stabilize build system: depends, installer, boost/bdb fixes, cross targets groundwork

depends/x86_64-pc-linux-gnu/include/boost/random/additive_combine.hpp

@@ -0,0 +1,283 @@
+/* boost random/additive_combine.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2001-02-18  moved to individual header files
+ */
+
+#ifndef BOOST_RANDOM_ADDITIVE_COMBINE_HPP
+#define BOOST_RANDOM_ADDITIVE_COMBINE_HPP
+
+#include <istream>
+#include <iosfwd>
+#include <algorithm> // for std::min and std::max
+#include <boost/config.hpp>
+#include <boost/cstdint.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/detail/seed.hpp>
+#include <boost/random/linear_congruential.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * An instantiation of class template @c additive_combine_engine models a
+ * \pseudo_random_number_generator. It combines two multiplicative
+ * \linear_congruential_engine number generators, i.e. those with @c c = 0.
+ * It is described in
+ *
+ *  @blockquote
+ *  "Efficient and Portable Combined Random Number Generators", Pierre L'Ecuyer,
+ *  Communications of the ACM, Vol. 31, No. 6, June 1988, pp. 742-749, 774
+ *  @endblockquote
+ *
+ * The template parameters MLCG1 and MLCG2 shall denote two different
+ * \linear_congruential_engine number generators, each with c = 0. Each
+ * invocation returns a random number
+ * X(n) := (MLCG1(n) - MLCG2(n)) mod (m1 - 1),
+ * where m1 denotes the modulus of MLCG1. 
+ */
+template<class MLCG1, class MLCG2>
+class additive_combine_engine
+{
+public:
+    typedef MLCG1 first_base;
+    typedef MLCG2 second_base;
+    typedef typename MLCG1::result_type result_type;
+
+    // Required by old Boost.Random concept
+    BOOST_STATIC_CONSTANT(bool, has_fixed_range = false);
+    /**
+     * Returns the smallest value that the generator can produce
+     */
+    static result_type min BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return 1; }
+    /**
+     * Returns the largest value that the generator can produce
+     */
+    static result_type max BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return MLCG1::modulus-1; }
+
+    /**
+     * Constructs an @c additive_combine_engine using the
+     * default constructors of the two base generators.
+     */
+    additive_combine_engine() : _mlcg1(), _mlcg2() { }
+    /**
+     * Constructs an @c additive_combine_engine, using seed as
+     * the constructor argument for both base generators.
+     */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(additive_combine_engine,
+        result_type, seed_arg)
+    {
+        _mlcg1.seed(seed_arg);
+        _mlcg2.seed(seed_arg);
+    }
+    /**
+     * Constructs an @c additive_combine_engine, using seq as
+     * the constructor argument for both base generators.
+     *
+     * @xmlwarning
+     * The semantics of this function are liable to change.
+     * A @c seed_seq is designed to generate all the seeds
+     * in one shot, but this seeds the two base engines
+     * independantly and probably ends up giving the same
+     * sequence to both.
+     * @endxmlwarning
+     */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_CONSTRUCTOR(additive_combine_engine,
+        SeedSeq, seq)
+    {
+        _mlcg1.seed(seq);
+        _mlcg2.seed(seq);
+    }
+    /**
+     * Constructs an @c additive_combine_engine, using
+     * @c seed1 and @c seed2 as the constructor argument to
+     * the first and second base generators, respectively.
+     */
+    additive_combine_engine(typename MLCG1::result_type seed1, 
+                            typename MLCG2::result_type seed2)
+      : _mlcg1(seed1), _mlcg2(seed2) { }
+    /**
+     * Contructs an @c additive_combine_engine with
+     * values from the range defined by the input iterators first
+     * and last.  first will be modified to point to the element
+     * after the last one used.
+     *
+     * Throws: @c std::invalid_argument if the input range is too small.
+     *
+     * Exception Safety: Basic
+     */
+    template<class It> additive_combine_engine(It& first, It last)
+      : _mlcg1(first, last), _mlcg2(first, last) { }
+
+    /**
+     * Seeds an @c additive_combine_engine using the default
+     * seeds of the two base generators.
+     */
+    void seed()
+    {
+        _mlcg1.seed();
+        _mlcg2.seed();
+    }
+
+    /**
+     * Seeds an @c additive_combine_engine, using @c seed as the
+     * seed for both base generators.
+     */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_SEED(additive_combine_engine,
+        result_type, seed_arg)
+    {
+        _mlcg1.seed(seed_arg);
+        _mlcg2.seed(seed_arg);
+    }
+
+    /**
+     * Seeds an @c additive_combine_engine, using @c seq to
+     * seed both base generators.
+     *
+     * See the warning on the corresponding constructor.
+     */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_SEED(additive_combine_engine,
+        SeedSeq, seq)
+    {
+        _mlcg1.seed(seq);
+        _mlcg2.seed(seq);
+    }
+
+    /**
+     * Seeds an @c additive_combine generator, using @c seed1 and @c seed2 as
+     * the seeds to the first and second base generators, respectively.
+     */
+    void seed(typename MLCG1::result_type seed1,
+              typename MLCG2::result_type seed2)
+    {
+        _mlcg1.seed(seed1);
+        _mlcg2.seed(seed2);
+    }
+
+    /**
+     * Seeds an @c additive_combine_engine with
+     * values from the range defined by the input iterators first
+     * and last.  first will be modified to point to the element
+     * after the last one used.
+     *
+     * Throws: @c std::invalid_argument if the input range is too small.
+     *
+     * Exception Safety: Basic
+     */
+    template<class It> void seed(It& first, It last)
+    {
+        _mlcg1.seed(first, last);
+        _mlcg2.seed(first, last);
+    }
+
+    /** Returns the next value of the generator. */
+    result_type operator()() {
+        result_type val1 = _mlcg1();
+        result_type val2 = _mlcg2();
+        if(val2 < val1) return val1 - val2;
+        else return val1 - val2 + MLCG1::modulus - 1;
+    }
+  
+    /** Fills a range with random values */
+    template<class Iter>
+    void generate(Iter first, Iter last)
+    { detail::generate_from_int(*this, first, last); }
+
+    /** Advances the state of the generator by @c z. */
+    void discard(boost::uintmax_t z)
+    {
+        _mlcg1.discard(z);
+        _mlcg2.discard(z);
+    }
+
+    /**
+     * Writes the state of an @c additive_combine_engine to a @c
+     * std::ostream.  The textual representation of an @c
+     * additive_combine_engine is the textual representation of
+     * the first base generator followed by the textual representation
+     * of the second base generator.
+     */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, additive_combine_engine, r)
+    { os << r._mlcg1 << ' ' << r._mlcg2; return os; }
+
+    /**
+     * Reads the state of an @c additive_combine_engine from a
+     * @c std::istream.
+     */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, additive_combine_engine, r)
+    { is >> r._mlcg1 >> std::ws >> r._mlcg2; return is; }
+
+    /**
+     * Returns: true iff the two @c additive_combine_engines will
+     * produce the same sequence of values.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(additive_combine_engine, x, y)
+    { return x._mlcg1 == y._mlcg1 && x._mlcg2 == y._mlcg2; }
+    /**
+     * Returns: true iff the two @c additive_combine_engines will
+     * produce different sequences of values.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(additive_combine_engine)
+
+private:
+    MLCG1 _mlcg1;
+    MLCG2 _mlcg2;
+};
+
+#ifndef BOOST_NO_INCLASS_MEMBER_INITIALIZATION
+template<class MLCG1, class MLCG2>
+const bool additive_combine_engine<MLCG1, MLCG2>::has_fixed_range;
+#endif
+
+/// \cond show_deprecated
+
+/** Provided for backwards compatibility. */
+template<class MLCG1, class MLCG2, typename MLCG1::result_type val = 0>
+class additive_combine : public additive_combine_engine<MLCG1, MLCG2>
+{
+    typedef additive_combine_engine<MLCG1, MLCG2> base_t;
+public:
+    typedef typename base_t::result_type result_type;
+    additive_combine() {}
+    template<class T>
+    additive_combine(T& arg) : base_t(arg) {}
+    template<class T>
+    additive_combine(const T& arg) : base_t(arg) {}
+    template<class It>
+    additive_combine(It& first, It last) : base_t(first, last) {}
+};
+
+/// \endcond
+
+/**
+ * The specialization \ecuyer1988 was suggested in
+ *
+ *  @blockquote
+ *  "Efficient and Portable Combined Random Number Generators", Pierre L'Ecuyer,
+ *  Communications of the ACM, Vol. 31, No. 6, June 1988, pp. 742-749, 774
+ *  @endblockquote
+ */
+typedef additive_combine_engine<
+    linear_congruential_engine<uint32_t, 40014, 0, 2147483563>,
+    linear_congruential_engine<uint32_t, 40692, 0, 2147483399>
+> ecuyer1988;
+
+} // namespace random
+
+using random::ecuyer1988;
+
+} // namespace boost
+
+#endif // BOOST_RANDOM_ADDITIVE_COMBINE_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/bernoulli_distribution.hpp

@@ -0,0 +1,197 @@
+/* boost random/bernoulli_distribution.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2001-02-18  moved to individual header files
+ */
+
+#ifndef BOOST_RANDOM_BERNOULLI_DISTRIBUTION_HPP
+#define BOOST_RANDOM_BERNOULLI_DISTRIBUTION_HPP
+
+#include <iosfwd>
+#include <boost/assert.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/operators.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * Instantiations of class template \bernoulli_distribution model a
+ * \random_distribution. Such a random distribution produces bool values
+ * distributed with probabilities P(true) = p and P(false) = 1-p. p is
+ * the parameter of the distribution.
+ */
+template<class RealType = double>
+class bernoulli_distribution
+{
+public:
+    // In principle, this could work with both integer and floating-point
+    // types.  Generating floating-point random numbers in the first
+    // place is probably more expensive, so use integer as input.
+    typedef int input_type;
+    typedef bool result_type;
+
+    class param_type
+    {
+    public:
+
+        typedef bernoulli_distribution distribution_type;
+
+        /** 
+         * Constructs the parameters of the distribution.
+         *
+         * Requires: 0 <= p <= 1
+         */
+        explicit param_type(RealType p_arg = RealType(0.5))
+          : _p(p_arg)
+        {
+            BOOST_ASSERT(_p >= 0);
+            BOOST_ASSERT(_p <= 1);
+        }
+
+        /** Returns the p parameter of the distribution. */
+        RealType p() const { return _p; }
+
+        /** Writes the parameters to a std::ostream. */
+        BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
+        {
+            os << parm._p;
+            return os;
+        }
+
+        /** Reads the parameters from a std::istream. */
+        BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
+        {
+            is >> parm._p;
+            return is;
+        }
+
+        /** Returns true if the two sets of parameters are equal. */
+        BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
+        { return lhs._p == rhs._p; }
+
+        /** Returns true if the two sets of parameters are different. */
+        BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+
+    private:
+        RealType _p;
+    };
+
+    /** 
+     * Constructs a \bernoulli_distribution object.
+     * p is the parameter of the distribution.
+     *
+     * Requires: 0 <= p <= 1
+     */
+    explicit bernoulli_distribution(const RealType& p_arg = RealType(0.5)) 
+      : _p(p_arg)
+    {
+        BOOST_ASSERT(_p >= 0);
+        BOOST_ASSERT(_p <= 1);
+    }
+    /**
+     * Constructs \bernoulli_distribution from its parameters
+     */
+    explicit bernoulli_distribution(const param_type& parm)
+      : _p(parm.p()) {}
+
+    // compiler-generated copy ctor and assignment operator are fine
+
+    /**
+     * Returns: The "p" parameter of the distribution.
+     */
+    RealType p() const { return _p; }
+
+    /** Returns the smallest value that the distribution can produce. */
+    bool min BOOST_PREVENT_MACRO_SUBSTITUTION () const
+    { return false; }
+    /** Returns the largest value that the distribution can produce. */
+    bool max BOOST_PREVENT_MACRO_SUBSTITUTION () const
+    { return true; }
+
+    /** Returns the parameters of the distribution. */
+    param_type param() const { return param_type(_p); }
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm) { _p = parm.p(); }
+
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { }
+
+    /**
+     * Returns: a random variate distributed according to the
+     * \bernoulli_distribution.
+     */
+    template<class Engine>
+    bool operator()(Engine& eng) const
+    {
+        if(_p == RealType(0))
+            return false;
+        else
+            return RealType(eng() - (eng.min)()) <= _p * RealType((eng.max)()-(eng.min)());
+    }
+
+    /**
+     * Returns: a random variate distributed according to the
+     * \bernoulli_distribution with parameters specified by param.
+     */
+    template<class Engine>
+    bool operator()(Engine& eng, const param_type& parm) const
+    {
+        return bernoulli_distribution(parm)(eng);
+    }
+
+    /**
+     * Writes the parameters of the distribution to a @c std::ostream.
+     */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, bernoulli_distribution, bd)
+    {
+        os << bd._p;
+        return os;
+    }
+
+    /**
+     * Reads the parameters of the distribution from a @c std::istream.
+     */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, bernoulli_distribution, bd)
+    {
+        is >> bd._p;
+        return is;
+    }
+
+    /**
+     * Returns true iff the two distributions will produce identical
+     * sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(bernoulli_distribution, lhs, rhs)
+    { return lhs._p == rhs._p; }
+    
+    /**
+     * Returns true iff the two distributions will produce different
+     * sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(bernoulli_distribution)
+
+private:
+    RealType _p;
+};
+
+} // namespace random
+
+using random::bernoulli_distribution;
+
+} // namespace boost
+
+#endif // BOOST_RANDOM_BERNOULLI_DISTRIBUTION_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/beta_distribution.hpp

@@ -0,0 +1,184 @@
+/* boost random/beta_distribution.hpp header file
+ *
+ * Copyright Steven Watanabe 2014
+ * 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.
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_BETA_DISTRIBUTION_HPP
+#define BOOST_RANDOM_BETA_DISTRIBUTION_HPP
+
+#include <cassert>
+#include <istream>
+#include <iosfwd>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/gamma_distribution.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * The beta distribution is a real-valued distribution which produces
+ * values in the range [0, 1].  It has two parameters, alpha and beta.
+ *
+ * It has \f$\displaystyle p(x) = \frac{x^{\alpha-1}(1-x)^{\beta-1}}{B(\alpha, \beta)}\f$.
+ */
+template<class RealType = double>
+class beta_distribution {
+public:
+    typedef RealType result_type;
+    typedef RealType input_type;
+
+    class param_type {
+    public:
+        typedef beta_distribution distribution_type;
+
+        /**
+         * Constructs a @c param_type from the "alpha" and "beta" parameters
+         * of the distribution.
+         *
+         * Requires: alpha > 0, beta > 0
+         */
+        explicit param_type(RealType alpha_arg = RealType(1.0),
+                            RealType beta_arg = RealType(1.0))
+          : _alpha(alpha_arg), _beta(beta_arg)
+        {
+            assert(alpha_arg > 0);
+            assert(beta_arg > 0);
+        }
+
+        /** Returns the "alpha" parameter of the distribtuion. */
+        RealType alpha() const { return _alpha; }
+        /** Returns the "beta" parameter of the distribution. */
+        RealType beta() const { return _beta; }
+
+        /** Writes a @c param_type to a @c std::ostream. */
+        BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
+        { os << parm._alpha << ' ' << parm._beta; return os; }
+
+        /** Reads a @c param_type from a @c std::istream. */
+        BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
+        { is >> parm._alpha >> std::ws >> parm._beta; return is; }
+
+        /** Returns true if the two sets of parameters are the same. */
+        BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
+        { return lhs._alpha == rhs._alpha && lhs._beta == rhs._beta; }
+        
+        /** Returns true if the two sets of parameters are the different. */
+        BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+
+    private:
+        RealType _alpha;
+        RealType _beta;
+    };
+
+    /**
+     * Constructs an @c beta_distribution from its "alpha" and "beta" parameters.
+     *
+     * Requires: alpha > 0, beta > 0
+     */
+    explicit beta_distribution(RealType alpha_arg = RealType(1.0),
+                               RealType beta_arg = RealType(1.0))
+      : _alpha(alpha_arg), _beta(beta_arg)
+    {
+        assert(alpha_arg > 0);
+        assert(beta_arg > 0);
+    }
+    /** Constructs an @c beta_distribution from its parameters. */
+    explicit beta_distribution(const param_type& parm)
+      : _alpha(parm.alpha()), _beta(parm.beta())
+    {}
+
+    /**
+     * Returns a random variate distributed according to the
+     * beta distribution.
+     */
+    template<class URNG>
+    RealType operator()(URNG& urng) const
+    {
+        RealType a = gamma_distribution<RealType>(_alpha, RealType(1.0))(urng);
+        RealType b = gamma_distribution<RealType>(_beta, RealType(1.0))(urng);
+        return a / (a + b);
+    }
+
+    /**
+     * Returns a random variate distributed accordint to the beta
+     * distribution with parameters specified by @c param.
+     */
+    template<class URNG>
+    RealType operator()(URNG& urng, const param_type& parm) const
+    {
+        return beta_distribution(parm)(urng);
+    }
+
+    /** Returns the "alpha" parameter of the distribution. */
+    RealType alpha() const { return _alpha; }
+    /** Returns the "beta" parameter of the distribution. */
+    RealType beta() const { return _beta; }
+
+    /** Returns the smallest value that the distribution can produce. */
+    RealType min BOOST_PREVENT_MACRO_SUBSTITUTION () const
+    { return RealType(0.0); }
+    /** Returns the largest value that the distribution can produce. */
+    RealType max BOOST_PREVENT_MACRO_SUBSTITUTION () const
+    { return RealType(1.0); }
+
+    /** Returns the parameters of the distribution. */
+    param_type param() const { return param_type(_alpha, _beta); }
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        _alpha = parm.alpha();
+        _beta = parm.beta();
+    }
+
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { }
+
+    /** Writes an @c beta_distribution to a @c std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, beta_distribution, wd)
+    {
+        os << wd.param();
+        return os;
+    }
+
+    /** Reads an @c beta_distribution from a @c std::istream. */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, beta_distribution, wd)
+    {
+        param_type parm;
+        if(is >> parm) {
+            wd.param(parm);
+        }
+        return is;
+    }
+
+    /**
+     * Returns true if the two instances of @c beta_distribution will
+     * return identical sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(beta_distribution, lhs, rhs)
+    { return lhs._alpha == rhs._alpha && lhs._beta == rhs._beta; }
+    
+    /**
+     * Returns true if the two instances of @c beta_distribution will
+     * return different sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(beta_distribution)
+
+private:
+    RealType _alpha;
+    RealType _beta;
+};
+
+} // namespace random
+} // namespace boost
+
+#endif // BOOST_RANDOM_BETA_DISTRIBUTION_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/binomial_distribution.hpp

