/* 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 60755 2010-03-22 00:45:06Z steven_watanabe $
+ * $Id: normal_distribution.hpp 71018 2011-04-05 21:27:52Z steven_watanabe $
*
* Revision history
* 2001-02-18 moved to individual header files
#define BOOST_RANDOM_NORMAL_DISTRIBUTION_HPP
#include <boost/config/no_tr1/cmath.hpp>
-#include <cassert>
-#include <iostream>
+#include <istream>
+#include <iosfwd>
+#include <boost/assert.hpp>
#include <boost/limits.hpp>
#include <boost/static_assert.hpp>
#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/uniform_01.hpp>
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$p(x) = \frac{1}{\sqrt{2\pi\sigma}} e^{-\frac{(x-\mu)^2}{2\sigma^2}}\f$,
+ * \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.
*/
-// deterministic Box-Muller method, uses trigonometric functions
template<class RealType = double>
class normal_distribution
{
public:
- typedef RealType input_type;
- typedef RealType result_type;
-
-#if !defined(BOOST_NO_LIMITS_COMPILE_TIME_CONSTANTS) && !(defined(BOOST_MSVC) && BOOST_MSVC <= 1300)
- BOOST_STATIC_ASSERT(!std::numeric_limits<RealType>::is_integer);
-#endif
-
- /**
- * Constructs a normal_distribution object. @c mean and @c sigma are
- * the parameters for the distribution.
- *
- * Requires: sigma > 0
- */
- explicit normal_distribution(const result_type& mean_arg = result_type(0),
- const result_type& sigma_arg = result_type(1))
- : _mean(mean_arg), _sigma(sigma_arg), _valid(false)
- {
- assert(_sigma >= result_type(0));
- }
-
- // compiler-generated copy constructor is NOT fine, need to purge cache
- normal_distribution(const normal_distribution& other)
- : _mean(other._mean), _sigma(other._sigma), _valid(false)
- {
- }
-
- // compiler-generated copy ctor and assignment operator are fine
-
- /**
- * Returns: The "mean" parameter of the distribution.
- */
- RealType mean() const { return _mean; }
- /**
- * Returns: The "sigma" parameter of the distribution.
- */
- RealType sigma() const { return _sigma; }
-
- void reset() { _valid = false; }
-
- template<class Engine>
- result_type operator()(Engine& eng)
- {
-#ifndef BOOST_NO_STDC_NAMESPACE
- // allow for Koenig lookup
- using std::sqrt; using std::log; using std::sin; using std::cos;
-#endif
- if(!_valid) {
- _r1 = eng();
- _r2 = eng();
- _cached_rho = sqrt(-result_type(2) * log(result_type(1)-_r2));
- _valid = true;
- } else {
- _valid = false;
+ 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));
}
- // 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;
- }
-
-#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
- template<class CharT, class Traits>
- friend std::basic_ostream<CharT,Traits>&
- operator<<(std::basic_ostream<CharT,Traits>& os, const normal_distribution& nd)
- {
- os << nd._mean << " " << nd._sigma << " "
- << nd._valid << " " << nd._cached_rho << " " << nd._r1;
- return os;
- }
-
- template<class CharT, class Traits>
- friend std::basic_istream<CharT,Traits>&
- operator>>(std::basic_istream<CharT,Traits>& 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;
- }
-#endif
+
+ /**
+ * 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<RealType>::infinity(); }
+ /** Returns the largest value that the distribution can produce. */
+ RealType max BOOST_PREVENT_MACRO_SUBSTITUTION () const
+ { return std::numeric_limits<RealType>::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<class Engine>
+ result_type operator()(Engine& eng)
+ {
+ using std::sqrt;
+ using std::log;
+ using std::sin;
+ using std::cos;
+
+ if(!_valid) {
+ _r1 = boost::uniform_01<RealType>()(eng);
+ _r2 = boost::uniform_01<RealType>()(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<class URNG>
+ 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:
- result_type _mean, _sigma;
- result_type _r1, _r2, _cached_rho;
- bool _valid;
+ RealType _mean, _sigma;
+ RealType _r1, _r2, _cached_rho;
+ bool _valid;
+
};
+} // namespace random
+
+using random::normal_distribution;
+
} // namespace boost
#endif // BOOST_RANDOM_NORMAL_DISTRIBUTION_HPP
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