--- /dev/null
+// random number generation -*- C++ -*-
+
+// Copyright (C) 2009-2012 Free Software Foundation, Inc.
+//
+// This file is part of the GNU ISO C++ Library. This library is free
+// software; you can redistribute it and/or modify it under the
+// terms of the GNU General Public License as published by the
+// Free Software Foundation; either version 3, or (at your option)
+// any later version.
+
+// This library is distributed in the hope that it will be useful,
+// but WITHOUT ANY WARRANTY; without even the implied warranty of
+// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+// GNU General Public License for more details.
+
+// Under Section 7 of GPL version 3, you are granted additional
+// permissions described in the GCC Runtime Library Exception, version
+// 3.1, as published by the Free Software Foundation.
+
+// You should have received a copy of the GNU General Public License and
+// a copy of the GCC Runtime Library Exception along with this program;
+// see the files COPYING3 and COPYING.RUNTIME respectively. If not, see
+// <http://www.gnu.org/licenses/>.
+
+/**
+ * @file bits/random.h
+ * This is an internal header file, included by other library headers.
+ * Do not attempt to use it directly. @headername{random}
+ */
+
+#ifndef _RANDOM_H
+#define _RANDOM_H 1
+
+#include <vector>
+
+namespace std _GLIBCXX_VISIBILITY(default)
+{
+_GLIBCXX_BEGIN_NAMESPACE_VERSION
+
+ // [26.4] Random number generation
+
+ /**
+ * @defgroup random Random Number Generation
+ * @ingroup numerics
+ *
+ * A facility for generating random numbers on selected distributions.
+ * @{
+ */
+
+ /**
+ * @brief A function template for converting the output of a (integral)
+ * uniform random number generator to a floatng point result in the range
+ * [0-1).
+ */
+ template<typename _RealType, size_t __bits,
+ typename _UniformRandomNumberGenerator>
+ _RealType
+ generate_canonical(_UniformRandomNumberGenerator& __g);
+
+_GLIBCXX_END_NAMESPACE_VERSION
+
+ /*
+ * Implementation-space details.
+ */
+ namespace __detail
+ {
+ _GLIBCXX_BEGIN_NAMESPACE_VERSION
+
+ template<typename _UIntType, size_t __w,
+ bool = __w < static_cast<size_t>
+ (std::numeric_limits<_UIntType>::digits)>
+ struct _Shift
+ { static const _UIntType __value = 0; };
+
+ template<typename _UIntType, size_t __w>
+ struct _Shift<_UIntType, __w, true>
+ { static const _UIntType __value = _UIntType(1) << __w; };
+
+ template<typename _Tp, _Tp __m, _Tp __a, _Tp __c, bool>
+ struct _Mod;
+
+ // Dispatch based on modulus value to prevent divide-by-zero compile-time
+ // errors when m == 0.
+ template<typename _Tp, _Tp __m, _Tp __a = 1, _Tp __c = 0>
+ inline _Tp
+ __mod(_Tp __x)
+ { return _Mod<_Tp, __m, __a, __c, __m == 0>::__calc(__x); }
+
+ /*
+ * An adaptor class for converting the output of any Generator into
+ * the input for a specific Distribution.
+ */
+ template<typename _Engine, typename _DInputType>
+ struct _Adaptor
+ {
+
+ public:
+ _Adaptor(_Engine& __g)
+ : _M_g(__g) { }
+
+ _DInputType
+ min() const
+ { return _DInputType(0); }
+
+ _DInputType
+ max() const
+ { return _DInputType(1); }
+
+ /*
+ * Converts a value generated by the adapted random number generator
+ * into a value in the input domain for the dependent random number
+ * distribution.
+ */
+ _DInputType
+ operator()()
+ {
+ return std::generate_canonical<_DInputType,
+ std::numeric_limits<_DInputType>::digits,
+ _Engine>(_M_g);
+ }
+
+ private:
+ _Engine& _M_g;
+ };
+
+ _GLIBCXX_END_NAMESPACE_VERSION
+ } // namespace __detail
+
+_GLIBCXX_BEGIN_NAMESPACE_VERSION
+
+ /**
+ * @addtogroup random_generators Random Number Generators
+ * @ingroup random
+ *
+ * These classes define objects which provide random or pseudorandom
+ * numbers, either from a discrete or a continuous interval. The
+ * random number generator supplied as a part of this library are
+ * all uniform random number generators which provide a sequence of
+ * random number uniformly distributed over their range.
+ *
+ * A number generator is a function object with an operator() that
+ * takes zero arguments and returns a number.
+ *
+ * A compliant random number generator must satisfy the following
+ * requirements. <table border=1 cellpadding=10 cellspacing=0>
+ * <caption align=top>Random Number Generator Requirements</caption>
+ * <tr><td>To be documented.</td></tr> </table>
+ *
+ * @{
+ */
+
+ /**
+ * @brief A model of a linear congruential random number generator.
+ *
+ * A random number generator that produces pseudorandom numbers via
+ * linear function:
+ * @f[
+ * x_{i+1}\leftarrow(ax_{i} + c) \bmod m
+ * @f]
+ *
+ * The template parameter @p _UIntType must be an unsigned integral type
+ * large enough to store values up to (__m-1). If the template parameter
+ * @p __m is 0, the modulus @p __m used is
+ * std::numeric_limits<_UIntType>::max() plus 1. Otherwise, the template
+ * parameters @p __a and @p __c must be less than @p __m.
+ *
+ * The size of the state is @f$1@f$.
+ */
+ template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
+ class linear_congruential_engine
+ {
+ static_assert(std::is_unsigned<_UIntType>::value, "template argument "
+ "substituting _UIntType not an unsigned integral type");
+ static_assert(__m == 0u || (__a < __m && __c < __m),
+ "template argument substituting __m out of bounds");
+
+ // XXX FIXME:
+ // _Mod::__calc should handle correctly __m % __a >= __m / __a too.
+ static_assert(__m % __a < __m / __a,
+ "sorry, not implemented yet: try a smaller 'a' constant");
+
+ public:
+ /** The type of the generated random value. */
+ typedef _UIntType result_type;
+
+ /** The multiplier. */
+ static constexpr result_type multiplier = __a;
+ /** An increment. */
+ static constexpr result_type increment = __c;
+ /** The modulus. */
+ static constexpr result_type modulus = __m;
+ static constexpr result_type default_seed = 1u;
+
+ /**
+ * @brief Constructs a %linear_congruential_engine random number
+ * generator engine with seed @p __s. The default seed value
+ * is 1.
+ *
+ * @param __s The initial seed value.
+ */
+ explicit
+ linear_congruential_engine(result_type __s = default_seed)
+ { seed(__s); }
+
+ /**
+ * @brief Constructs a %linear_congruential_engine random number
+ * generator engine seeded from the seed sequence @p __q.
+ *
+ * @param __q the seed sequence.
+ */
+ template<typename _Sseq, typename = typename
+ std::enable_if<!std::is_same<_Sseq, linear_congruential_engine>::value>
+ ::type>
+ explicit
+ linear_congruential_engine(_Sseq& __q)
+ { seed(__q); }
+
+ /**
+ * @brief Reseeds the %linear_congruential_engine random number generator
+ * engine sequence to the seed @p __s.
+ *
+ * @param __s The new seed.
+ */
+ void
+ seed(result_type __s = default_seed);
+
+ /**
+ * @brief Reseeds the %linear_congruential_engine random number generator
+ * engine
+ * sequence using values from the seed sequence @p __q.
+ *
+ * @param __q the seed sequence.
+ */
+ template<typename _Sseq>
+ typename std::enable_if<std::is_class<_Sseq>::value>::type
+ seed(_Sseq& __q);
+
+ /**
+ * @brief Gets the smallest possible value in the output range.
+ *
+ * The minimum depends on the @p __c parameter: if it is zero, the
+ * minimum generated must be > 0, otherwise 0 is allowed.
+ */
+ static constexpr result_type
+ min()
+ { return __c == 0u ? 1u : 0u; }
+
+ /**
+ * @brief Gets the largest possible value in the output range.
+ */
+ static constexpr result_type
+ max()
+ { return __m - 1u; }
+
+ /**
+ * @brief Discard a sequence of random numbers.
+ */
+ void
+ discard(unsigned long long __z)
+ {
+ for (; __z != 0ULL; --__z)
+ (*this)();
+ }
+
+ /**
+ * @brief Gets the next random number in the sequence.
+ */
+ result_type
+ operator()()
+ {
+ _M_x = __detail::__mod<_UIntType, __m, __a, __c>(_M_x);
+ return _M_x;
+ }
+
+ /**
+ * @brief Compares two linear congruential random number generator
+ * objects of the same type for equality.
+ *
+ * @param __lhs A linear congruential random number generator object.
+ * @param __rhs Another linear congruential random number generator
+ * object.
+ *
+ * @returns true if the infinite sequences of generated values
+ * would be equal, false otherwise.
+ */
+ friend bool
+ operator==(const linear_congruential_engine& __lhs,
+ const linear_congruential_engine& __rhs)
+ { return __lhs._M_x == __rhs._M_x; }
+
+ /**
+ * @brief Writes the textual representation of the state x(i) of x to
+ * @p __os.
+ *
+ * @param __os The output stream.
+ * @param __lcr A % linear_congruential_engine random number generator.
+ * @returns __os.
+ */
+ template<typename _UIntType1, _UIntType1 __a1, _UIntType1 __c1,
+ _UIntType1 __m1, typename _CharT, typename _Traits>
+ friend std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::linear_congruential_engine<_UIntType1,
+ __a1, __c1, __m1>& __lcr);
+
+ /**
+ * @brief Sets the state of the engine by reading its textual
+ * representation from @p __is.
+ *
+ * The textual representation must have been previously written using
+ * an output stream whose imbued locale and whose type's template
+ * specialization arguments _CharT and _Traits were the same as those
+ * of @p __is.
+ *
+ * @param __is The input stream.
+ * @param __lcr A % linear_congruential_engine random number generator.
+ * @returns __is.
+ */
+ template<typename _UIntType1, _UIntType1 __a1, _UIntType1 __c1,
+ _UIntType1 __m1, typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::linear_congruential_engine<_UIntType1, __a1,
+ __c1, __m1>& __lcr);
+
+ private:
+ _UIntType _M_x;
+ };
+
+ /**
+ * @brief Compares two linear congruential random number generator
+ * objects of the same type for inequality.
+ *
+ * @param __lhs A linear congruential random number generator object.
+ * @param __rhs Another linear congruential random number generator
+ * object.
+ *
+ * @returns true if the infinite sequences of generated values
+ * would be different, false otherwise.
+ */
+ template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
+ inline bool
+ operator!=(const std::linear_congruential_engine<_UIntType, __a,
+ __c, __m>& __lhs,
+ const std::linear_congruential_engine<_UIntType, __a,
+ __c, __m>& __rhs)
+ { return !(__lhs == __rhs); }
+
+
+ /**
+ * A generalized feedback shift register discrete random number generator.
+ *
+ * This algorithm avoids multiplication and division and is designed to be
+ * friendly to a pipelined architecture. If the parameters are chosen
+ * correctly, this generator will produce numbers with a very long period and
+ * fairly good apparent entropy, although still not cryptographically strong.
+ *
+ * The best way to use this generator is with the predefined mt19937 class.
+ *
+ * This algorithm was originally invented by Makoto Matsumoto and
+ * Takuji Nishimura.
+ *
+ * @tparam __w Word size, the number of bits in each element of
+ * the state vector.
+ * @tparam __n The degree of recursion.
+ * @tparam __m The period parameter.
+ * @tparam __r The separation point bit index.
+ * @tparam __a The last row of the twist matrix.
+ * @tparam __u The first right-shift tempering matrix parameter.
+ * @tparam __d The first right-shift tempering matrix mask.
+ * @tparam __s The first left-shift tempering matrix parameter.
+ * @tparam __b The first left-shift tempering matrix mask.
+ * @tparam __t The second left-shift tempering matrix parameter.
+ * @tparam __c The second left-shift tempering matrix mask.
+ * @tparam __l The second right-shift tempering matrix parameter.
+ * @tparam __f Initialization multiplier.
+ */
+ template<typename _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
+ {
+ static_assert(std::is_unsigned<_UIntType>::value, "template argument "
+ "substituting _UIntType not an unsigned integral type");
+ static_assert(1u <= __m && __m <= __n,
+ "template argument substituting __m out of bounds");
+ static_assert(__r <= __w, "template argument substituting "
+ "__r out of bound");
+ static_assert(__u <= __w, "template argument substituting "
+ "__u out of bound");
+ static_assert(__s <= __w, "template argument substituting "
+ "__s out of bound");
+ static_assert(__t <= __w, "template argument substituting "
+ "__t out of bound");
+ static_assert(__l <= __w, "template argument substituting "
+ "__l out of bound");
+ static_assert(__w <= std::numeric_limits<_UIntType>::digits,
+ "template argument substituting __w out of bound");
+ static_assert(__a <= (__detail::_Shift<_UIntType, __w>::__value - 1),
+ "template argument substituting __a out of bound");
+ static_assert(__b <= (__detail::_Shift<_UIntType, __w>::__value - 1),
+ "template argument substituting __b out of bound");
+ static_assert(__c <= (__detail::_Shift<_UIntType, __w>::__value - 1),
+ "template argument substituting __c out of bound");
+ static_assert(__d <= (__detail::_Shift<_UIntType, __w>::__value - 1),
+ "template argument substituting __d out of bound");
+ static_assert(__f <= (__detail::_Shift<_UIntType, __w>::__value - 1),
+ "template argument substituting __f out of bound");
+
+ public:
+ /** The type of the generated random value. */
+ typedef _UIntType result_type;
+
+ // parameter values
+ 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 result_type xor_mask = __a;
+ static constexpr size_t tempering_u = __u;
+ static constexpr result_type tempering_d = __d;
+ static constexpr size_t tempering_s = __s;
+ static constexpr result_type tempering_b = __b;
+ static constexpr size_t tempering_t = __t;
+ static constexpr result_type tempering_c = __c;
+ static constexpr size_t tempering_l = __l;
+ static constexpr result_type initialization_multiplier = __f;
+ static constexpr result_type default_seed = 5489u;
+
+ // constructors and member function
+ explicit
+ mersenne_twister_engine(result_type __sd = default_seed)
+ { seed(__sd); }
+
+ /**
+ * @brief Constructs a %mersenne_twister_engine random number generator
+ * engine seeded from the seed sequence @p __q.
+ *
+ * @param __q the seed sequence.
+ */
+ template<typename _Sseq, typename = typename
+ std::enable_if<!std::is_same<_Sseq, mersenne_twister_engine>::value>
+ ::type>
+ explicit
+ mersenne_twister_engine(_Sseq& __q)
+ { seed(__q); }
+
+ void
+ seed(result_type __sd = default_seed);
+
+ template<typename _Sseq>
+ typename std::enable_if<std::is_class<_Sseq>::value>::type
+ seed(_Sseq& __q);
+
+ /**
+ * @brief Gets the smallest possible value in the output range.
+ */
+ static constexpr result_type
+ min()
+ { return 0; };
+
+ /**
+ * @brief Gets the largest possible value in the output range.
+ */
+ static constexpr result_type
+ max()
+ { return __detail::_Shift<_UIntType, __w>::__value - 1; }
+
+ /**
+ * @brief Discard a sequence of random numbers.
+ */
+ void
+ discard(unsigned long long __z)
+ {
+ for (; __z != 0ULL; --__z)
+ (*this)();
+ }
+
+ result_type
+ operator()();
+
+ /**
+ * @brief Compares two % mersenne_twister_engine random number generator
+ * objects of the same type for equality.