@@ -0,0 +1,434 @@
+/* boost random/binomial_distribution.hpp header file
+ *
+ * Copyright Steven Watanabe 2010
+ * 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.
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_BINOMIAL_DISTRIBUTION_HPP_INCLUDED
+#define BOOST_RANDOM_BINOMIAL_DISTRIBUTION_HPP_INCLUDED
+
+#include <boost/config/no_tr1/cmath.hpp>
+#include <cstdlib>
+#include <iosfwd>
+
+#include <boost/random/detail/config.hpp>
+#include <boost/random/uniform_01.hpp>
+
+#include <boost/random/detail/disable_warnings.hpp>
+
+namespace boost {
+namespace random {
+
+namespace detail {
+
+template<class RealType>
+struct binomial_table {
+    static const RealType table[10];
+};
+
+template<class RealType>
+const RealType binomial_table<RealType>::table[10] = {
+    0.08106146679532726,
+    0.04134069595540929,
+    0.02767792568499834,
+    0.02079067210376509,
+    0.01664469118982119,
+    0.01387612882307075,
+    0.01189670994589177,
+    0.01041126526197209,
+    0.009255462182712733,
+    0.008330563433362871
+};
+
+}
+
+/**
+ * The binomial distribution is an integer valued distribution with
+ * two parameters, @c t and @c p.  The values of the distribution
+ * are within the range [0,t].
+ *
+ * The distribution function is
+ * \f$\displaystyle P(k) = {t \choose k}p^k(1-p)^{t-k}\f$.
+ *
+ * The algorithm used is the BTRD algorithm described in
+ *
+ *  @blockquote
+ *  "The generation of binomial random variates", Wolfgang Hormann,
+ *  Journal of Statistical Computation and Simulation, Volume 46,
+ *  Issue 1 & 2 April 1993 , pages 101 - 110
+ *  @endblockquote
+ */
+template<class IntType = int, class RealType = double>
+class binomial_distribution {
+public:
+    typedef IntType result_type;
+    typedef RealType input_type;
+
+    class param_type {
+    public:
+        typedef binomial_distribution distribution_type;
+        /**
+         * Construct a param_type object.  @c t and @c p
+         * are the parameters of the distribution.
+         *
+         * Requires: t >=0 && 0 <= p <= 1
+         */
+        explicit param_type(IntType t_arg = 1, RealType p_arg = RealType (0.5))
+          : _t(t_arg), _p(p_arg)
+        {}
+        /** Returns the @c t parameter of the distribution. */
+        IntType t() const { return _t; }
+        /** Returns the @c p parameter of the distribution. */
+        RealType p() const { return _p; }
+#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
+        /** Writes the parameters of the distribution to a @c std::ostream. */
+        template<class CharT, class Traits>
+        friend std::basic_ostream<CharT,Traits>&
+        operator<<(std::basic_ostream<CharT,Traits>& os,
+                   const param_type& parm)
+        {
+            os << parm._p << " " << parm._t;
+            return os;
+        }
+    
+        /** Reads the parameters of the distribution from a @c std::istream. */
+        template<class CharT, class Traits>
+        friend std::basic_istream<CharT,Traits>&
+        operator>>(std::basic_istream<CharT,Traits>& is, param_type& parm)
+        {
+            is >> parm._p >> std::ws >> parm._t;
+            return is;
+        }
+#endif
+        /** Returns true if the parameters have the same values. */
+        friend bool operator==(const param_type& lhs, const param_type& rhs)
+        {
+            return lhs._t == rhs._t && lhs._p == rhs._p;
+        }
+        /** Returns true if the parameters have different values. */
+        friend bool operator!=(const param_type& lhs, const param_type& rhs)
+        {
+            return !(lhs == rhs);
+        }
+    private:
+        IntType _t;
+        RealType _p;
+    };
+    
+    /**
+     * Construct a @c binomial_distribution object. @c t and @c p
+     * are the parameters of the distribution.
+     *
+     * Requires: t >=0 && 0 <= p <= 1
+     */
+    explicit binomial_distribution(IntType t_arg = 1,
+                                   RealType p_arg = RealType(0.5))
+      : _t(t_arg), _p(p_arg)
+    {
+        init();
+    }
+    
+    /**
+     * Construct an @c binomial_distribution object from the
+     * parameters.
+     */
+    explicit binomial_distribution(const param_type& parm)
+      : _t(parm.t()), _p(parm.p())
+    {
+        init();
+    }
+    
+    /**
+     * Returns a random variate distributed according to the
+     * binomial distribution.
+     */
+    template<class URNG>
+    IntType operator()(URNG& urng) const
+    {
+        if(use_inversion()) {
+            if(0.5 < _p) {
+                return _t - invert(_t, 1-_p, urng);
+            } else {
+                return invert(_t, _p, urng);
+            }
+        } else if(0.5 < _p) {
+            return _t - generate(urng);
+        } else {
+            return generate(urng);
+        }
+    }
+    
+    /**
+     * Returns a random variate distributed according to the
+     * binomial distribution with parameters specified by @c param.
+     */
+    template<class URNG>
+    IntType operator()(URNG& urng, const param_type& parm) const
+    {
+        return binomial_distribution(parm)(urng);
+    }
+
+    /** Returns the @c t parameter of the distribution. */
+    IntType t() const { return _t; }
+    /** Returns the @c p parameter of the distribution. */
+    RealType p() const { return _p; }
+
+    /** Returns the smallest value that the distribution can produce. */
+    IntType min BOOST_PREVENT_MACRO_SUBSTITUTION() const { return 0; }
+    /** Returns the largest value that the distribution can produce. */
+    IntType max BOOST_PREVENT_MACRO_SUBSTITUTION() const { return _t; }
+
+    /** Returns the parameters of the distribution. */
+    param_type param() const { return param_type(_t, _p); }
+    /** Sets parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        _t = parm.t();
+        _p = parm.p();
+        init();
+    }
+
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { }
+
+#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
+    /** Writes the parameters of the distribution to a @c std::ostream. */
+    template<class CharT, class Traits>
+    friend std::basic_ostream<CharT,Traits>&
+    operator<<(std::basic_ostream<CharT,Traits>& os,
+               const binomial_distribution& bd)
+    {
+        os << bd.param();
+        return os;
+    }
+    
+    /** Reads the parameters of the distribution from a @c std::istream. */
+    template<class CharT, class Traits>
+    friend std::basic_istream<CharT,Traits>&
+    operator>>(std::basic_istream<CharT,Traits>& is, binomial_distribution& bd)
+    {
+        bd.read(is);
+        return is;
+    }
+#endif
+
+    /** Returns true if the two distributions will produce the same
+        sequence of values, given equal generators. */
+    friend bool operator==(const binomial_distribution& lhs,
+                           const binomial_distribution& rhs)
+    {
+        return lhs._t == rhs._t && lhs._p == rhs._p;
+    }
+    /** Returns true if the two distributions could produce different
+        sequences of values, given equal generators. */
+    friend bool operator!=(const binomial_distribution& lhs,
+                           const binomial_distribution& rhs)
+    {
+        return !(lhs == rhs);
+    }
+
+private:
+
+    /// @cond show_private
+
+    template<class CharT, class Traits>
+    void read(std::basic_istream<CharT, Traits>& is) {
+        param_type parm;
+        if(is >> parm) {
+            param(parm);
+        }
+    }
+
+    bool use_inversion() const
+    {
+        // BTRD is safe when np >= 10
+        return m < 11;
+    }
+
+    // computes the correction factor for the Stirling approximation
+    // for log(k!)
+    static RealType fc(IntType k)
+    {
+        if(k < 10) return detail::binomial_table<RealType>::table[k];
+        else {
+            RealType ikp1 = RealType(1) / (k + 1);
+            return (RealType(1)/12
+                 - (RealType(1)/360
+                 - (RealType(1)/1260)*(ikp1*ikp1))*(ikp1*ikp1))*ikp1;
+        }
+    }
+
+    void init()
+    {
+        using std::sqrt;
+        using std::pow;
+
+        RealType p = (0.5 < _p)? (1 - _p) : _p;
+        IntType t = _t;
+        
+        m = static_cast<IntType>((t+1)*p);
+
+        if(use_inversion()) {
+            q_n = pow((1 - p), static_cast<RealType>(t));
+        } else {
+            btrd.r = p/(1-p);
+            btrd.nr = (t+1)*btrd.r;
+            btrd.npq = t*p*(1-p);
+            RealType sqrt_npq = sqrt(btrd.npq);
+            btrd.b = 1.15 + 2.53 * sqrt_npq;
+            btrd.a = -0.0873 + 0.0248*btrd.b + 0.01*p;
+            btrd.c = t*p + 0.5;
+            btrd.alpha = (2.83 + 5.1/btrd.b) * sqrt_npq;
+            btrd.v_r = 0.92 - 4.2/btrd.b;
+            btrd.u_rv_r = 0.86*btrd.v_r;
+        }
+    }
+
+    template<class URNG>
+    result_type generate(URNG& urng) const
+    {
+        using std::floor;
+        using std::abs;
+        using std::log;
+
+        while(true) {
+            RealType u;
+            RealType v = uniform_01<RealType>()(urng);
+            if(v <= btrd.u_rv_r) {
+                u = v/btrd.v_r - 0.43;
+                return static_cast<IntType>(floor(
+                    (2*btrd.a/(0.5 - abs(u)) + btrd.b)*u + btrd.c));
+            }
+
+            if(v >= btrd.v_r) {
+                u = uniform_01<RealType>()(urng) - 0.5;
+            } else {
+                u = v/btrd.v_r - 0.93;
+                u = ((u < 0)? -0.5 : 0.5) - u;
+                v = uniform_01<RealType>()(urng) * btrd.v_r;
+            }
+
+            RealType us = 0.5 - abs(u);
+            IntType k = static_cast<IntType>(floor((2*btrd.a/us + btrd.b)*u + btrd.c));
+            if(k < 0 || k > _t) continue;
+            v = v*btrd.alpha/(btrd.a/(us*us) + btrd.b);
+            RealType km = abs(k - m);
+            if(km <= 15) {
+                RealType f = 1;
+                if(m < k) {
+                    IntType i = m;
+                    do {
+                        ++i;
+                        f = f*(btrd.nr/i - btrd.r);
+                    } while(i != k);
+                } else if(m > k) {
+                    IntType i = k;
+                    do {
+                        ++i;
+                        v = v*(btrd.nr/i - btrd.r);
+                    } while(i != m);
+                }
+                if(v <= f) return k;
+                else continue;
+            } else {
+                // final acceptance/rejection
+                v = log(v);
+                RealType rho =
+                    (km/btrd.npq)*(((km/3. + 0.625)*km + 1./6)/btrd.npq + 0.5);
+                RealType t = -km*km/(2*btrd.npq);
+                if(v < t - rho) return k;
+                if(v > t + rho) continue;
+
+                IntType nm = _t - m + 1;
+                RealType h = (m + 0.5)*log((m + 1)/(btrd.r*nm))
+                           + fc(m) + fc(_t - m);
+
+                IntType nk = _t - k + 1;
+                if(v <= h + (_t+1)*log(static_cast<RealType>(nm)/nk)
+                          + (k + 0.5)*log(nk*btrd.r/(k+1))
+                          - fc(k)
+                          - fc(_t - k))
+                {
+                    return k;
+                } else {
+                    continue;
+                }
+            }
+        }
+    }
+
+    template<class URNG>
+    IntType invert(IntType t, RealType p, URNG& urng) const
+    {
+        RealType q = 1 - p;
+        RealType s = p / q;
+        RealType a = (t + 1) * s;
+        RealType r = q_n;
+        RealType u = uniform_01<RealType>()(urng);
+        IntType x = 0;
+        while(u > r) {
+            u = u - r;
+            ++x;
+            RealType r1 = ((a/x) - s) * r;
+            // If r gets too small then the round-off error
+            // becomes a problem.  At this point, p(i) is
+            // decreasing exponentially, so if we just call
+            // it 0, it's close enough.  Note that the
+            // minimum value of q_n is about 1e-7, so we
+            // may need to be a little careful to make sure that
+            // we don't terminate the first time through the loop
+            // for float.  (Hence the test that r is decreasing)
+            if(r1 < std::numeric_limits<RealType>::epsilon() && r1 < r) {
+                break;
+            }
+            r = r1;
+        }
+        return x;
+    }
+
+    // parameters
+    IntType _t;
+    RealType _p;
+
+    // common data
+    IntType m;
+
+    union {
+        // for btrd
+        struct {
+            RealType r;
+            RealType nr;
+            RealType npq;
+            RealType b;
+            RealType a;
+            RealType c;
+            RealType alpha;
+            RealType v_r;
+            RealType u_rv_r;
+        } btrd;
+        // for inversion
+        RealType q_n;
+    };
+
+    /// @endcond
+};
+
+}
+
+// backwards compatibility
+using random::binomial_distribution;
+
+}
+
+#include <boost/random/detail/enable_warnings.hpp>
+
+#endif

depends/x86_64-pc-linux-gnu/include/boost/random/cauchy_distribution.hpp

@@ -0,0 +1,214 @@
+/* boost random/cauchy_distribution.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2001-02-18  moved to individual header files
+ */
+
+#ifndef BOOST_RANDOM_CAUCHY_DISTRIBUTION_HPP
+#define BOOST_RANDOM_CAUCHY_DISTRIBUTION_HPP
+
+#include <boost/config/no_tr1/cmath.hpp>
+#include <iosfwd>
+#include <istream>
+#include <boost/limits.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/uniform_01.hpp>
+
+namespace boost {
+namespace random {
+
+// Cauchy distribution: 
+
+/**
+ * The cauchy distribution is a continuous distribution with two
+ * parameters, median and sigma.
+ *
+ * It has \f$\displaystyle p(x) = \frac{\sigma}{\pi(\sigma^2 + (x-m)^2)}\f$
+ */
+template<class RealType = double>
+class cauchy_distribution
+{
+public:
+    typedef RealType input_type;
+    typedef RealType result_type;
+
+    class param_type
+    {
+    public:
+
+        typedef cauchy_distribution distribution_type;
+
+        /** Constructs the parameters of the cauchy distribution. */
+        explicit param_type(RealType median_arg = RealType(0.0),
+                            RealType sigma_arg = RealType(1.0))
+          : _median(median_arg), _sigma(sigma_arg) {}
+
+        // backwards compatibility for Boost.Random
+
+        /** Returns the median of the distribution. */
+        RealType median() const { return _median; }
+        /** Returns the sigma parameter of the distribution. */
+        RealType sigma() const { return _sigma; }
+
+        // The new names in C++0x.
+
+        /** Returns the median of the distribution. */
+        RealType a() const { return _median; }
+        /** Returns the sigma parameter of the distribution. */
+        RealType b() const { return _sigma; }
+
+        /** Writes the parameters to a std::ostream. */
+        BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
+        {
+            os << parm._median << " " << parm._sigma;
+            return os;
+        }
+
+        /** Reads the parameters from a std::istream. */
+        BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
+        {
+            is >> parm._median >> std::ws >> parm._sigma;
+            return is;
+        }
+
+        /** Returns true if the two sets of parameters are equal. */
+        BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
+        { return lhs._median == rhs._median && lhs._sigma == rhs._sigma; }
+
+        /** Returns true if the two sets of parameters are different. */
+        BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+
+    private:
+        RealType _median;
+        RealType _sigma;
+    };
+
+    /**
+     * Constructs a \cauchy_distribution with the paramters @c median
+     * and @c sigma.
+     */
+    explicit cauchy_distribution(RealType median_arg = RealType(0.0), 
+                                 RealType sigma_arg = RealType(1.0))
+      : _median(median_arg), _sigma(sigma_arg) { }
+    
+    /**
+     * Constructs a \cauchy_distribution from it's parameters.
+     */
+    explicit cauchy_distribution(const param_type& parm)
+      : _median(parm.median()), _sigma(parm.sigma()) { }
+
+    // compiler-generated copy ctor and assignment operator are fine
+
+    // backwards compatibility for Boost.Random
+
+    /** Returns: the "median" parameter of the distribution */
+    RealType median() const { return _median; }
+    /** Returns: the "sigma" parameter of the distribution */
+    RealType sigma() const { return _sigma; }
+    
+    // The new names in C++0x
+
+    /** Returns: the "median" parameter of the distribution */
+    RealType a() const { return _median; }
+    /** Returns: the "sigma" parameter of the distribution */
+    RealType b() 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)(); }
+
+    param_type param() const { return param_type(_median, _sigma); }
+
+    void param(const param_type& parm)
+    {
+        _median = parm.median();
+        _sigma = parm.sigma();
+    }
+
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { }
+
+    /**
+     * Returns: A random variate distributed according to the
+     * cauchy distribution.
+     */
+    template<class Engine>
+    result_type operator()(Engine& eng)
+    {
+        // Can we have a boost::mathconst please?
+        const result_type pi = result_type(3.14159265358979323846);
+        using std::tan;
+        RealType val = uniform_01<RealType>()(eng)-result_type(0.5);
+        return _median + _sigma * tan(pi*val);
+    }
+
+    /**
+     * Returns: A random variate distributed according to the
+     * cauchy distribution with parameters specified by param.
+     */
+    template<class Engine>
+    result_type operator()(Engine& eng, const param_type& parm)
+    {
+        return cauchy_distribution(parm)(eng);
+    }
+
+    /**
+     * Writes the distribution to a @c std::ostream.
+     */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, cauchy_distribution, cd)
+    {
+        os << cd._median << " " << cd._sigma;
+        return os;
+    }
+
+    /**
+     * Reads the distribution from a @c std::istream.
+     */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, cauchy_distribution, cd)
+    {
+        is >> cd._median >> std::ws >> cd._sigma;
+        return is;
+    }
+
+    /**
+     * Returns true if the two distributions will produce
+     * identical sequences of values, given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(cauchy_distribution, lhs, rhs)
+    { return lhs._median == rhs._median && lhs._sigma == rhs._sigma; }
+
+    /**
+     * Returns true if the two distributions may produce
+     * different sequences of values, given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(cauchy_distribution)
+
+private:
+    RealType _median;
+    RealType _sigma;
+};
+
+} // namespace random
+
+using random::cauchy_distribution;
+
+} // namespace boost
+
+#endif // BOOST_RANDOM_CAUCHY_DISTRIBUTION_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/chi_squared_distribution.hpp

@@ -0,0 +1,209 @@
+/* boost random/chi_squared_distribution.hpp header file
+ *
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_CHI_SQUARED_DISTRIBUTION_HPP_INCLUDED
+#define BOOST_RANDOM_CHI_SQUARED_DISTRIBUTION_HPP_INCLUDED
+
+#include <iosfwd>
+#include <boost/limits.hpp>
+
+#include <boost/random/detail/config.hpp>
+#include <boost/random/gamma_distribution.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * The chi squared distribution is a real valued distribution with
+ * one parameter, @c n.  The distribution produces values > 0.
+ *
+ * The distribution function is
+ * \f$\displaystyle P(x) = \frac{x^{(n/2)-1}e^{-x/2}}{\Gamma(n/2)2^{n/2}}\f$.
+ */
+template<class RealType = double>
+class chi_squared_distribution {
+public:
+    typedef RealType result_type;
+    typedef RealType input_type;
+
+    class param_type {
+    public:
+        typedef chi_squared_distribution distribution_type;
+        /**
+         * Construct a param_type object.  @c n
+         * is the parameter of the distribution.
+         *
+         * Requires: t >=0 && 0 <= p <= 1
+         */
+        explicit param_type(RealType n_arg = RealType(1))
+          : _n(n_arg)
+        {}
+        /** Returns the @c n parameter of the distribution. */
+        RealType n() const { return _n; }
+#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
+        /** Writes the parameters of the distribution to a @c std::ostream. */
+        template<class CharT, class Traits>
+        friend std::basic_ostream<CharT,Traits>&
+        operator<<(std::basic_ostream<CharT,Traits>& os,
+                   const param_type& parm)
+        {
+            os << parm._n;
+            return os;
+        }
+    
+        /** Reads the parameters of the distribution from a @c std::istream. */
+        template<class CharT, class Traits>
+        friend std::basic_istream<CharT,Traits>&
+        operator>>(std::basic_istream<CharT,Traits>& is, param_type& parm)
+        {
+            is >> parm._n;
+            return is;
+        }
+#endif
+        /** Returns true if the parameters have the same values. */
+        friend bool operator==(const param_type& lhs, const param_type& rhs)
+        {
+            return lhs._n == rhs._n;
+        }
+        /** Returns true if the parameters have different values. */
+        friend bool operator!=(const param_type& lhs, const param_type& rhs)
+        {
+            return !(lhs == rhs);
+        }
+    private:
+        RealType _n;
+    };
+    
+    /**
+     * Construct a @c chi_squared_distribution object. @c n
+     * is the parameter of the distribution.
+     *
+     * Requires: t >=0 && 0 <= p <= 1
+     */
+    explicit chi_squared_distribution(RealType n_arg = RealType(1))
+      : _impl(static_cast<RealType>(n_arg / 2))
+    {
+    }
+    
+    /**
+     * Construct an @c chi_squared_distribution object from the
+     * parameters.
+     */
+    explicit chi_squared_distribution(const param_type& parm)
+      : _impl(static_cast<RealType>(parm.n() / 2))
+    {
+    }
+    
+    /**
+     * Returns a random variate distributed according to the
+     * chi squared distribution.
+     */
+    template<class URNG>
+    RealType operator()(URNG& urng)
+    {
+        return 2 * _impl(urng);
+    }
+    
+    /**
+     * Returns a random variate distributed according to the
+     * chi squared distribution with parameters specified by @c param.
+     */
+    template<class URNG>
+    RealType operator()(URNG& urng, const param_type& parm) const
+    {
+        return chi_squared_distribution(parm)(urng);
+    }
+
+    /** Returns the @c n parameter of the distribution. */
+    RealType n() const { return 2 * _impl.alpha(); }
+
+    /** Returns the smallest value that the distribution can produce. */
+    RealType min BOOST_PREVENT_MACRO_SUBSTITUTION() const { return 0; }
+    /** 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(n()); }
+    /** Sets parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        typedef gamma_distribution<RealType> impl_type;
+        typename impl_type::param_type impl_parm(static_cast<RealType>(parm.n() / 2));
+        _impl.param(impl_parm);
+    }
+
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { _impl.reset(); }
+
+#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
+    /** Writes the parameters of the distribution to a @c std::ostream. */
+    template<class CharT, class Traits>
+    friend std::basic_ostream<CharT,Traits>&
+    operator<<(std::basic_ostream<CharT,Traits>& os,
+               const chi_squared_distribution& c2d)
+    {
+        os << c2d.param();
+        return os;
+    }
+    
+    /** Reads the parameters of the distribution from a @c std::istream. */
+    template<class CharT, class Traits>
+    friend std::basic_istream<CharT,Traits>&
+    operator>>(std::basic_istream<CharT,Traits>& is,
+               chi_squared_distribution& c2d)
+    {
+        c2d.read(is);
+        return is;
+    }
+#endif
+
+    /** Returns true if the two distributions will produce the same
+        sequence of values, given equal generators. */
+    friend bool operator==(const chi_squared_distribution& lhs,
+                           const chi_squared_distribution& rhs)
+    {
+        return lhs._impl == rhs._impl;
+    }
+    /** Returns true if the two distributions could produce different
+        sequences of values, given equal generators. */
+    friend bool operator!=(const chi_squared_distribution& lhs,
+                           const chi_squared_distribution& rhs)
+    {
+        return !(lhs == rhs);
+    }
+
+private:
+
+    /// @cond show_private
+
+    template<class CharT, class Traits>
+    void read(std::basic_istream<CharT, Traits>& is) {
+        param_type parm;
+        if(is >> parm) {
+            param(parm);
+        }
+    }
+
+    gamma_distribution<RealType> _impl;
+
+    /// @endcond
+};
+
+}
+
+}
+
+#endif

depends/x86_64-pc-linux-gnu/include/boost/random/detail/auto_link.hpp

@@ -0,0 +1,40 @@
+/* boost random auto_link.hpp header file
+ *
+ * Copyright Steven Watanabe 2010
+ * 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)
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_DETAIL_AUTO_LINK_HPP
+#define BOOST_RANDOM_DETAIL_AUTO_LINK_HPP
+
+#include <boost/config.hpp>
+
+#if defined(BOOST_ALL_DYN_LINK) || defined(BOOST_RANDOM_DYN_LINK)
+    #if defined(BOOST_RANDOM_SOURCE)
+        #define BOOST_RANDOM_DECL BOOST_SYMBOL_EXPORT
+    #else
+        #define BOOST_RANDOM_DECL BOOST_SYMBOL_IMPORT
+    #endif
+#endif
+
+#ifndef BOOST_RANDOM_DECL
+    #define BOOST_RANDOM_DECL
+#endif
+
+#if !defined(BOOST_RANDOM_NO_LIB) && !defined(BOOST_ALL_NO_LIB) && !defined(BOOST_RANDOM_SOURCE)
+
+#define BOOST_LIB_NAME boost_random
+
+#if defined(BOOST_RANDOM_DYN_LINK) || defined(BOOST_ALL_DYN_LINK)
+    #define BOOST_DYN_LINK
+#endif
+
+#include <boost/config/auto_link.hpp>
+
+#endif
+
+#endif

depends/x86_64-pc-linux-gnu/include/boost/random/detail/config.hpp

@@ -0,0 +1,18 @@
+/* boost random/detail/config.hpp header file
+ *
+ * Copyright Steven Watanabe 2009
+ * 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.
+ *
+ * $Id$
+ */
+
+#include <boost/config.hpp>
+
+#if (defined(BOOST_NO_OPERATORS_IN_NAMESPACE) || defined(BOOST_NO_MEMBER_TEMPLATE_FRIENDS)) \
+    && !defined(BOOST_MSVC)
+    #define BOOST_RANDOM_NO_STREAM_OPERATORS
+#endif

