      void seed();
      void seed(result_type s);
      template<class Sseq> void seed(Sseq& q);

      // generating functions
      result_type operator()();
      void discard(unsigned long long z);

      // property functions
      const Engine& base() const noexcept { return e; };

    private:
      Engine e;           // exposition only
      result_type V[k];   // exposition only
      result_type Y;      // exposition only
    };
}

定義済みのパラメータを持つエンジンおよびエンジンアダプタ

namespace std {
  using minstd_rand0 =
        linear_congruential_engine<uint_fast32_t, 16'807, 0, 2'147'483'647>;
  using minstd_rand =
        linear_congruential_engine<uint_fast32_t, 48'271, 0, 2'147'483'647>;
  using mt19937 =
        mersenne_twister_engine<uint_fast32_t, 32, 624, 397, 31,
         0x9908'b0df, 11, 0xffff'ffff, 7, 0x9d2c'5680, 15, 0xefc6'0000, 18, 1'812'433'253>;
  using mt19937_64 =
        mersenne_twister_engine<uint_fast64_t, 64, 312, 156, 31,
         0xb502'6f5a'a966'19e9, 29, 0x5555'5555'5555'5555, 17,
         0x71d6'7fff'eda6'0000, 37, 0xfff7'eee0'0000'0000, 43, 6'364'136'223'846'793'005>;
  using ranlux24_base =
        subtract_with_carry_engine<uint_fast32_t, 24, 10, 24>;
  using ranlux48_base =
        subtract_with_carry_engine<uint_fast64_t, 48, 5, 12>;
  using ranlux24 = discard_block_engine<ranlux24_base, 223, 23>;
  using ranlux48 = discard_block_engine<ranlux48_base, 389, 11>;
  using knuth_b = shuffle_order_engine<minstd_rand0,256>;
  using default_random_engine = /* implementation-defined */;
}

クラス std::random_device

namespace std {
  class random_device {
  public:
    // types
    using result_type = unsigned int;

    // generator characteristics
    static constexpr result_type min() { return numeric_limits<result_type>::min(); }
    static constexpr result_type max() { return numeric_limits<result_type>::max(); }

    // constructors
    random_device() : random_device(/* implementation-defined */) {}
    explicit random_device(const string& token);

    // generating functions
    result_type operator()();

    // property functions
    double entropy() const noexcept;

    // no copy functions
    random_device(const random_device&) = delete;
    void operator=(const random_device&) = delete;
  };
}

クラス std::seed_seq

namespace std {
  class seed_seq {
  public:
    // types
    using result_type = uint_least32_t;

    // constructors
    seed_seq();
    template<class T>
      seed_seq(initializer_list<T> il);
    template<class InputIt>
      seed_seq(InputIt begin, InputIt end);

    // generating functions
    template<class RandomAccessIt>
      void generate(RandomAccessIt begin, RandomAccessIt end);

    // property functions
    size_t size() const noexcept;
    template<class OutputIt>
      void param(OutputIt dest) const;

    // no copy functions
    seed_seq(const seed_seq&) = delete;
    void operator=(const seed_seq&) = delete;

  private:
    vector<result_type> v;        // exposition only
  };
}

クラステンプレート std::uniform_int_distribution

namespace std {
  template<class IntType = int>
    class uniform_int_distribution {
    public:
      // types
      using result_type = IntType;
      using param_type  = /* unspecified */;

      // constructors and reset functions
      uniform_int_distribution() : uniform_int_distribution(0) {}
      explicit uniform_int_distribution(IntType a,
                                        IntType b = numeric_limits<IntType>::max());
      explicit uniform_int_distribution(const param_type& parm);
      void reset();

      // generating functions
      template<class URBG>
        result_type operator()(URBG& g);
      template<class URBG>
        result_type operator()(URBG& g, const param_type& parm);

      // property functions
      result_type a() const;
      result_type b() const;
      param_type param() const;
      void param(const param_type& parm);
      result_type min() const;
      result_type max() const;
    };
}

クラステンプレート std::uniform_real_distribution

namespace std {
  template<class RealType = double>
    class uniform_real_distribution {
    public:
      // types
      using result_type = RealType;
      using param_type  = /* unspecified */;

      // constructors and reset functions
      uniform_real_distribution() : uniform_real_distribution(0.0) {}
      explicit uniform_real_distribution(RealType a, RealType b = 1.0);
      explicit uniform_real_distribution(const param_type& parm);
      void reset();

      // generating functions
      template<class URBG>
        result_type operator()(URBG& g);
      template<class URBG>
        result_type operator()(URBG& g, const param_type& parm);

      // property functions
      result_type a() const;
      result_type b() const;
      param_type param() const;
      void param(const param_type& parm);
      result_type min() const;
      result_type max() const;
    };
}

