diff DEPENDENCIES/generic/include/boost/random/normal_distribution.hpp @ 16:2665513ce2d3

Add boost headers
author Chris Cannam
date Tue, 05 Aug 2014 11:11:38 +0100
parents
children c530137014c0
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/DEPENDENCIES/generic/include/boost/random/normal_distribution.hpp	Tue Aug 05 11:11:38 2014 +0100
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+/* 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 <boost/config/no_tr1/cmath.hpp>
+#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$\displaystyle p(x) =
+ *   \frac{1}{\sqrt{2\pi\sigma}} e^{-\frac{(x-\mu)^2}{2\sigma^2}}
+ * \f$,
+ * where mean and sigma are the parameters of the distribution.
+ */
+template<class RealType = double>
+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<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:
+    RealType _mean, _sigma;
+    RealType _r1, _r2, _cached_rho;
+    bool _valid;
+
+};
+
+} // namespace random
+
+using random::normal_distribution;
+
+} // namespace boost
+
+#endif // BOOST_RANDOM_NORMAL_DISTRIBUTION_HPP