depends/x86_64-pc-linux-gnu/include/boost/random/detail/const_mod.hpp

@@ -0,0 +1,216 @@
+/* boost random/detail/const_mod.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2001-02-18  moved to individual header files
+ */
+
+#ifndef BOOST_RANDOM_CONST_MOD_HPP
+#define BOOST_RANDOM_CONST_MOD_HPP
+
+#include <boost/assert.hpp>
+#include <boost/static_assert.hpp>
+#include <boost/integer_traits.hpp>
+#include <boost/type_traits/make_unsigned.hpp>
+#include <boost/random/detail/large_arithmetic.hpp>
+
+#include <boost/random/detail/disable_warnings.hpp>
+
+namespace boost {
+namespace random {
+
+template<class IntType, IntType m>
+class const_mod
+{
+public:
+  static IntType apply(IntType x)
+  {
+    if(((unsigned_m() - 1) & unsigned_m()) == 0)
+      return (unsigned_type(x)) & (unsigned_m() - 1);
+    else {
+      IntType suppress_warnings = (m == 0);
+      BOOST_ASSERT(suppress_warnings == 0);
+      return x % (m + suppress_warnings);
+    }
+  }
+
+  static IntType add(IntType x, IntType c)
+  {
+    if(((unsigned_m() - 1) & unsigned_m()) == 0)
+      return (unsigned_type(x) + unsigned_type(c)) & (unsigned_m() - 1);
+    else if(c == 0)
+      return x;
+    else if(x < m - c)
+      return x + c;
+    else
+      return x - (m - c);
+  }
+
+  static IntType mult(IntType a, IntType x)
+  {
+    if(((unsigned_m() - 1) & unsigned_m()) == 0)
+      return unsigned_type(a) * unsigned_type(x) & (unsigned_m() - 1);
+    else if(a == 0)
+      return 0;
+    else if(a == 1)
+      return x;
+    else if(m <= traits::const_max/a)      // i.e. a*m <= max
+      return mult_small(a, x);
+    else if(traits::is_signed && (m%a < m/a))
+      return mult_schrage(a, x);
+    else
+      return mult_general(a, x);
+  }
+
+  static IntType mult_add(IntType a, IntType x, IntType c)
+  {
+    if(((unsigned_m() - 1) & unsigned_m()) == 0)
+      return (unsigned_type(a) * unsigned_type(x) + unsigned_type(c)) & (unsigned_m() - 1);
+    else if(a == 0)
+      return c;
+    else if(m <= (traits::const_max-c)/a) {  // i.e. a*m+c <= max
+      IntType suppress_warnings = (m == 0);
+      BOOST_ASSERT(suppress_warnings == 0);
+      return (a*x+c) % (m + suppress_warnings);
+    } else
+      return add(mult(a, x), c);
+  }
+
+  static IntType pow(IntType a, boost::uintmax_t exponent)
+  {
+      IntType result = 1;
+      while(exponent != 0) {
+          if(exponent % 2 == 1) {
+              result = mult(result, a);
+          }
+          a = mult(a, a);
+          exponent /= 2;
+      }
+      return result;
+  }
+
+  static IntType invert(IntType x)
+  { return x == 0 ? 0 : (m == 0? invert_euclidian0(x) : invert_euclidian(x)); }
+
+private:
+  typedef integer_traits<IntType> traits;
+  typedef typename make_unsigned<IntType>::type unsigned_type;
+
+  const_mod();      // don't instantiate
+
+  static IntType mult_small(IntType a, IntType x)
+  {
+    IntType suppress_warnings = (m == 0);
+    BOOST_ASSERT(suppress_warnings == 0);
+    return a*x % (m + suppress_warnings);
+  }
+
+  static IntType mult_schrage(IntType a, IntType value)
+  {
+    const IntType q = m / a;
+    const IntType r = m % a;
+
+    BOOST_ASSERT(r < q);        // check that overflow cannot happen
+
+    return sub(a*(value%q), r*(value/q));
+  }
+
+  static IntType mult_general(IntType a, IntType b)
+  {
+    IntType suppress_warnings = (m == 0);
+    BOOST_ASSERT(suppress_warnings == 0);
+    IntType modulus = m + suppress_warnings;
+    BOOST_ASSERT(modulus == m);
+    if(::boost::uintmax_t(modulus) <=
+        (::std::numeric_limits< ::boost::uintmax_t>::max)() / modulus)
+    {
+      return static_cast<IntType>(boost::uintmax_t(a) * b % modulus);
+    } else {
+      return static_cast<IntType>(detail::mulmod(a, b, modulus));
+    }
+  }
+
+  static IntType sub(IntType a, IntType b)
+  {
+    if(a < b)
+      return m - (b - a);
+    else
+      return a - b;
+  }
+
+  static unsigned_type unsigned_m()
+  {
+      if(m == 0) {
+          return unsigned_type((std::numeric_limits<IntType>::max)()) + 1;
+      } else {
+          return unsigned_type(m);
+      }
+  }
+
+  // invert c in the finite field (mod m) (m must be prime)
+  static IntType invert_euclidian(IntType c)
+  {
+    // we are interested in the gcd factor for c, because this is our inverse
+    BOOST_ASSERT(c > 0);
+    IntType l1 = 0;
+    IntType l2 = 1;
+    IntType n = c;
+    IntType p = m;
+    for(;;) {
+      IntType q = p / n;
+      l1 += q * l2;
+      p -= q * n;
+      if(p == 0)
+        return l2;
+      IntType q2 = n / p;
+      l2 += q2 * l1;
+      n -= q2 * p;
+      if(n == 0)
+        return m - l1;
+    }
+  }
+
+  // invert c in the finite field (mod m) (c must be relatively prime to m)
+  static IntType invert_euclidian0(IntType c)
+  {
+    // we are interested in the gcd factor for c, because this is our inverse
+    BOOST_ASSERT(c > 0);
+    if(c == 1) return 1;
+    IntType l1 = 0;
+    IntType l2 = 1;
+    IntType n = c;
+    IntType p = m;
+    IntType max = (std::numeric_limits<IntType>::max)();
+    IntType q = max / n;
+    BOOST_ASSERT(max % n != n - 1 && "c must be relatively prime to m.");
+    l1 += q * l2;
+    p = max - q * n + 1;
+    for(;;) {
+      if(p == 0)
+        return l2;
+      IntType q2 = n / p;
+      l2 += q2 * l1;
+      n -= q2 * p;
+      if(n == 0)
+        return m - l1;
+      q = p / n;
+      l1 += q * l2;
+      p -= q * n;
+    }
+  }
+};
+
+} // namespace random
+} // namespace boost
+
+#include <boost/random/detail/enable_warnings.hpp>
+
+#endif // BOOST_RANDOM_CONST_MOD_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/detail/disable_warnings.hpp

@@ -0,0 +1,29 @@
+/* boost random/detail/disable_warnings.hpp header file
+ *
+ * Copyright Steven Watanabe 2009
+ * 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.
+ *
+ * $Id$
+ *
+ */
+
+// No #include guard.  This header is intended to be included multiple times.
+
+#include <boost/config.hpp>
+
+#ifdef BOOST_MSVC
+#pragma warning(push)
+#pragma warning(disable:4512)
+#pragma warning(disable:4127)
+#pragma warning(disable:4724)
+#pragma warning(disable:4800) // 'int' : forcing value to bool 'true' or 'false' (performance warning)
+#endif
+
+#if defined(BOOST_GCC) && BOOST_GCC >= 40600
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wlogical-op"
+#endif

depends/x86_64-pc-linux-gnu/include/boost/random/detail/enable_warnings.hpp

@@ -0,0 +1,22 @@
+/* boost random/detail/enable_warnings.hpp header file
+ *
+ * Copyright Steven Watanabe 2009
+ * 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.
+ *
+ * $Id$
+ *
+ */
+
+// No #include guard.  This header is intended to be included multiple times.
+
+#ifdef BOOST_MSVC
+#pragma warning(pop)
+#endif
+
+#if defined(BOOST_GCC) && BOOST_GCC >= 40600
+#pragma GCC diagnostic pop
+#endif

depends/x86_64-pc-linux-gnu/include/boost/random/detail/generator_bits.hpp

@@ -0,0 +1,36 @@
+/* boost random/detail/generator_bits.hpp header file
+ *
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ *
+ */
+
+#ifndef BOOST_RANDOM_DETAIL_GENERATOR_BITS_HPP
+#define BOOST_RANDOM_DETAIL_GENERATOR_BITS_HPP
+
+#include <boost/limits.hpp>
+
+namespace boost {
+namespace random {
+namespace detail {
+
+// This is a temporary measure that retains backwards
+// compatibility.
+template<class URNG>
+struct generator_bits {
+    static std::size_t value() {
+        return std::numeric_limits<typename URNG::result_type>::digits;
+    }
+};
+
+} // namespace detail
+} // namespace random
+} // namespace boost
+
+#endif // BOOST_RANDOM_DETAIL_GENERATOR_BITS_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/detail/generator_seed_seq.hpp

@@ -0,0 +1,40 @@
+/* boost random/mersenne_twister.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * Copyright Steven Watanabe 2010
+ * 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.
+ *
+ * $Id$
+ *
+ */
+
+#ifndef BOOST_RANDOM_DETAIL_GENERATOR_SEED_SEQ_HPP_INCLUDED
+#define BOOST_RANDOM_DETAIL_GENERATOR_SEED_SEQ_HPP_INCLUDED
+
+namespace boost {
+namespace random {
+namespace detail {
+
+template<class Generator>
+class generator_seed_seq {
+public:
+    generator_seed_seq(Generator& g) : gen(&g) {}
+    template<class It>
+    void generate(It first, It last) {
+        for(; first != last; ++first) {
+            *first = (*gen)();
+        }
+    }
+private:
+    Generator* gen;
+};
+
+}
+}
+}
+
+#endif

depends/x86_64-pc-linux-gnu/include/boost/random/detail/int_float_pair.hpp

@@ -0,0 +1,121 @@
+/* boost random/detail/int_float_pair.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.
+ *
+ * $Id$
+ *
+ */
+
+#ifndef BOOST_RANDOM_DETAIL_INT_FLOAT_PAIR_HPP
+#define BOOST_RANDOM_DETAIL_INT_FLOAT_PAIR_HPP
+
+#include <utility>
+#include <boost/integer.hpp>
+#include <boost/integer/integer_mask.hpp>
+#include <boost/type_traits/make_unsigned.hpp>
+#include <boost/type_traits/is_integral.hpp>
+#include <boost/random/uniform_01.hpp>
+#include <boost/random/uniform_int_distribution.hpp>
+#include <boost/random/detail/signed_unsigned_tools.hpp>
+#include <boost/random/detail/integer_log2.hpp>
+#include <boost/mpl/bool.hpp>
+
+namespace boost {
+namespace random {
+namespace detail {
+
+template<class Engine>
+inline typename boost::make_unsigned<typename Engine::result_type>::type
+generate_one_digit(Engine& eng, std::size_t bits)
+{
+    typedef typename Engine::result_type base_result;
+    typedef typename boost::make_unsigned<base_result>::type base_unsigned;
+    
+    base_unsigned range =
+        detail::subtract<base_result>()((eng.max)(), (eng.min)());
+    base_unsigned y0_mask = (base_unsigned(2) << (bits - 1)) - 1;
+    base_unsigned y0 = (range + 1) & ~y0_mask;
+    base_unsigned u;
+    do {
+        u = detail::subtract<base_result>()(eng(), (eng.min)());
+    } while(y0 != 0 && u > base_unsigned(y0 - 1));
+    return u & y0_mask;
+}
+
+template<class RealType, std::size_t w, class Engine>
+std::pair<RealType, int> generate_int_float_pair(Engine& eng, boost::mpl::true_)
+{
+    typedef typename Engine::result_type base_result;
+    typedef typename boost::make_unsigned<base_result>::type base_unsigned;
+    
+    base_unsigned range =
+        detail::subtract<base_result>()((eng.max)(), (eng.min)());
+    
+    std::size_t m =
+        (range == (std::numeric_limits<base_unsigned>::max)()) ?
+            std::numeric_limits<base_unsigned>::digits :
+            detail::integer_log2(range + 1);
+            
+    int bucket = 0;
+    // process as many full digits as possible into the int part
+    for(std::size_t i = 0; i < w/m; ++i) {
+        base_unsigned u = generate_one_digit(eng, m);
+        bucket = (bucket << m) | u;
+    }
+    RealType r;
+
+    const std::size_t digits = std::numeric_limits<RealType>::digits;
+    {
+        base_unsigned u = generate_one_digit(eng, m);
+        base_unsigned mask = (base_unsigned(1) << (w%m)) - 1;
+        bucket = (bucket << (w%m)) | (mask & u);
+        const RealType mult = RealType(1)/RealType(base_unsigned(1) << (m - w%m));
+        // zero out unused bits
+        if (m - w%m > digits) {
+            u &= ~(base_unsigned(1) << (m - digits));
+        }
+        r = RealType(u >> (w%m)) * mult;
+    }
+    for(std::size_t i = m - w%m; i + m < digits; ++i) {
+        base_unsigned u = generate_one_digit(eng, m);
+        r += u;
+        r *= RealType(0.5)/RealType(base_unsigned(1) << (m - 1));
+    }
+    if (m - w%m < digits)
+    {
+        const std::size_t remaining = (digits - m + w%m) % m;
+        base_unsigned u = generate_one_digit(eng, m);
+        r += u & ((base_unsigned(2) << (remaining - 1)) - 1);
+        const RealType mult = RealType(0.5)/RealType(base_unsigned(1) << (remaining - 1));
+        r *= mult;
+    }
+    return std::make_pair(r, bucket);
+}
+
+template<class RealType, std::size_t w, class Engine>
+inline std::pair<RealType, int> generate_int_float_pair(Engine& eng, boost::mpl::false_)
+{
+    int bucket = uniform_int_distribution<>(0, (1 << w) - 1)(eng);
+    RealType r = uniform_01<RealType>()(eng);
+    return std::make_pair(r, bucket);
+}
+
+template<class RealType, std::size_t w, class Engine>
+inline std::pair<RealType, int> generate_int_float_pair(Engine& eng)
+{
+    typedef typename Engine::result_type base_result;
+    return generate_int_float_pair<RealType, w>(eng,
+        boost::is_integral<base_result>());
+}
+
+} // namespace detail
+} // namespace random
+} // namespace boost
+
+#endif // BOOST_RANDOM_DETAIL_INT_FLOAT_PAIR_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/detail/integer_log2.hpp

@@ -0,0 +1,84 @@
+/* boost random/detail/integer_log2.hpp header file
+ *
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ *
+ */
+
+#ifndef BOOST_RANDOM_DETAIL_INTEGER_LOG2_HPP
+#define BOOST_RANDOM_DETAIL_INTEGER_LOG2_HPP
+
+#include <boost/config.hpp>
+#include <boost/limits.hpp>
+#include <boost/pending/integer_log2.hpp>
+
+namespace boost {
+namespace random {
+namespace detail {
+
+#if !defined(BOOST_NO_CXX11_CONSTEXPR)
+#define BOOST_RANDOM_DETAIL_CONSTEXPR constexpr
+#elif defined(BOOST_MSVC)
+#define BOOST_RANDOM_DETAIL_CONSTEXPR __forceinline
+#elif defined(__GNUC__) && __GNUC__ >= 4
+#define BOOST_RANDOM_DETAIL_CONSTEXPR inline __attribute__((__const__)) __attribute__((__always_inline__))
+#else
+#define BOOST_RANDOM_DETAIL_CONSTEXPR inline
+#endif
+
+template<int Shift>
+struct integer_log2_impl
+{
+#if defined(BOOST_NO_CXX11_CONSTEXPR)
+    template<class T>
+    BOOST_RANDOM_DETAIL_CONSTEXPR static int apply(T t, int accum)
+    {
+        int update = ((t >> Shift) != 0) * Shift;
+        return integer_log2_impl<Shift / 2>::apply(t >> update, accum + update);
+    }
+#else
+    template<class T>
+    BOOST_RANDOM_DETAIL_CONSTEXPR static int apply2(T t, int accum, int update)
+    {
+        return integer_log2_impl<Shift / 2>::apply(t >> update, accum + update);
+    }
+
+    template<class T>
+    BOOST_RANDOM_DETAIL_CONSTEXPR static int apply(T t, int accum)
+    {
+        return apply2(t, accum, ((t >> Shift) != 0) * Shift);
+    }
+#endif
+};
+
+template<>
+struct integer_log2_impl<1>
+{
+    template<class T>
+    BOOST_RANDOM_DETAIL_CONSTEXPR static int apply(T t, int accum)
+    {
+        return int(t >> 1) + accum;
+    }
+};
+
+template<class T>
+BOOST_RANDOM_DETAIL_CONSTEXPR int integer_log2(T t)
+{
+    return integer_log2_impl<
+        ::boost::detail::max_pow2_less<
+            ::std::numeric_limits<T>::digits, 4
+        >::value
+    >::apply(t, 0);
+}
+
+} // namespace detail
+} // namespace random
+} // namespace boost
+
+#endif // BOOST_RANDOM_DETAIL_INTEGER_LOG2_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/detail/iterator_mixin.hpp

@@ -0,0 +1,45 @@
+/* boost random/detail/iterator_mixin.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * 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.
+ *
+ * Revision history
+ */
+
+#ifndef BOOST_ITERATOR_MIXIN_HPP
+#define BOOST_ITERATOR_MIXIN_HPP
+
+#include <boost/operators.hpp>
+
+namespace boost {
+
+// must be in boost namespace, otherwise the inline friend trick fails
+template<class Generator, class ResultType>
+class generator_iterator_mixin_adapter
+  : incrementable<Generator>, equality_comparable<Generator>
+{
+public:
+  typedef std::input_iterator_tag iterator_category;
+  typedef ResultType value_type;
+  typedef std::ptrdiff_t difference_type;
+  typedef const value_type * pointer;
+  typedef const value_type & reference;
+  Generator& operator++() { v = cast()(); return cast(); }
+  const value_type& operator*() const { return v; }
+
+protected:
+  // instantiate from derived classes only
+  generator_iterator_mixin_adapter() { }
+  void iterator_init() { operator++(); }
+private:
+  Generator & cast() { return static_cast<Generator&>(*this); }
+  value_type v;
+};
+
+} // namespace boost
+
+#endif // BOOST_ITERATOR_MIXIN_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/detail/large_arithmetic.hpp

@@ -0,0 +1,122 @@
+/* boost random/detail/large_arithmetic.hpp header file
+ *
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_DETAIL_LARGE_ARITHMETIC_HPP
+#define BOOST_RANDOM_DETAIL_LARGE_ARITHMETIC_HPP
+
+#include <boost/cstdint.hpp>
+#include <boost/integer.hpp>
+#include <boost/limits.hpp>
+#include <boost/random/detail/integer_log2.hpp>
+
+#include <boost/random/detail/disable_warnings.hpp>
+
+namespace boost {
+namespace random {
+namespace detail {
+
+struct div_t {
+    boost::uintmax_t quotient;
+    boost::uintmax_t remainder;
+};
+
+inline div_t muldivmod(boost::uintmax_t a, boost::uintmax_t b, boost::uintmax_t m)
+{
+    const int bits =
+        ::std::numeric_limits< ::boost::uintmax_t>::digits / 2;
+    const ::boost::uintmax_t mask = (::boost::uintmax_t(1) << bits) - 1;
+    typedef ::boost::uint_t<bits>::fast digit_t;
+
+    int shift = std::numeric_limits< ::boost::uintmax_t>::digits - 1
+        - detail::integer_log2(m);
+
+    a <<= shift;
+    m <<= shift;
+
+    digit_t product[4] = { 0, 0, 0, 0 };
+    digit_t a_[2] = { digit_t(a & mask), digit_t((a >> bits) & mask) };
+    digit_t b_[2] = { digit_t(b & mask), digit_t((b >> bits) & mask) };
+    digit_t m_[2] = { digit_t(m & mask), digit_t((m >> bits) & mask) };
+
+    // multiply a * b
+    for(int i = 0; i < 2; ++i) {
+        digit_t carry = 0;
+        for(int j = 0; j < 2; ++j) {
+            ::boost::uint64_t temp = ::boost::uintmax_t(a_[i]) * b_[j] +
+                carry + product[i + j];
+            product[i + j] = digit_t(temp & mask);
+            carry = digit_t(temp >> bits);
+        }
+        if(carry != 0) {
+            product[i + 2] += carry;
+        }
+    }
+
+    digit_t quotient[2];
+
+    if(m == 0) {
+        div_t result = {
+            ((::boost::uintmax_t(product[3]) << bits) | product[2]),
+            ((::boost::uintmax_t(product[1]) << bits) | product[0]) >> shift,
+        };
+        return result;
+    }
+
+    // divide product / m
+    for(int i = 3; i >= 2; --i) {
+        ::boost::uintmax_t temp =
+            ::boost::uintmax_t(product[i]) << bits | product[i - 1];
+
+        digit_t q = digit_t((product[i] == m_[1]) ? mask : temp / m_[1]);
+
+        ::boost::uintmax_t rem =
+            ((temp - ::boost::uintmax_t(q) * m_[1]) << bits) + product[i - 2];
+
+        ::boost::uintmax_t diff = m_[0] * ::boost::uintmax_t(q);
+
+        int error = 0;
+        if(diff > rem) {
+            if(diff - rem > m) {
+                error = 2;
+            } else {
+                error = 1;
+            }
+        }
+        q -= error;
+        rem = rem + error * m - diff;
+
+        quotient[i - 2] = q;
+        product[i] = 0;
+        product[i-1] = static_cast<digit_t>((rem >> bits) & mask);
+        product[i-2] = static_cast<digit_t>(rem & mask);
+    }
+
+    div_t result = {
+        ((::boost::uintmax_t(quotient[1]) << bits) | quotient[0]),
+        ((::boost::uintmax_t(product[1]) << bits) | product[0]) >> shift,
+    };
+    return result;
+}
+
+inline boost::uintmax_t muldiv(boost::uintmax_t a, boost::uintmax_t b, boost::uintmax_t m)
+{ return detail::muldivmod(a, b, m).quotient; }
+
+inline boost::uintmax_t mulmod(boost::uintmax_t a, boost::uintmax_t b, boost::uintmax_t m)
+{ return detail::muldivmod(a, b, m).remainder; }
+
+} // namespace detail
+} // namespace random
+} // namespace boost
+
+#include <boost/random/detail/enable_warnings.hpp>
+
+#endif // BOOST_RANDOM_DETAIL_LARGE_ARITHMETIC_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/detail/operators.hpp