クラス std::bernoulli_distribution

namespace std {
  class bernoulli_distribution {
  public:
    // types
    using result_type = bool;
    using param_type  = /* unspecified */;

    // constructors and reset functions
    bernoulli_distribution() : bernoulli_distribution(0.5) {}
    explicit bernoulli_distribution(double p);
    explicit bernoulli_distribution(const param_type& parm);
    void reset();

    // generating functions
    template<class URBG>
      result_type operator()(URBG& g);
    template<class URBG>
      result_type operator()(URBG& g, const param_type& parm);

    // property functions
    double p() const;
    param_type param() const;
    void param(const param_type& parm);
    result_type min() const;
    result_type max() const;
  };
}

クラステンプレート std::binomial_distribution

namespace std {
  template<class IntType = int>
    class binomial_distribution {
    public:
      // types
      using result_type = IntType;
      using param_type  = /* unspecified */;

      // constructors and reset functions
      binomial_distribution() : binomial_distribution(1) {}
      explicit binomial_distribution(IntType t, double p = 0.5);
      explicit binomial_distribution(const param_type& parm);
      void reset();

      // generating functions
      template<class URBG>
        result_type operator()(URBG& g);
      template<class URBG>
        result_type operator()(URBG& g, const param_type& parm);

      // property functions
      IntType t() const;
      double p() const;
      param_type param() const;
      void param(const param_type& parm);
      result_type min() const;
      result_type max() const;
    };
}

クラステンプレート std::geometric_distribution

namespace std {
  template<class IntType = int>
    class geometric_distribution {
    public:
      // types
      using result_type = IntType;
      using param_type  = /* unspecified */;

      // constructors and reset functions
      geometric_distribution() : geometric_distribution(0.5) {}
      explicit geometric_distribution(double p);
      explicit geometric_distribution(const param_type& parm);
      void reset();

      // generating functions
      template<class URBG>
        result_type operator()(URBG& g);
      template<class URBG>
        result_type operator()(URBG& g, const param_type& parm);

      // property functions
      double p() const;
      param_type param() const;
      void param(const param_type& parm);
      result_type min() const;
      result_type max() const;
    };
}

クラステンプレート std::negative_binomial_distribution

namespace std {
  template<class IntType = int>
    class negative_binomial_distribution {
    public:
      // types
      using result_type = IntType;
      using param_type  = /* unspecified */;

      // constructor and reset functions
      negative_binomial_distribution() : negative_binomial_distribution(1) {}
      explicit negative_binomial_distribution(IntType k, double p = 0.5);
      explicit negative_binomial_distribution(const param_type& parm);
      void reset();

      // generating functions
      template<class URBG>
        result_type operator()(URBG& g);
      template<class URBG>
        result_type operator()(URBG& g, const param_type& parm);

      // property functions
      IntType k() const;
      double p() const;
      param_type param() const;
      void param(const param_type& parm);
      result_type min() const;
      result_type max() const;
    };
}

クラステンプレート std::poisson_distribution

namespace std {
  template<class IntType = int>
    class poisson_distribution {
    public:
      // types
      using result_type = IntType;
      using param_type  = /* unspecified */;

      // constructors and reset functions
      poisson_distribution() : poisson_distribution(1.0) {}
      explicit poisson_distribution(double mean);
      explicit poisson_distribution(const param_type& parm);
      void reset();

      // generating functions
      template<class URBG>
        result_type operator()(URBG& g);
      template<class URBG>
        result_type operator()(URBG& g, const param_type& parm);

      // property functions
      double mean() const;
      param_type param() const;
      void param(const param_type& parm);
      result_type min() const;
      result_type max() const;
    };
}

クラステンプレート std::exponential_distribution

namespace std {
  template<class RealType = double>
    class exponential_distribution {
    public:
      // types
      using result_type = RealType;
      using param_type  = /* unspecified */;

      // constructors and reset functions
      exponential_distribution() : exponential_distribution(1.0) {}
      explicit exponential_distribution(RealType lambda);
      explicit exponential_distribution(const param_type& parm);
      void reset();

      // generating functions
      template<class URBG>
        result_type operator()(URBG& g);
      template<class URBG>
        result_type operator()(URBG& g, const param_type& parm);

      // property functions
      RealType lambda() const;
      param_type param() const;
      void param(const param_type& parm);
      result_type min() const;
      result_type max() const;
  };
}

クラステンプレート std::gamma_distribution

namespace std {
  template<class RealType = double>
    class gamma_distribution {
    public:
      // types
      using result_type = RealType;
      using param_type  = /* unspecified */;

      // constructors and reset functions
      gamma_distribution() : gamma_distribution(1.0) {}
      explicit gamma_distribution(RealType alpha, RealType beta = 1.0);
      explicit gamma_distribution(const param_type& parm);
      void reset();

