/* boost random/normal_distribution.hpp header file * * Copyright Jens Maurer 2000-2001 * Copyright Steven Watanabe 2010-2011 * Distributed under the Boost Software License, Version 1.0. (See * accompanying file LICENSE_1_0.txt or copy at * http://www.boost.org/LICENSE_1_0.txt) * * See http://www.boost.org for most recent version including documentation. * * $Id: normal_distribution.hpp 71018 2011-04-05 21:27:52Z steven_watanabe $ * * Revision history * 2001-02-18 moved to individual header files */ #ifndef BOOST_RANDOM_NORMAL_DISTRIBUTION_HPP #define BOOST_RANDOM_NORMAL_DISTRIBUTION_HPP #include #include #include #include #include #include #include #include #include namespace boost { namespace random { // deterministic Box-Muller method, uses trigonometric functions /** * Instantiations of class template normal_distribution model a * \random_distribution. Such a distribution produces random numbers * @c x distributed with probability density function * \f$\displaystyle p(x) = * \frac{1}{\sqrt{2\pi\sigma}} e^{-\frac{(x-\mu)^2}{2\sigma^2}} * \f$, * where mean and sigma are the parameters of the distribution. */ template class normal_distribution { public: typedef RealType input_type; typedef RealType result_type; class param_type { public: typedef normal_distribution distribution_type; /** * Constructs a @c param_type with a given mean and * standard deviation. * * Requires: sigma >= 0 */ explicit param_type(RealType mean_arg = RealType(0.0), RealType sigma_arg = RealType(1.0)) : _mean(mean_arg), _sigma(sigma_arg) {} /** Returns the mean of the distribution. */ RealType mean() const { return _mean; } /** Returns the standand deviation of the distribution. */ RealType sigma() const { return _sigma; } /** Writes a @c param_type to a @c std::ostream. */ BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm) { os << parm._mean << " " << parm._sigma ; return os; } /** Reads a @c param_type from a @c std::istream. */ BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm) { is >> parm._mean >> std::ws >> parm._sigma; return is; } /** Returns true if the two sets of parameters are the same. */ BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs) { return lhs._mean == rhs._mean && lhs._sigma == rhs._sigma; } /** Returns true if the two sets of parameters are the different. */ BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type) private: RealType _mean; RealType _sigma; }; /** * Constructs a @c normal_distribution object. @c mean and @c sigma are * the parameters for the distribution. * * Requires: sigma >= 0 */ explicit normal_distribution(const RealType& mean_arg = RealType(0.0), const RealType& sigma_arg = RealType(1.0)) : _mean(mean_arg), _sigma(sigma_arg), _r1(0), _r2(0), _cached_rho(0), _valid(false) { BOOST_ASSERT(_sigma >= RealType(0)); } /** * Constructs a @c normal_distribution object from its parameters. */ explicit normal_distribution(const param_type& parm) : _mean(parm.mean()), _sigma(parm.sigma()), _r1(0), _r2(0), _cached_rho(0), _valid(false) {} /** Returns the mean of the distribution. */ RealType mean() const { return _mean; } /** Returns the standard deviation of the distribution. */ RealType sigma() const { return _sigma; } /** Returns the smallest value that the distribution can produce. */ RealType min BOOST_PREVENT_MACRO_SUBSTITUTION () const { return -std::numeric_limits::infinity(); } /** Returns the largest value that the distribution can produce. */ RealType max BOOST_PREVENT_MACRO_SUBSTITUTION () const { return std::numeric_limits::infinity(); } /** Returns the parameters of the distribution. */ param_type param() const { return param_type(_mean, _sigma); } /** Sets the parameters of the distribution. */ void param(const param_type& parm) { _mean = parm.mean(); _sigma = parm.sigma(); _valid = false; } /** * Effects: Subsequent uses of the distribution do not depend * on values produced by any engine prior to invoking reset. */ void reset() { _valid = false; } /** Returns a normal variate. */ template result_type operator()(Engine& eng) { using std::sqrt; using std::log; using std::sin; using std::cos; if(!_valid) { _r1 = boost::uniform_01()(eng); _r2 = boost::uniform_01()(eng); _cached_rho = sqrt(-result_type(2) * log(result_type(1)-_r2)); _valid = true; } else { _valid = false; } // Can we have a boost::mathconst please? const result_type pi = result_type(3.14159265358979323846); return _cached_rho * (_valid ? cos(result_type(2)*pi*_r1) : sin(result_type(2)*pi*_r1)) * _sigma + _mean; } /** Returns a normal variate with parameters specified by @c param. */ template result_type operator()(URNG& urng, const param_type& parm) { return normal_distribution(parm)(urng); } /** Writes a @c normal_distribution to a @c std::ostream. */ BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, normal_distribution, nd) { os << nd._mean << " " << nd._sigma << " " << nd._valid << " " << nd._cached_rho << " " << nd._r1; return os; } /** Reads a @c normal_distribution from a @c std::istream. */ BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, normal_distribution, nd) { is >> std::ws >> nd._mean >> std::ws >> nd._sigma >> std::ws >> nd._valid >> std::ws >> nd._cached_rho >> std::ws >> nd._r1; return is; } /** * Returns true if the two instances of @c normal_distribution will * return identical sequences of values given equal generators. */ BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(normal_distribution, lhs, rhs) { return lhs._mean == rhs._mean && lhs._sigma == rhs._sigma && lhs._valid == rhs._valid && (!lhs._valid || (lhs._r1 == rhs._r1 && lhs._r2 == rhs._r2)); } /** * Returns true if the two instances of @c normal_distribution will * return different sequences of values given equal generators. */ BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(normal_distribution) private: RealType _mean, _sigma; RealType _r1, _r2, _cached_rho; bool _valid; }; } // namespace random using random::normal_distribution; } // namespace boost #endif // BOOST_RANDOM_NORMAL_DISTRIBUTION_HPP