+ *
+ * @param __lhs A % mersenne_twister_engine random number generator
+ * object.
+ * @param __rhs Another % mersenne_twister_engine random number
+ * generator object.
+ *
+ * @returns true if the infinite sequences of generated values
+ * would be equal, false otherwise.
+ */
+ friend bool
+ operator==(const mersenne_twister_engine& __lhs,
+ const mersenne_twister_engine& __rhs)
+ { return (std::equal(__lhs._M_x, __lhs._M_x + state_size, __rhs._M_x)
+ && __lhs._M_p == __rhs._M_p); }
+
+ /**
+ * @brief Inserts the current state of a % mersenne_twister_engine
+ * random number generator engine @p __x into the output stream
+ * @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A % mersenne_twister_engine random number generator
+ * engine.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _UIntType1,
+ size_t __w1, size_t __n1,
+ size_t __m1, size_t __r1,
+ _UIntType1 __a1, size_t __u1,
+ _UIntType1 __d1, size_t __s1,
+ _UIntType1 __b1, size_t __t1,
+ _UIntType1 __c1, size_t __l1, _UIntType1 __f1,
+ typename _CharT, typename _Traits>
+ friend std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::mersenne_twister_engine<_UIntType1, __w1, __n1,
+ __m1, __r1, __a1, __u1, __d1, __s1, __b1, __t1, __c1,
+ __l1, __f1>& __x);
+
+ /**
+ * @brief Extracts the current state of a % mersenne_twister_engine
+ * random number generator engine @p __x from the input stream
+ * @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A % mersenne_twister_engine random number generator
+ * engine.
+ *
+ * @returns The input stream with the state of @p __x extracted or in
+ * an error state.
+ */
+ template<typename _UIntType1,
+ size_t __w1, size_t __n1,
+ size_t __m1, size_t __r1,
+ _UIntType1 __a1, size_t __u1,
+ _UIntType1 __d1, size_t __s1,
+ _UIntType1 __b1, size_t __t1,
+ _UIntType1 __c1, size_t __l1, _UIntType1 __f1,
+ typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::mersenne_twister_engine<_UIntType1, __w1, __n1, __m1,
+ __r1, __a1, __u1, __d1, __s1, __b1, __t1, __c1,
+ __l1, __f1>& __x);
+
+ private:
+ _UIntType _M_x[state_size];
+ size_t _M_p;
+ };
+
+ /**
+ * @brief Compares two % mersenne_twister_engine random number generator
+ * objects of the same type for inequality.
+ *
+ * @param __lhs A % mersenne_twister_engine random number generator
+ * object.
+ * @param __rhs Another % mersenne_twister_engine random number
+ * generator object.
+ *
+ * @returns true if the infinite sequences of generated values
+ * would be different, false otherwise.
+ */
+ template<typename _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>
+ inline bool
+ operator!=(const std::mersenne_twister_engine<_UIntType, __w, __n, __m,
+ __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __lhs,
+ const std::mersenne_twister_engine<_UIntType, __w, __n, __m,
+ __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __rhs)
+ { return !(__lhs == __rhs); }
+
+
+ /**
+ * @brief The Marsaglia-Zaman generator.
+ *
+ * This is a model of a Generalized Fibonacci discrete random number
+ * generator, sometimes referred to as the SWC generator.
+ *
+ * A discrete random number generator that produces pseudorandom
+ * numbers using:
+ * @f[
+ * x_{i}\leftarrow(x_{i - s} - x_{i - r} - carry_{i-1}) \bmod m
+ * @f]
+ *
+ * The size of the state is @f$r@f$
+ * and the maximum period of the generator is @f$(m^r - m^s - 1)@f$.
+ *
+ * @var _M_x The state of the generator. This is a ring buffer.
+ * @var _M_carry The carry.
+ * @var _M_p Current index of x(i - r).
+ */
+ template<typename _UIntType, size_t __w, size_t __s, size_t __r>
+ class subtract_with_carry_engine
+ {
+ static_assert(std::is_unsigned<_UIntType>::value, "template argument "
+ "substituting _UIntType not an unsigned integral type");
+ static_assert(0u < __s && __s < __r,
+ "template argument substituting __s out of bounds");
+ static_assert(0u < __w && __w <= std::numeric_limits<_UIntType>::digits,
+ "template argument substituting __w out of bounds");
+
+ public:
+ /** The type of the generated random value. */
+ typedef _UIntType result_type;
+
+ // parameter values
+ 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 default_seed = 19780503u;
+
+ /**
+ * @brief Constructs an explicitly seeded % subtract_with_carry_engine
+ * random number generator.
+ */
+ explicit
+ subtract_with_carry_engine(result_type __sd = default_seed)
+ { seed(__sd); }
+
+ /**
+ * @brief Constructs a %subtract_with_carry_engine random number engine
+ * seeded from the seed sequence @p __q.
+ *
+ * @param __q the seed sequence.
+ */
+ template<typename _Sseq, typename = typename
+ std::enable_if<!std::is_same<_Sseq, subtract_with_carry_engine>::value>
+ ::type>
+ explicit
+ subtract_with_carry_engine(_Sseq& __q)
+ { seed(__q); }
+
+ /**
+ * @brief Seeds the initial state @f$x_0@f$ of the random number
+ * generator.
+ *
+ * N1688[4.19] modifies this as follows. If @p __value == 0,
+ * sets value to 19780503. In any case, with a linear
+ * congruential generator lcg(i) having parameters @f$ m_{lcg} =
+ * 2147483563, a_{lcg} = 40014, c_{lcg} = 0, and lcg(0) = value
+ * @f$, sets @f$ x_{-r} \dots x_{-1} @f$ to @f$ lcg(1) \bmod m
+ * \dots lcg(r) \bmod m @f$ respectively. If @f$ x_{-1} = 0 @f$
+ * set carry to 1, otherwise sets carry to 0.
+ */
+ void
+ seed(result_type __sd = default_seed);
+
+ /**
+ * @brief Seeds the initial state @f$x_0@f$ of the
+ * % subtract_with_carry_engine random number generator.
+ */
+ template<typename _Sseq>
+ typename std::enable_if<std::is_class<_Sseq>::value>::type
+ seed(_Sseq& __q);
+
+ /**
+ * @brief Gets the inclusive minimum value of the range of random
+ * integers returned by this generator.
+ */
+ static constexpr result_type
+ min()
+ { return 0; }
+
+ /**
+ * @brief Gets the inclusive maximum value of the range of random
+ * integers returned by this generator.
+ */
+ static constexpr result_type
+ max()
+ { return __detail::_Shift<_UIntType, __w>::__value - 1; }
+
+ /**
+ * @brief Discard a sequence of random numbers.
+ */
+ void
+ discard(unsigned long long __z)
+ {
+ for (; __z != 0ULL; --__z)
+ (*this)();
+ }
+
+ /**
+ * @brief Gets the next random number in the sequence.
+ */
+ result_type
+ operator()();
+
+ /**
+ * @brief Compares two % subtract_with_carry_engine random number
+ * generator objects of the same type for equality.
+ *
+ * @param __lhs A % subtract_with_carry_engine random number generator
+ * object.
+ * @param __rhs Another % subtract_with_carry_engine random number
+ * generator object.
+ *
+ * @returns true if the infinite sequences of generated values
+ * would be equal, false otherwise.
+ */
+ friend bool
+ operator==(const subtract_with_carry_engine& __lhs,
+ const subtract_with_carry_engine& __rhs)
+ { return (std::equal(__lhs._M_x, __lhs._M_x + long_lag, __rhs._M_x)
+ && __lhs._M_carry == __rhs._M_carry
+ && __lhs._M_p == __rhs._M_p); }
+
+ /**
+ * @brief Inserts the current state of a % subtract_with_carry_engine
+ * random number generator engine @p __x into the output stream
+ * @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A % subtract_with_carry_engine random number generator
+ * engine.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _UIntType1, size_t __w1, size_t __s1, size_t __r1,
+ typename _CharT, typename _Traits>
+ friend std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>&,
+ const std::subtract_with_carry_engine<_UIntType1, __w1,
+ __s1, __r1>&);
+
+ /**
+ * @brief Extracts the current state of a % subtract_with_carry_engine
+ * random number generator engine @p __x from the input stream
+ * @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A % subtract_with_carry_engine random number generator
+ * engine.
+ *
+ * @returns The input stream with the state of @p __x extracted or in
+ * an error state.
+ */
+ template<typename _UIntType1, size_t __w1, size_t __s1, size_t __r1,
+ typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>&,
+ std::subtract_with_carry_engine<_UIntType1, __w1,
+ __s1, __r1>&);
+
+ private:
+ _UIntType _M_x[long_lag];
+ _UIntType _M_carry;
+ size_t _M_p;
+ };
+
+ /**
+ * @brief Compares two % subtract_with_carry_engine random number
+ * generator objects of the same type for inequality.
+ *
+ * @param __lhs A % subtract_with_carry_engine random number generator
+ * object.
+ * @param __rhs Another % subtract_with_carry_engine random number
+ * generator object.
+ *
+ * @returns true if the infinite sequences of generated values
+ * would be different, false otherwise.
+ */
+ template<typename _UIntType, size_t __w, size_t __s, size_t __r>
+ inline bool
+ operator!=(const std::subtract_with_carry_engine<_UIntType, __w,
+ __s, __r>& __lhs,
+ const std::subtract_with_carry_engine<_UIntType, __w,
+ __s, __r>& __rhs)
+ { return !(__lhs == __rhs); }
+
+
+ /**
+ * Produces random numbers from some base engine by discarding blocks of
+ * data.
+ *
+ * 0 <= @p __r <= @p __p
+ */
+ template<typename _RandomNumberEngine, size_t __p, size_t __r>
+ class discard_block_engine
+ {
+ static_assert(1 <= __r && __r <= __p,
+ "template argument substituting __r out of bounds");
+
+ public:
+ /** The type of the generated random value. */
+ typedef typename _RandomNumberEngine::result_type result_type;
+
+ // parameter values
+ static constexpr size_t block_size = __p;
+ static constexpr size_t used_block = __r;
+
+ /**
+ * @brief Constructs a default %discard_block_engine engine.
+ *
+ * The underlying engine is default constructed as well.
+ */
+ discard_block_engine()
+ : _M_b(), _M_n(0) { }
+
+ /**
+ * @brief Copy constructs a %discard_block_engine engine.
+ *
+ * Copies an existing base class random number generator.
+ * @param __rng An existing (base class) engine object.
+ */
+ explicit
+ discard_block_engine(const _RandomNumberEngine& __rng)
+ : _M_b(__rng), _M_n(0) { }
+
+ /**
+ * @brief Move constructs a %discard_block_engine engine.
+ *
+ * Copies an existing base class random number generator.
+ * @param __rng An existing (base class) engine object.
+ */
+ explicit
+ discard_block_engine(_RandomNumberEngine&& __rng)
+ : _M_b(std::move(__rng)), _M_n(0) { }
+
+ /**
+ * @brief Seed constructs a %discard_block_engine engine.
+ *
+ * Constructs the underlying generator engine seeded with @p __s.
+ * @param __s A seed value for the base class engine.
+ */
+ explicit
+ discard_block_engine(result_type __s)
+ : _M_b(__s), _M_n(0) { }
+
+ /**
+ * @brief Generator construct a %discard_block_engine engine.
+ *
+ * @param __q A seed sequence.
+ */
+ template<typename _Sseq, typename = typename
+ std::enable_if<!std::is_same<_Sseq, discard_block_engine>::value
+ && !std::is_same<_Sseq, _RandomNumberEngine>::value>
+ ::type>
+ explicit
+ discard_block_engine(_Sseq& __q)
+ : _M_b(__q), _M_n(0)
+ { }
+
+ /**
+ * @brief Reseeds the %discard_block_engine object with the default
+ * seed for the underlying base class generator engine.
+ */
+ void
+ seed()
+ {
+ _M_b.seed();
+ _M_n = 0;
+ }
+
+ /**
+ * @brief Reseeds the %discard_block_engine object with the default
+ * seed for the underlying base class generator engine.
+ */
+ void
+ seed(result_type __s)
+ {
+ _M_b.seed(__s);
+ _M_n = 0;
+ }
+
+ /**
+ * @brief Reseeds the %discard_block_engine object with the given seed
+ * sequence.
+ * @param __q A seed generator function.
+ */
+ template<typename _Sseq>
+ void
+ seed(_Sseq& __q)
+ {
+ _M_b.seed(__q);
+ _M_n = 0;
+ }
+
+ /**
+ * @brief Gets a const reference to the underlying generator engine
+ * object.
+ */
+ const _RandomNumberEngine&
+ base() const noexcept
+ { return _M_b; }
+
+ /**
+ * @brief Gets the minimum value in the generated random number range.
+ */
+ static constexpr result_type
+ min()
+ { return _RandomNumberEngine::min(); }
+
+ /**
+ * @brief Gets the maximum value in the generated random number range.
+ */
+ static constexpr result_type
+ max()
+ { return _RandomNumberEngine::max(); }
+
+ /**
+ * @brief Discard a sequence of random numbers.
+ */
+ void
+ discard(unsigned long long __z)
+ {
+ for (; __z != 0ULL; --__z)
+ (*this)();
+ }
+
+ /**
+ * @brief Gets the next value in the generated random number sequence.
+ */
+ result_type
+ operator()();
+
+ /**
+ * @brief Compares two %discard_block_engine random number generator
+ * objects of the same type for equality.
+ *
+ * @param __lhs A %discard_block_engine random number generator object.
+ * @param __rhs Another %discard_block_engine random number generator
+ * object.
+ *
+ * @returns true if the infinite sequences of generated values
+ * would be equal, false otherwise.
+ */
+ friend bool
+ operator==(const discard_block_engine& __lhs,
+ const discard_block_engine& __rhs)
+ { return __lhs._M_b == __rhs._M_b && __lhs._M_n == __rhs._M_n; }
+
+ /**
+ * @brief Inserts the current state of a %discard_block_engine random
+ * number generator engine @p __x into the output stream
+ * @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %discard_block_engine random number generator engine.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _RandomNumberEngine1, size_t __p1, size_t __r1,
+ typename _CharT, typename _Traits>
+ friend std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::discard_block_engine<_RandomNumberEngine1,
+ __p1, __r1>& __x);
+
+ /**
+ * @brief Extracts the current state of a % subtract_with_carry_engine
+ * random number generator engine @p __x from the input stream
+ * @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %discard_block_engine random number generator engine.
+ *
+ * @returns The input stream with the state of @p __x extracted or in
+ * an error state.
+ */
+ template<typename _RandomNumberEngine1, size_t __p1, size_t __r1,
+ typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::discard_block_engine<_RandomNumberEngine1,
+ __p1, __r1>& __x);
+
+ private:
+ _RandomNumberEngine _M_b;
+ size_t _M_n;
+ };
+
+ /**
+ * @brief Compares two %discard_block_engine random number generator
+ * objects of the same type for inequality.
+ *
+ * @param __lhs A %discard_block_engine random number generator object.
+ * @param __rhs Another %discard_block_engine random number generator
+ * object.
+ *
+ * @returns true if the infinite sequences of generated values
+ * would be different, false otherwise.
+ */
+ template<typename _RandomNumberEngine, size_t __p, size_t __r>
+ inline bool
+ operator!=(const std::discard_block_engine<_RandomNumberEngine, __p,
+ __r>& __lhs,
+ const std::discard_block_engine<_RandomNumberEngine, __p,
+ __r>& __rhs)
+ { return !(__lhs == __rhs); }
+
+
+ /**
+ * Produces random numbers by combining random numbers from some base
+ * engine to produce random numbers with a specifies number of bits @p __w.