@@ -0,0 +1,84 @@
+/* boost random/detail/operators.hpp header file
+ *
+ * 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.
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_DETAIL_OPERATORS_HPP
+#define BOOST_RANDOM_DETAIL_OPERATORS_HPP
+
+#include <boost/random/detail/config.hpp>
+#include <boost/detail/workaround.hpp>
+
+#if BOOST_WORKAROUND(BOOST_MSVC, <= 1310)   \
+    || BOOST_WORKAROUND(__SUNPRO_CC, BOOST_TESTED_AT(0x5100))
+
+#define BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, T, t)                  \
+    template<class CharT, class Traits>                                 \
+    friend std::basic_ostream<CharT,Traits>&                            \
+    operator<<(std::basic_ostream<CharT,Traits>& os, const T& t) {      \
+        t.print(os, t);                                                 \
+        return os;                                                      \
+    }                                                                   \
+    template<class CharT, class Traits>                                 \
+    static std::basic_ostream<CharT,Traits>&                            \
+    print(std::basic_ostream<CharT,Traits>& os, const T& t)
+
+#define BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, T, t)                  \
+    template<class CharT, class Traits>                                 \
+    friend std::basic_istream<CharT,Traits>&                            \
+    operator>>(std::basic_istream<CharT,Traits>& is, T& t) {            \
+        t.read(is, t);                                                  \
+        return is;                                                      \
+    }                                                                   \
+    template<class CharT, class Traits>                                 \
+    static std::basic_istream<CharT,Traits>&                            \
+    read(std::basic_istream<CharT,Traits>& is, T& t)
+
+#endif
+
+#if defined(__BORLANDC__)
+
+#define BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(T, lhs, rhs)              \
+    bool operator==(const T& rhs) const                                 \
+    { return T::is_equal(*this, rhs); }                                 \
+    static bool is_equal(const T& lhs, const T& rhs)
+
+#define BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(T)                      \
+    bool operator!=(const T& rhs) const                                 \
+    { return !T::is_equal(*this, rhs); }
+
+#endif
+
+#ifndef BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR
+#define BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, T, t)                  \
+    template<class CharT, class Traits>                                 \
+    friend std::basic_ostream<CharT,Traits>&                            \
+    operator<<(std::basic_ostream<CharT,Traits>& os, const T& t)
+#endif
+
+#ifndef BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR
+#define BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, T, t)                  \
+    template<class CharT, class Traits>                                 \
+    friend std::basic_istream<CharT,Traits>&                            \
+    operator>>(std::basic_istream<CharT,Traits>& is, T& t)
+#endif
+
+#ifndef BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR
+#define BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(T, lhs, rhs)              \
+    friend bool operator==(const T& lhs, const T& rhs)
+#endif
+
+#ifndef BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR
+#define BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(T)                      \
+    friend bool operator!=(const T& lhs, const T& rhs)                  \
+    { return !(lhs == rhs); }
+#endif
+
+#endif

depends/x86_64-pc-linux-gnu/include/boost/random/detail/polynomial.hpp

@@ -0,0 +1,384 @@
+/* boost random/detail/polynomial.hpp header file
+ *
+ * Copyright Steven Watanabe 2014
+ * 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.
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_DETAIL_POLYNOMIAL_HPP
+#define BOOST_RANDOM_DETAIL_POLYNOMIAL_HPP
+
+#include <cstddef>
+#include <limits>
+#include <vector>
+#include <algorithm>
+#include <boost/assert.hpp>
+#include <boost/cstdint.hpp>
+
+namespace boost {
+namespace random {
+namespace detail {
+
+class polynomial_ops {
+public:
+    typedef unsigned long digit_t;
+
+    static void add(std::size_t size, const digit_t * lhs,
+                       const digit_t * rhs, digit_t * output)
+    {
+        for(std::size_t i = 0; i < size; ++i) {
+            output[i] = lhs[i] ^ rhs[i];
+        }
+    }
+
+    static void add_shifted_inplace(std::size_t size, const digit_t * lhs,
+                                    digit_t * output, std::size_t shift)
+    {
+        if(shift == 0) {
+            add(size, lhs, output, output);
+            return;
+        }
+        std::size_t bits = std::numeric_limits<digit_t>::digits;
+        digit_t prev = 0;
+        for(std::size_t i = 0; i < size; ++i) {
+            digit_t tmp = lhs[i];
+            output[i] ^= (tmp << shift) | (prev >> (bits-shift));
+            prev = tmp;
+        }
+        output[size] ^= (prev >> (bits-shift));
+    }
+
+    static void multiply_simple(std::size_t size, const digit_t * lhs,
+                                   const digit_t * rhs, digit_t * output)
+    {
+        std::size_t bits = std::numeric_limits<digit_t>::digits;
+        for(std::size_t i = 0; i < 2*size; ++i) {
+            output[i] = 0;
+        }
+        for(std::size_t i = 0; i < size; ++i) {
+            for(std::size_t j = 0; j < bits; ++j) {
+                if((lhs[i] & (digit_t(1) << j)) != 0) {
+                    add_shifted_inplace(size, rhs, output + i, j);
+                }
+            }
+        }
+    }
+
+    // memory requirements: (size - cutoff) * 4 + next_smaller
+    static void multiply_karatsuba(std::size_t size,
+                               const digit_t * lhs, const digit_t * rhs,
+                               digit_t * output)
+    {
+        if(size < 64) {
+            multiply_simple(size, lhs, rhs, output);
+            return;
+        }
+        // split in half
+        std::size_t cutoff = size/2;
+        multiply_karatsuba(cutoff, lhs, rhs, output);
+        multiply_karatsuba(size - cutoff, lhs + cutoff, rhs + cutoff,
+                              output + cutoff*2);
+        std::vector<digit_t> local1(size - cutoff);
+        std::vector<digit_t> local2(size - cutoff);
+        // combine the digits for the inner multiply
+        add(cutoff, lhs, lhs + cutoff, &local1[0]);
+        if(size & 1) local1[cutoff] = lhs[size - 1];
+        add(cutoff, rhs + cutoff, rhs, &local2[0]);
+        if(size & 1) local2[cutoff] = rhs[size - 1];
+        std::vector<digit_t> local3((size - cutoff) * 2);
+        multiply_karatsuba(size - cutoff, &local1[0], &local2[0], &local3[0]);
+        add(cutoff * 2, output, &local3[0], &local3[0]);
+        add((size - cutoff) * 2, output + cutoff*2, &local3[0], &local3[0]);
+        // Finally, add the inner result
+        add((size - cutoff) * 2, output + cutoff, &local3[0], output + cutoff);
+    }
+    
+    static void multiply_add_karatsuba(std::size_t size,
+                                       const digit_t * lhs, const digit_t * rhs,
+                                       digit_t * output)
+    {
+        std::vector<digit_t> buf(size * 2);
+        multiply_karatsuba(size, lhs, rhs, &buf[0]);
+        add(size * 2, &buf[0], output, output);
+    }
+
+    static void multiply(const digit_t * lhs, std::size_t lhs_size,
+                         const digit_t * rhs, std::size_t rhs_size,
+                         digit_t * output)
+    {
+        std::fill_n(output, lhs_size + rhs_size, digit_t(0));
+        multiply_add(lhs, lhs_size, rhs, rhs_size, output);
+    }
+
+    static void multiply_add(const digit_t * lhs, std::size_t lhs_size,
+                             const digit_t * rhs, std::size_t rhs_size,
+                             digit_t * output)
+    {
+        // split into pieces that can be passed to
+        // karatsuba multiply.
+        while(lhs_size != 0) {
+            if(lhs_size < rhs_size) {
+                std::swap(lhs, rhs);
+                std::swap(lhs_size, rhs_size);
+            }
+            
+            multiply_add_karatsuba(rhs_size, lhs, rhs, output);
+            
+            lhs += rhs_size;
+            lhs_size -= rhs_size;
+            output += rhs_size;
+        }
+    }
+
+    static void copy_bits(const digit_t * x, std::size_t low, std::size_t high,
+                   digit_t * out)
+    {
+        const std::size_t bits = std::numeric_limits<digit_t>::digits;
+        std::size_t offset = low/bits;
+        x += offset;
+        low -= offset*bits;
+        high -= offset*bits;
+        std::size_t n = (high-low)/bits;
+        if(low == 0) {
+            for(std::size_t i = 0; i < n; ++i) {
+                out[i] = x[i];
+            }
+        } else {
+            for(std::size_t i = 0; i < n; ++i) {
+                out[i] = (x[i] >> low) | (x[i+1] << (bits-low));
+            }
+        }
+        if((high-low)%bits) {
+            digit_t low_mask = (digit_t(1) << ((high-low)%bits)) - 1;
+            digit_t result = (x[n] >> low);
+            if(low != 0 && (n+1)*bits < high) {
+                result |= (x[n+1] << (bits-low));
+            }
+            out[n] = (result & low_mask);
+        }
+    }
+
+    static void shift_left(digit_t * val, std::size_t size, std::size_t shift)
+    {
+        const std::size_t bits = std::numeric_limits<digit_t>::digits;
+        BOOST_ASSERT(shift > 0);
+        BOOST_ASSERT(shift < bits);
+        digit_t prev = 0;
+        for(std::size_t i = 0; i < size; ++i) {
+            digit_t tmp = val[i];
+            val[i] = (prev >> (bits - shift)) | (val[i] << shift);
+            prev = tmp;
+        }
+    }
+
+    static digit_t sqr(digit_t val) {
+        const std::size_t bits = std::numeric_limits<digit_t>::digits;
+        digit_t mask = (digit_t(1) << bits/2) - 1;
+        for(std::size_t i = bits; i > 1; i /= 2) {
+            val = ((val & ~mask) << i/2) | (val & mask);
+            mask = mask & (mask >> i/4);
+            mask = mask | (mask << i/2);
+        }
+        return val;
+    }
+
+    static void sqr(digit_t * val, std::size_t size)
+    {
+        const std::size_t bits = std::numeric_limits<digit_t>::digits;
+        digit_t mask = (digit_t(1) << bits/2) - 1;
+        for(std::size_t i = 0; i < size; ++i) {
+            digit_t x = val[size - i - 1];
+            val[(size - i - 1) * 2] = sqr(x & mask);
+            val[(size - i - 1) * 2 + 1] = sqr(x >> bits/2);
+        }
+    }
+
+    // optimized for the case when the modulus has few bits set.
+    struct sparse_mod {
+        sparse_mod(const digit_t * divisor, std::size_t divisor_bits)
+        {
+            const std::size_t bits = std::numeric_limits<digit_t>::digits;
+            _remainder_bits = divisor_bits - 1;
+            for(std::size_t i = 0; i < divisor_bits; ++i) {
+                if(divisor[i/bits] & (digit_t(1) << i%bits)) {
+                    _bit_indices.push_back(i);
+                }
+            }
+            BOOST_ASSERT(_bit_indices.back() == divisor_bits - 1);
+            _bit_indices.pop_back();
+            if(_bit_indices.empty()) {
+                _block_bits = divisor_bits;
+                _lower_bits = 0;
+            } else {
+                _block_bits = divisor_bits - _bit_indices.back() - 1;
+                _lower_bits = _bit_indices.back() + 1;
+            }
+            
+            _partial_quotient.resize((_block_bits + bits - 1)/bits);
+        }
+        void operator()(digit_t * dividend, std::size_t dividend_bits)
+        {
+            const std::size_t bits = std::numeric_limits<digit_t>::digits;
+            while(dividend_bits > _remainder_bits) {
+                std::size_t block_start = (std::max)(dividend_bits - _block_bits, _remainder_bits);
+                std::size_t block_size = (dividend_bits - block_start + bits - 1) / bits;
+                copy_bits(dividend, block_start, dividend_bits, &_partial_quotient[0]);
+                for(std::size_t i = 0; i < _bit_indices.size(); ++i) {
+                    std::size_t pos = _bit_indices[i] + block_start - _remainder_bits;
+                    add_shifted_inplace(block_size, &_partial_quotient[0], dividend + pos/bits, pos%bits);
+                }
+                add_shifted_inplace(block_size, &_partial_quotient[0], dividend + block_start/bits, block_start%bits);
+                dividend_bits = block_start;
+            }
+        }
+        std::vector<digit_t> _partial_quotient;
+        std::size_t _remainder_bits;
+        std::size_t _block_bits;
+        std::size_t _lower_bits;
+        std::vector<std::size_t> _bit_indices;
+    };
+
+    // base should have the same number of bits as mod
+    // base, and mod should both be able to hold a power
+    // of 2 >= mod_bits.  out needs to be twice as large.
+    static void mod_pow_x(boost::uintmax_t exponent, const digit_t * mod, std::size_t mod_bits, digit_t * out)
+    {
+        const std::size_t bits = std::numeric_limits<digit_t>::digits;
+        const std::size_t n = (mod_bits + bits - 1) / bits;
+        const std::size_t highbit = mod_bits - 1;
+        if(exponent == 0) {
+            out[0] = 1;
+            std::fill_n(out + 1, n - 1, digit_t(0));
+            return;
+        }
+        boost::uintmax_t i = std::numeric_limits<boost::uintmax_t>::digits - 1;
+        while(((boost::uintmax_t(1) << i) & exponent) == 0) {
+            --i;
+        }
+        out[0] = 2;
+        std::fill_n(out + 1, n - 1, digit_t(0));
+        sparse_mod m(mod, mod_bits);
+        while(i--) {
+            sqr(out, n);
+            m(out, 2 * mod_bits - 1);
+            if((boost::uintmax_t(1) << i) & exponent) {
+                shift_left(out, n, 1);
+                if(out[highbit / bits] & (digit_t(1) << highbit%bits))
+                    add(n, out, mod, out);
+            }
+        }
+    }
+};
+
+class polynomial
+{
+    typedef polynomial_ops::digit_t digit_t;
+public:
+    polynomial() : _size(0) {}
+    class reference {
+    public:
+        reference(digit_t &value, int idx)
+            : _value(value), _idx(idx) {}
+        operator bool() const { return (_value & (digit_t(1) << _idx)) != 0; }
+        reference& operator=(bool b)
+        {
+            if(b) {
+                _value |= (digit_t(1) << _idx);
+            } else {
+                _value &= ~(digit_t(1) << _idx);
+            }
+            return *this;
+        }
+        reference &operator^=(bool b)
+        {
+            _value ^= (digit_t(b) << _idx);
+            return *this;
+        }
+
+        reference &operator=(const reference &other)
+        {
+            return *this = static_cast<bool>(other);
+        }
+    private:
+        digit_t &_value;
+        int _idx;
+    };
+    reference operator[](std::size_t i)
+    {
+        static const std::size_t bits = std::numeric_limits<digit_t>::digits;
+        ensure_bit(i);
+        return reference(_storage[i/bits], i%bits);
+    }
+    bool operator[](std::size_t i) const
+    {
+        static const std::size_t bits = std::numeric_limits<digit_t>::digits;
+        if(i < size())
+            return (_storage[i/bits] & (digit_t(1) << (i%bits))) != 0;
+        else
+            return false;
+    }
+    std::size_t size() const
+    {
+        return _size;
+    }
+    void resize(std::size_t n)
+    {
+        static const std::size_t bits = std::numeric_limits<digit_t>::digits;
+        _storage.resize((n + bits - 1)/bits);
+        // clear the high order bits in case we're shrinking.
+        if(n%bits) {
+            _storage.back() &= ((digit_t(1) << (n%bits)) - 1);
+        }
+        _size = n;
+    }
+    friend polynomial operator*(const polynomial &lhs, const polynomial &rhs);
+    friend polynomial mod_pow_x(boost::uintmax_t exponent, polynomial mod);
+private:
+    std::vector<polynomial_ops::digit_t> _storage;
+    std::size_t _size;
+    void ensure_bit(std::size_t i)
+    {
+        if(i >= size()) {
+            resize(i + 1);
+        }
+    }
+    void normalize()
+    {
+        while(size() && (*this)[size() - 1] == 0)
+            resize(size() - 1);
+    }
+};
+
+inline polynomial operator*(const polynomial &lhs, const polynomial &rhs)
+{
+    polynomial result;
+    result._storage.resize(lhs._storage.size() + rhs._storage.size());
+    polynomial_ops::multiply(&lhs._storage[0], lhs._storage.size(),
+                             &rhs._storage[0], rhs._storage.size(),
+                             &result._storage[0]);
+    result._size = lhs._size + rhs._size;
+    return result;
+}
+
+inline polynomial mod_pow_x(boost::uintmax_t exponent, polynomial mod)
+{
+    polynomial result;
+    mod.normalize();
+    std::size_t mod_size = mod.size();
+    result._storage.resize(mod._storage.size() * 2);
+    result._size = mod.size() * 2;
+    polynomial_ops::mod_pow_x(exponent, &mod._storage[0], mod_size, &result._storage[0]);
+    result.resize(mod.size() - 1);
+    return result;
+}
+
+}
+}
+}
+
+#endif // BOOST_RANDOM_DETAIL_POLYNOMIAL_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/detail/ptr_helper.hpp

@@ -0,0 +1,67 @@
+/* boost random/detail/ptr_helper.hpp header file
+ *
+ * Copyright Jens Maurer 2002
+ * 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.
+ *
+ * $Id$
+ *
+ */
+
+#ifndef BOOST_RANDOM_DETAIL_PTR_HELPER_HPP
+#define BOOST_RANDOM_DETAIL_PTR_HELPER_HPP
+
+#include <boost/config.hpp>
+
+
+namespace boost {
+namespace random {
+namespace detail {
+
+// type_traits could help here, but I don't want to depend on type_traits.
+template<class T>
+struct ptr_helper
+{
+  typedef T value_type;
+  typedef T& reference_type;
+  typedef const T& rvalue_type;
+  static reference_type ref(T& r) { return r; }
+  static const T& ref(const T& r) { return r; }
+};
+
+template<class T>
+struct ptr_helper<T&>
+{
+  typedef T value_type;
+  typedef T& reference_type;
+  typedef T& rvalue_type;
+  static reference_type ref(T& r) { return r; }
+  static const T& ref(const T& r) { return r; }
+};
+
+template<class T>
+struct ptr_helper<T*>
+{
+  typedef T value_type;
+  typedef T& reference_type;
+  typedef T* rvalue_type;
+  static reference_type ref(T * p) { return *p; }
+  static const T& ref(const T * p) { return *p; }
+};
+
+} // namespace detail
+} // namespace random
+} // namespace boost
+
+//
+// BOOST_RANDOM_PTR_HELPER_SPEC --
+//
+//  Helper macro for broken compilers defines specializations of
+//  ptr_helper.
+//
+# define BOOST_RANDOM_PTR_HELPER_SPEC(T)
+
+#endif // BOOST_RANDOM_DETAIL_PTR_HELPER_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/detail/seed.hpp

@@ -0,0 +1,115 @@
+/* boost random/detail/seed.hpp header file
+ *
+ * Copyright Steven Watanabe 2009
+ * 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.
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_DETAIL_SEED_HPP
+#define BOOST_RANDOM_DETAIL_SEED_HPP
+
+#include <boost/config.hpp>
+
+// Sun seems to have trouble with the use of SFINAE for the
+// templated constructor.  So does Borland.
+#if !defined(BOOST_NO_SFINAE) && !defined(__SUNPRO_CC) && !defined(__BORLANDC__)
+
+#include <boost/utility/enable_if.hpp>
+#include <boost/type_traits/is_arithmetic.hpp>
+#include <boost/mpl/bool.hpp>
+
+namespace boost {
+namespace random {
+namespace detail {
+
+template<class T>
+struct disable_seed : boost::disable_if<boost::is_arithmetic<T> > {};
+
+template<class Engine, class T>
+struct disable_constructor : disable_seed<T> {};
+
+template<class Engine>
+struct disable_constructor<Engine, Engine> {};
+
+#define BOOST_RANDOM_DETAIL_GENERATOR_CONSTRUCTOR(Self, Generator, gen) \
+    template<class Generator>                                           \
+    explicit Self(Generator& gen, typename ::boost::random::detail::disable_constructor<Self, Generator>::type* = 0)
+
+#define BOOST_RANDOM_DETAIL_GENERATOR_SEED(Self, Generator, gen)    \
+    template<class Generator>                                       \
+    void seed(Generator& gen, typename ::boost::random::detail::disable_seed<Generator>::type* = 0)
+
+#define BOOST_RANDOM_DETAIL_SEED_SEQ_CONSTRUCTOR(Self, SeedSeq, seq)    \
+    template<class SeedSeq>                                             \
+    explicit Self(SeedSeq& seq, typename ::boost::random::detail::disable_constructor<Self, SeedSeq>::type* = 0)
+
+#define BOOST_RANDOM_DETAIL_SEED_SEQ_SEED(Self, SeedSeq, seq)   \
+    template<class SeedSeq>                                     \
+    void seed(SeedSeq& seq, typename ::boost::random::detail::disable_seed<SeedSeq>::type* = 0)
+
+#define BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(Self, T, x)  \
+    explicit Self(const T& x)
+
+#define BOOST_RANDOM_DETAIL_ARITHMETIC_SEED(Self, T, x) \
+    void seed(const T& x)
+}
+}
+}
+
+#else
+
+#include <boost/type_traits/is_arithmetic.hpp>
+#include <boost/mpl/bool.hpp>
+
+#define BOOST_RANDOM_DETAIL_GENERATOR_CONSTRUCTOR(Self, Generator, gen) \
+    Self(Self& other) { *this = other; }                                \
+    Self(const Self& other) { *this = other; }                          \
+    template<class Generator>                                           \
+    explicit Self(Generator& gen) {                                     \
+        boost_random_constructor_impl(gen, ::boost::is_arithmetic<Generator>());\
+    }                                                                   \
+    template<class Generator>                                           \
+    void boost_random_constructor_impl(Generator& gen, ::boost::mpl::false_)
+
+#define BOOST_RANDOM_DETAIL_GENERATOR_SEED(Self, Generator, gen)    \
+    template<class Generator>                                       \
+    void seed(Generator& gen) {                                     \
+        boost_random_seed_impl(gen, ::boost::is_arithmetic<Generator>());\
+    }\
+    template<class Generator>\
+    void boost_random_seed_impl(Generator& gen, ::boost::mpl::false_)
+
+#define BOOST_RANDOM_DETAIL_SEED_SEQ_CONSTRUCTOR(Self, SeedSeq, seq)    \
+    Self(Self& other) { *this = other; }                                \
+    Self(const Self& other) { *this = other; }                          \
+    template<class SeedSeq>                                             \
+    explicit Self(SeedSeq& seq) {                                       \
+        boost_random_constructor_impl(seq, ::boost::is_arithmetic<SeedSeq>());\
+    }                                                                   \
+    template<class SeedSeq>                                             \
+    void boost_random_constructor_impl(SeedSeq& seq, ::boost::mpl::false_)
+
+#define BOOST_RANDOM_DETAIL_SEED_SEQ_SEED(Self, SeedSeq, seq)           \
+    template<class SeedSeq>                                             \
+    void seed(SeedSeq& seq) {                                           \
+        boost_random_seed_impl(seq, ::boost::is_arithmetic<SeedSeq>()); \
+    }                                                                   \
+    template<class SeedSeq>                                             \
+    void boost_random_seed_impl(SeedSeq& seq, ::boost::mpl::false_)
+
+#define BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(Self, T, x)  \
+    explicit Self(const T& x) { boost_random_constructor_impl(x, ::boost::mpl::true_()); }\
+    void boost_random_constructor_impl(const T& x, ::boost::mpl::true_)
+
+#define BOOST_RANDOM_DETAIL_ARITHMETIC_SEED(Self, T, x) \
+    void seed(const T& x) { boost_random_seed_impl(x, ::boost::mpl::true_()); }\
+    void boost_random_seed_impl(const T& x, ::boost::mpl::true_)
+
+#endif
+
+#endif