      // generating functions
      template<class URBG>
        result_type operator()(URBG& g);
      template<class URBG>
        result_type operator()(URBG& g, const param_type& parm);

      // property functions
      RealType alpha() const;
      RealType beta() const;
      param_type param() const;
      void param(const param_type& parm);
      result_type min() const;
      result_type max() const;
    };
}

クラステンプレート std::weibull_distribution

namespace std {
  template<class RealType = double>
    class weibull_distribution {
    public:
      // types
      using result_type = RealType;
      using param_type  = /* unspecified */;

      // constructor and reset functions
      weibull_distribution() : weibull_distribution(1.0) {}
      explicit weibull_distribution(RealType a, RealType b = 1.0);
      explicit weibull_distribution(const param_type& parm);
      void reset();

      // generating functions
      template<class URBG>
        result_type operator()(URBG& g);
      template<class URBG>
        result_type operator()(URBG& g, const param_type& parm);

      // property functions
      RealType a() const;
      RealType b() const;
      param_type param() const;
      void param(const param_type& parm);
      result_type min() const;
      result_type max() const;
    };
}

クラステンプレート std::extreme_value_distribution

namespace std {
  template<class RealType = double>
    class extreme_value_distribution {
    public:
      // types
      using result_type = RealType;
      using param_type  = /* unspecified */;

      // constructor and reset functions
      extreme_value_distribution() : extreme_value_distribution(0.0) {}
      explicit extreme_value_distribution(RealType a, RealType b = 1.0);
      explicit extreme_value_distribution(const param_type& parm);
      void reset();

      // generating functions
      template<class URBG>
        result_type operator()(URBG& g);
      template<class URBG>
        result_type operator()(URBG& g, const param_type& parm);

      // property functions
      RealType a() const;
      RealType b() const;
      param_type param() const;
      void param(const param_type& parm);
      result_type min() const;
      result_type max() const;
    };
}

クラステンプレート std::normal_distribution

namespace std {
  template<class RealType = double>
    class normal_distribution {
    public:
      // types
      using result_type = RealType;
      using param_type  = /* unspecified */;

      // constructors and reset functions
      normal_distribution() : normal_distribution(0.0) {}
      explicit normal_distribution(RealType mean, RealType stddev = 1.0);
      explicit normal_distribution(const param_type& parm);
      void reset();

      // generating functions
      template<class URBG>
        result_type operator()(URBG& g);
      template<class URBG>
        result_type operator()(URBG& g, const param_type& parm);

      // property functions
      RealType mean() const;
      RealType stddev() const;
      param_type param() const;
      void param(const param_type& parm);
      result_type min() const;
      result_type max() const;
    };
}

クラステンプレート std::lognormal_distribution

namespace std {
  template<class RealType = double>
    class lognormal_distribution {
    public:
      // types
      using result_type = RealType;
      using param_type  = /* unspecified */;

      // constructor and reset functions
      lognormal_distribution() : lognormal_distribution(0.0) {}
      explicit lognormal_distribution(RealType m, RealType s = 1.0);
      explicit lognormal_distribution(const param_type& parm);
      void reset();

      // generating functions
      template<class URBG>
        result_type operator()(URBG& g);
      template<class URBG>
        result_type operator()(URBG& g, const param_type& parm);

      // property functions
      RealType m() const;
      RealType s() const;
      param_type param() const;
      void param(const param_type& parm);
      result_type min() const;
      result_type max() const;
    };
}

クラステンプレート std::chi_squared_distribution

namespace std {
  template<class RealType = double>
    class chi_squared_distribution {
    public:
      // types
      using result_type = RealType;
      using param_type  = /* unspecified */;

      // constructor and reset functions
      chi_squared_distribution() : chi_squared_distribution(1.0) {}
      explicit chi_squared_distribution(RealType n);
      explicit chi_squared_distribution(const param_type& parm);
      void reset();

      // generating functions
      template<class URBG>
        result_type operator()(URBG& g);
      template<class URBG>
        result_type operator()(URBG& g, const param_type& parm);

      // property functions
      RealType n() const;
      param_type param() const;
      void param(const param_type& parm);
      result_type min() const;
      result_type max() const;
    };
}

クラステンプレート std::cauchy_distribution

namespace std {
  template<class RealType = double>
    class cauchy_distribution {
    public:
      // types
      using result_type = RealType;
      using param_type  = /* unspecified */;

      // constructor and reset functions
      cauchy_distribution() : cauchy_distribution(0.0) {}
      explicit cauchy_distribution(RealType a, RealType b = 1.0);
      explicit cauchy_distribution(const param_type& parm);
      void reset();

      // generating functions
      template<class URBG>
        result_type operator()(URBG& g);
      template<class URBG>
        result_type operator()(URBG& g, const param_type& parm);