+ */
+ template<typename _RandomNumberEngine, size_t __w, typename _UIntType>
+ class independent_bits_engine
+ {
+ static_assert(std::is_unsigned<_UIntType>::value, "template argument "
+ "substituting _UIntType not an unsigned integral type");
+ static_assert(0u < __w && __w <= std::numeric_limits<_UIntType>::digits,
+ "template argument substituting __w out of bounds");
+
+ public:
+ /** The type of the generated random value. */
+ typedef _UIntType result_type;
+
+ /**
+ * @brief Constructs a default %independent_bits_engine engine.
+ *
+ * The underlying engine is default constructed as well.
+ */
+ independent_bits_engine()
+ : _M_b() { }
+
+ /**
+ * @brief Copy constructs a %independent_bits_engine engine.
+ *
+ * Copies an existing base class random number generator.
+ * @param __rng An existing (base class) engine object.
+ */
+ explicit
+ independent_bits_engine(const _RandomNumberEngine& __rng)
+ : _M_b(__rng) { }
+
+ /**
+ * @brief Move constructs a %independent_bits_engine engine.
+ *
+ * Copies an existing base class random number generator.
+ * @param __rng An existing (base class) engine object.
+ */
+ explicit
+ independent_bits_engine(_RandomNumberEngine&& __rng)
+ : _M_b(std::move(__rng)) { }
+
+ /**
+ * @brief Seed constructs a %independent_bits_engine engine.
+ *
+ * Constructs the underlying generator engine seeded with @p __s.
+ * @param __s A seed value for the base class engine.
+ */
+ explicit
+ independent_bits_engine(result_type __s)
+ : _M_b(__s) { }
+
+ /**
+ * @brief Generator construct a %independent_bits_engine engine.
+ *
+ * @param __q A seed sequence.
+ */
+ template<typename _Sseq, typename = typename
+ std::enable_if<!std::is_same<_Sseq, independent_bits_engine>::value
+ && !std::is_same<_Sseq, _RandomNumberEngine>::value>
+ ::type>
+ explicit
+ independent_bits_engine(_Sseq& __q)
+ : _M_b(__q)
+ { }
+
+ /**
+ * @brief Reseeds the %independent_bits_engine object with the default
+ * seed for the underlying base class generator engine.
+ */
+ void
+ seed()
+ { _M_b.seed(); }
+
+ /**
+ * @brief Reseeds the %independent_bits_engine object with the default
+ * seed for the underlying base class generator engine.
+ */
+ void
+ seed(result_type __s)
+ { _M_b.seed(__s); }
+
+ /**
+ * @brief Reseeds the %independent_bits_engine object with the given
+ * seed sequence.
+ * @param __q A seed generator function.
+ */
+ template<typename _Sseq>
+ void
+ seed(_Sseq& __q)
+ { _M_b.seed(__q); }
+
+ /**
+ * @brief Gets a const reference to the underlying generator engine
+ * object.
+ */
+ const _RandomNumberEngine&
+ base() const noexcept
+ { return _M_b; }
+
+ /**
+ * @brief Gets the minimum value in the generated random number range.
+ */
+ static constexpr result_type
+ min()
+ { return 0U; }
+
+ /**
+ * @brief Gets the maximum value in the generated random number range.
+ */
+ static constexpr result_type
+ max()
+ { return __detail::_Shift<_UIntType, __w>::__value - 1; }
+
+ /**
+ * @brief Discard a sequence of random numbers.
+ */
+ void
+ discard(unsigned long long __z)
+ {
+ for (; __z != 0ULL; --__z)
+ (*this)();
+ }
+
+ /**
+ * @brief Gets the next value in the generated random number sequence.
+ */
+ result_type
+ operator()();
+
+ /**
+ * @brief Compares two %independent_bits_engine random number generator
+ * objects of the same type for equality.
+ *
+ * @param __lhs A %independent_bits_engine random number generator
+ * object.
+ * @param __rhs Another %independent_bits_engine random number generator
+ * object.
+ *
+ * @returns true if the infinite sequences of generated values
+ * would be equal, false otherwise.
+ */
+ friend bool
+ operator==(const independent_bits_engine& __lhs,
+ const independent_bits_engine& __rhs)
+ { return __lhs._M_b == __rhs._M_b; }
+
+ /**
+ * @brief Extracts the current state of a % subtract_with_carry_engine
+ * random number generator engine @p __x from the input stream
+ * @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %independent_bits_engine random number generator
+ * engine.
+ *
+ * @returns The input stream with the state of @p __x extracted or in
+ * an error state.
+ */
+ template<typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::independent_bits_engine<_RandomNumberEngine,
+ __w, _UIntType>& __x)
+ {
+ __is >> __x._M_b;
+ return __is;
+ }
+
+ private:
+ _RandomNumberEngine _M_b;
+ };
+
+ /**
+ * @brief Compares two %independent_bits_engine random number generator
+ * objects of the same type for inequality.
+ *
+ * @param __lhs A %independent_bits_engine random number generator
+ * object.
+ * @param __rhs Another %independent_bits_engine random number generator
+ * object.
+ *
+ * @returns true if the infinite sequences of generated values
+ * would be different, false otherwise.
+ */
+ template<typename _RandomNumberEngine, size_t __w, typename _UIntType>
+ inline bool
+ operator!=(const std::independent_bits_engine<_RandomNumberEngine, __w,
+ _UIntType>& __lhs,
+ const std::independent_bits_engine<_RandomNumberEngine, __w,
+ _UIntType>& __rhs)
+ { return !(__lhs == __rhs); }
+
+ /**
+ * @brief Inserts the current state of a %independent_bits_engine random
+ * number generator engine @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %independent_bits_engine random number generator engine.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _RandomNumberEngine, size_t __w, typename _UIntType,
+ typename _CharT, typename _Traits>
+ std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::independent_bits_engine<_RandomNumberEngine,
+ __w, _UIntType>& __x)
+ {
+ __os << __x.base();
+ return __os;
+ }
+
+
+ /**
+ * @brief Produces random numbers by combining random numbers from some
+ * base engine to produce random numbers with a specifies number of bits
+ * @p __w.
+ */
+ template<typename _RandomNumberEngine, size_t __k>
+ class shuffle_order_engine
+ {
+ static_assert(1u <= __k, "template argument substituting "
+ "__k out of bound");
+
+ public:
+ /** The type of the generated random value. */
+ typedef typename _RandomNumberEngine::result_type result_type;
+
+ static constexpr size_t table_size = __k;
+
+ /**
+ * @brief Constructs a default %shuffle_order_engine engine.
+ *
+ * The underlying engine is default constructed as well.
+ */
+ shuffle_order_engine()
+ : _M_b()
+ { _M_initialize(); }
+
+ /**
+ * @brief Copy constructs a %shuffle_order_engine engine.
+ *
+ * Copies an existing base class random number generator.
+ * @param __rng An existing (base class) engine object.
+ */
+ explicit
+ shuffle_order_engine(const _RandomNumberEngine& __rng)
+ : _M_b(__rng)
+ { _M_initialize(); }
+
+ /**
+ * @brief Move constructs a %shuffle_order_engine engine.
+ *
+ * Copies an existing base class random number generator.
+ * @param __rng An existing (base class) engine object.
+ */
+ explicit
+ shuffle_order_engine(_RandomNumberEngine&& __rng)
+ : _M_b(std::move(__rng))
+ { _M_initialize(); }
+
+ /**
+ * @brief Seed constructs a %shuffle_order_engine engine.
+ *
+ * Constructs the underlying generator engine seeded with @p __s.
+ * @param __s A seed value for the base class engine.
+ */
+ explicit
+ shuffle_order_engine(result_type __s)
+ : _M_b(__s)
+ { _M_initialize(); }
+
+ /**
+ * @brief Generator construct a %shuffle_order_engine engine.
+ *
+ * @param __q A seed sequence.
+ */
+ template<typename _Sseq, typename = typename
+ std::enable_if<!std::is_same<_Sseq, shuffle_order_engine>::value
+ && !std::is_same<_Sseq, _RandomNumberEngine>::value>
+ ::type>
+ explicit
+ shuffle_order_engine(_Sseq& __q)
+ : _M_b(__q)
+ { _M_initialize(); }
+
+ /**
+ * @brief Reseeds the %shuffle_order_engine object with the default seed
+ for the underlying base class generator engine.
+ */
+ void
+ seed()
+ {
+ _M_b.seed();
+ _M_initialize();
+ }
+
+ /**
+ * @brief Reseeds the %shuffle_order_engine object with the default seed
+ * for the underlying base class generator engine.
+ */
+ void
+ seed(result_type __s)
+ {
+ _M_b.seed(__s);
+ _M_initialize();
+ }
+
+ /**
+ * @brief Reseeds the %shuffle_order_engine object with the given seed
+ * sequence.
+ * @param __q A seed generator function.
+ */
+ template<typename _Sseq>
+ void
+ seed(_Sseq& __q)
+ {
+ _M_b.seed(__q);
+ _M_initialize();
+ }
+
+ /**
+ * Gets a const reference to the underlying generator engine object.
+ */
+ const _RandomNumberEngine&
+ base() const noexcept
+ { return _M_b; }
+
+ /**
+ * Gets the minimum value in the generated random number range.
+ */
+ static constexpr result_type
+ min()
+ { return _RandomNumberEngine::min(); }
+
+ /**
+ * Gets the maximum value in the generated random number range.
+ */
+ static constexpr result_type
+ max()
+ { return _RandomNumberEngine::max(); }
+
+ /**
+ * Discard a sequence of random numbers.
+ */
+ void
+ discard(unsigned long long __z)
+ {
+ for (; __z != 0ULL; --__z)
+ (*this)();
+ }
+
+ /**
+ * Gets the next value in the generated random number sequence.
+ */
+ result_type
+ operator()();
+
+ /**
+ * Compares two %shuffle_order_engine random number generator objects
+ * of the same type for equality.
+ *
+ * @param __lhs A %shuffle_order_engine random number generator object.
+ * @param __rhs Another %shuffle_order_engine random number generator
+ * object.
+ *
+ * @returns true if the infinite sequences of generated values
+ * would be equal, false otherwise.
+ */
+ friend bool
+ operator==(const shuffle_order_engine& __lhs,
+ const shuffle_order_engine& __rhs)
+ { return (__lhs._M_b == __rhs._M_b
+ && std::equal(__lhs._M_v, __lhs._M_v + __k, __rhs._M_v)
+ && __lhs._M_y == __rhs._M_y); }
+
+ /**
+ * @brief Inserts the current state of a %shuffle_order_engine random
+ * number generator engine @p __x into the output stream
+ @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %shuffle_order_engine random number generator engine.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _RandomNumberEngine1, size_t __k1,
+ typename _CharT, typename _Traits>
+ friend std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::shuffle_order_engine<_RandomNumberEngine1,
+ __k1>& __x);
+
+ /**
+ * @brief Extracts the current state of a % subtract_with_carry_engine
+ * random number generator engine @p __x from the input stream
+ * @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %shuffle_order_engine random number generator engine.
+ *
+ * @returns The input stream with the state of @p __x extracted or in
+ * an error state.
+ */
+ template<typename _RandomNumberEngine1, size_t __k1,
+ typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::shuffle_order_engine<_RandomNumberEngine1, __k1>& __x);
+
+ private:
+ void _M_initialize()
+ {
+ for (size_t __i = 0; __i < __k; ++__i)
+ _M_v[__i] = _M_b();
+ _M_y = _M_b();
+ }
+
+ _RandomNumberEngine _M_b;
+ result_type _M_v[__k];
+ result_type _M_y;
+ };
+
+ /**
+ * Compares two %shuffle_order_engine random number generator objects
+ * of the same type for inequality.
+ *
+ * @param __lhs A %shuffle_order_engine random number generator object.
+ * @param __rhs Another %shuffle_order_engine random number generator
+ * object.
+ *
+ * @returns true if the infinite sequences of generated values
+ * would be different, false otherwise.
+ */
+ template<typename _RandomNumberEngine, size_t __k>
+ inline bool
+ operator!=(const std::shuffle_order_engine<_RandomNumberEngine,
+ __k>& __lhs,
+ const std::shuffle_order_engine<_RandomNumberEngine,
+ __k>& __rhs)
+ { return !(__lhs == __rhs); }
+
+
+ /**
+ * The classic Minimum Standard rand0 of Lewis, Goodman, and Miller.
+ */
+ typedef linear_congruential_engine<uint_fast32_t, 16807UL, 0UL, 2147483647UL>
+ minstd_rand0;
+
+ /**
+ * An alternative LCR (Lehmer Generator function).
+ */
+ typedef linear_congruential_engine<uint_fast32_t, 48271UL, 0UL, 2147483647UL>
+ minstd_rand;
+
+ /**
+ * The classic Mersenne Twister.
+ *
+ * Reference:
+ * M. Matsumoto and T. Nishimura, Mersenne Twister: A 623-Dimensionally
+ * Equidistributed Uniform Pseudo-Random Number Generator, ACM Transactions
+ * on Modeling and Computer Simulation, Vol. 8, No. 1, January 1998, pp 3-30.
+ */
+ typedef mersenne_twister_engine<
+ uint_fast32_t,
+ 32, 624, 397, 31,
+ 0x9908b0dfUL, 11,
+ 0xffffffffUL, 7,
+ 0x9d2c5680UL, 15,
+ 0xefc60000UL, 18, 1812433253UL> mt19937;
+
+ /**
+ * An alternative Mersenne Twister.
+ */
+ typedef mersenne_twister_engine<
+ uint_fast64_t,
+ 64, 312, 156, 31,
+ 0xb5026f5aa96619e9ULL, 29,
+ 0x5555555555555555ULL, 17,
+ 0x71d67fffeda60000ULL, 37,
+ 0xfff7eee000000000ULL, 43,
+ 6364136223846793005ULL> mt19937_64;
+
+ typedef subtract_with_carry_engine<uint_fast32_t, 24, 10, 24>
+ ranlux24_base;
+
+ typedef subtract_with_carry_engine<uint_fast64_t, 48, 5, 12>
+ ranlux48_base;
+
+ typedef discard_block_engine<ranlux24_base, 223, 23> ranlux24;
+
+ typedef discard_block_engine<ranlux48_base, 389, 11> ranlux48;
+
+ typedef shuffle_order_engine<minstd_rand0, 256> knuth_b;
+
+ typedef minstd_rand0 default_random_engine;
+
+ /**
+ * A standard interface to a platform-specific non-deterministic
+ * random number generator (if any are available).
+ */
+ class random_device
+ {
+ public:
+ /** The type of the generated random value. */
+ typedef unsigned int result_type;
+
+ // constructors, destructors and member functions
+
+#ifdef _GLIBCXX_USE_RANDOM_TR1
+
+ explicit
+ random_device(const std::string& __token = "/dev/urandom")
+ {
+ if ((__token != "/dev/urandom" && __token != "/dev/random")
+ || !(_M_file = std::fopen(__token.c_str(), "rb")))
+ std::__throw_runtime_error(__N("random_device::"
+ "random_device(const std::string&)"));
+ }
+
+ ~random_device()
+ { std::fclose(_M_file); }
+
+#else
+
+ explicit
+ random_device(const std::string& __token = "mt19937")
+ : _M_mt(_M_strtoul(__token)) { }
+
+ private:
+ static unsigned long
+ _M_strtoul(const std::string& __str)
+ {
+ unsigned long __ret = 5489UL;
+ if (__str != "mt19937")
+ {
+ const char* __nptr = __str.c_str();
+ char* __endptr;
+ __ret = std::strtoul(__nptr, &__endptr, 0);
+ if (*__nptr == '\0' || *__endptr != '\0')
+ std::__throw_runtime_error(__N("random_device::_M_strtoul"
+ "(const std::string&)"));
+ }
+ return __ret;
+ }
+
+ public:
+
+#endif
+
+ static constexpr result_type
+ min()
+ { return std::numeric_limits<result_type>::min(); }
+
+ static constexpr result_type
+ max()
+ { return std::numeric_limits<result_type>::max(); }
+
+ double
+ entropy() const noexcept
+ { return 0.0; }
+
+ result_type
+ operator()()
+ {
+#ifdef _GLIBCXX_USE_RANDOM_TR1
+ result_type __ret;
+ std::fread(reinterpret_cast<void*>(&__ret), sizeof(result_type),
+ 1, _M_file);
+ return __ret;
+#else
+ return _M_mt();
+#endif
+ }
+
+ // No copy functions.