depends/x86_64-pc-linux-gnu/include/boost/random/detail/seed_impl.hpp

@@ -0,0 +1,398 @@
+/* boost random/detail/seed.hpp header file
+ *
+ * Copyright Steven Watanabe 2009
+ * 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.
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_DETAIL_SEED_IMPL_HPP
+#define BOOST_RANDOM_DETAIL_SEED_IMPL_HPP
+
+#include <stdexcept>
+#include <boost/cstdint.hpp>
+#include <boost/throw_exception.hpp>
+#include <boost/config/no_tr1/cmath.hpp>
+#include <boost/integer/integer_mask.hpp>
+#include <boost/integer/static_log2.hpp>
+#include <boost/random/traits.hpp>
+#include <boost/mpl/bool.hpp>
+#include <boost/mpl/if.hpp>
+#include <boost/mpl/int.hpp>
+#include <boost/random/detail/const_mod.hpp>
+#include <boost/random/detail/integer_log2.hpp>
+#include <boost/random/detail/signed_unsigned_tools.hpp>
+#include <boost/random/detail/generator_bits.hpp>
+
+#include <boost/random/detail/disable_warnings.hpp>
+
+namespace boost {
+namespace random {
+namespace detail {
+
+// finds the seed type of an engine, given its
+// result_type.  If the result_type is integral
+// the seed type is the same.  If the result_type
+// is floating point, the seed type is uint32_t
+template<class T>
+struct seed_type
+{
+    typedef typename boost::mpl::if_<boost::is_integral<T>,
+        T,
+        boost::uint32_t
+    >::type type;
+};
+
+template<int N>
+struct const_pow_impl
+{
+    template<class T>
+    static T call(T arg, int n, T result)
+    {
+        return const_pow_impl<N / 2>::call(T(arg * arg), n / 2,
+            n%2 == 0? result : T(result * arg));
+    }
+};
+
+template<>
+struct const_pow_impl<0>
+{
+    template<class T>
+    static T call(T, int, T result)
+    {
+        return result;
+    }
+};
+
+// requires N is an upper bound on n
+template<int N, class T>
+inline T const_pow(T arg, int n) { return const_pow_impl<N>::call(arg, n, T(1)); }
+
+template<class T>
+inline T pow2(int n)
+{
+    typedef unsigned int_type;
+    const int max_bits = std::numeric_limits<int_type>::digits;
+    T multiplier = T(int_type(1) << (max_bits - 1)) * 2;
+    return (int_type(1) << (n % max_bits)) *
+        const_pow<std::numeric_limits<T>::digits / max_bits>(multiplier, n / max_bits);
+}
+
+template<class Engine, class Iter>
+void generate_from_real(Engine& eng, Iter begin, Iter end)
+{
+    using std::fmod;
+    typedef typename Engine::result_type RealType;
+    const int Bits = detail::generator_bits<Engine>::value();
+    int remaining_bits = 0;
+    boost::uint_least32_t saved_bits = 0;
+    RealType multiplier = pow2<RealType>( Bits);
+    RealType mult32 = RealType(4294967296.0); // 2^32
+    while(true) {
+        RealType val = eng() * multiplier;
+        int available_bits = Bits;
+        // Make sure the compiler can optimize this out
+        // if it isn't possible.
+        if(Bits < 32 && available_bits < 32 - remaining_bits) {
+            saved_bits |= boost::uint_least32_t(val) << remaining_bits;
+            remaining_bits += Bits;
+        } else {
+            // If Bits < 32, then remaining_bits != 0, since
+            // if remaining_bits == 0, available_bits < 32 - 0,
+            // and we won't get here to begin with.
+            if(Bits < 32 || remaining_bits != 0) {
+                boost::uint_least32_t divisor =
+                    (boost::uint_least32_t(1) << (32 - remaining_bits));
+                boost::uint_least32_t extra_bits = boost::uint_least32_t(fmod(val, mult32)) & (divisor - 1);
+                val = val / divisor;
+                *begin++ = saved_bits | (extra_bits << remaining_bits);
+                if(begin == end) return;
+                available_bits -= 32 - remaining_bits;
+                remaining_bits = 0;
+            }
+            // If Bits < 32 we should never enter this loop
+            if(Bits >= 32) {
+                for(; available_bits >= 32; available_bits -= 32) {
+                    boost::uint_least32_t word = boost::uint_least32_t(fmod(val, mult32));
+                    val /= mult32;
+                    *begin++ = word;
+                    if(begin == end) return;
+                }
+            }
+            remaining_bits = available_bits;
+            saved_bits = static_cast<boost::uint_least32_t>(val);
+        }
+    }
+}
+
+template<class Engine, class Iter>
+void generate_from_int(Engine& eng, Iter begin, Iter end)
+{
+    typedef typename Engine::result_type IntType;
+    typedef typename boost::random::traits::make_unsigned<IntType>::type unsigned_type;
+    int remaining_bits = 0;
+    boost::uint_least32_t saved_bits = 0;
+    unsigned_type range = boost::random::detail::subtract<IntType>()((eng.max)(), (eng.min)());
+
+    int bits =
+        (range == (std::numeric_limits<unsigned_type>::max)()) ?
+            std::numeric_limits<unsigned_type>::digits :
+            detail::integer_log2(range + 1);
+
+    {
+        int discarded_bits = detail::integer_log2(bits);
+        unsigned_type excess = (range + 1) >> (bits - discarded_bits);
+        if(excess != 0) {
+            int extra_bits = detail::integer_log2((excess - 1) ^ excess);
+            bits = bits - discarded_bits + extra_bits;
+        }
+    }
+
+    unsigned_type mask = (static_cast<unsigned_type>(2) << (bits - 1)) - 1;
+    unsigned_type limit = ((range + 1) & ~mask) - 1;
+
+    while(true) {
+        unsigned_type val;
+        do {
+            val = boost::random::detail::subtract<IntType>()(eng(), (eng.min)());
+        } while(limit != range && val > limit);
+        val &= mask;
+        int available_bits = bits;
+        if(available_bits == 32) {
+            *begin++ = static_cast<boost::uint_least32_t>(val) & 0xFFFFFFFFu;
+            if(begin == end) return;
+        } else if(available_bits % 32 == 0) {
+            for(int i = 0; i < available_bits / 32; ++i) {
+                boost::uint_least32_t word = boost::uint_least32_t(val) & 0xFFFFFFFFu;
+                int suppress_warning = (bits >= 32);
+                BOOST_ASSERT(suppress_warning == 1);
+                val >>= (32 * suppress_warning);
+                *begin++ = word;
+                if(begin == end) return;
+            }
+        } else if(bits < 32 && available_bits < 32 - remaining_bits) {
+            saved_bits |= boost::uint_least32_t(val) << remaining_bits;
+            remaining_bits += bits;
+        } else {
+            if(bits < 32 || remaining_bits != 0) {
+                boost::uint_least32_t extra_bits = boost::uint_least32_t(val) & ((boost::uint_least32_t(1) << (32 - remaining_bits)) - 1);
+                val >>= 32 - remaining_bits;
+                *begin++ = saved_bits | (extra_bits << remaining_bits);
+                if(begin == end) return;
+                available_bits -= 32 - remaining_bits;
+                remaining_bits = 0;
+            }
+            if(bits >= 32) {
+                for(; available_bits >= 32; available_bits -= 32) {
+                    boost::uint_least32_t word = boost::uint_least32_t(val) & 0xFFFFFFFFu;
+                    int suppress_warning = (bits >= 32);
+                    BOOST_ASSERT(suppress_warning == 1);
+                    val >>= (32 * suppress_warning);
+                    *begin++ = word;
+                    if(begin == end) return;
+                }
+            }
+            remaining_bits = available_bits;
+            saved_bits = static_cast<boost::uint_least32_t>(val);
+        }
+    }
+}
+
+template<class Engine, class Iter>
+void generate_impl(Engine& eng, Iter first, Iter last, boost::mpl::true_)
+{
+    return detail::generate_from_int(eng, first, last);
+}
+
+template<class Engine, class Iter>
+void generate_impl(Engine& eng, Iter first, Iter last, boost::mpl::false_)
+{
+    return detail::generate_from_real(eng, first, last);
+}
+
+template<class Engine, class Iter>
+void generate(Engine& eng, Iter first, Iter last)
+{
+    return detail::generate_impl(eng, first, last, boost::random::traits::is_integral<typename Engine::result_type>());
+}
+
+
+
+template<class IntType, IntType m, class SeedSeq>
+IntType seed_one_int(SeedSeq& seq)
+{
+    static const int log = ::boost::mpl::if_c<(m == 0),
+        ::boost::mpl::int_<(::std::numeric_limits<IntType>::digits)>,
+        ::boost::static_log2<m> >::type::value;
+    static const int k =
+        (log + ((~(static_cast<IntType>(2) << (log - 1)) & m)? 32 : 31)) / 32;
+    ::boost::uint_least32_t array[log / 32 + 4];
+    seq.generate(&array[0], &array[0] + k + 3);
+    IntType s = 0;
+    for(int j = 0; j < k; ++j) {
+        IntType digit = const_mod<IntType, m>::apply(IntType(array[j+3]));
+        IntType mult = IntType(1) << 32*j;
+        s = const_mod<IntType, m>::mult_add(mult, digit, s);
+    }
+    return s;
+}
+
+template<class IntType, IntType m, class Iter>
+IntType get_one_int(Iter& first, Iter last)
+{
+    static const int log = ::boost::mpl::if_c<(m == 0),
+        ::boost::mpl::int_<(::std::numeric_limits<IntType>::digits)>,
+        ::boost::static_log2<m> >::type::value;
+    static const int k =
+        (log + ((~(static_cast<IntType>(2) << (log - 1)) & m)? 32 : 31)) / 32;
+    IntType s = 0;
+    for(int j = 0; j < k; ++j) {
+        if(first == last) {
+            boost::throw_exception(::std::invalid_argument("Not enough elements in call to seed."));
+        }
+        IntType digit = const_mod<IntType, m>::apply(IntType(*first++));
+        IntType mult = IntType(1) << 32*j;
+        s = const_mod<IntType, m>::mult_add(mult, digit, s);
+    }
+    return s;
+}
+
+// TODO: work in-place whenever possible
+template<int w, std::size_t n, class SeedSeq, class UIntType>
+void seed_array_int_impl(SeedSeq& seq, UIntType (&x)[n])
+{
+    boost::uint_least32_t storage[((w+31)/32) * n];
+    seq.generate(&storage[0], &storage[0] + ((w+31)/32) * n);
+    for(std::size_t j = 0; j < n; j++) {
+        UIntType val = 0;
+        for(std::size_t k = 0; k < (w+31)/32; ++k) {
+            val += static_cast<UIntType>(storage[(w+31)/32*j + k]) << 32*k;
+        }
+        x[j] = val & ::boost::low_bits_mask_t<w>::sig_bits;
+    }
+}
+
+template<int w, std::size_t n, class SeedSeq, class IntType>
+inline void seed_array_int_impl(SeedSeq& seq, IntType (&x)[n], boost::mpl::true_)
+{
+    BOOST_STATIC_ASSERT_MSG(boost::is_integral<IntType>::value, "Sorry but this routine has not been ported to non built-in integers as it relies on a reinterpret_cast.");
+    typedef typename boost::make_unsigned<IntType>::type unsigned_array[n];
+    seed_array_int_impl<w>(seq, reinterpret_cast<unsigned_array&>(x));
+}
+
+template<int w, std::size_t n, class SeedSeq, class IntType>
+inline void seed_array_int_impl(SeedSeq& seq, IntType (&x)[n], boost::mpl::false_)
+{
+    seed_array_int_impl<w>(seq, x);
+}
+
+template<int w, std::size_t n, class SeedSeq, class IntType>
+inline void seed_array_int(SeedSeq& seq, IntType (&x)[n])
+{
+    seed_array_int_impl<w>(seq, x, boost::random::traits::is_signed<IntType>());
+}
+
+template<int w, std::size_t n, class Iter, class UIntType>
+void fill_array_int_impl(Iter& first, Iter last, UIntType (&x)[n])
+{
+    for(std::size_t j = 0; j < n; j++) {
+        UIntType val = 0;
+        for(std::size_t k = 0; k < (w+31)/32; ++k) {
+            if(first == last) {
+                boost::throw_exception(std::invalid_argument("Not enough elements in call to seed."));
+            }
+            val += static_cast<UIntType>(*first++) << 32*k;
+        }
+        x[j] = val & ::boost::low_bits_mask_t<w>::sig_bits;
+    }
+}
+
+template<int w, std::size_t n, class Iter, class IntType>
+inline void fill_array_int_impl(Iter& first, Iter last, IntType (&x)[n], boost::mpl::true_)
+{
+    BOOST_STATIC_ASSERT_MSG(boost::is_integral<IntType>::value, "Sorry but this routine has not been ported to non built-in integers as it relies on a reinterpret_cast.");
+    typedef typename boost::make_unsigned<IntType>::type unsigned_array[n];
+    fill_array_int_impl<w>(first, last, reinterpret_cast<unsigned_array&>(x));
+}
+
+template<int w, std::size_t n, class Iter, class IntType>
+inline void fill_array_int_impl(Iter& first, Iter last, IntType (&x)[n], boost::mpl::false_)
+{
+    fill_array_int_impl<w>(first, last, x);
+}
+
+template<int w, std::size_t n, class Iter, class IntType>
+inline void fill_array_int(Iter& first, Iter last, IntType (&x)[n])
+{
+    fill_array_int_impl<w>(first, last, x, boost::random::traits::is_signed<IntType>());
+}
+
+template<int w, std::size_t n, class RealType>
+void seed_array_real_impl(const boost::uint_least32_t* storage, RealType (&x)[n])
+{
+    boost::uint_least32_t mask = ~((~boost::uint_least32_t(0)) << (w%32));
+    RealType two32 = 4294967296.0;
+    const RealType divisor = RealType(1)/detail::pow2<RealType>(w);
+    unsigned int j;
+    for(j = 0; j < n; ++j) {
+        RealType val = RealType(0);
+        RealType mult = divisor;
+        for(int k = 0; k < w/32; ++k) {
+            val += *storage++ * mult;
+            mult *= two32;
+        }
+        if(mask != 0) {
+            val += (*storage++ & mask) * mult;
+        }
+        BOOST_ASSERT(val >= 0);
+        BOOST_ASSERT(val < 1);
+        x[j] = val;
+    }
+}
+
+template<int w, std::size_t n, class SeedSeq, class RealType>
+void seed_array_real(SeedSeq& seq, RealType (&x)[n])
+{
+    using std::pow;
+    boost::uint_least32_t storage[((w+31)/32) * n];
+    seq.generate(&storage[0], &storage[0] + ((w+31)/32) * n);
+    seed_array_real_impl<w>(storage, x);
+}
+
+template<int w, std::size_t n, class Iter, class RealType>
+void fill_array_real(Iter& first, Iter last, RealType (&x)[n])
+{
+    boost::uint_least32_t mask = ~((~boost::uint_least32_t(0)) << (w%32));
+    RealType two32 = 4294967296.0;
+    const RealType divisor = RealType(1)/detail::pow2<RealType>(w);
+    unsigned int j;
+    for(j = 0; j < n; ++j) {
+        RealType val = RealType(0);
+        RealType mult = divisor;
+        for(int k = 0; k < w/32; ++k, ++first) {
+            if(first == last) boost::throw_exception(std::invalid_argument("Not enough elements in call to seed."));
+            val += *first * mult;
+            mult *= two32;
+        }
+        if(mask != 0) {
+            if(first == last) boost::throw_exception(std::invalid_argument("Not enough elements in call to seed."));
+            val += (*first & mask) * mult;
+            ++first;
+        }
+        BOOST_ASSERT(val >= 0);
+        BOOST_ASSERT(val < 1);
+        x[j] = val;
+    }
+}
+
+}
+}
+}
+
+#include <boost/random/detail/enable_warnings.hpp>
+
+#endif

depends/x86_64-pc-linux-gnu/include/boost/random/detail/signed_unsigned_tools.hpp

@@ -0,0 +1,89 @@
+/* boost random/detail/signed_unsigned_tools.hpp header file
+ *
+ * Copyright Jens Maurer 2006
+ * 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.
+ */
+
+#ifndef BOOST_RANDOM_DETAIL_SIGNED_UNSIGNED_TOOLS
+#define BOOST_RANDOM_DETAIL_SIGNED_UNSIGNED_TOOLS
+
+#include <boost/limits.hpp>
+#include <boost/config.hpp>
+#include <boost/random/traits.hpp>
+
+namespace boost {
+namespace random {
+namespace detail {
+
+
+/*
+ * Compute x - y, we know that x >= y, return an unsigned value.
+ */
+
+template<class T, bool sgn = std::numeric_limits<T>::is_signed && std::numeric_limits<T>::is_bounded>
+struct subtract { };
+
+template<class T>
+struct subtract<T, /* signed */ false>
+{
+  typedef T result_type;
+  result_type operator()(T x, T y) { return x - y; }
+};
+
+template<class T>
+struct subtract<T, /* signed */ true>
+{
+  typedef typename boost::random::traits::make_unsigned_or_unbounded<T>::type result_type;
+  result_type operator()(T x, T y)
+  {
+    if (y >= 0)   // because x >= y, it follows that x >= 0, too
+      return result_type(x) - result_type(y);
+    if (x >= 0)   // y < 0
+      // avoid the nasty two's complement case for y == min()
+      return result_type(x) + result_type(-(y+1)) + 1;
+    // both x and y are negative: no signed overflow
+    return result_type(x - y);
+  }
+};
+
+/*
+ * Compute x + y, x is unsigned, result fits in type of "y".
+ */
+
+template<class T1, class T2, bool sgn = (std::numeric_limits<T2>::is_signed && (std::numeric_limits<T1>::digits >= std::numeric_limits<T2>::digits))>
+struct add { };
+
+template<class T1, class T2>
+struct add<T1, T2, /* signed or else T2 has more digits than T1 so the cast always works - needed when T2 is a multiprecision type and T1 is a native integer */ false>
+{
+  typedef T2 result_type;
+  result_type operator()(T1 x, T2 y) { return T2(x) + y; }
+};
+
+template<class T1, class T2>
+struct add<T1, T2, /* signed */ true>
+{
+  typedef T2 result_type;
+  result_type operator()(T1 x, T2 y)
+  {
+    if (y >= 0)
+      return T2(x) + y;
+    // y < 0
+    if (x > T1(-(y+1)))  // result >= 0 after subtraction
+      // avoid the nasty two's complement edge case for y == min()
+      return T2(x - T1(-(y+1)) - 1);
+    // abs(x) < abs(y), thus T2 able to represent x
+    return T2(x) + y;
+  }
+};
+
+} // namespace detail
+} // namespace random
+} // namespace boost
+
+#endif // BOOST_RANDOM_DETAIL_SIGNED_UNSIGNED_TOOLS
+

depends/x86_64-pc-linux-gnu/include/boost/random/detail/uniform_int_float.hpp

@@ -0,0 +1,76 @@
+/* boost random/detail/uniform_int_float.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ *
+ */
+
+#ifndef BOOST_RANDOM_DETAIL_UNIFORM_INT_FLOAT_HPP
+#define BOOST_RANDOM_DETAIL_UNIFORM_INT_FLOAT_HPP
+
+#include <boost/limits.hpp>
+#include <boost/config.hpp>
+#include <boost/integer.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/generator_bits.hpp>
+
+#include <boost/random/detail/disable_warnings.hpp>
+
+namespace boost {
+namespace random {
+namespace detail {
+
+template<class URNG>
+class uniform_int_float
+{
+public:
+    typedef URNG base_type;
+    typedef typename base_type::result_type base_result;
+
+    typedef typename boost::uint_t<
+        (std::numeric_limits<boost::uintmax_t>::digits <
+            std::numeric_limits<base_result>::digits)?
+        std::numeric_limits<boost::uintmax_t>::digits :
+        std::numeric_limits<base_result>::digits
+    >::fast result_type;
+
+    uniform_int_float(base_type& rng)
+      : _rng(rng) {}
+
+    static result_type min BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return 0; }
+    static result_type max BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    {
+        std::size_t digits = std::numeric_limits<result_type>::digits;
+        if(detail::generator_bits<URNG>::value() < digits) {
+            digits = detail::generator_bits<URNG>::value();
+        }
+        return (result_type(2) << (digits - 1)) - 1;
+    }
+    base_type& base() { return _rng; }
+    const base_type& base() const { return _rng; }
+
+    result_type operator()()
+    {
+        base_result range = static_cast<base_result>((max)())+1;
+        return static_cast<result_type>(_rng() * range);
+    }
+
+private:
+    base_type& _rng;
+};
+
+} // namespace detail
+} // namespace random
+} // namespace boost
+
+#include <boost/random/detail/enable_warnings.hpp>
+
+#endif // BOOST_RANDOM_DETAIL_UNIFORM_INT_FLOAT_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/detail/vector_io.hpp