      // property functions
      RealType a() const;
      RealType b() const;
      param_type param() const;
      void param(const param_type& parm);
      result_type min() const;
      result_type max() const;
    };

クラステンプレート std::fisher_f_distribution

namespace std {
  template<class RealType = double>
    class fisher_f_distribution {
    public:
      // types
      using result_type = RealType;
      using param_type  = /* unspecified */;

      // constructor and reset functions
      fisher_f_distribution() : fisher_f_distribution(1.0) {}
      explicit fisher_f_distribution(RealType m, RealType n = 1.0);
      explicit fisher_f_distribution(const param_type& parm);
      void reset();

      // generating functions
      template<class URBG>
        result_type operator()(URBG& g);
      template<class URBG>
        result_type operator()(URBG& g, const param_type& parm);

      // property functions
      RealType m() const;
      RealType n() const;
      param_type param() const;
      void param(const param_type& parm);
      result_type min() const;
      result_type max() const;
    };
}

クラステンプレート std::student_t_distribution

namespace std {
  template<class RealType = double>
    class student_t_distribution {
    public:
      // types
      using result_type = RealType;
      using param_type  = /* unspecified */;

      // constructor and reset functions
      student_t_distribution() : student_t_distribution(1.0) {}
      explicit student_t_distribution(RealType n);
      explicit student_t_distribution(const param_type& parm);
      void reset();

      // generating functions
      template<class URBG>
        result_type operator()(URBG& g);
      template<class URBG>
        result_type operator()(URBG& g, const param_type& parm);

      // property functions
      RealType n() const;
      param_type param() const;
      void param(const param_type& parm);
      result_type min() const;
      result_type max() const;
    };
}

クラステンプレート std::discrete_distribution

namespace std {
  template<class IntType = int>
    class discrete_distribution {
    public:
      // types
      using result_type = IntType;
      using param_type  = /* unspecified */;

      // constructor and reset functions
      discrete_distribution();
      template<class InputIt>
        discrete_distribution(InputIt firstW, InputIt lastW);
      discrete_distribution(initializer_list<double> wl);
      template<class UnaryOperation>
        discrete_distribution(size_t nw, double xmin, double xmax, UnaryOperation fw);
      explicit discrete_distribution(const param_type& parm);
      void reset();

      // generating functions
      template<class URBG>
        result_type operator()(URBG& g);
      template<class URBG>
        result_type operator()(URBG& g, const param_type& parm);

      // property functions
      vector<double> probabilities() const;
      param_type param() const;
      void param(const param_type& parm);
      result_type min() const;
      result_type max() const;
    };
}

クラステンプレート std::piecewise_constant_distribution

namespace std {
   template<class RealType = double>
    class piecewise_constant_distribution {
    public:
      // types
      using result_type = RealType;
      using param_type  = /* unspecified */;

      // constructor and reset functions
      piecewise_constant_distribution();
      template<class InputItB, class InputItW>
        piecewise_constant_distribution(InputItB firstB, InputItB lastB, InputItW firstW);
      template<class UnaryOperation>
        piecewise_constant_distribution(initializer_list<RealType> bl, UnaryOperation fw);
      template<class UnaryOperation>
        piecewise_constant_distribution(size_t nw, RealType xmin, RealType xmax,
                                        UnaryOperation fw);
      explicit piecewise_constant_distribution(const param_type& parm);
      void reset();

      // generating functions
      template<class URBG>
        result_type operator()(URBG& g);
      template<class URBG>
        result_type operator()(URBG& g, const param_type& parm);

      // property functions
      vector<result_type> intervals() const;
      vector<result_type> densities() const;
      param_type param() const;
      void param(const param_type& parm);
      result_type min() const;
      result_type max() const;
    };
}

クラステンプレート std::piecewise_linear_distribution

namespace std {
  template<class RealType = double>
    class piecewise_linear_distribution {
    public:
      // types
      using result_type = RealType;
      using param_type  = /* unspecified */;

      // constructor and reset functions
      piecewise_linear_distribution();
      template<class InputItB, class InputItW>
        piecewise_linear_distribution(InputItB firstB, InputItB lastB, InputItW firstW);
      template<class UnaryOperation>
        piecewise_linear_distribution(initializer_list<RealType> bl, UnaryOperation fw);
      template<class UnaryOperation>
        piecewise_linear_distribution(size_t nw, RealType xmin, RealType xmax,
                                      UnaryOperation fw);
      explicit piecewise_linear_distribution(const param_type& parm);
      void reset();

      // generating functions
      template<class URBG>
        result_type operator()(URBG& g);
      template<class URBG>
        result_type operator()(URBG& g, const param_type& parm);

      // property functions
      vector<result_type> intervals() const;
      vector<result_type> densities() const;
      param_type param() const;
      void param(const param_type& parm);
      result_type min() const;
      result_type max() const;
    };
}