+ random_device(const random_device&) = delete;
+ void operator=(const random_device&) = delete;
+
+ private:
+
+#ifdef _GLIBCXX_USE_RANDOM_TR1
+ FILE* _M_file;
+#else
+ mt19937 _M_mt;
+#endif
+ };
+
+ /* @} */ // group random_generators
+
+ /**
+ * @addtogroup random_distributions Random Number Distributions
+ * @ingroup random
+ * @{
+ */
+
+ /**
+ * @addtogroup random_distributions_uniform Uniform Distributions
+ * @ingroup random_distributions
+ * @{
+ */
+
+ /**
+ * @brief Uniform discrete distribution for random numbers.
+ * A discrete random distribution on the range @f$[min, max]@f$ with equal
+ * probability throughout the range.
+ */
+ template<typename _IntType = int>
+ class uniform_int_distribution
+ {
+ static_assert(std::is_integral<_IntType>::value,
+ "template argument not an integral type");
+
+ public:
+ /** The type of the range of the distribution. */
+ typedef _IntType result_type;
+ /** Parameter type. */
+ struct param_type
+ {
+ typedef uniform_int_distribution<_IntType> distribution_type;
+
+ explicit
+ param_type(_IntType __a = 0,
+ _IntType __b = std::numeric_limits<_IntType>::max())
+ : _M_a(__a), _M_b(__b)
+ {
+ _GLIBCXX_DEBUG_ASSERT(_M_a <= _M_b);
+ }
+
+ result_type
+ a() const
+ { return _M_a; }
+
+ result_type
+ b() const
+ { return _M_b; }
+
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; }
+
+ private:
+ _IntType _M_a;
+ _IntType _M_b;
+ };
+
+ public:
+ /**
+ * @brief Constructs a uniform distribution object.
+ */
+ explicit
+ uniform_int_distribution(_IntType __a = 0,
+ _IntType __b = std::numeric_limits<_IntType>::max())
+ : _M_param(__a, __b)
+ { }
+
+ explicit
+ uniform_int_distribution(const param_type& __p)
+ : _M_param(__p)
+ { }
+
+ /**
+ * @brief Resets the distribution state.
+ *
+ * Does nothing for the uniform integer distribution.
+ */
+ void
+ reset() { }
+
+ result_type
+ a() const
+ { return _M_param.a(); }
+
+ result_type
+ b() const
+ { return _M_param.b(); }
+
+ /**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
+ * @brief Returns the inclusive lower bound of the distribution range.
+ */
+ result_type
+ min() const
+ { return this->a(); }
+
+ /**
+ * @brief Returns the inclusive upper bound of the distribution range.
+ */
+ result_type
+ max() const
+ { return this->b(); }
+
+ /**
+ * @brief Generating functions.
+ */
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng)
+ { return this->operator()(__urng, _M_param); }
+
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
+ /**
+ * @brief Return true if two uniform integer distributions have
+ * the same parameters.
+ */
+ friend bool
+ operator==(const uniform_int_distribution& __d1,
+ const uniform_int_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
+ private:
+ param_type _M_param;
+ };
+
+ /**
+ * @brief Return true if two uniform integer distributions have
+ * different parameters.
+ */
+ template<typename _IntType>
+ inline bool
+ operator!=(const std::uniform_int_distribution<_IntType>& __d1,
+ const std::uniform_int_distribution<_IntType>& __d2)
+ { return !(__d1 == __d2); }
+
+ /**
+ * @brief Inserts a %uniform_int_distribution random number
+ * distribution @p __x into the output stream @p os.
+ *
+ * @param __os An output stream.
+ * @param __x A %uniform_int_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _IntType, typename _CharT, typename _Traits>
+ std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>&,
+ const std::uniform_int_distribution<_IntType>&);
+
+ /**
+ * @brief Extracts a %uniform_int_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %uniform_int_distribution random number generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error state.
+ */
+ template<typename _IntType, typename _CharT, typename _Traits>
+ std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>&,
+ std::uniform_int_distribution<_IntType>&);
+
+
+ /**
+ * @brief Uniform continuous distribution for random numbers.
+ *
+ * A continuous random distribution on the range [min, max) with equal
+ * probability throughout the range. The URNG should be real-valued and
+ * deliver number in the range [0, 1).
+ */
+ template<typename _RealType = double>
+ class uniform_real_distribution
+ {
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
+ public:
+ /** The type of the range of the distribution. */
+ typedef _RealType result_type;
+ /** Parameter type. */
+ struct param_type
+ {
+ typedef uniform_real_distribution<_RealType> distribution_type;
+
+ explicit
+ param_type(_RealType __a = _RealType(0),
+ _RealType __b = _RealType(1))
+ : _M_a(__a), _M_b(__b)
+ {
+ _GLIBCXX_DEBUG_ASSERT(_M_a <= _M_b);
+ }
+
+ result_type
+ a() const
+ { return _M_a; }
+
+ result_type
+ b() const
+ { return _M_b; }
+
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; }
+
+ private:
+ _RealType _M_a;
+ _RealType _M_b;
+ };
+
+ public:
+ /**
+ * @brief Constructs a uniform_real_distribution object.
+ *
+ * @param __a [IN] The lower bound of the distribution.
+ * @param __b [IN] The upper bound of the distribution.
+ */
+ explicit
+ uniform_real_distribution(_RealType __a = _RealType(0),
+ _RealType __b = _RealType(1))
+ : _M_param(__a, __b)
+ { }
+
+ explicit
+ uniform_real_distribution(const param_type& __p)
+ : _M_param(__p)
+ { }
+
+ /**
+ * @brief Resets the distribution state.
+ *
+ * Does nothing for the uniform real distribution.
+ */
+ void
+ reset() { }
+
+ result_type
+ a() const
+ { return _M_param.a(); }
+
+ result_type
+ b() const
+ { return _M_param.b(); }
+
+ /**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
+ * @brief Returns the inclusive lower bound of the distribution range.
+ */
+ result_type
+ min() const
+ { return this->a(); }
+
+ /**
+ * @brief Returns the inclusive upper bound of the distribution range.
+ */
+ result_type
+ max() const
+ { return this->b(); }
+
+ /**
+ * @brief Generating functions.
+ */
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng)
+ { return this->operator()(__urng, _M_param); }
+
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ {
+ __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
+ __aurng(__urng);
+ return (__aurng() * (__p.b() - __p.a())) + __p.a();
+ }
+
+ /**
+ * @brief Return true if two uniform real distributions have
+ * the same parameters.
+ */
+ friend bool
+ operator==(const uniform_real_distribution& __d1,
+ const uniform_real_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
+ private:
+ param_type _M_param;
+ };
+
+ /**
+ * @brief Return true if two uniform real distributions have
+ * different parameters.
+ */
+ template<typename _IntType>
+ inline bool
+ operator!=(const std::uniform_real_distribution<_IntType>& __d1,
+ const std::uniform_real_distribution<_IntType>& __d2)
+ { return !(__d1 == __d2); }
+
+ /**
+ * @brief Inserts a %uniform_real_distribution random number
+ * distribution @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %uniform_real_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _RealType, typename _CharT, typename _Traits>
+ std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>&,
+ const std::uniform_real_distribution<_RealType>&);
+
+ /**
+ * @brief Extracts a %uniform_real_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %uniform_real_distribution random number generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error state.
+ */
+ template<typename _RealType, typename _CharT, typename _Traits>
+ std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>&,
+ std::uniform_real_distribution<_RealType>&);
+
+ /* @} */ // group random_distributions_uniform
+
+ /**
+ * @addtogroup random_distributions_normal Normal Distributions
+ * @ingroup random_distributions
+ * @{
+ */
+
+ /**
+ * @brief A normal continuous distribution for random numbers.
+ *
+ * The formula for the normal probability density function is
+ * @f[
+ * p(x|\mu,\sigma) = \frac{1}{\sigma \sqrt{2 \pi}}
+ * e^{- \frac{{x - \mu}^ {2}}{2 \sigma ^ {2}} }
+ * @f]
+ */
+ template<typename _RealType = double>
+ class normal_distribution
+ {
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
+ public:
+ /** The type of the range of the distribution. */
+ typedef _RealType result_type;
+ /** Parameter type. */
+ struct param_type
+ {
+ typedef normal_distribution<_RealType> distribution_type;
+
+ explicit
+ param_type(_RealType __mean = _RealType(0),
+ _RealType __stddev = _RealType(1))
+ : _M_mean(__mean), _M_stddev(__stddev)
+ {
+ _GLIBCXX_DEBUG_ASSERT(_M_stddev > _RealType(0));
+ }
+
+ _RealType
+ mean() const
+ { return _M_mean; }
+
+ _RealType
+ stddev() const
+ { return _M_stddev; }
+
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return (__p1._M_mean == __p2._M_mean
+ && __p1._M_stddev == __p2._M_stddev); }
+
+ private:
+ _RealType _M_mean;
+ _RealType _M_stddev;
+ };
+
+ public:
+ /**
+ * Constructs a normal distribution with parameters @f$mean@f$ and
+ * standard deviation.
+ */
+ explicit
+ normal_distribution(result_type __mean = result_type(0),
+ result_type __stddev = result_type(1))
+ : _M_param(__mean, __stddev), _M_saved_available(false)
+ { }
+
+ explicit
+ normal_distribution(const param_type& __p)
+ : _M_param(__p), _M_saved_available(false)
+ { }
+
+ /**
+ * @brief Resets the distribution state.
+ */
+ void
+ reset()
+ { _M_saved_available = false; }
+
+ /**
+ * @brief Returns the mean of the distribution.
+ */
+ _RealType
+ mean() const
+ { return _M_param.mean(); }
+
+ /**
+ * @brief Returns the standard deviation of the distribution.
+ */
+ _RealType
+ stddev() const
+ { return _M_param.stddev(); }
+
+ /**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
+ * @brief Returns the greatest lower bound value of the distribution.
+ */
+ result_type
+ min() const
+ { return std::numeric_limits<result_type>::min(); }
+
+ /**
+ * @brief Returns the least upper bound value of the distribution.
+ */
+ result_type
+ max() const
+ { return std::numeric_limits<result_type>::max(); }
+
+ /**
+ * @brief Generating functions.
+ */
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng)
+ { return this->operator()(__urng, _M_param); }
+
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
+ /**
+ * @brief Return true if two normal distributions have
+ * the same parameters and the sequences that would
+ * be generated are equal.
+ */
+ template<typename _RealType1>
+ friend bool
+ operator==(const std::normal_distribution<_RealType1>& __d1,
+ const std::normal_distribution<_RealType1>& __d2);
+
+ /**
+ * @brief Inserts a %normal_distribution random number distribution
+ * @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %normal_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::normal_distribution<_RealType1>& __x);
+
+ /**
+ * @brief Extracts a %normal_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %normal_distribution random number generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error
+ * state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::normal_distribution<_RealType1>& __x);
+
+ private:
+ param_type _M_param;
+ result_type _M_saved;
+ bool _M_saved_available;
+ };
+
+ /**
+ * @brief Return true if two normal distributions are different.
+ */
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::normal_distribution<_RealType>& __d1,
+ const std::normal_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
+
+
+ /**
+ * @brief A lognormal_distribution random number distribution.
+ *
+ * The formula for the normal probability mass function is
+ * @f[
+ * p(x|m,s) = \frac{1}{sx\sqrt{2\pi}}
+ * \exp{-\frac{(\ln{x} - m)^2}{2s^2}}
+ * @f]
+ */
+ template<typename _RealType = double>
+ class lognormal_distribution
+ {
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
+ public:
+ /** The type of the range of the distribution. */
+ typedef _RealType result_type;
+ /** Parameter type. */
+ struct param_type
+ {
+ typedef lognormal_distribution<_RealType> distribution_type;
+
+ explicit
+ param_type(_RealType __m = _RealType(0),
+ _RealType __s = _RealType(1))
+ : _M_m(__m), _M_s(__s)
+ { }
+
+ _RealType
+ m() const
+ { return _M_m; }
+
+ _RealType
+ s() const
+ { return _M_s; }
+
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_m == __p2._M_m && __p1._M_s == __p2._M_s; }
+
+ private:
+ _RealType _M_m;
+ _RealType _M_s;
+ };
+
+ explicit
+ lognormal_distribution(_RealType __m = _RealType(0),
+ _RealType __s = _RealType(1))
+ : _M_param(__m, __s), _M_nd()
+ { }
+
+ explicit
+ lognormal_distribution(const param_type& __p)
+ : _M_param(__p), _M_nd()
+ { }
+
+ /**
+ * Resets the distribution state.
+ */
+ void
+ reset()
+ { _M_nd.reset(); }
+
+ /**
+ *
+ */
+ _RealType
+ m() const
+ { return _M_param.m(); }
+
+ _RealType
+ s() const
+ { return _M_param.s(); }
+
+ /**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
+ * @brief Returns the greatest lower bound value of the distribution.
+ */
+ result_type
+ min() const
+ { return result_type(0); }
+
+ /**
+ * @brief Returns the least upper bound value of the distribution.
+ */
+ result_type
+ max() const
+ { return std::numeric_limits<result_type>::max(); }
+
+ /**
+ * @brief Generating functions.
+ */
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng)
+ { return this->operator()(__urng, _M_param); }
+
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ { return std::exp(__p.s() * _M_nd(__urng) + __p.m()); }
+
+ /**
+ * @brief Return true if two lognormal distributions have
+ * the same parameters and the sequences that would
+ * be generated are equal.
+ */
+ friend bool
+ operator==(const lognormal_distribution& __d1,
+ const lognormal_distribution& __d2)
+ { return (__d1._M_param == __d2._M_param
+ && __d1._M_nd == __d2._M_nd); }
+
+ /**
+ * @brief Inserts a %lognormal_distribution random number distribution
+ * @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %lognormal_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::lognormal_distribution<_RealType1>& __x);
+
+ /**
+ * @brief Extracts a %lognormal_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %lognormal_distribution random number
+ * generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::lognormal_distribution<_RealType1>& __x);
+
+ private:
+ param_type _M_param;
+
+ std::normal_distribution<result_type> _M_nd;
+ };
+
+ /**
+ * @brief Return true if two lognormal distributions are different.
+ */
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::lognormal_distribution<_RealType>& __d1,
+ const std::lognormal_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
+
+
+ /**
+ * @brief A gamma continuous distribution for random numbers.