@@ -0,0 +1,75 @@
+/* boost random/vector_io.hpp header file
+ *
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_DETAIL_VECTOR_IO_HPP
+#define BOOST_RANDOM_DETAIL_VECTOR_IO_HPP
+
+#include <vector>
+#include <iosfwd>
+#include <istream>
+
+namespace boost {
+namespace random {
+namespace detail {
+
+template<class CharT, class Traits, class T>
+void print_vector(std::basic_ostream<CharT, Traits>& os,
+                  const std::vector<T>& vec)
+{
+    typename std::vector<T>::const_iterator
+        iter = vec.begin(),
+        end =  vec.end();
+    os << os.widen('[');
+    if(iter != end) {
+        os << *iter;
+        ++iter;
+        for(; iter != end; ++iter)
+        {
+            os << os.widen(' ') << *iter;
+        }
+    }
+    os << os.widen(']');
+}
+
+template<class CharT, class Traits, class T>
+void read_vector(std::basic_istream<CharT, Traits>& is, std::vector<T>& vec)
+{
+    CharT ch;
+    if(!(is >> ch)) {
+        return;
+    }
+    if(ch != is.widen('[')) {
+        is.putback(ch);
+        is.setstate(std::ios_base::failbit);
+        return;
+    }
+    T val;
+    while(is >> std::ws >> val) {
+        vec.push_back(val);
+    }
+    if(is.fail()) {
+        is.clear();
+        if(!(is >> ch)) {
+            return;
+        }
+        if(ch != is.widen(']')) {
+            is.putback(ch);
+            is.setstate(std::ios_base::failbit);
+        }
+    }
+}
+
+}
+}
+}
+
+#endif // BOOST_RANDOM_DETAIL_VECTOR_IO_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/discard_block.hpp

@@ -0,0 +1,241 @@
+/* boost random/discard_block.hpp header file
+ *
+ * Copyright Jens Maurer 2002
+ * Copyright Steven Watanabe 2010
+ * 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2001-03-02  created
+ */
+
+#ifndef BOOST_RANDOM_DISCARD_BLOCK_HPP
+#define BOOST_RANDOM_DISCARD_BLOCK_HPP
+
+#include <iostream>
+#include <boost/config.hpp>
+#include <boost/cstdint.hpp>
+#include <boost/limits.hpp>
+#include <boost/static_assert.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/seed.hpp>
+#include <boost/random/detail/seed_impl.hpp>
+
+
+namespace boost {
+namespace random {
+
+/**
+ * The class template \discard_block_engine is a model of
+ * \pseudo_random_number_generator.  It modifies
+ * another generator by discarding parts of its output.
+ * Out of every block of @c p results, the first @c r
+ * will be returned and the rest discarded.
+ *
+ * Requires: 0 < p <= r
+ */
+template<class UniformRandomNumberGenerator, std::size_t p, std::size_t r>
+class discard_block_engine
+{
+    typedef typename detail::seed_type<
+        typename UniformRandomNumberGenerator::result_type>::type seed_type;
+public:
+    typedef UniformRandomNumberGenerator base_type;
+    typedef typename base_type::result_type result_type;
+
+    BOOST_STATIC_CONSTANT(std::size_t, block_size = p);
+    BOOST_STATIC_CONSTANT(std::size_t, used_block = r);
+
+    BOOST_STATIC_CONSTANT(bool, has_fixed_range = false);
+    BOOST_STATIC_CONSTANT(std::size_t, total_block = p);
+    BOOST_STATIC_CONSTANT(std::size_t, returned_block = r);
+
+    BOOST_STATIC_ASSERT(total_block >= returned_block);
+
+    /** Uses the default seed for the base generator. */
+    discard_block_engine() : _rng(), _n(0) { }
+    /** Constructs a new \discard_block_engine with a copy of rng. */
+    explicit discard_block_engine(const base_type & rng) : _rng(rng), _n(0) { }
+
+#ifndef BOOST_NO_CXX11_RVALUE_REFERENCES
+    /** Constructs a new \discard_block_engine with rng. */
+    explicit discard_block_engine(base_type && rng) : _rng(rng), _n(0) { }
+#endif
+
+    /**
+     * Creates a new \discard_block_engine and seeds the underlying
+     * generator with @c value
+     */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(discard_block_engine,
+                                               seed_type, value)
+    { _rng.seed(value); _n = 0; }
+    
+    /**
+     * Creates a new \discard_block_engine and seeds the underlying
+     * generator with @c seq
+     */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_CONSTRUCTOR(discard_block_engine, SeedSeq, seq)
+    { _rng.seed(seq); _n = 0; }
+    
+    /**
+     * Creates a new \discard_block_engine and seeds the underlying
+     * generator with first and last.
+     */
+    template<class It> discard_block_engine(It& first, It last)
+      : _rng(first, last), _n(0) { }
+    
+    /** default seeds the underlying generator. */
+    void seed() { _rng.seed(); _n = 0; }
+    /** Seeds the underlying generator with s. */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_SEED(discard_block_engine, seed_type, s)
+    { _rng.seed(s); _n = 0; }
+    /** Seeds the underlying generator with seq. */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_SEED(discard_block_engine, SeedSeq, seq)
+    { _rng.seed(seq); _n = 0; }
+    /** Seeds the underlying generator with first and last. */
+    template<class It> void seed(It& first, It last)
+    { _rng.seed(first, last); _n = 0; }
+
+    /** Returns the underlying engine. */
+    const base_type& base() const { return _rng; }
+
+    /** Returns the next value of the generator. */
+    result_type operator()()
+    {
+        if(_n >= returned_block) {
+            // discard values of random number generator
+            // Don't use discard, since we still need to
+            // be somewhat compatible with TR1.
+            // _rng.discard(total_block - _n);
+            for(std::size_t i = 0; i < total_block - _n; ++i) {
+                _rng();
+            }
+            _n = 0;
+        }
+        ++_n;
+        return _rng();
+    }
+
+    void discard(boost::uintmax_t z)
+    {
+        for(boost::uintmax_t j = 0; j < z; ++j) {
+            (*this)();
+        }
+    }
+
+    template<class It>
+    void generate(It first, It last)
+    { detail::generate(*this, first, last); }
+
+    /**
+     * Returns the smallest value that the generator can produce.
+     * This is the same as the minimum of the underlying generator.
+     */
+    static result_type min BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return (base_type::min)(); }
+    /**
+     * Returns the largest value that the generator can produce.
+     * This is the same as the maximum of the underlying generator.
+     */
+    static result_type max BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return (base_type::max)(); }
+
+#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
+    /** Writes a \discard_block_engine to a @c std::ostream. */
+    template<class CharT, class Traits>
+    friend std::basic_ostream<CharT,Traits>&
+    operator<<(std::basic_ostream<CharT,Traits>& os,
+               const discard_block_engine& s)
+    {
+        os << s._rng << ' ' << s._n;
+        return os;
+    }
+
+    /** Reads a \discard_block_engine from a @c std::istream. */
+    template<class CharT, class Traits>
+    friend std::basic_istream<CharT,Traits>&
+    operator>>(std::basic_istream<CharT,Traits>& is, discard_block_engine& s)
+    {
+        is >> s._rng >> std::ws >> s._n;
+        return is;
+    }
+#endif
+
+    /** Returns true if the two generators will produce identical sequences. */
+    friend bool operator==(const discard_block_engine& x,
+                           const discard_block_engine& y)
+    { return x._rng == y._rng && x._n == y._n; }
+    /** Returns true if the two generators will produce different sequences. */
+    friend bool operator!=(const discard_block_engine& x,
+                           const discard_block_engine& y)
+    { return !(x == y); }
+
+private:
+    base_type _rng;
+    std::size_t _n;
+};
+
+#ifndef BOOST_NO_INCLASS_MEMBER_INITIALIZATION
+//  A definition is required even for integral static constants
+template<class URNG, std::size_t p, std::size_t r>
+const bool discard_block_engine<URNG, p, r>::has_fixed_range;
+template<class URNG, std::size_t p, std::size_t r>
+const std::size_t discard_block_engine<URNG, p, r>::total_block;
+template<class URNG, std::size_t p, std::size_t r>
+const std::size_t discard_block_engine<URNG, p, r>::returned_block;
+template<class URNG, std::size_t p, std::size_t r>
+const std::size_t discard_block_engine<URNG, p, r>::block_size;
+template<class URNG, std::size_t p, std::size_t r>
+const std::size_t discard_block_engine<URNG, p, r>::used_block;
+#endif
+
+/// \cond \show_deprecated
+
+template<class URNG, int p, int r>
+class discard_block : public discard_block_engine<URNG, p, r>
+{
+    typedef discard_block_engine<URNG, p, r> base_t;
+public:
+    typedef typename base_t::result_type result_type;
+    discard_block() {}
+    template<class T>
+    discard_block(T& arg) : base_t(arg) {}
+    template<class T>
+    discard_block(const T& arg) : base_t(arg) {}
+    template<class It>
+    discard_block(It& first, It last) : base_t(first, last) {}
+    result_type min BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return (this->base().min)(); }
+    result_type max BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return (this->base().max)(); }
+};
+
+/// \endcond
+
+namespace detail {
+
+    template<class Engine>
+    struct generator_bits;
+    
+    template<class URNG, std::size_t p, std::size_t r>
+    struct generator_bits<discard_block_engine<URNG, p, r> > {
+        static std::size_t value() { return generator_bits<URNG>::value(); }
+    };
+
+    template<class URNG, int p, int r>
+    struct generator_bits<discard_block<URNG, p, r> > {
+        static std::size_t value() { return generator_bits<URNG>::value(); }
+    };
+
+}
+
+} // namespace random
+
+} // namespace boost
+
+#endif // BOOST_RANDOM_DISCARD_BLOCK_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/discrete_distribution.hpp

@@ -0,0 +1,636 @@
+/* boost random/discrete_distribution.hpp header file
+ *
+ * Copyright Steven Watanabe 2009-2011
+ * 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.
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_DISCRETE_DISTRIBUTION_HPP_INCLUDED
+#define BOOST_RANDOM_DISCRETE_DISTRIBUTION_HPP_INCLUDED
+
+#include <vector>
+#include <limits>
+#include <numeric>
+#include <utility>
+#include <iterator>
+#include <boost/assert.hpp>
+#include <boost/random/uniform_01.hpp>
+#include <boost/random/uniform_int_distribution.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/detail/vector_io.hpp>
+
+#ifndef BOOST_NO_CXX11_HDR_INITIALIZER_LIST
+#include <initializer_list>
+#endif
+
+#include <boost/range/begin.hpp>
+#include <boost/range/end.hpp>
+
+#include <boost/random/detail/disable_warnings.hpp>
+
+namespace boost {
+namespace random {
+namespace detail {
+
+template<class IntType, class WeightType>
+struct integer_alias_table {
+    WeightType get_weight(IntType bin) const {
+        WeightType result = _average;
+        if(bin < _excess) ++result;
+        return result;
+    }
+    template<class Iter>
+    WeightType init_average(Iter begin, Iter end) {
+        WeightType weight_average = 0;
+        IntType excess = 0;
+        IntType n = 0;
+        // weight_average * n + excess == current partial sum
+        // This is a bit messy, but it's guaranteed not to overflow
+        for(Iter iter = begin; iter != end; ++iter) {
+            ++n;
+            if(*iter < weight_average) {
+                WeightType diff = weight_average - *iter;
+                weight_average -= diff / n;
+                if(diff % n > excess) {
+                    --weight_average;
+                    excess += n - diff % n;
+                } else {
+                    excess -= diff % n;
+                }
+            } else {
+                WeightType diff = *iter - weight_average;
+                weight_average += diff / n;
+                if(diff % n < n - excess) {
+                    excess += diff % n;
+                } else {
+                    ++weight_average;
+                    excess -= n - diff % n;
+                }
+            }
+        }
+        _alias_table.resize(static_cast<std::size_t>(n));
+        _average = weight_average;
+        _excess = excess;
+        return weight_average;
+    }
+    void init_empty()
+    {
+        _alias_table.clear();
+        _alias_table.push_back(std::make_pair(static_cast<WeightType>(1),
+                                              static_cast<IntType>(0)));
+        _average = static_cast<WeightType>(1);
+        _excess = static_cast<IntType>(0);
+    }
+    bool operator==(const integer_alias_table& other) const
+    {
+        return _alias_table == other._alias_table &&
+            _average == other._average && _excess == other._excess;
+    }
+    static WeightType normalize(WeightType val, WeightType average)
+    {
+        return val;
+    }
+    static void normalize(std::vector<WeightType>&) {}
+    template<class URNG>
+    WeightType test(URNG &urng) const
+    {
+        return uniform_int_distribution<WeightType>(0, _average)(urng);
+    }
+    bool accept(IntType result, WeightType val) const
+    {
+        return result < _excess || val < _average;
+    }
+    static WeightType try_get_sum(const std::vector<WeightType>& weights)
+    {
+        WeightType result = static_cast<WeightType>(0);
+        for(typename std::vector<WeightType>::const_iterator
+                iter = weights.begin(), end = weights.end();
+            iter != end; ++iter)
+        {
+            if((std::numeric_limits<WeightType>::max)() - result > *iter) {
+                return static_cast<WeightType>(0);
+            }
+            result += *iter;
+        }
+        return result;
+    }
+    template<class URNG>
+    static WeightType generate_in_range(URNG &urng, WeightType max)
+    {
+        return uniform_int_distribution<WeightType>(
+            static_cast<WeightType>(0), max-1)(urng);
+    }
+    typedef std::vector<std::pair<WeightType, IntType> > alias_table_t;
+    alias_table_t _alias_table;
+    WeightType _average;
+    IntType _excess;
+};
+
+template<class IntType, class WeightType>
+struct real_alias_table {
+    WeightType get_weight(IntType) const
+    {
+        return WeightType(1.0);
+    }
+    template<class Iter>
+    WeightType init_average(Iter first, Iter last)
+    {
+        std::size_t size = std::distance(first, last);
+        WeightType weight_sum =
+            std::accumulate(first, last, static_cast<WeightType>(0));
+        _alias_table.resize(size);
+        return weight_sum / size;
+    }
+    void init_empty()
+    {
+        _alias_table.clear();
+        _alias_table.push_back(std::make_pair(static_cast<WeightType>(1),
+                                              static_cast<IntType>(0)));
+    }
+    bool operator==(const real_alias_table& other) const
+    {
+        return _alias_table == other._alias_table;
+    }
+    static WeightType normalize(WeightType val, WeightType average)
+    {
+        return val / average;
+    }
+    static void normalize(std::vector<WeightType>& weights)
+    {
+        WeightType sum =
+            std::accumulate(weights.begin(), weights.end(),
+                            static_cast<WeightType>(0));
+        for(typename std::vector<WeightType>::iterator
+                iter = weights.begin(),
+                end = weights.end();
+            iter != end; ++iter)
+        {
+            *iter /= sum;
+        }
+    }
+    template<class URNG>
+    WeightType test(URNG &urng) const
+    {
+        return uniform_01<WeightType>()(urng);
+    }
+    bool accept(IntType, WeightType) const
+    {
+        return true;
+    }
+    static WeightType try_get_sum(const std::vector<WeightType>& weights)
+    {
+        return static_cast<WeightType>(1);
+    }
+    template<class URNG>
+    static WeightType generate_in_range(URNG &urng, WeightType)
+    {
+        return uniform_01<WeightType>()(urng);
+    }
+    typedef std::vector<std::pair<WeightType, IntType> > alias_table_t;
+    alias_table_t _alias_table;
+};
+
+template<bool IsIntegral>
+struct select_alias_table;
+
+template<>
+struct select_alias_table<true> {
+    template<class IntType, class WeightType>
+    struct apply {
+        typedef integer_alias_table<IntType, WeightType> type;
+    };
+};
+
+template<>
+struct select_alias_table<false> {
+    template<class IntType, class WeightType>
+    struct apply {
+        typedef real_alias_table<IntType, WeightType> type;
+    };
+};
+
+}
+
+/**
+ * The class @c discrete_distribution models a \random_distribution.
+ * It produces integers in the range [0, n) with the probability
+ * of producing each value is specified by the parameters of the
+ * distribution.
+ */
+template<class IntType = int, class WeightType = double>
+class discrete_distribution {
+public:
+    typedef WeightType input_type;
+    typedef IntType result_type;
+
+    class param_type {
+    public:
+
+        typedef discrete_distribution distribution_type;
+
+        /**
+         * Constructs a @c param_type object, representing a distribution
+         * with \f$p(0) = 1\f$ and \f$p(k|k>0) = 0\f$.
+         */
+        param_type() : _probabilities(1, static_cast<WeightType>(1)) {}
+        /**
+         * If @c first == @c last, equivalent to the default constructor.
+         * Otherwise, the values of the range represent weights for the
+         * possible values of the distribution.
+         */
+        template<class Iter>
+        param_type(Iter first, Iter last) : _probabilities(first, last)
+        {
+            normalize();
+        }
+#ifndef BOOST_NO_CXX11_HDR_INITIALIZER_LIST
+        /**
+         * If wl.size() == 0, equivalent to the default constructor.
+         * Otherwise, the values of the @c initializer_list represent
+         * weights for the possible values of the distribution.
+         */
+        param_type(const std::initializer_list<WeightType>& wl)
+          : _probabilities(wl)
+        {
+            normalize();
+        }
+#endif
+        /**
+         * If the range is empty, equivalent to the default constructor.
+         * Otherwise, the elements of the range represent
+         * weights for the possible values of the distribution.
+         */
+        template<class Range>
+        explicit param_type(const Range& range)
+          : _probabilities(boost::begin(range), boost::end(range))
+        {
+            normalize();
+        }
+
+        /**
+         * If nw is zero, equivalent to the default constructor.
+         * Otherwise, the range of the distribution is [0, nw),
+         * and the weights are found by  calling fw with values
+         * evenly distributed between \f$\mbox{xmin} + \delta/2\f$ and
+         * \f$\mbox{xmax} - \delta/2\f$, where
+         * \f$\delta = (\mbox{xmax} - \mbox{xmin})/\mbox{nw}\f$.
+         */
+        template<class Func>
+        param_type(std::size_t nw, double xmin, double xmax, Func fw)
+        {
+            std::size_t n = (nw == 0) ? 1 : nw;
+            double delta = (xmax - xmin) / n;
+            BOOST_ASSERT(delta > 0);
+            for(std::size_t k = 0; k < n; ++k) {
+                _probabilities.push_back(fw(xmin + k*delta + delta/2));
+            }
+            normalize();
+        }
+
+        /**
+         * Returns a vector containing the probabilities of each possible
+         * value of the distribution.
+         */
+        std::vector<WeightType> probabilities() const
+        {
+            return _probabilities;
+        }
+
+        /** Writes the parameters to a @c std::ostream. */
+        BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
+        {
+            detail::print_vector(os, parm._probabilities);
+            return os;
+        }
+        
+        /** Reads the parameters from a @c std::istream. */
+        BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
+        {
+            std::vector<WeightType> temp;
+            detail::read_vector(is, temp);
+            if(is) {
+                parm._probabilities.swap(temp);
+            }
+            return is;
+        }
+
+        /** Returns true if the two sets of parameters are the same. */
+        BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
+        {
+            return lhs._probabilities == rhs._probabilities;
+        }
+        /** Returns true if the two sets of parameters are different. */
+        BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+    private:
+        /// @cond show_private
+        friend class discrete_distribution;
+        explicit param_type(const discrete_distribution& dist)
+          : _probabilities(dist.probabilities())
+        {}
+        void normalize()
+        {
+            impl_type::normalize(_probabilities);
+        }
+        std::vector<WeightType> _probabilities;
+        /// @endcond
+    };
+
+    /**
+     * Creates a new @c discrete_distribution object that has
+     * \f$p(0) = 1\f$ and \f$p(i|i>0) = 0\f$.
+     */
+    discrete_distribution()
+    {
+        _impl.init_empty();
+    }
+    /**
+     * Constructs a discrete_distribution from an iterator range.
+     * If @c first == @c last, equivalent to the default constructor.
+     * Otherwise, the values of the range represent weights for the
+     * possible values of the distribution.
+     */
+    template<class Iter>
+    discrete_distribution(Iter first, Iter last)
+    {
+        init(first, last);
+    }
+#ifndef BOOST_NO_CXX11_HDR_INITIALIZER_LIST
+    /**
+     * Constructs a @c discrete_distribution from a @c std::initializer_list.
+     * If the @c initializer_list is empty, equivalent to the default
+     * constructor.  Otherwise, the values of the @c initializer_list
+     * represent weights for the possible values of the distribution.
+     * For example, given the distribution
+     *
+     * @code
+     * discrete_distribution<> dist{1, 4, 5};
+     * @endcode
+     *
+     * The probability of a 0 is 1/10, the probability of a 1 is 2/5,
+     * the probability of a 2 is 1/2, and no other values are possible.
+     */
+    discrete_distribution(std::initializer_list<WeightType> wl)
+    {
+        init(wl.begin(), wl.end());
+    }
+#endif
+    /**
+     * Constructs a discrete_distribution from a Boost.Range range.
+     * If the range is empty, equivalent to the default constructor.
+     * Otherwise, the values of the range represent weights for the
+     * possible values of the distribution.
+     */
+    template<class Range>
+    explicit discrete_distribution(const Range& range)
+    {
+        init(boost::begin(range), boost::end(range));
+    }
+    /**
+     * Constructs a discrete_distribution that approximates a function.
+     * If nw is zero, equivalent to the default constructor.
+     * Otherwise, the range of the distribution is [0, nw),
+     * and the weights are found by  calling fw with values
+     * evenly distributed between \f$\mbox{xmin} + \delta/2\f$ and
+     * \f$\mbox{xmax} - \delta/2\f$, where
+     * \f$\delta = (\mbox{xmax} - \mbox{xmin})/\mbox{nw}\f$.
+     */
+    template<class Func>
+    discrete_distribution(std::size_t nw, double xmin, double xmax, Func fw)
+    {
+        std::size_t n = (nw == 0) ? 1 : nw;
+        double delta = (xmax - xmin) / n;
+        BOOST_ASSERT(delta > 0);
+        std::vector<WeightType> weights;
+        for(std::size_t k = 0; k < n; ++k) {
+            weights.push_back(fw(xmin + k*delta + delta/2));
+        }
+        init(weights.begin(), weights.end());
+    }
+    /**
+     * Constructs a discrete_distribution from its parameters.
+     */
+    explicit discrete_distribution(const param_type& parm)
+    {
+        param(parm);
+    }
+
+    /**
+     * Returns a value distributed according to the parameters of the
+     * discrete_distribution.
+     */
+    template<class URNG>
+    IntType operator()(URNG& urng) const
+    {
+        BOOST_ASSERT(!_impl._alias_table.empty());
+        IntType result;
+        WeightType test;
+        do {
+            result = uniform_int_distribution<IntType>((min)(), (max)())(urng);
+            test = _impl.test(urng);
+        } while(!_impl.accept(result, test));
+        if(test < _impl._alias_table[static_cast<std::size_t>(result)].first) {
+            return result;
+        } else {
+            return(_impl._alias_table[static_cast<std::size_t>(result)].second);
+        }
+    }
+    
+    /**
+     * Returns a value distributed according to the parameters
+     * specified by param.
+     */
+    template<class URNG>
+    IntType operator()(URNG& urng, const param_type& parm) const
+    {
+        if(WeightType limit = impl_type::try_get_sum(parm._probabilities)) {
+            WeightType val = impl_type::generate_in_range(urng, limit);
+            WeightType sum = 0;
+            std::size_t result = 0;
+            for(typename std::vector<WeightType>::const_iterator
+                    iter = parm._probabilities.begin(),
+                    end = parm._probabilities.end();
+                iter != end; ++iter, ++result)
+            {
+                sum += *iter;
+                if(sum > val) {
+                    return result;
+                }
+            }
+            // This shouldn't be reachable, but round-off error
+            // can prevent any match from being found when val is
+            // very close to 1.
+            return static_cast<IntType>(parm._probabilities.size() - 1);
+        } else {
+            // WeightType is integral and sum(parm._probabilities)
+            // would overflow.  Just use the easy solution.
+            return discrete_distribution(parm)(urng);
+        }
+    }
+    
+    /** Returns the smallest value that the distribution can produce. */
+    result_type min BOOST_PREVENT_MACRO_SUBSTITUTION () const { return 0; }
+    /** Returns the largest value that the distribution can produce. */
+    result_type max BOOST_PREVENT_MACRO_SUBSTITUTION () const
+    { return static_cast<result_type>(_impl._alias_table.size() - 1); }
+
+    /**
+     * Returns a vector containing the probabilities of each
+     * value of the distribution.  For example, given
+     *
+     * @code
+     * discrete_distribution<> dist = { 1, 4, 5 };
+     * std::vector<double> p = dist.param();
+     * @endcode
+     *
+     * the vector, p will contain {0.1, 0.4, 0.5}.
+     *
+     * If @c WeightType is integral, then the weights
+     * will be returned unchanged.
+     */
+    std::vector<WeightType> probabilities() const
+    {
+        std::vector<WeightType> result(_impl._alias_table.size(), static_cast<WeightType>(0));
+        std::size_t i = 0;
+        for(typename impl_type::alias_table_t::const_iterator
+                iter = _impl._alias_table.begin(),
+                end = _impl._alias_table.end();
+                iter != end; ++iter, ++i)
+        {
+            WeightType val = iter->first;
+            result[i] += val;
+            result[static_cast<std::size_t>(iter->second)] += _impl.get_weight(i) - val;
+        }
+        impl_type::normalize(result);
+        return(result);
+    }
+
+    /** Returns the parameters of the distribution. */
+    param_type param() const
+    {
+        return param_type(*this);
+    }
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        init(parm._probabilities.begin(), parm._probabilities.end());
+    }
+    
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() {}
+
+    /** Writes a distribution to a @c std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, discrete_distribution, dd)
+    {
+        os << dd.param();
+        return os;
+    }
+
+    /** Reads a distribution from a @c std::istream */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, discrete_distribution, dd)
+    {
+        param_type parm;
+        if(is >> parm) {
+            dd.param(parm);
+        }
+        return is;
+    }
+
+    /**
+     * Returns true if the two distributions will return the
+     * same sequence of values, when passed equal generators.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(discrete_distribution, lhs, rhs)
+    {
+        return lhs._impl == rhs._impl;
+    }
+    /**
+     * Returns true if the two distributions may return different
+     * sequences of values, when passed equal generators.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(discrete_distribution)
+
+private:
+
+    /// @cond show_private
+
+    template<class Iter>
+    void init(Iter first, Iter last, std::input_iterator_tag)
+    {
+        std::vector<WeightType> temp(first, last);
+        init(temp.begin(), temp.end());
+    }
+    template<class Iter>
+    void init(Iter first, Iter last, std::forward_iterator_tag)
+    {
+        std::vector<std::pair<WeightType, IntType> > below_average;
+        std::vector<std::pair<WeightType, IntType> > above_average;
+        WeightType weight_average = _impl.init_average(first, last);
+        WeightType normalized_average = _impl.get_weight(0);
+        std::size_t i = 0;
+        for(; first != last; ++first, ++i) {
+            WeightType val = impl_type::normalize(*first, weight_average);
+            std::pair<WeightType, IntType> elem(val, static_cast<IntType>(i));
+            if(val < normalized_average) {
+                below_average.push_back(elem);
+            } else {
+                above_average.push_back(elem);
+            }
+        }
+
+        typename impl_type::alias_table_t::iterator
+            b_iter = below_average.begin(),
+            b_end = below_average.end(),
+            a_iter = above_average.begin(),
+            a_end = above_average.end()
+            ;
+        while(b_iter != b_end && a_iter != a_end) {
+            _impl._alias_table[static_cast<std::size_t>(b_iter->second)] =
+                std::make_pair(b_iter->first, a_iter->second);
+            a_iter->first -= (_impl.get_weight(b_iter->second) - b_iter->first);
+            if(a_iter->first < normalized_average) {
+                *b_iter = *a_iter++;
+            } else {
+                ++b_iter;
+            }
+        }
+        for(; b_iter != b_end; ++b_iter) {
+            _impl._alias_table[static_cast<std::size_t>(b_iter->second)].first =
+                _impl.get_weight(b_iter->second);
+        }
+        for(; a_iter != a_end; ++a_iter) {
+            _impl._alias_table[static_cast<std::size_t>(a_iter->second)].first =
+                _impl.get_weight(a_iter->second);
+        }
+    }
+    template<class Iter>
+    void init(Iter first, Iter last)
+    {
+        if(first == last) {
+            _impl.init_empty();
+        } else {
+            typename std::iterator_traits<Iter>::iterator_category category;
+            init(first, last, category);
+        }
+    }
+    typedef typename detail::select_alias_table<
+        (::boost::is_integral<WeightType>::value)
+    >::template apply<IntType, WeightType>::type impl_type;
+    impl_type _impl;
+    /// @endcond
+};
+
+}
+}
+
+#include <boost/random/detail/enable_warnings.hpp>
+
+#endif