+ *
+ * The formula for the gamma probability density function is:
+ * @f[
+ * p(x|\alpha,\beta) = \frac{1}{\beta\Gamma(\alpha)}
+ * (x/\beta)^{\alpha - 1} e^{-x/\beta}
+ * @f]
+ */
+ template<typename _RealType = double>
+ class gamma_distribution
+ {
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
+ public:
+ /** The type of the range of the distribution. */
+ typedef _RealType result_type;
+ /** Parameter type. */
+ struct param_type
+ {
+ typedef gamma_distribution<_RealType> distribution_type;
+ friend class gamma_distribution<_RealType>;
+
+ explicit
+ param_type(_RealType __alpha_val = _RealType(1),
+ _RealType __beta_val = _RealType(1))
+ : _M_alpha(__alpha_val), _M_beta(__beta_val)
+ {
+ _GLIBCXX_DEBUG_ASSERT(_M_alpha > _RealType(0));
+ _M_initialize();
+ }
+
+ _RealType
+ alpha() const
+ { return _M_alpha; }
+
+ _RealType
+ beta() const
+ { return _M_beta; }
+
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return (__p1._M_alpha == __p2._M_alpha
+ && __p1._M_beta == __p2._M_beta); }
+
+ private:
+ void
+ _M_initialize();
+
+ _RealType _M_alpha;
+ _RealType _M_beta;
+
+ _RealType _M_malpha, _M_a2;
+ };
+
+ public:
+ /**
+ * @brief Constructs a gamma distribution with parameters
+ * @f$\alpha@f$ and @f$\beta@f$.
+ */
+ explicit
+ gamma_distribution(_RealType __alpha_val = _RealType(1),
+ _RealType __beta_val = _RealType(1))
+ : _M_param(__alpha_val, __beta_val), _M_nd()
+ { }
+
+ explicit
+ gamma_distribution(const param_type& __p)
+ : _M_param(__p), _M_nd()
+ { }
+
+ /**
+ * @brief Resets the distribution state.
+ */
+ void
+ reset()
+ { _M_nd.reset(); }
+
+ /**
+ * @brief Returns the @f$\alpha@f$ of the distribution.
+ */
+ _RealType
+ alpha() const
+ { return _M_param.alpha(); }
+
+ /**
+ * @brief Returns the @f$\beta@f$ of the distribution.
+ */
+ _RealType
+ beta() const
+ { return _M_param.beta(); }
+
+ /**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
+ * @brief Returns the greatest lower bound value of the distribution.
+ */
+ result_type
+ min() const
+ { return result_type(0); }
+
+ /**
+ * @brief Returns the least upper bound value of the distribution.
+ */
+ result_type
+ max() const
+ { return std::numeric_limits<result_type>::max(); }
+
+ /**
+ * @brief Generating functions.
+ */
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng)
+ { return this->operator()(__urng, _M_param); }
+
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
+ /**
+ * @brief Return true if two gamma distributions have the same
+ * parameters and the sequences that would be generated
+ * are equal.
+ */
+ friend bool
+ operator==(const gamma_distribution& __d1,
+ const gamma_distribution& __d2)
+ { return (__d1._M_param == __d2._M_param
+ && __d1._M_nd == __d2._M_nd); }
+
+ /**
+ * @brief Inserts a %gamma_distribution random number distribution
+ * @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %gamma_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::gamma_distribution<_RealType1>& __x);
+
+ /**
+ * @brief Extracts a %gamma_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %gamma_distribution random number generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::gamma_distribution<_RealType1>& __x);
+
+ private:
+ param_type _M_param;
+
+ std::normal_distribution<result_type> _M_nd;
+ };
+
+ /**
+ * @brief Return true if two gamma distributions are different.
+ */
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::gamma_distribution<_RealType>& __d1,
+ const std::gamma_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
+
+
+ /**
+ * @brief A chi_squared_distribution random number distribution.
+ *
+ * The formula for the normal probability mass function is
+ * @f$p(x|n) = \frac{x^{(n/2) - 1}e^{-x/2}}{\Gamma(n/2) 2^{n/2}}@f$
+ */
+ template<typename _RealType = double>
+ class chi_squared_distribution
+ {
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
+ public:
+ /** The type of the range of the distribution. */
+ typedef _RealType result_type;
+ /** Parameter type. */
+ struct param_type
+ {
+ typedef chi_squared_distribution<_RealType> distribution_type;
+
+ explicit
+ param_type(_RealType __n = _RealType(1))
+ : _M_n(__n)
+ { }
+
+ _RealType
+ n() const
+ { return _M_n; }
+
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_n == __p2._M_n; }
+
+ private:
+ _RealType _M_n;
+ };
+
+ explicit
+ chi_squared_distribution(_RealType __n = _RealType(1))
+ : _M_param(__n), _M_gd(__n / 2)
+ { }
+
+ explicit
+ chi_squared_distribution(const param_type& __p)
+ : _M_param(__p), _M_gd(__p.n() / 2)
+ { }
+
+ /**
+ * @brief Resets the distribution state.
+ */
+ void
+ reset()
+ { _M_gd.reset(); }
+
+ /**
+ *
+ */
+ _RealType
+ n() const
+ { return _M_param.n(); }
+
+ /**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
+ * @brief Returns the greatest lower bound value of the distribution.
+ */
+ result_type
+ min() const
+ { return result_type(0); }
+
+ /**
+ * @brief Returns the least upper bound value of the distribution.
+ */
+ result_type
+ max() const
+ { return std::numeric_limits<result_type>::max(); }
+
+ /**
+ * @brief Generating functions.
+ */
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng)
+ { return 2 * _M_gd(__urng); }
+
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ {
+ typedef typename std::gamma_distribution<result_type>::param_type
+ param_type;
+ return 2 * _M_gd(__urng, param_type(__p.n() / 2));
+ }
+
+ /**
+ * @brief Return true if two Chi-squared distributions have
+ * the same parameters and the sequences that would be
+ * generated are equal.
+ */
+ friend bool
+ operator==(const chi_squared_distribution& __d1,
+ const chi_squared_distribution& __d2)
+ { return __d1._M_param == __d2._M_param && __d1._M_gd == __d2._M_gd; }
+
+ /**
+ * @brief Inserts a %chi_squared_distribution random number distribution
+ * @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %chi_squared_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::chi_squared_distribution<_RealType1>& __x);
+
+ /**
+ * @brief Extracts a %chi_squared_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %chi_squared_distribution random number
+ * generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::chi_squared_distribution<_RealType1>& __x);
+
+ private:
+ param_type _M_param;
+
+ std::gamma_distribution<result_type> _M_gd;
+ };
+
+ /**
+ * @brief Return true if two Chi-squared distributions are different.
+ */
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::chi_squared_distribution<_RealType>& __d1,
+ const std::chi_squared_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
+
+
+ /**
+ * @brief A cauchy_distribution random number distribution.
+ *
+ * The formula for the normal probability mass function is
+ * @f$p(x|a,b) = (\pi b (1 + (\frac{x-a}{b})^2))^{-1}@f$
+ */
+ template<typename _RealType = double>
+ class cauchy_distribution
+ {
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
+ public:
+ /** The type of the range of the distribution. */
+ typedef _RealType result_type;
+ /** Parameter type. */
+ struct param_type
+ {
+ typedef cauchy_distribution<_RealType> distribution_type;
+
+ explicit
+ param_type(_RealType __a = _RealType(0),
+ _RealType __b = _RealType(1))
+ : _M_a(__a), _M_b(__b)
+ { }
+
+ _RealType
+ a() const
+ { return _M_a; }
+
+ _RealType
+ b() const
+ { return _M_b; }
+
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; }
+
+ private:
+ _RealType _M_a;
+ _RealType _M_b;
+ };
+
+ explicit
+ cauchy_distribution(_RealType __a = _RealType(0),
+ _RealType __b = _RealType(1))
+ : _M_param(__a, __b)
+ { }
+
+ explicit
+ cauchy_distribution(const param_type& __p)
+ : _M_param(__p)
+ { }
+
+ /**
+ * @brief Resets the distribution state.
+ */
+ void
+ reset()
+ { }
+
+ /**
+ *
+ */
+ _RealType
+ a() const
+ { return _M_param.a(); }
+
+ _RealType
+ b() const
+ { return _M_param.b(); }
+
+ /**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
+ * @brief Returns the greatest lower bound value of the distribution.
+ */
+ result_type
+ min() const
+ { return std::numeric_limits<result_type>::min(); }
+
+ /**
+ * @brief Returns the least upper bound value of the distribution.
+ */
+ result_type
+ max() const
+ { return std::numeric_limits<result_type>::max(); }
+
+ /**
+ * @brief Generating functions.
+ */
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng)
+ { return this->operator()(__urng, _M_param); }
+
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
+ /**
+ * @brief Return true if two Cauchy distributions have
+ * the same parameters.
+ */
+ friend bool
+ operator==(const cauchy_distribution& __d1,
+ const cauchy_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
+ private:
+ param_type _M_param;
+ };
+
+ /**
+ * @brief Return true if two Cauchy distributions have
+ * different parameters.
+ */
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::cauchy_distribution<_RealType>& __d1,
+ const std::cauchy_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
+
+ /**
+ * @brief Inserts a %cauchy_distribution random number distribution
+ * @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %cauchy_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _RealType, typename _CharT, typename _Traits>
+ std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::cauchy_distribution<_RealType>& __x);
+
+ /**
+ * @brief Extracts a %cauchy_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %cauchy_distribution random number
+ * generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error state.
+ */
+ template<typename _RealType, typename _CharT, typename _Traits>
+ std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::cauchy_distribution<_RealType>& __x);
+
+
+ /**
+ * @brief A fisher_f_distribution random number distribution.
+ *
+ * The formula for the normal probability mass function is
+ * @f[
+ * p(x|m,n) = \frac{\Gamma((m+n)/2)}{\Gamma(m/2)\Gamma(n/2)}
+ * (\frac{m}{n})^{m/2} x^{(m/2)-1}
+ * (1 + \frac{mx}{n})^{-(m+n)/2}
+ * @f]
+ */
+ template<typename _RealType = double>
+ class fisher_f_distribution
+ {
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
+ public:
+ /** The type of the range of the distribution. */
+ typedef _RealType result_type;
+ /** Parameter type. */
+ struct param_type
+ {
+ typedef fisher_f_distribution<_RealType> distribution_type;
+
+ explicit
+ param_type(_RealType __m = _RealType(1),
+ _RealType __n = _RealType(1))
+ : _M_m(__m), _M_n(__n)
+ { }
+
+ _RealType
+ m() const
+ { return _M_m; }
+
+ _RealType
+ n() const
+ { return _M_n; }
+
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_m == __p2._M_m && __p1._M_n == __p2._M_n; }
+
+ private:
+ _RealType _M_m;
+ _RealType _M_n;
+ };
+
+ explicit
+ fisher_f_distribution(_RealType __m = _RealType(1),
+ _RealType __n = _RealType(1))
+ : _M_param(__m, __n), _M_gd_x(__m / 2), _M_gd_y(__n / 2)
+ { }
+
+ explicit
+ fisher_f_distribution(const param_type& __p)
+ : _M_param(__p), _M_gd_x(__p.m() / 2), _M_gd_y(__p.n() / 2)
+ { }
+
+ /**
+ * @brief Resets the distribution state.
+ */
+ void
+ reset()
+ {
+ _M_gd_x.reset();
+ _M_gd_y.reset();
+ }
+
+ /**
+ *
+ */
+ _RealType
+ m() const
+ { return _M_param.m(); }
+
+ _RealType
+ n() const
+ { return _M_param.n(); }
+
+ /**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
+ * @brief Returns the greatest lower bound value of the distribution.
+ */
+ result_type
+ min() const
+ { return result_type(0); }
+
+ /**
+ * @brief Returns the least upper bound value of the distribution.
+ */
+ result_type
+ max() const
+ { return std::numeric_limits<result_type>::max(); }
+
+ /**
+ * @brief Generating functions.
+ */
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng)
+ { return (_M_gd_x(__urng) * n()) / (_M_gd_y(__urng) * m()); }
+
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ {
+ typedef typename std::gamma_distribution<result_type>::param_type
+ param_type;
+ return ((_M_gd_x(__urng, param_type(__p.m() / 2)) * n())
+ / (_M_gd_y(__urng, param_type(__p.n() / 2)) * m()));
+ }
+
+ /**
+ * @brief Return true if two Fisher f distributions have
+ * the same parameters and the sequences that would
+ * be generated are equal.
+ */
+ friend bool
+ operator==(const fisher_f_distribution& __d1,
+ const fisher_f_distribution& __d2)
+ { return (__d1._M_param == __d2._M_param
+ && __d1._M_gd_x == __d2._M_gd_x
+ && __d1._M_gd_y == __d2._M_gd_y); }
+
+ /**
+ * @brief Inserts a %fisher_f_distribution random number distribution
+ * @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %fisher_f_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::fisher_f_distribution<_RealType1>& __x);
+
+ /**
+ * @brief Extracts a %fisher_f_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %fisher_f_distribution random number
+ * generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::fisher_f_distribution<_RealType1>& __x);
+
+ private:
+ param_type _M_param;
+
+ std::gamma_distribution<result_type> _M_gd_x, _M_gd_y;
+ };
+
+ /**
+ * @brief Return true if two Fisher f distributions are diferent.
+ */
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::fisher_f_distribution<_RealType>& __d1,
+ const std::fisher_f_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
+
+ /**
+ * @brief A student_t_distribution random number distribution.
+ *
+ * The formula for the normal probability mass function is:
+ * @f[
+ * p(x|n) = \frac{1}{\sqrt(n\pi)} \frac{\Gamma((n+1)/2)}{\Gamma(n/2)}
+ * (1 + \frac{x^2}{n}) ^{-(n+1)/2}
+ * @f]
+ */
+ template<typename _RealType = double>
+ class student_t_distribution
+ {
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
+ public:
+ /** The type of the range of the distribution. */
+ typedef _RealType result_type;
+ /** Parameter type. */
+ struct param_type
+ {
+ typedef student_t_distribution<_RealType> distribution_type;
+
+ explicit
+ param_type(_RealType __n = _RealType(1))
+ : _M_n(__n)
+ { }
+
+ _RealType
+ n() const
+ { return _M_n; }
+
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_n == __p2._M_n; }
+
+ private:
+ _RealType _M_n;
+ };
+
+ explicit
+ student_t_distribution(_RealType __n = _RealType(1))
+ : _M_param(__n), _M_nd(), _M_gd(__n / 2, 2)
+ { }
+
+ explicit
+ student_t_distribution(const param_type& __p)
+ : _M_param(__p), _M_nd(), _M_gd(__p.n() / 2, 2)
+ { }
+
+ /**
+ * @brief Resets the distribution state.
+ */
+ void
+ reset()
+ {
+ _M_nd.reset();
+ _M_gd.reset();
+ }
+
+ /**
+ *
+ */
+ _RealType
+ n() const
+ { return _M_param.n(); }
+
+ /**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
+ * @brief Returns the greatest lower bound value of the distribution.
+ */
+ result_type
+ min() const
+ { return std::numeric_limits<result_type>::min(); }
+
+ /**
+ * @brief Returns the least upper bound value of the distribution.
+ */
+ result_type
+ max() const
+ { return std::numeric_limits<result_type>::max(); }
+
+ /**
+ * @brief Generating functions.
+ */
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng)
+ { return _M_nd(__urng) * std::sqrt(n() / _M_gd(__urng)); }
+
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ {
+ typedef typename std::gamma_distribution<result_type>::param_type
+ param_type;
+
+ const result_type __g = _M_gd(__urng, param_type(__p.n() / 2, 2));
+ return _M_nd(__urng) * std::sqrt(__p.n() / __g);
+ }
+
+ /**
+ * @brief Return true if two Student t distributions have
+ * the same parameters and the sequences that would
+ * be generated are equal.
+ */
+ friend bool
+ operator==(const student_t_distribution& __d1,
+ const student_t_distribution& __d2)
+ { return (__d1._M_param == __d2._M_param
+ && __d1._M_nd == __d2._M_nd && __d1._M_gd == __d2._M_gd); }
+
+ /**
+ * @brief Inserts a %student_t_distribution random number distribution
+ * @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %student_t_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::student_t_distribution<_RealType1>& __x);
+
+ /**
+ * @brief Extracts a %student_t_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %student_t_distribution random number
+ * generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::student_t_distribution<_RealType1>& __x);
+
+ private:
+ param_type _M_param;
+
+ std::normal_distribution<result_type> _M_nd;
+ std::gamma_distribution<result_type> _M_gd;
+ };
+
+ /**
+ * @brief Return true if two Student t distributions are different.
+ */
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::student_t_distribution<_RealType>& __d1,
+ const std::student_t_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
+
+
+ /* @} */ // group random_distributions_normal
+
+ /**
+ * @addtogroup random_distributions_bernoulli Bernoulli Distributions
+ * @ingroup random_distributions
+ * @{
+ */
+
+ /**
+ * @brief A Bernoulli random number distribution.
+ *
+ * Generates a sequence of true and false values with likelihood @f$p@f$
+ * that true will come up and @f$(1 - p)@f$ that false will appear.
+ */
+ class bernoulli_distribution
+ {
+ public:
+ /** The type of the range of the distribution. */
+ typedef bool result_type;
+ /** Parameter type. */
+ struct param_type
+ {
+ typedef bernoulli_distribution distribution_type;
+
+ explicit
+ param_type(double __p = 0.5)
+ : _M_p(__p)
+ {
+ _GLIBCXX_DEBUG_ASSERT((_M_p >= 0.0) && (_M_p <= 1.0));
+ }
+
+ double
+ p() const
+ { return _M_p; }
+
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_p == __p2._M_p; }
+
+ private:
+ double _M_p;
+ };
+
+ public:
+ /**
+ * @brief Constructs a Bernoulli distribution with likelihood @p p.
+ *
+ * @param __p [IN] The likelihood of a true result being returned.
+ * Must be in the interval @f$[0, 1]@f$.
+ */
+ explicit
+ bernoulli_distribution(double __p = 0.5)
+ : _M_param(__p)
+ { }
+
+ explicit
+ bernoulli_distribution(const param_type& __p)
+ : _M_param(__p)
+ { }
+
+ /**
+ * @brief Resets the distribution state.
+ *
+ * Does nothing for a Bernoulli distribution.
+ */
+ void
+ reset() { }
+
+ /**
+ * @brief Returns the @p p parameter of the distribution.
+ */
+ double
+ p() const
+ { return _M_param.p(); }
+
+ /**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
+ * @brief Returns the greatest lower bound value of the distribution.
+ */
+ result_type
+ min() const
+ { return std::numeric_limits<result_type>::min(); }
+
+ /**
+ * @brief Returns the least upper bound value of the distribution.
+ */
+ result_type
+ max() const
+ { return std::numeric_limits<result_type>::max(); }
+
+ /**
+ * @brief Generating functions.
+ */
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng)
+ { return this->operator()(__urng, _M_param); }
+
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ {
+ __detail::_Adaptor<_UniformRandomNumberGenerator, double>
+ __aurng(__urng);
+ if ((__aurng() - __aurng.min())
+ < __p.p() * (__aurng.max() - __aurng.min()))
+ return true;
+ return false;
+ }
+
+ /**
+ * @brief Return true if two Bernoulli distributions have
+ * the same parameters.
+ */
+ friend bool
+ operator==(const bernoulli_distribution& __d1,
+ const bernoulli_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
+ private:
+ param_type _M_param;
+ };
+
+ /**
+ * @brief Return true if two Bernoulli distributions have
+ * different parameters.
+ */
+ inline bool
+ operator!=(const std::bernoulli_distribution& __d1,
+ const std::bernoulli_distribution& __d2)
+ { return !(__d1 == __d2); }
+
+ /**
+ * @brief Inserts a %bernoulli_distribution random number distribution
+ * @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %bernoulli_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _CharT, typename _Traits>
+ std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::bernoulli_distribution& __x);
+
+ /**
+ * @brief Extracts a %bernoulli_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %bernoulli_distribution random number generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error state.
+ */
+ template<typename _CharT, typename _Traits>
+ std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::bernoulli_distribution& __x)
+ {
+ double __p;
+ __is >> __p;
+ __x.param(bernoulli_distribution::param_type(__p));
+ return __is;
+ }
+
+
+ /**
+ * @brief A discrete binomial random number distribution.
+ *
+ * The formula for the binomial probability density function is
+ * @f$p(i|t,p) = \binom{n}{i} p^i (1 - p)^{t - i}@f$ where @f$t@f$
+ * and @f$p@f$ are the parameters of the distribution.
+ */
+ template<typename _IntType = int>
+ class binomial_distribution
+ {
+ static_assert(std::is_integral<_IntType>::value,
+ "template argument not an integral type");
+
+ public:
+ /** The type of the range of the distribution. */
+ typedef _IntType result_type;
+ /** Parameter type. */
+ struct param_type
+ {
+ typedef binomial_distribution<_IntType> distribution_type;
+ friend class binomial_distribution<_IntType>;
+
+ explicit
+ param_type(_IntType __t = _IntType(1), double __p = 0.5)
+ : _M_t(__t), _M_p(__p)
+ {
+ _GLIBCXX_DEBUG_ASSERT((_M_t >= _IntType(0))
+ && (_M_p >= 0.0)
+ && (_M_p <= 1.0));
+ _M_initialize();
+ }
+
+ _IntType
+ t() const
+ { return _M_t; }
+
+ double
+ p() const
+ { return _M_p; }
+
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_t == __p2._M_t && __p1._M_p == __p2._M_p; }
+
+ private:
+ void
+ _M_initialize();
+
+ _IntType _M_t;
+ double _M_p;
+
+ double _M_q;
+#if _GLIBCXX_USE_C99_MATH_TR1
+ double _M_d1, _M_d2, _M_s1, _M_s2, _M_c,
+ _M_a1, _M_a123, _M_s, _M_lf, _M_lp1p;
+#endif
+ bool _M_easy;
+ };
+
+ // constructors and member function
+ explicit
+ binomial_distribution(_IntType __t = _IntType(1),
+ double __p = 0.5)
+ : _M_param(__t, __p), _M_nd()
+ { }
+
+ explicit
+ binomial_distribution(const param_type& __p)
+ : _M_param(__p), _M_nd()
+ { }
+
+ /**
+ * @brief Resets the distribution state.
+ */
+ void
+ reset()
+ { _M_nd.reset(); }
+
+ /**
+ * @brief Returns the distribution @p t parameter.
+ */
+ _IntType
+ t() const
+ { return _M_param.t(); }
+
+ /**
+ * @brief Returns the distribution @p p parameter.
+ */
+ double
+ p() const
+ { return _M_param.p(); }
+
+ /**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
+ * @brief Returns the greatest lower bound value of the distribution.
+ */
+ result_type
+ min() const
+ { return 0; }
+
+ /**
+ * @brief Returns the least upper bound value of the distribution.
+ */
+ result_type
+ max() const
+ { return _M_param.t(); }
+
+ /**
+ * @brief Generating functions.
+ */
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng)
+ { return this->operator()(__urng, _M_param); }
+
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
+ /**
+ * @brief Return true if two binomial distributions have
+ * the same parameters and the sequences that would
+ * be generated are equal.
+ */
+ friend bool
+ operator==(const binomial_distribution& __d1,
+ const binomial_distribution& __d2)
+#ifdef _GLIBCXX_USE_C99_MATH_TR1
+ { return __d1._M_param == __d2._M_param && __d1._M_nd == __d2._M_nd; }
+#else
+ { return __d1._M_param == __d2._M_param; }
+#endif
+
+ /**
+ * @brief Inserts a %binomial_distribution random number distribution
+ * @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %binomial_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _IntType1,
+ typename _CharT, typename _Traits>
+ friend std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::binomial_distribution<_IntType1>& __x);
+
+ /**
+ * @brief Extracts a %binomial_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %binomial_distribution random number generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error
+ * state.
+ */
+ template<typename _IntType1,
+ typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::binomial_distribution<_IntType1>& __x);
+
+ private:
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ _M_waiting(_UniformRandomNumberGenerator& __urng, _IntType __t);
+
+ param_type _M_param;
+
+ // NB: Unused when _GLIBCXX_USE_C99_MATH_TR1 is undefined.
+ std::normal_distribution<double> _M_nd;
+ };
+
+ /**
+ * @brief Return true if two binomial distributions are different.
+ */
+ template<typename _IntType>
+ inline bool
+ operator!=(const std::binomial_distribution<_IntType>& __d1,
+ const std::binomial_distribution<_IntType>& __d2)
+ { return !(__d1 == __d2); }
+
+
+ /**
+ * @brief A discrete geometric random number distribution.
+ *
+ * The formula for the geometric probability density function is
+ * @f$p(i|p) = p(1 - p)^{i}@f$ where @f$p@f$ is the parameter of the
+ * distribution.
+ */
+ template<typename _IntType = int>
+ class geometric_distribution
+ {
+ static_assert(std::is_integral<_IntType>::value,
+ "template argument not an integral type");
+
+ public:
+ /** The type of the range of the distribution. */
+ typedef _IntType result_type;
+ /** Parameter type. */
+ struct param_type
+ {
+ typedef geometric_distribution<_IntType> distribution_type;
+ friend class geometric_distribution<_IntType>;
+
+ explicit
+ param_type(double __p = 0.5)
+ : _M_p(__p)
+ {
+ _GLIBCXX_DEBUG_ASSERT((_M_p > 0.0) && (_M_p < 1.0));
+ _M_initialize();
+ }
+
+ double
+ p() const
+ { return _M_p; }
+
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_p == __p2._M_p; }
+
+ private:
+ void
+ _M_initialize()
+ { _M_log_1_p = std::log(1.0 - _M_p); }
+
+ double _M_p;
+
+ double _M_log_1_p;
+ };
+
+ // constructors and member function
+ explicit
+ geometric_distribution(double __p = 0.5)
+ : _M_param(__p)
+ { }
+
+ explicit
+ geometric_distribution(const param_type& __p)
+ : _M_param(__p)
+ { }
+
+ /**
+ * @brief Resets the distribution state.
+ *
+ * Does nothing for the geometric distribution.
+ */
+ void
+ reset() { }
+
+ /**
+ * @brief Returns the distribution parameter @p p.
+ */
+ double
+ p() const
+ { return _M_param.p(); }
+
+ /**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
+ * @brief Returns the greatest lower bound value of the distribution.
+ */
+ result_type
+ min() const
+ { return 0; }
+
+ /**
+ * @brief Returns the least upper bound value of the distribution.
+ */
+ result_type
+ max() const
+ { return std::numeric_limits<result_type>::max(); }
+
+ /**
+ * @brief Generating functions.
+ */
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng)
+ { return this->operator()(__urng, _M_param); }
+
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
+ /**
+ * @brief Return true if two geometric distributions have
+ * the same parameters.
+ */
+ friend bool
+ operator==(const geometric_distribution& __d1,
+ const geometric_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
+ private:
+ param_type _M_param;
+ };
+
+ /**
+ * @brief Return true if two geometric distributions have
+ * different parameters.
+ */
+ template<typename _IntType>
+ inline bool
+ operator!=(const std::geometric_distribution<_IntType>& __d1,
+ const std::geometric_distribution<_IntType>& __d2)
+ { return !(__d1 == __d2); }
+
+ /**
+ * @brief Inserts a %geometric_distribution random number distribution
+ * @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %geometric_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _IntType,
+ typename _CharT, typename _Traits>
+ std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::geometric_distribution<_IntType>& __x);
+
+ /**
+ * @brief Extracts a %geometric_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %geometric_distribution random number generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error state.
+ */
+ template<typename _IntType,
+ typename _CharT, typename _Traits>
+ std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::geometric_distribution<_IntType>& __x);
+
+
+ /**
+ * @brief A negative_binomial_distribution random number distribution.
+ *
+ * The formula for the negative binomial probability mass function is
+ * @f$p(i) = \binom{n}{i} p^i (1 - p)^{t - i}@f$ where @f$t@f$
+ * and @f$p@f$ are the parameters of the distribution.
+ */
+ template<typename _IntType = int>
+ class negative_binomial_distribution
+ {
+ static_assert(std::is_integral<_IntType>::value,
+ "template argument not an integral type");
+
+ public:
+ /** The type of the range of the distribution. */
+ typedef _IntType result_type;
+ /** Parameter type. */
+ struct param_type
+ {
+ typedef negative_binomial_distribution<_IntType> distribution_type;
+
+ explicit
+ param_type(_IntType __k = 1, double __p = 0.5)
+ : _M_k(__k), _M_p(__p)
+ {
+ _GLIBCXX_DEBUG_ASSERT((_M_k > 0) && (_M_p > 0.0) && (_M_p <= 1.0));
+ }
+
+ _IntType
+ k() const
+ { return _M_k; }
+
+ double
+ p() const
+ { return _M_p; }
+
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_k == __p2._M_k && __p1._M_p == __p2._M_p; }
+
+ private:
+ _IntType _M_k;
+ double _M_p;
+ };
+
+ explicit
+ negative_binomial_distribution(_IntType __k = 1, double __p = 0.5)
+ : _M_param(__k, __p), _M_gd(__k, (1.0 - __p) / __p)
+ { }
+
+ explicit
+ negative_binomial_distribution(const param_type& __p)
+ : _M_param(__p), _M_gd(__p.k(), (1.0 - __p.p()) / __p.p())
+ { }
+
+ /**
+ * @brief Resets the distribution state.
+ */
+ void
+ reset()
+ { _M_gd.reset(); }
+
+ /**
+ * @brief Return the @f$k@f$ parameter of the distribution.
+ */
+ _IntType
+ k() const
+ { return _M_param.k(); }
+
+ /**
+ * @brief Return the @f$p@f$ parameter of the distribution.
+ */
+ double
+ p() const
+ { return _M_param.p(); }
+
+ /**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
+ * @brief Returns the greatest lower bound value of the distribution.
+ */
+ result_type
+ min() const
+ { return result_type(0); }
+
+ /**
+ * @brief Returns the least upper bound value of the distribution.
+ */
+ result_type
+ max() const
+ { return std::numeric_limits<result_type>::max(); }
+
+ /**
+ * @brief Generating functions.
+ */
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng);
+
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
+ /**
+ * @brief Return true if two negative binomial distributions have
+ * the same parameters and the sequences that would be
+ * generated are equal.
+ */
+ friend bool
+ operator==(const negative_binomial_distribution& __d1,
+ const negative_binomial_distribution& __d2)
+ { return __d1._M_param == __d2._M_param && __d1._M_gd == __d2._M_gd; }
+
+ /**
+ * @brief Inserts a %negative_binomial_distribution random
+ * number distribution @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %negative_binomial_distribution random number
+ * distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _IntType1, typename _CharT, typename _Traits>
+ friend std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::negative_binomial_distribution<_IntType1>& __x);
+
+ /**
+ * @brief Extracts a %negative_binomial_distribution random number
+ * distribution @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %negative_binomial_distribution random number
+ * generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error state.
+ */
+ template<typename _IntType1, typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::negative_binomial_distribution<_IntType1>& __x);
+
+ private:
+ param_type _M_param;
+
+ std::gamma_distribution<double> _M_gd;
+ };
+
+ /**
+ * @brief Return true if two negative binomial distributions are different.
+ */
+ template<typename _IntType>
+ inline bool
+ operator!=(const std::negative_binomial_distribution<_IntType>& __d1,
+ const std::negative_binomial_distribution<_IntType>& __d2)
+ { return !(__d1 == __d2); }
+
+
+ /* @} */ // group random_distributions_bernoulli
+
+ /**
+ * @addtogroup random_distributions_poisson Poisson Distributions
+ * @ingroup random_distributions
+ * @{
+ */
+
+ /**
+ * @brief A discrete Poisson random number distribution.