depends/x86_64-pc-linux-gnu/include/boost/random/exponential_distribution.hpp

@@ -0,0 +1,386 @@
+/* boost random/exponential_distribution.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * Copyright Steven Watanabe 2011
+ * Copyright Jason Rhinelander 2016
+ * 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2001-02-18  moved to individual header files
+ */
+
+#ifndef BOOST_RANDOM_EXPONENTIAL_DISTRIBUTION_HPP
+#define BOOST_RANDOM_EXPONENTIAL_DISTRIBUTION_HPP
+
+#include <boost/config/no_tr1/cmath.hpp>
+#include <iosfwd>
+#include <boost/assert.hpp>
+#include <boost/limits.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/detail/int_float_pair.hpp>
+#include <boost/random/uniform_01.hpp>
+
+namespace boost {
+namespace random {
+
+namespace detail {
+
+// tables for the ziggurat algorithm
+template<class RealType>
+struct exponential_table {
+    static const RealType table_x[257];
+    static const RealType table_y[257];
+};
+
+template<class RealType>
+const RealType exponential_table<RealType>::table_x[257] = {
+    8.6971174701310497140, 7.6971174701310497140, 6.9410336293772123602, 6.4783784938325698538,
+    6.1441646657724730491, 5.8821443157953997963, 5.6664101674540337371, 5.4828906275260628694,
+    5.3230905057543986131, 5.1814872813015010392, 5.0542884899813047117, 4.9387770859012514838,
+    4.8329397410251125881, 4.7352429966017412526, 4.6444918854200854873, 4.5597370617073515513,
+    4.4802117465284221949, 4.4052876934735729805, 4.3344436803172730116, 4.2672424802773661873,
+    4.2033137137351843802, 4.1423408656640511251, 4.0840513104082974638, 4.0282085446479365106,
+    3.9746060666737884793, 3.9230625001354895926, 3.8734176703995089983, 3.8255294185223367372,
+    3.7792709924116678992, 3.7345288940397975350, 3.6912010902374189454, 3.6491955157608538478,
+    3.6084288131289096339, 3.5688252656483374051, 3.5303158891293438633, 3.4928376547740601814,
+    3.4563328211327607625, 3.4207483572511205323, 3.3860354424603017887, 3.3521490309001100106,
+    3.3190474709707487166, 3.2866921715990692095, 3.2550473085704501813, 3.2240795652862645207,
+    3.1937579032122407483, 3.1640533580259734580, 3.1349388580844407393, 3.1063890623398246660,
+    3.0783802152540905188, 3.0508900166154554479, 3.0238975044556767713, 2.9973829495161306949,
+    2.9713277599210896472, 2.9457143948950456386, 2.9205262865127406647, 2.8957477686001416838,
+    2.8713640120155362592, 2.8473609656351888266, 2.8237253024500354905, 2.8004443702507381944,
+    2.7775061464397572041, 2.7548991965623453650, 2.7326126361947007411, 2.7106360958679293686,
+    2.6889596887418041593, 2.6675739807732670816, 2.6464699631518093905, 2.6256390267977886123,
+    2.6050729387408355373, 2.5847638202141406911, 2.5647041263169053687, 2.5448866271118700928,
+    2.5253043900378279427, 2.5059507635285939648, 2.4868193617402096807, 2.4679040502973649846,
+    2.4491989329782498908, 2.4306983392644199088, 2.4123968126888708336, 2.3942890999214583288,
+    2.3763701405361408194, 2.3586350574093374601, 2.3410791477030346875, 2.3236978743901964559,
+    2.3064868582835798692, 2.2894418705322694265, 2.2725588255531546952, 2.2558337743672190441,
+    2.2392628983129087111, 2.2228425031110364013, 2.2065690132576635755, 2.1904389667232199235,
+    2.1744490099377744673, 2.1585958930438856781, 2.1428764653998416425, 2.1272876713173679737,
+    2.1118265460190418108, 2.0964902118017147637, 2.0812758743932248696, 2.0661808194905755036,
+    2.0512024094685848641, 2.0363380802487695916, 2.0215853383189260770, 2.0069417578945183144,
+    1.9924049782135764992, 1.9779727009573602295, 1.9636426877895480401, 1.9494127580071845659,
+    1.9352807862970511135, 1.9212447005915276767, 1.9073024800183871196, 1.8934521529393077332,
+    1.8796917950722108462, 1.8660195276928275962, 1.8524335159111751661, 1.8389319670188793980,
+    1.8255131289035192212, 1.8121752885263901413, 1.7989167704602903934, 1.7857359354841254047,
+    1.7726311792313049959, 1.7596009308890742369, 1.7466436519460739352, 1.7337578349855711926,
+    1.7209420025219350428, 1.7081947058780575683, 1.6955145241015377061, 1.6829000629175537544,
+    1.6703499537164519163, 1.6578628525741725325, 1.6454374393037234057, 1.6330724165359912048,
+    1.6207665088282577216, 1.6085184617988580769, 1.5963270412864831349, 1.5841910325326886695,
+    1.5721092393862294810, 1.5600804835278879161, 1.5481036037145133070, 1.5361774550410318943,
+    1.5243009082192260050, 1.5124728488721167573, 1.5006921768428164936, 1.4889578055167456003,
+    1.4772686611561334579, 1.4656236822457450411, 1.4540218188487932264, 1.4424620319720121876,
+    1.4309432929388794104, 1.4194645827699828254, 1.4080248915695353509, 1.3966232179170417110,
+    1.3852585682631217189, 1.3739299563284902176, 1.3626364025050864742, 1.3513769332583349176,
+    1.3401505805295045843, 1.3289563811371163220, 1.3177933761763245480, 1.3066606104151739482,
+    1.2955571316866007210, 1.2844819902750125450, 1.2734342382962410994, 1.2624129290696153434,
+    1.2514171164808525098, 1.2404458543344064544, 1.2294981956938491599, 1.2185731922087903071,
+    1.2076698934267612830, 1.1967873460884031665, 1.1859245934042023557, 1.1750806743109117687,
+    1.1642546227056790397, 1.1534454666557748056, 1.1426522275816728928, 1.1318739194110786733,
+    1.1211095477013306083, 1.1103581087274114281, 1.0996185885325976575, 1.0888899619385472598,
+    1.0781711915113727024, 1.0674612264799681530, 1.0567590016025518414, 1.0460634359770445503,
+    1.0353734317905289496, 1.0246878730026178052, 1.0140056239570971074, 1.0033255279156973717,
+    0.99264640550727647009, 0.98196705308506317914, 0.97128624098390397896, 0.96060271166866709917,
+    0.94991517776407659940, 0.93922231995526297952, 0.92852278474721113999, 0.91781518207004493915,
+    0.90709808271569100600, 0.89637001558989069006, 0.88562946476175228052, 0.87487486629102585352,
+    0.86410460481100519511, 0.85331700984237406386, 0.84251035181036928333, 0.83168283773427388393,
+    0.82083260655441252290, 0.80995772405741906620, 0.79905617735548788109, 0.78812586886949324977,
+    0.77716460975913043936, 0.76617011273543541328, 0.75513998418198289808, 0.74407171550050873971,
+    0.73296267358436604916, 0.72181009030875689912, 0.71061105090965570413, 0.69936248110323266174,
+    0.68806113277374858613, 0.67670356802952337911, 0.66528614139267855405, 0.65380497984766565353,
+    0.64225596042453703448, 0.63063468493349100113, 0.61893645139487678178, 0.60715622162030085137,
+    0.59528858429150359384, 0.58332771274877027785, 0.57126731653258903915, 0.55910058551154127652,
+    0.54682012516331112550, 0.53441788123716615385, 0.52188505159213564105, 0.50921198244365495319,
+    0.49638804551867159754, 0.48340149165346224782, 0.47023927508216945338, 0.45688684093142071279,
+    0.44332786607355296305, 0.42954394022541129589, 0.41551416960035700100, 0.40121467889627836229,
+    0.38661797794112021568, 0.37169214532991786118, 0.35639976025839443721, 0.34069648106484979674,
+    0.32452911701691008547, 0.30783295467493287307, 0.29052795549123115167, 0.27251318547846547924,
+    0.25365836338591284433, 0.23379048305967553619, 0.21267151063096745264, 0.18995868962243277774,
+    0.16512762256418831796, 0.13730498094001380420, 0.10483850756582017915, 0.063852163815003480173,
+    0
+};
+
+template<class RealType>
+const RealType exponential_table<RealType>::table_y[257] = {
+    0, 0.00045413435384149675545, 0.00096726928232717452884, 0.0015362997803015723824,
+    0.0021459677437189061793, 0.0027887987935740759640, 0.0034602647778369039855, 0.0041572951208337952532,
+    0.0048776559835423925804, 0.0056196422072054831710, 0.0063819059373191794422, 0.0071633531836349841425,
+    0.0079630774380170392396, 0.0087803149858089752347, 0.0096144136425022094101, 0.010464810181029979488,
+    0.011331013597834597488, 0.012212592426255380661, 0.013109164931254991070, 0.014020391403181937334,
+    0.014945968011691148079, 0.015885621839973162490, 0.016839106826039946359, 0.017806200410911360563,
+    0.018786700744696029497, 0.019780424338009741737, 0.020787204072578117603, 0.021806887504283582125,
+    0.022839335406385238829, 0.023884420511558170348, 0.024942026419731782971, 0.026012046645134218076,
+    0.027094383780955798424, 0.028188948763978634421, 0.029295660224637394015, 0.030414443910466605492,
+    0.031545232172893605499, 0.032687963508959533317, 0.033842582150874329031, 0.035009037697397411067,
+    0.036187284781931419754, 0.037377282772959360128, 0.038578995503074859626, 0.039792391023374122670,
+    0.041017441380414820816, 0.042254122413316231413, 0.043502413568888183301, 0.044762297732943280694,
+    0.046033761076175166762, 0.047316792913181548703, 0.048611385573379494401, 0.049917534282706374944,
+    0.051235237055126279830, 0.052564494593071689595, 0.053905310196046085104, 0.055257689676697038322,
+    0.056621641283742874438, 0.057997175631200659098, 0.059384305633420264487, 0.060783046445479636051,
+    0.062193415408540996150, 0.063615431999807331076, 0.065049117786753755036, 0.066494496385339779043,
+    0.067951593421936607770, 0.069420436498728751675, 0.070901055162371828426, 0.072393480875708743023,
+    0.073897746992364746308, 0.075413888734058408453, 0.076941943170480510100, 0.078481949201606426042,
+    0.080033947542319910023, 0.081597980709237420930, 0.083174093009632380354, 0.084762330532368125386,
+    0.086362741140756912277, 0.087975374467270219300, 0.089600281910032864534, 0.091237516631040162057,
+    0.092887133556043546523, 0.094549189376055853718, 0.096223742550432800103, 0.097910853311492199618,
+    0.099610583670637128826, 0.10132299742595363588, 0.10304816017125771553, 0.10478613930657016928,
+    0.10653700405000166218, 0.10830082545103379867, 0.11007767640518539026, 0.11186763167005629731,
+    0.11367076788274431301, 0.11548716357863353664, 0.11731689921155557057, 0.11916005717532768467,
+    0.12101672182667483729, 0.12288697950954513498, 0.12477091858083096578, 0.12666862943751066518,
+    0.12858020454522817870, 0.13050573846833078225, 0.13244532790138752023, 0.13439907170221363078,
+    0.13636707092642885841, 0.13834942886358021406, 0.14034625107486244210, 0.14235764543247220043,
+    0.14438372216063476473, 0.14642459387834493787, 0.14848037564386679222, 0.15055118500103990354,
+    0.15263714202744286154, 0.15473836938446807312, 0.15685499236936522013, 0.15898713896931420572,
+    0.16113493991759203183, 0.16329852875190180795, 0.16547804187493600915, 0.16767361861725019322,
+    0.16988540130252766513, 0.17211353531532005700, 0.17435816917135348788, 0.17661945459049489581,
+    0.17889754657247831241, 0.18119260347549629488, 0.18350478709776746150, 0.18583426276219711495,
+    0.18818119940425430485, 0.19054576966319540013, 0.19292814997677133873, 0.19532852067956322315,
+    0.19774706610509886464, 0.20018397469191127727, 0.20263943909370901930, 0.20511365629383770880,
+    0.20760682772422204205, 0.21011915938898825914, 0.21265086199297827522, 0.21520215107537867786,
+    0.21777324714870053264, 0.22036437584335949720, 0.22297576805812018050, 0.22560766011668406495,
+    0.22826029393071670664, 0.23093391716962742173, 0.23362878343743333945, 0.23634515245705964715,
+    0.23908329026244917002, 0.24184346939887722761, 0.24462596913189210901, 0.24743107566532763894,
+    0.25025908236886230967, 0.25311029001562948171, 0.25598500703041538015, 0.25888354974901621678,
+    0.26180624268936295243, 0.26475341883506220209, 0.26772541993204481808, 0.27072259679906003167,
+    0.27374530965280298302, 0.27679392844851734458, 0.27986883323697289920, 0.28297041453878076010,
+    0.28609907373707684673, 0.28925522348967773308, 0.29243928816189258772, 0.29565170428126120948,
+    0.29889292101558177099, 0.30216340067569352897, 0.30546361924459023541, 0.30879406693456016794,
+    0.31215524877417956945, 0.31554768522712893632, 0.31897191284495723773, 0.32242848495608914289,
+    0.32591797239355619822, 0.32944096426413633091, 0.33299806876180896713, 0.33658991402867758144,
+    0.34021714906678004560, 0.34388044470450243010, 0.34758049462163698567, 0.35131801643748334681,
+    0.35509375286678745925, 0.35890847294874976196, 0.36276297335481777335, 0.36665807978151414890,
+    0.37059464843514599421, 0.37457356761590215193, 0.37859575940958081092, 0.38266218149600982112,
+    0.38677382908413768115, 0.39093173698479710717, 0.39513698183329015336, 0.39939068447523107877,
+    0.40369401253053026739, 0.40804818315203238238, 0.41245446599716116772, 0.41691418643300289465,
+    0.42142872899761659635, 0.42599954114303435739, 0.43062813728845883923, 0.43531610321563659758,
+    0.44006510084235387501, 0.44487687341454851593, 0.44975325116275498919, 0.45469615747461548049,
+    0.45970761564213768669, 0.46478975625042618067, 0.46994482528395999841, 0.47517519303737738299,
+    0.48048336393045423016, 0.48587198734188493564, 0.49134386959403255500, 0.49690198724154955294,
+    0.50254950184134769289, 0.50828977641064283495, 0.51412639381474855788, 0.52006317736823356823,
+    0.52610421398361972602, 0.53225388026304326945, 0.53851687200286186590, 0.54489823767243963663,
+    0.55140341654064131685, 0.55803828226258748140, 0.56480919291240022434, 0.57172304866482579008,
+    0.57878735860284503057, 0.58601031847726802755, 0.59340090169173341521, 0.60096896636523224742,
+    0.60872538207962206507, 0.61668218091520762326, 0.62485273870366592605, 0.63325199421436607968,
+    0.64189671642726607018, 0.65080583341457104881, 0.66000084107899974178, 0.66950631673192477684,
+    0.67935057226476538741, 0.68956649611707798890, 0.70019265508278816709, 0.71127476080507597882,
+    0.72286765959357200702, 0.73503809243142351530, 0.74786862198519510742, 0.76146338884989624862,
+    0.77595685204011559675, 0.79152763697249565519, 0.80842165152300838005, 0.82699329664305033399,
+    0.84778550062398962096, 0.87170433238120363669, 0.90046992992574643800, 0.93814368086217467916,
+    1
+};
+
+template<class RealType = double>
+struct unit_exponential_distribution
+{
+    template<class Engine>
+    RealType operator()(Engine& eng) {
+        const double * const table_x = exponential_table<double>::table_x;
+        const double * const table_y = exponential_table<double>::table_y;
+        RealType shift(0);
+        for(;;) {
+            std::pair<RealType, int> vals = generate_int_float_pair<RealType, 8>(eng);
+            int i = vals.second;
+            RealType x = vals.first * RealType(table_x[i]);
+            if(x < RealType(table_x[i + 1])) return shift + x;
+            // For i=0 we need to generate from the tail, but because this is an exponential
+            // distribution, the tail looks exactly like the body, so we can simply repeat with a
+            // shift:
+            if (i == 0) shift += RealType(table_x[1]);
+            else {
+                RealType y01 = uniform_01<RealType>()(eng);
+                RealType y = RealType(table_y[i]) + y01 * RealType(table_y[i+1] - table_y[i]);
+
+                // All we care about is whether these are < or > 0; these values are equal to
+                // (lbound) or proportional to (ubound) `y` minus the lower/upper bound.
+                RealType y_above_ubound = RealType(table_x[i] - table_x[i+1]) * y01 - (RealType(table_x[i]) - x),
+                         y_above_lbound = y - (RealType(table_y[i+1]) + (RealType(table_x[i+1]) - x) * RealType(table_y[i+1]));
+
+                if (y_above_ubound < 0 // if above the upper bound reject immediately
+                        &&
+                        (
+                         y_above_lbound < 0 // If below the lower bound accept immediately
+                         ||
+                         y < f(x) // Otherwise it's between the bounds and we need a full check
+                        )
+                   ) {
+                    return x + shift;
+                }
+            }
+        }
+    }
+    static RealType f(RealType x) {
+        using std::exp;
+        return exp(-x);
+    }
+};
+
+} // namespace detail
+
+
+/**
+ * The exponential distribution is a model of \random_distribution with
+ * a single parameter lambda.
+ *
+ * It has \f$\displaystyle p(x) = \lambda e^{-\lambda x}\f$
+ *
+ * The implementation uses the "ziggurat" algorithm, as described in
+ *
+ *  @blockquote
+ *  "The Ziggurat Method for Generating Random Variables",
+ *  George Marsaglia and Wai Wan Tsang, Journal of Statistical Software
+ *  Volume 5, Number 8 (2000), 1-7.
+ *  @endblockquote
+ */
+template<class RealType = double>
+class exponential_distribution
+{
+public:
+    typedef RealType input_type;
+    typedef RealType result_type;
+
+    class param_type
+    {
+    public:
+
+        typedef exponential_distribution distribution_type;
+
+        /**
+         * Constructs parameters with a given lambda.
+         *
+         * Requires: lambda > 0
+         */
+        param_type(RealType lambda_arg = RealType(1.0))
+          : _lambda(lambda_arg) { BOOST_ASSERT(_lambda > RealType(0)); }
+
+        /** Returns the lambda parameter of the distribution. */
+        RealType lambda() const { return _lambda; }
+
+        /** Writes the parameters to a @c std::ostream. */
+        BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
+        {
+            os << parm._lambda;
+            return os;
+        }
+        
+        /** Reads the parameters from a @c std::istream. */
+        BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
+        {
+            is >> parm._lambda;
+            return is;
+        }
+
+        /** Returns true if the two sets of parameters are equal. */
+        BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
+        { return lhs._lambda == rhs._lambda; }
+
+        /** Returns true if the two sets of parameters are different. */
+        BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+
+    private:
+        RealType _lambda;
+    };
+
+    /**
+     * Constructs an exponential_distribution with a given lambda.
+     *
+     * Requires: lambda > 0
+     */
+    explicit exponential_distribution(RealType lambda_arg = RealType(1.0))
+      : _lambda(lambda_arg) { BOOST_ASSERT(_lambda > RealType(0)); }
+
+    /**
+     * Constructs an exponential_distribution from its parameters
+     */
+    explicit exponential_distribution(const param_type& parm)
+      : _lambda(parm.lambda()) {}
+
+    // compiler-generated copy ctor and assignment operator are fine
+
+    /** Returns the lambda parameter of the distribution. */
+    RealType lambda() const { return _lambda; }
+
+    /** Returns the smallest value that the distribution can produce. */
+    RealType min BOOST_PREVENT_MACRO_SUBSTITUTION () const
+    { return RealType(0); }
+    /** 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(_lambda); }
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm) { _lambda = parm.lambda(); }
+
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { }
+
+    /**
+     * Returns a random variate distributed according to the
+     * exponential distribution.
+     */
+    template<class Engine>
+    result_type operator()(Engine& eng) const
+    { 
+        detail::unit_exponential_distribution<RealType> impl;
+        return impl(eng) / _lambda;
+    }
+
+    /**
+     * Returns a random variate distributed according to the exponential
+     * distribution with parameters specified by param.
+     */
+    template<class Engine>
+    result_type operator()(Engine& eng, const param_type& parm) const
+    { 
+        return exponential_distribution(parm)(eng);
+    }
+
+    /** Writes the distribution to a std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, exponential_distribution, ed)
+    {
+        os << ed._lambda;
+        return os;
+    }
+
+    /** Reads the distribution from a std::istream. */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, exponential_distribution, ed)
+    {
+        is >> ed._lambda;
+        return is;
+    }
+
+    /**
+     * Returns true iff the two distributions will produce identical
+     * sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(exponential_distribution, lhs, rhs)
+    { return lhs._lambda == rhs._lambda; }
+    
+    /**
+     * Returns true iff the two distributions will produce different
+     * sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(exponential_distribution)
+
+private:
+    result_type _lambda;
+};
+
+} // namespace random
+
+using random::exponential_distribution;
+
+} // namespace boost
+
+#endif // BOOST_RANDOM_EXPONENTIAL_DISTRIBUTION_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/extreme_value_distribution.hpp