+ *
+ * The formula for the Poisson probability density function is
+ * @f$p(i|\mu) = \frac{\mu^i}{i!} e^{-\mu}@f$ where @f$\mu@f$ is the
+ * parameter of the distribution.
+ */
+ template<typename _IntType = int>
+ class poisson_distribution
+ {
+ static_assert(std::is_integral<_IntType>::value,
+ "template argument not an integral type");
+
+ public:
+ /** The type of the range of the distribution. */
+ typedef _IntType result_type;
+ /** Parameter type. */
+ struct param_type
+ {
+ typedef poisson_distribution<_IntType> distribution_type;
+ friend class poisson_distribution<_IntType>;
+
+ explicit
+ param_type(double __mean = 1.0)
+ : _M_mean(__mean)
+ {
+ _GLIBCXX_DEBUG_ASSERT(_M_mean > 0.0);
+ _M_initialize();
+ }
+
+ double
+ mean() const
+ { return _M_mean; }
+
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_mean == __p2._M_mean; }
+
+ private:
+ // Hosts either log(mean) or the threshold of the simple method.
+ void
+ _M_initialize();
+
+ double _M_mean;
+
+ double _M_lm_thr;
+#if _GLIBCXX_USE_C99_MATH_TR1
+ double _M_lfm, _M_sm, _M_d, _M_scx, _M_1cx, _M_c2b, _M_cb;
+#endif
+ };
+
+ // constructors and member function
+ explicit
+ poisson_distribution(double __mean = 1.0)
+ : _M_param(__mean), _M_nd()
+ { }
+
+ explicit
+ poisson_distribution(const param_type& __p)
+ : _M_param(__p), _M_nd()
+ { }
+
+ /**
+ * @brief Resets the distribution state.
+ */
+ void
+ reset()
+ { _M_nd.reset(); }
+
+ /**
+ * @brief Returns the distribution parameter @p mean.
+ */
+ double
+ mean() const
+ { return _M_param.mean(); }
+
+ /**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
+ * @brief Returns the greatest lower bound value of the distribution.
+ */
+ result_type
+ min() const
+ { return 0; }
+
+ /**
+ * @brief Returns the least upper bound value of the distribution.
+ */
+ result_type
+ max() const
+ { return std::numeric_limits<result_type>::max(); }
+
+ /**
+ * @brief Generating functions.
+ */
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng)
+ { return this->operator()(__urng, _M_param); }
+
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
+ /**
+ * @brief Return true if two Poisson distributions have the same
+ * parameters and the sequences that would be generated
+ * are equal.
+ */
+ friend bool
+ operator==(const poisson_distribution& __d1,
+ const poisson_distribution& __d2)
+#ifdef _GLIBCXX_USE_C99_MATH_TR1
+ { return __d1._M_param == __d2._M_param && __d1._M_nd == __d2._M_nd; }
+#else
+ { return __d1._M_param == __d2._M_param; }
+#endif
+
+ /**
+ * @brief Inserts a %poisson_distribution random number distribution
+ * @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %poisson_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _IntType1, typename _CharT, typename _Traits>
+ friend std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::poisson_distribution<_IntType1>& __x);
+
+ /**
+ * @brief Extracts a %poisson_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %poisson_distribution random number generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error
+ * state.
+ */
+ template<typename _IntType1, typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::poisson_distribution<_IntType1>& __x);
+
+ private:
+ param_type _M_param;
+
+ // NB: Unused when _GLIBCXX_USE_C99_MATH_TR1 is undefined.
+ std::normal_distribution<double> _M_nd;
+ };
+
+ /**
+ * @brief Return true if two Poisson distributions are different.
+ */
+ template<typename _IntType>
+ inline bool
+ operator!=(const std::poisson_distribution<_IntType>& __d1,
+ const std::poisson_distribution<_IntType>& __d2)
+ { return !(__d1 == __d2); }
+
+
+ /**
+ * @brief An exponential continuous distribution for random numbers.
+ *
+ * The formula for the exponential probability density function is
+ * @f$p(x|\lambda) = \lambda e^{-\lambda x}@f$.
+ *
+ * <table border=1 cellpadding=10 cellspacing=0>
+ * <caption align=top>Distribution Statistics</caption>
+ * <tr><td>Mean</td><td>@f$\frac{1}{\lambda}@f$</td></tr>
+ * <tr><td>Median</td><td>@f$\frac{\ln 2}{\lambda}@f$</td></tr>
+ * <tr><td>Mode</td><td>@f$zero@f$</td></tr>
+ * <tr><td>Range</td><td>@f$[0, \infty]@f$</td></tr>
+ * <tr><td>Standard Deviation</td><td>@f$\frac{1}{\lambda}@f$</td></tr>
+ * </table>
+ */
+ template<typename _RealType = double>
+ class exponential_distribution
+ {
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
+ public:
+ /** The type of the range of the distribution. */
+ typedef _RealType result_type;
+ /** Parameter type. */
+ struct param_type
+ {
+ typedef exponential_distribution<_RealType> distribution_type;
+
+ explicit
+ param_type(_RealType __lambda = _RealType(1))
+ : _M_lambda(__lambda)
+ {
+ _GLIBCXX_DEBUG_ASSERT(_M_lambda > _RealType(0));
+ }
+
+ _RealType
+ lambda() const
+ { return _M_lambda; }
+
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_lambda == __p2._M_lambda; }
+
+ private:
+ _RealType _M_lambda;
+ };
+
+ public:
+ /**
+ * @brief Constructs an exponential distribution with inverse scale
+ * parameter @f$\lambda@f$.
+ */
+ explicit
+ exponential_distribution(const result_type& __lambda = result_type(1))
+ : _M_param(__lambda)
+ { }
+
+ explicit
+ exponential_distribution(const param_type& __p)
+ : _M_param(__p)
+ { }
+
+ /**
+ * @brief Resets the distribution state.
+ *
+ * Has no effect on exponential distributions.
+ */
+ void
+ reset() { }
+
+ /**
+ * @brief Returns the inverse scale parameter of the distribution.
+ */
+ _RealType
+ lambda() const
+ { return _M_param.lambda(); }
+
+ /**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
+ * @brief Returns the greatest lower bound value of the distribution.
+ */
+ result_type
+ min() const
+ { return result_type(0); }
+
+ /**
+ * @brief Returns the least upper bound value of the distribution.
+ */
+ result_type
+ max() const
+ { return std::numeric_limits<result_type>::max(); }
+
+ /**
+ * @brief Generating functions.
+ */
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng)
+ { return this->operator()(__urng, _M_param); }
+
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng,
+ const param_type& __p)
+ {
+ __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
+ __aurng(__urng);
+ return -std::log(result_type(1) - __aurng()) / __p.lambda();
+ }
+
+ /**
+ * @brief Return true if two exponential distributions have the same
+ * parameters.
+ */
+ friend bool
+ operator==(const exponential_distribution& __d1,
+ const exponential_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
+ private:
+ param_type _M_param;
+ };
+
+ /**
+ * @brief Return true if two exponential distributions have different
+ * parameters.
+ */
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::exponential_distribution<_RealType>& __d1,
+ const std::exponential_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
+
+ /**
+ * @brief Inserts a %exponential_distribution random number distribution
+ * @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %exponential_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _RealType, typename _CharT, typename _Traits>
+ std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::exponential_distribution<_RealType>& __x);
+
+ /**
+ * @brief Extracts a %exponential_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %exponential_distribution random number
+ * generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error state.
+ */
+ template<typename _RealType, typename _CharT, typename _Traits>
+ std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::exponential_distribution<_RealType>& __x);
+
+
+ /**
+ * @brief A weibull_distribution random number distribution.
+ *
+ * The formula for the normal probability density function is:
+ * @f[
+ * p(x|\alpha,\beta) = \frac{\alpha}{\beta} (\frac{x}{\beta})^{\alpha-1}
+ * \exp{(-(\frac{x}{\beta})^\alpha)}
+ * @f]
+ */
+ template<typename _RealType = double>
+ class weibull_distribution
+ {
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
+ public:
+ /** The type of the range of the distribution. */
+ typedef _RealType result_type;
+ /** Parameter type. */
+ struct param_type
+ {
+ typedef weibull_distribution<_RealType> distribution_type;
+
+ explicit
+ param_type(_RealType __a = _RealType(1),
+ _RealType __b = _RealType(1))
+ : _M_a(__a), _M_b(__b)
+ { }
+
+ _RealType
+ a() const
+ { return _M_a; }
+
+ _RealType
+ b() const
+ { return _M_b; }
+
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; }
+
+ private:
+ _RealType _M_a;
+ _RealType _M_b;
+ };
+
+ explicit
+ weibull_distribution(_RealType __a = _RealType(1),
+ _RealType __b = _RealType(1))
+ : _M_param(__a, __b)
+ { }
+
+ explicit
+ weibull_distribution(const param_type& __p)
+ : _M_param(__p)
+ { }
+
+ /**
+ * @brief Resets the distribution state.
+ */
+ void
+ reset()
+ { }
+
+ /**
+ * @brief Return the @f$a@f$ parameter of the distribution.
+ */
+ _RealType
+ a() const
+ { return _M_param.a(); }
+
+ /**
+ * @brief Return the @f$b@f$ parameter of the distribution.
+ */
+ _RealType
+ b() const
+ { return _M_param.b(); }
+
+ /**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
+ * @brief Returns the greatest lower bound value of the distribution.
+ */
+ result_type
+ min() const
+ { return result_type(0); }
+
+ /**
+ * @brief Returns the least upper bound value of the distribution.
+ */
+ result_type
+ max() const
+ { return std::numeric_limits<result_type>::max(); }
+
+ /**
+ * @brief Generating functions.
+ */
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng)
+ { return this->operator()(__urng, _M_param); }
+
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
+ /**
+ * @brief Return true if two Weibull distributions have the same
+ * parameters.
+ */
+ friend bool
+ operator==(const weibull_distribution& __d1,
+ const weibull_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
+ private:
+ param_type _M_param;
+ };
+
+ /**
+ * @brief Return true if two Weibull distributions have different
+ * parameters.
+ */
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::weibull_distribution<_RealType>& __d1,
+ const std::weibull_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
+
+ /**
+ * @brief Inserts a %weibull_distribution random number distribution
+ * @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %weibull_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _RealType, typename _CharT, typename _Traits>
+ std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::weibull_distribution<_RealType>& __x);
+
+ /**
+ * @brief Extracts a %weibull_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %weibull_distribution random number
+ * generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error state.
+ */
+ template<typename _RealType, typename _CharT, typename _Traits>
+ std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::weibull_distribution<_RealType>& __x);
+
+
+ /**
+ * @brief A extreme_value_distribution random number distribution.
+ *
+ * The formula for the normal probability mass function is
+ * @f[
+ * p(x|a,b) = \frac{1}{b}
+ * \exp( \frac{a-x}{b} - \exp(\frac{a-x}{b}))
+ * @f]
+ */
+ template<typename _RealType = double>
+ class extreme_value_distribution
+ {
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
+ public:
+ /** The type of the range of the distribution. */
+ typedef _RealType result_type;
+ /** Parameter type. */
+ struct param_type
+ {
+ typedef extreme_value_distribution<_RealType> distribution_type;
+
+ explicit
+ param_type(_RealType __a = _RealType(0),
+ _RealType __b = _RealType(1))
+ : _M_a(__a), _M_b(__b)
+ { }
+
+ _RealType
+ a() const
+ { return _M_a; }
+
+ _RealType
+ b() const
+ { return _M_b; }
+
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; }
+
+ private:
+ _RealType _M_a;
+ _RealType _M_b;
+ };
+
+ explicit
+ extreme_value_distribution(_RealType __a = _RealType(0),
+ _RealType __b = _RealType(1))
+ : _M_param(__a, __b)
+ { }
+
+ explicit
+ extreme_value_distribution(const param_type& __p)
+ : _M_param(__p)
+ { }
+
+ /**
+ * @brief Resets the distribution state.
+ */
+ void
+ reset()
+ { }
+
+ /**
+ * @brief Return the @f$a@f$ parameter of the distribution.
+ */
+ _RealType
+ a() const
+ { return _M_param.a(); }
+
+ /**
+ * @brief Return the @f$b@f$ parameter of the distribution.
+ */
+ _RealType
+ b() const
+ { return _M_param.b(); }
+
+ /**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
+ * @brief Returns the greatest lower bound value of the distribution.
+ */
+ result_type
+ min() const
+ { return std::numeric_limits<result_type>::min(); }
+
+ /**
+ * @brief Returns the least upper bound value of the distribution.
+ */
+ result_type
+ max() const
+ { return std::numeric_limits<result_type>::max(); }
+
+ /**
+ * @brief Generating functions.
+ */
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng)
+ { return this->operator()(__urng, _M_param); }
+
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
+ /**
+ * @brief Return true if two extreme value distributions have the same
+ * parameters.
+ */
+ friend bool
+ operator==(const extreme_value_distribution& __d1,
+ const extreme_value_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
+ private:
+ param_type _M_param;
+ };
+
+ /**
+ * @brief Return true if two extreme value distributions have different
+ * parameters.
+ */
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::extreme_value_distribution<_RealType>& __d1,
+ const std::extreme_value_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
+
+ /**
+ * @brief Inserts a %extreme_value_distribution random number distribution
+ * @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %extreme_value_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _RealType, typename _CharT, typename _Traits>
+ std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::extreme_value_distribution<_RealType>& __x);
+
+ /**
+ * @brief Extracts a %extreme_value_distribution random number
+ * distribution @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %extreme_value_distribution random number
+ * generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error state.
+ */
+ template<typename _RealType, typename _CharT, typename _Traits>
+ std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::extreme_value_distribution<_RealType>& __x);
+
+
+ /**
+ * @brief A discrete_distribution random number distribution.
+ *
+ * The formula for the discrete probability mass function is
+ *
+ */
+ template<typename _IntType = int>
+ class discrete_distribution
+ {
+ static_assert(std::is_integral<_IntType>::value,
+ "template argument not an integral type");
+
+ public:
+ /** The type of the range of the distribution. */
+ typedef _IntType result_type;
+ /** Parameter type. */
+ struct param_type
+ {
+ typedef discrete_distribution<_IntType> distribution_type;
+ friend class discrete_distribution<_IntType>;
+
+ param_type()
+ : _M_prob(), _M_cp()
+ { }
+
+ template<typename _InputIterator>
+ param_type(_InputIterator __wbegin,
+ _InputIterator __wend)
+ : _M_prob(__wbegin, __wend), _M_cp()
+ { _M_initialize(); }
+
+ param_type(initializer_list<double> __wil)
+ : _M_prob(__wil.begin(), __wil.end()), _M_cp()
+ { _M_initialize(); }
+
+ template<typename _Func>
+ param_type(size_t __nw, double __xmin, double __xmax,
+ _Func __fw);
+
+ // See: http://cpp-next.com/archive/2010/10/implicit-move-must-go/
+ param_type(const param_type&) = default;
+ param_type& operator=(const param_type&) = default;
+
+ std::vector<double>
+ probabilities() const
+ { return _M_prob.empty() ? std::vector<double>(1, 1.0) : _M_prob; }
+
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_prob == __p2._M_prob; }
+
+ private:
+ void
+ _M_initialize();
+
+ std::vector<double> _M_prob;
+ std::vector<double> _M_cp;
+ };
+
+ discrete_distribution()
+ : _M_param()
+ { }
+
+ template<typename _InputIterator>
+ discrete_distribution(_InputIterator __wbegin,
+ _InputIterator __wend)
+ : _M_param(__wbegin, __wend)
+ { }
+
+ discrete_distribution(initializer_list<double> __wl)
+ : _M_param(__wl)
+ { }
+
+ template<typename _Func>
+ discrete_distribution(size_t __nw, double __xmin, double __xmax,
+ _Func __fw)
+ : _M_param(__nw, __xmin, __xmax, __fw)
+ { }
+
+ explicit
+ discrete_distribution(const param_type& __p)
+ : _M_param(__p)
+ { }
+
+ /**
+ * @brief Resets the distribution state.
+ */
+ void
+ reset()
+ { }
+
+ /**
+ * @brief Returns the probabilities of the distribution.
+ */
+ std::vector<double>
+ probabilities() const
+ {
+ return _M_param._M_prob.empty()
+ ? std::vector<double>(1, 1.0) : _M_param._M_prob;
+ }
+
+ /**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
+ * @brief Returns the greatest lower bound value of the distribution.
+ */
+ result_type
+ min() const
+ { return result_type(0); }
+
+ /**
+ * @brief Returns the least upper bound value of the distribution.
+ */
+ result_type
+ max() const
+ {
+ return _M_param._M_prob.empty()
+ ? result_type(0) : result_type(_M_param._M_prob.size() - 1);
+ }
+
+ /**
+ * @brief Generating functions.
+ */
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng)
+ { return this->operator()(__urng, _M_param); }
+
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
+ /**
+ * @brief Return true if two discrete distributions have the same
+ * parameters.
+ */
+ friend bool
+ operator==(const discrete_distribution& __d1,
+ const discrete_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
+ /**
+ * @brief Inserts a %discrete_distribution random number distribution
+ * @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %discrete_distribution random number distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _IntType1, typename _CharT, typename _Traits>
+ friend std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::discrete_distribution<_IntType1>& __x);
+
+ /**
+ * @brief Extracts a %discrete_distribution random number distribution
+ * @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %discrete_distribution random number
+ * generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error
+ * state.
+ */
+ template<typename _IntType1, typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::discrete_distribution<_IntType1>& __x);
+
+ private:
+ param_type _M_param;
+ };
+
+ /**
+ * @brief Return true if two discrete distributions have different
+ * parameters.
+ */
+ template<typename _IntType>
+ inline bool
+ operator!=(const std::discrete_distribution<_IntType>& __d1,
+ const std::discrete_distribution<_IntType>& __d2)
+ { return !(__d1 == __d2); }
+
+
+ /**
+ * @brief A piecewise_constant_distribution random number distribution.
+ *
+ * The formula for the piecewise constant probability mass function is
+ *
+ */
+ template<typename _RealType = double>
+ class piecewise_constant_distribution
+ {
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
+ public:
+ /** The type of the range of the distribution. */
+ typedef _RealType result_type;
+ /** Parameter type. */
+ struct param_type
+ {
+ typedef piecewise_constant_distribution<_RealType> distribution_type;
+ friend class piecewise_constant_distribution<_RealType>;
+
+ param_type()
+ : _M_int(), _M_den(), _M_cp()
+ { }
+
+ template<typename _InputIteratorB, typename _InputIteratorW>
+ param_type(_InputIteratorB __bfirst,
+ _InputIteratorB __bend,
+ _InputIteratorW __wbegin);
+
+ template<typename _Func>
+ param_type(initializer_list<_RealType> __bi, _Func __fw);
+
+ template<typename _Func>
+ param_type(size_t __nw, _RealType __xmin, _RealType __xmax,
+ _Func __fw);
+
+ // See: http://cpp-next.com/archive/2010/10/implicit-move-must-go/
+ param_type(const param_type&) = default;
+ param_type& operator=(const param_type&) = default;
+
+ std::vector<_RealType>
+ intervals() const
+ {
+ if (_M_int.empty())
+ {
+ std::vector<_RealType> __tmp(2);
+ __tmp[1] = _RealType(1);
+ return __tmp;
+ }
+ else
+ return _M_int;
+ }
+
+ std::vector<double>
+ densities() const
+ { return _M_den.empty() ? std::vector<double>(1, 1.0) : _M_den; }
+
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return __p1._M_int == __p2._M_int && __p1._M_den == __p2._M_den; }
+
+ private:
+ void
+ _M_initialize();
+
+ std::vector<_RealType> _M_int;
+ std::vector<double> _M_den;
+ std::vector<double> _M_cp;
+ };
+
+ explicit
+ piecewise_constant_distribution()
+ : _M_param()
+ { }
+
+ template<typename _InputIteratorB, typename _InputIteratorW>
+ piecewise_constant_distribution(_InputIteratorB __bfirst,
+ _InputIteratorB __bend,
+ _InputIteratorW __wbegin)
+ : _M_param(__bfirst, __bend, __wbegin)
+ { }
+
+ template<typename _Func>
+ piecewise_constant_distribution(initializer_list<_RealType> __bl,
+ _Func __fw)
+ : _M_param(__bl, __fw)
+ { }
+
+ template<typename _Func>
+ piecewise_constant_distribution(size_t __nw,
+ _RealType __xmin, _RealType __xmax,
+ _Func __fw)
+ : _M_param(__nw, __xmin, __xmax, __fw)
+ { }
+
+ explicit
+ piecewise_constant_distribution(const param_type& __p)
+ : _M_param(__p)
+ { }
+
+ /**
+ * @brief Resets the distribution state.
+ */
+ void
+ reset()
+ { }
+
+ /**
+ * @brief Returns a vector of the intervals.
+ */
+ std::vector<_RealType>
+ intervals() const
+ {
+ if (_M_param._M_int.empty())
+ {
+ std::vector<_RealType> __tmp(2);
+ __tmp[1] = _RealType(1);
+ return __tmp;
+ }
+ else
+ return _M_param._M_int;
+ }
+
+ /**
+ * @brief Returns a vector of the probability densities.
+ */
+ std::vector<double>
+ densities() const
+ {
+ return _M_param._M_den.empty()
+ ? std::vector<double>(1, 1.0) : _M_param._M_den;
+ }
+
+ /**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
+ * @brief Returns the greatest lower bound value of the distribution.
+ */
+ result_type
+ min() const
+ {
+ return _M_param._M_int.empty()
+ ? result_type(0) : _M_param._M_int.front();
+ }
+
+ /**
+ * @brief Returns the least upper bound value of the distribution.
+ */
+ result_type
+ max() const
+ {
+ return _M_param._M_int.empty()
+ ? result_type(1) : _M_param._M_int.back();
+ }
+
+ /**
+ * @brief Generating functions.
+ */
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng)
+ { return this->operator()(__urng, _M_param); }
+
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
+ /**
+ * @brief Return true if two piecewise constant distributions have the
+ * same parameters.
+ */
+ friend bool
+ operator==(const piecewise_constant_distribution& __d1,
+ const piecewise_constant_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
+ /**
+ * @brief Inserts a %piecewise_constan_distribution random
+ * number distribution @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %piecewise_constan_distribution random number
+ * distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::piecewise_constant_distribution<_RealType1>& __x);
+
+ /**
+ * @brief Extracts a %piecewise_constan_distribution random
+ * number distribution @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %piecewise_constan_distribution random number
+ * generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error
+ * state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::piecewise_constant_distribution<_RealType1>& __x);
+
+ private:
+ param_type _M_param;
+ };
+
+ /**
+ * @brief Return true if two piecewise constant distributions have
+ * different parameters.
+ */
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::piecewise_constant_distribution<_RealType>& __d1,
+ const std::piecewise_constant_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
+
+
+ /**
+ * @brief A piecewise_linear_distribution random number distribution.
+ *
+ * The formula for the piecewise linear probability mass function is
+ *
+ */
+ template<typename _RealType = double>
+ class piecewise_linear_distribution
+ {
+ static_assert(std::is_floating_point<_RealType>::value,
+ "template argument not a floating point type");
+
+ public:
+ /** The type of the range of the distribution. */
+ typedef _RealType result_type;
+ /** Parameter type. */
+ struct param_type
+ {
+ typedef piecewise_linear_distribution<_RealType> distribution_type;
+ friend class piecewise_linear_distribution<_RealType>;
+
+ param_type()
+ : _M_int(), _M_den(), _M_cp(), _M_m()
+ { }
+
+ template<typename _InputIteratorB, typename _InputIteratorW>
+ param_type(_InputIteratorB __bfirst,
+ _InputIteratorB __bend,
+ _InputIteratorW __wbegin);
+
+ template<typename _Func>
+ param_type(initializer_list<_RealType> __bl, _Func __fw);
+
+ template<typename _Func>
+ param_type(size_t __nw, _RealType __xmin, _RealType __xmax,
+ _Func __fw);
+
+ // See: http://cpp-next.com/archive/2010/10/implicit-move-must-go/
+ param_type(const param_type&) = default;
+ param_type& operator=(const param_type&) = default;
+
+ std::vector<_RealType>
+ intervals() const
+ {
+ if (_M_int.empty())
+ {
+ std::vector<_RealType> __tmp(2);
+ __tmp[1] = _RealType(1);
+ return __tmp;
+ }
+ else
+ return _M_int;
+ }
+
+ std::vector<double>
+ densities() const
+ { return _M_den.empty() ? std::vector<double>(2, 1.0) : _M_den; }
+
+ friend bool
+ operator==(const param_type& __p1, const param_type& __p2)
+ { return (__p1._M_int == __p2._M_int
+ && __p1._M_den == __p2._M_den); }
+
+ private:
+ void
+ _M_initialize();
+
+ std::vector<_RealType> _M_int;
+ std::vector<double> _M_den;
+ std::vector<double> _M_cp;
+ std::vector<double> _M_m;
+ };
+
+ explicit
+ piecewise_linear_distribution()
+ : _M_param()
+ { }
+
+ template<typename _InputIteratorB, typename _InputIteratorW>
+ piecewise_linear_distribution(_InputIteratorB __bfirst,
+ _InputIteratorB __bend,
+ _InputIteratorW __wbegin)
+ : _M_param(__bfirst, __bend, __wbegin)
+ { }
+
+ template<typename _Func>
+ piecewise_linear_distribution(initializer_list<_RealType> __bl,
+ _Func __fw)
+ : _M_param(__bl, __fw)
+ { }
+
+ template<typename _Func>
+ piecewise_linear_distribution(size_t __nw,
+ _RealType __xmin, _RealType __xmax,
+ _Func __fw)
+ : _M_param(__nw, __xmin, __xmax, __fw)
+ { }
+
+ explicit
+ piecewise_linear_distribution(const param_type& __p)
+ : _M_param(__p)
+ { }
+
+ /**
+ * Resets the distribution state.
+ */
+ void
+ reset()
+ { }
+
+ /**
+ * @brief Return the intervals of the distribution.
+ */
+ std::vector<_RealType>
+ intervals() const
+ {
+ if (_M_param._M_int.empty())
+ {
+ std::vector<_RealType> __tmp(2);
+ __tmp[1] = _RealType(1);
+ return __tmp;
+ }
+ else
+ return _M_param._M_int;
+ }
+
+ /**
+ * @brief Return a vector of the probability densities of the
+ * distribution.
+ */
+ std::vector<double>
+ densities() const
+ {
+ return _M_param._M_den.empty()
+ ? std::vector<double>(2, 1.0) : _M_param._M_den;
+ }
+
+ /**
+ * @brief Returns the parameter set of the distribution.
+ */
+ param_type
+ param() const
+ { return _M_param; }
+
+ /**
+ * @brief Sets the parameter set of the distribution.
+ * @param __param The new parameter set of the distribution.
+ */
+ void
+ param(const param_type& __param)
+ { _M_param = __param; }
+
+ /**
+ * @brief Returns the greatest lower bound value of the distribution.
+ */
+ result_type
+ min() const
+ {
+ return _M_param._M_int.empty()
+ ? result_type(0) : _M_param._M_int.front();
+ }
+
+ /**
+ * @brief Returns the least upper bound value of the distribution.
+ */
+ result_type
+ max() const
+ {
+ return _M_param._M_int.empty()
+ ? result_type(1) : _M_param._M_int.back();
+ }
+
+ /**
+ * @brief Generating functions.
+ */
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng)
+ { return this->operator()(__urng, _M_param); }
+
+ template<typename _UniformRandomNumberGenerator>
+ result_type
+ operator()(_UniformRandomNumberGenerator& __urng,
+ const param_type& __p);
+
+ /**
+ * @brief Return true if two piecewise linear distributions have the
+ * same parameters.
+ */
+ friend bool
+ operator==(const piecewise_linear_distribution& __d1,
+ const piecewise_linear_distribution& __d2)
+ { return __d1._M_param == __d2._M_param; }
+
+ /**
+ * @brief Inserts a %piecewise_linear_distribution random number
+ * distribution @p __x into the output stream @p __os.
+ *
+ * @param __os An output stream.
+ * @param __x A %piecewise_linear_distribution random number
+ * distribution.
+ *
+ * @returns The output stream with the state of @p __x inserted or in
+ * an error state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_ostream<_CharT, _Traits>&
+ operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+ const std::piecewise_linear_distribution<_RealType1>& __x);
+
+ /**
+ * @brief Extracts a %piecewise_linear_distribution random number
+ * distribution @p __x from the input stream @p __is.
+ *
+ * @param __is An input stream.
+ * @param __x A %piecewise_linear_distribution random number
+ * generator engine.
+ *
+ * @returns The input stream with @p __x extracted or in an error
+ * state.
+ */
+ template<typename _RealType1, typename _CharT, typename _Traits>
+ friend std::basic_istream<_CharT, _Traits>&
+ operator>>(std::basic_istream<_CharT, _Traits>& __is,
+ std::piecewise_linear_distribution<_RealType1>& __x);
+
+ private:
+ param_type _M_param;
+ };
+
+ /**
+ * @brief Return true if two piecewise linear distributions have
+ * different parameters.
+ */
+ template<typename _RealType>
+ inline bool
+ operator!=(const std::piecewise_linear_distribution<_RealType>& __d1,
+ const std::piecewise_linear_distribution<_RealType>& __d2)
+ { return !(__d1 == __d2); }
+
+
+ /* @} */ // group random_distributions_poisson
+
+ /* @} */ // group random_distributions
+
+ /**
+ * @addtogroup random_utilities Random Number Utilities
+ * @ingroup random
+ * @{
+ */
+
+ /**
+ * @brief The seed_seq class generates sequences of seeds for random
+ * number generators.
+ */
+ class seed_seq
+ {
+
+ public:
+ /** The type of the seed vales. */
+ typedef uint_least32_t result_type;
+
+ /** Default constructor. */
+ seed_seq()
+ : _M_v()
+ { }
+
+ template<typename _IntType>
+ seed_seq(std::initializer_list<_IntType> il);
+
+ template<typename _InputIterator>
+ seed_seq(_InputIterator __begin, _InputIterator __end);
+
+ // generating functions
+ template<typename _RandomAccessIterator>
+ void
+ generate(_RandomAccessIterator __begin, _RandomAccessIterator __end);
+
+ // property functions
+ size_t size() const
+ { return _M_v.size(); }
+
+ template<typename OutputIterator>
+ void
+ param(OutputIterator __dest) const
+ { std::copy(_M_v.begin(), _M_v.end(), __dest); }
+
+ private:
+ ///
+ std::vector<result_type> _M_v;
+ };
+
+ /* @} */ // group random_utilities
+
+ /* @} */ // group random
+
+_GLIBCXX_END_NAMESPACE_VERSION
+} // namespace std
+
+#endif
projects / cross.git / blobdiff