@@ -0,0 +1,177 @@
+/* boost random/extreme_value_distribution.hpp header file
+ *
+ * Copyright Steven Watanabe 2010
+ * 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.
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_EXTREME_VALUE_DISTRIBUTION_HPP
+#define BOOST_RANDOM_EXTREME_VALUE_DISTRIBUTION_HPP
+
+#include <boost/config/no_tr1/cmath.hpp>
+#include <iosfwd>
+#include <istream>
+#include <boost/config.hpp>
+#include <boost/limits.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/uniform_01.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * The extreme value distribution is a real valued distribution with two
+ * parameters a and b.
+ *
+ * It has \f$\displaystyle p(x) = \frac{1}{b}e^{\frac{a-x}{b} - e^\frac{a-x}{b}}\f$.
+ */
+template<class RealType = double>
+class extreme_value_distribution {
+public:
+    typedef RealType result_type;
+    typedef RealType input_type;
+
+    class param_type {
+    public:
+        typedef extreme_value_distribution distribution_type;
+
+        /**
+         * Constructs a @c param_type from the "a" and "b" parameters
+         * of the distribution.
+         *
+         * Requires: b > 0
+         */
+        explicit param_type(RealType a_arg = 1.0, RealType b_arg = 1.0)
+          : _a(a_arg), _b(b_arg)
+        {}
+
+        /** Returns the "a" parameter of the distribtuion. */
+        RealType a() const { return _a; }
+        /** Returns the "b" parameter of the distribution. */
+        RealType b() const { return _b; }
+
+        /** Writes a @c param_type to a @c std::ostream. */
+        BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
+        { os << parm._a << ' ' << parm._b; return os; }
+
+        /** Reads a @c param_type from a @c std::istream. */
+        BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
+        { is >> parm._a >> std::ws >> parm._b; return is; }
+
+        /** Returns true if the two sets of parameters are the same. */
+        BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
+        { return lhs._a == rhs._a && lhs._b == rhs._b; }
+        
+        /** Returns true if the two sets of parameters are the different. */
+        BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+
+    private:
+        RealType _a;
+        RealType _b;
+    };
+
+    /**
+     * Constructs an @c extreme_value_distribution from its "a" and "b" parameters.
+     *
+     * Requires: b > 0
+     */
+    explicit extreme_value_distribution(RealType a_arg = 1.0, RealType b_arg = 1.0)
+      : _a(a_arg), _b(b_arg)
+    {}
+    /** Constructs an @c extreme_value_distribution from its parameters. */
+    explicit extreme_value_distribution(const param_type& parm)
+      : _a(parm.a()), _b(parm.b())
+    {}
+
+    /**
+     * Returns a random variate distributed according to the
+     * @c extreme_value_distribution.
+     */
+    template<class URNG>
+    RealType operator()(URNG& urng) const
+    {
+        using std::log;
+        return _a - log(-log(uniform_01<RealType>()(urng))) * _b;
+    }
+
+    /**
+     * Returns a random variate distributed accordint to the extreme
+     * value distribution with parameters specified by @c param.
+     */
+    template<class URNG>
+    RealType operator()(URNG& urng, const param_type& parm) const
+    {
+        return extreme_value_distribution(parm)(urng);
+    }
+
+    /** Returns the "a" parameter of the distribution. */
+    RealType a() const { return _a; }
+    /** Returns the "b" parameter of the distribution. */
+    RealType b() const { return _b; }
+
+    /** 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(_a, _b); }
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        _a = parm.a();
+        _b = parm.b();
+    }
+
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { }
+
+    /** Writes an @c extreme_value_distribution to a @c std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, extreme_value_distribution, wd)
+    {
+        os << wd.param();
+        return os;
+    }
+
+    /** Reads an @c extreme_value_distribution from a @c std::istream. */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, extreme_value_distribution, wd)
+    {
+        param_type parm;
+        if(is >> parm) {
+            wd.param(parm);
+        }
+        return is;
+    }
+
+    /**
+     * Returns true if the two instances of @c extreme_value_distribution will
+     * return identical sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(extreme_value_distribution, lhs, rhs)
+    { return lhs._a == rhs._a && lhs._b == rhs._b; }
+    
+    /**
+     * Returns true if the two instances of @c extreme_value_distribution will
+     * return different sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(extreme_value_distribution)
+
+private:
+    RealType _a;
+    RealType _b;
+};
+
+} // namespace random
+} // namespace boost
+
+#endif // BOOST_RANDOM_EXTREME_VALUE_DISTRIBUTION_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/fisher_f_distribution.hpp

@@ -0,0 +1,183 @@
+/* boost random/fisher_f_distribution.hpp header file
+ *
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_FISHER_F_DISTRIBUTION_HPP
+#define BOOST_RANDOM_FISHER_F_DISTRIBUTION_HPP
+
+#include <iosfwd>
+#include <istream>
+#include <boost/config.hpp>
+#include <boost/limits.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/chi_squared_distribution.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * The Fisher F distribution is a real valued distribution with two
+ * parameters m and n.
+ *
+ * It has \f$\displaystyle p(x) =
+ *   \frac{\Gamma((m+n)/2)}{\Gamma(m/2)\Gamma(n/2)}
+ *   \left(\frac{m}{n}\right)^{m/2}
+ *   x^{(m/2)-1} \left(1+\frac{mx}{n}\right)^{-(m+n)/2}
+ * \f$.
+ */
+template<class RealType = double>
+class fisher_f_distribution {
+public:
+    typedef RealType result_type;
+    typedef RealType input_type;
+
+    class param_type {
+    public:
+        typedef fisher_f_distribution distribution_type;
+
+        /**
+         * Constructs a @c param_type from the "m" and "n" parameters
+         * of the distribution.
+         *
+         * Requires: m > 0 and n > 0
+         */
+        explicit param_type(RealType m_arg = RealType(1.0),
+                            RealType n_arg = RealType(1.0))
+          : _m(m_arg), _n(n_arg)
+        {}
+
+        /** Returns the "m" parameter of the distribtuion. */
+        RealType m() const { return _m; }
+        /** Returns the "n" parameter of the distribution. */
+        RealType n() const { return _n; }
+
+        /** Writes a @c param_type to a @c std::ostream. */
+        BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
+        { os << parm._m << ' ' << parm._n; return os; }
+
+        /** Reads a @c param_type from a @c std::istream. */
+        BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
+        { is >> parm._m >> std::ws >> parm._n; return is; }
+
+        /** Returns true if the two sets of parameters are the same. */
+        BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
+        { return lhs._m == rhs._m && lhs._n == rhs._n; }
+        
+        /** Returns true if the two sets of parameters are the different. */
+        BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+
+    private:
+        RealType _m;
+        RealType _n;
+    };
+
+    /**
+     * Constructs a @c fisher_f_distribution from its "m" and "n" parameters.
+     *
+     * Requires: m > 0 and n > 0
+     */
+    explicit fisher_f_distribution(RealType m_arg = RealType(1.0),
+                                   RealType n_arg = RealType(1.0))
+      : _impl_m(m_arg), _impl_n(n_arg)
+    {}
+    /** Constructs an @c fisher_f_distribution from its parameters. */
+    explicit fisher_f_distribution(const param_type& parm)
+      : _impl_m(parm.m()), _impl_n(parm.n())
+    {}
+
+    /**
+     * Returns a random variate distributed according to the
+     * F distribution.
+     */
+    template<class URNG>
+    RealType operator()(URNG& urng)
+    {
+        return (_impl_m(urng) * n()) / (_impl_n(urng) * m());
+    }
+
+    /**
+     * Returns a random variate distributed according to the
+     * F distribution with parameters specified by @c param.
+     */
+    template<class URNG>
+    RealType operator()(URNG& urng, const param_type& parm) const
+    {
+        return fisher_f_distribution(parm)(urng);
+    }
+
+    /** Returns the "m" parameter of the distribution. */
+    RealType m() const { return _impl_m.n(); }
+    /** Returns the "n" parameter of the distribution. */
+    RealType n() const { return _impl_n.n(); }
+
+    /** Returns the smallest value that the distribution can produce. */
+    RealType min BOOST_PREVENT_MACRO_SUBSTITUTION () const { return 0; }
+    /** 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(m(), n()); }
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        typedef chi_squared_distribution<RealType> impl_type;
+        typename impl_type::param_type m_param(parm.m());
+        _impl_m.param(m_param);
+        typename impl_type::param_type n_param(parm.n());
+        _impl_n.param(n_param);
+    }
+
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { }
+
+    /** Writes an @c fisher_f_distribution to a @c std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, fisher_f_distribution, fd)
+    {
+        os << fd.param();
+        return os;
+    }
+
+    /** Reads an @c fisher_f_distribution from a @c std::istream. */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, fisher_f_distribution, fd)
+    {
+        param_type parm;
+        if(is >> parm) {
+            fd.param(parm);
+        }
+        return is;
+    }
+
+    /**
+     * Returns true if the two instances of @c fisher_f_distribution will
+     * return identical sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(fisher_f_distribution, lhs, rhs)
+    { return lhs._impl_m == rhs._impl_m && lhs._impl_n == rhs._impl_n; }
+    
+    /**
+     * Returns true if the two instances of @c fisher_f_distribution will
+     * return different sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(fisher_f_distribution)
+
+private:
+    chi_squared_distribution<RealType> _impl_m;
+    chi_squared_distribution<RealType> _impl_n;
+};
+
+} // namespace random
+} // namespace boost
+
+#endif // BOOST_RANDOM_EXTREME_VALUE_DISTRIBUTION_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/gamma_distribution.hpp

@@ -0,0 +1,292 @@
+/* boost random/gamma_distribution.hpp header file
+ *
+ * Copyright Jens Maurer 2002
+ * Copyright Steven Watanabe 2010
+ * 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.
+ *
+ * $Id$
+ *
+ */
+
+#ifndef BOOST_RANDOM_GAMMA_DISTRIBUTION_HPP
+#define BOOST_RANDOM_GAMMA_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/exponential_distribution.hpp>
+
+namespace boost {
+namespace random {
+
+// The algorithm is taken from Knuth
+
+/**
+ * The gamma distribution is a continuous distribution with two
+ * parameters alpha and beta.  It produces values > 0.
+ *
+ * It has
+ * \f$\displaystyle p(x) = x^{\alpha-1}\frac{e^{-x/\beta}}{\beta^\alpha\Gamma(\alpha)}\f$.
+ */
+template<class RealType = double>
+class gamma_distribution
+{
+public:
+    typedef RealType input_type;
+    typedef RealType result_type;
+
+    class param_type
+    {
+    public:
+        typedef gamma_distribution distribution_type;
+
+        /**
+         * Constructs a @c param_type object from the "alpha" and "beta"
+         * parameters.
+         *
+         * Requires: alpha > 0 && beta > 0
+         */
+        param_type(const RealType& alpha_arg = RealType(1.0),
+                   const RealType& beta_arg = RealType(1.0))
+          : _alpha(alpha_arg), _beta(beta_arg)
+        {
+        }
+
+        /** Returns the "alpha" parameter of the distribution. */
+        RealType alpha() const { return _alpha; }
+        /** Returns the "beta" parameter of the distribution. */
+        RealType beta() const { return _beta; }
+
+#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
+        /** Writes the parameters to a @c std::ostream. */
+        template<class CharT, class Traits>
+        friend std::basic_ostream<CharT, Traits>&
+        operator<<(std::basic_ostream<CharT, Traits>& os,
+                   const param_type& parm)
+        {
+            os << parm._alpha << ' ' << parm._beta;
+            return os;
+        }
+        
+        /** Reads the parameters from a @c std::istream. */
+        template<class CharT, class Traits>
+        friend std::basic_istream<CharT, Traits>&
+        operator>>(std::basic_istream<CharT, Traits>& is, param_type& parm)
+        {
+            is >> parm._alpha >> std::ws >> parm._beta;
+            return is;
+        }
+#endif
+
+        /** Returns true if the two sets of parameters are the same. */
+        friend bool operator==(const param_type& lhs, const param_type& rhs)
+        {
+            return lhs._alpha == rhs._alpha && lhs._beta == rhs._beta;
+        }
+        /** Returns true if the two sets fo parameters are different. */
+        friend bool operator!=(const param_type& lhs, const param_type& rhs)
+        {
+            return !(lhs == rhs);
+        }
+    private:
+        RealType _alpha;
+        RealType _beta;
+    };
+
+#ifndef BOOST_NO_LIMITS_COMPILE_TIME_CONSTANTS
+    BOOST_STATIC_ASSERT(!std::numeric_limits<RealType>::is_integer);
+#endif
+
+    /**
+     * Creates a new gamma_distribution with parameters "alpha" and "beta".
+     *
+     * Requires: alpha > 0 && beta > 0
+     */
+    explicit gamma_distribution(const result_type& alpha_arg = result_type(1.0),
+                                const result_type& beta_arg = result_type(1.0))
+      : _exp(result_type(1)), _alpha(alpha_arg), _beta(beta_arg)
+    {
+        BOOST_ASSERT(_alpha > result_type(0));
+        BOOST_ASSERT(_beta > result_type(0));
+        init();
+    }
+
+    /** Constructs a @c gamma_distribution from its parameters. */
+    explicit gamma_distribution(const param_type& parm)
+      : _exp(result_type(1)), _alpha(parm.alpha()), _beta(parm.beta())
+    {
+        init();
+    }
+
+    // compiler-generated copy ctor and assignment operator are fine
+
+    /** Returns the "alpha" paramter of the distribution. */
+    RealType alpha() const { return _alpha; }
+    /** Returns the "beta" parameter of the distribution. */
+    RealType beta() const { return _beta; }
+    /** Returns the smallest value that the distribution can produce. */
+    RealType min BOOST_PREVENT_MACRO_SUBSTITUTION () const { return 0; }
+    /* 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(_alpha, _beta); }
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        _alpha = parm.alpha();
+        _beta = parm.beta();
+        init();
+    }
+    
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { _exp.reset(); }
+
+    /**
+     * Returns a random variate distributed according to
+     * the gamma distribution.
+     */
+    template<class Engine>
+    result_type operator()(Engine& eng)
+    {
+#ifndef BOOST_NO_STDC_NAMESPACE
+        // allow for Koenig lookup
+        using std::tan; using std::sqrt; using std::exp; using std::log;
+        using std::pow;
+#endif
+        if(_alpha == result_type(1)) {
+            return _exp(eng) * _beta;
+        } else if(_alpha > result_type(1)) {
+            // Can we have a boost::mathconst please?
+            const result_type pi = result_type(3.14159265358979323846);
+            for(;;) {
+                result_type y = tan(pi * uniform_01<RealType>()(eng));
+                result_type x = sqrt(result_type(2)*_alpha-result_type(1))*y
+                    + _alpha-result_type(1);
+                if(x <= result_type(0))
+                    continue;
+                if(uniform_01<RealType>()(eng) >
+                    (result_type(1)+y*y) * exp((_alpha-result_type(1))
+                                               *log(x/(_alpha-result_type(1)))
+                                               - sqrt(result_type(2)*_alpha
+                                                      -result_type(1))*y))
+                    continue;
+                return x * _beta;
+            }
+        } else /* alpha < 1.0 */ {
+            for(;;) {
+                result_type u = uniform_01<RealType>()(eng);
+                result_type y = _exp(eng);
+                result_type x, q;
+                if(u < _p) {
+                    x = exp(-y/_alpha);
+                    q = _p*exp(-x);
+                } else {
+                    x = result_type(1)+y;
+                    q = _p + (result_type(1)-_p) * pow(x,_alpha-result_type(1));
+                }
+                if(u >= q)
+                    continue;
+                return x * _beta;
+            }
+        }
+    }
+
+    template<class URNG>
+    RealType operator()(URNG& urng, const param_type& parm) const
+    {
+        return gamma_distribution(parm)(urng);
+    }
+
+#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
+    /** Writes a @c gamma_distribution to a @c std::ostream. */
+    template<class CharT, class Traits>
+    friend std::basic_ostream<CharT,Traits>&
+    operator<<(std::basic_ostream<CharT,Traits>& os,
+               const gamma_distribution& gd)
+    {
+        os << gd.param();
+        return os;
+    }
+    
+    /** Reads a @c gamma_distribution from a @c std::istream. */
+    template<class CharT, class Traits>
+    friend std::basic_istream<CharT,Traits>&
+    operator>>(std::basic_istream<CharT,Traits>& is, gamma_distribution& gd)
+    {
+        gd.read(is);
+        return is;
+    }
+#endif
+
+    /**
+     * Returns true if the two distributions will produce identical
+     * sequences of random variates given equal generators.
+     */
+    friend bool operator==(const gamma_distribution& lhs,
+                           const gamma_distribution& rhs)
+    {
+        return lhs._alpha == rhs._alpha
+            && lhs._beta == rhs._beta
+            && lhs._exp == rhs._exp;
+    }
+
+    /**
+     * Returns true if the two distributions can produce different
+     * sequences of random variates, given equal generators.
+     */
+    friend bool operator!=(const gamma_distribution& lhs,
+                           const gamma_distribution& rhs)
+    {
+        return !(lhs == rhs);
+    }
+
+private:
+    /// \cond hide_private_members
+
+    template<class CharT, class Traits>
+    void read(std::basic_istream<CharT, Traits>& is)
+    {
+        param_type parm;
+        if(is >> parm) {
+            param(parm);
+        }
+    }
+
+    void init()
+    {
+#ifndef BOOST_NO_STDC_NAMESPACE
+        // allow for Koenig lookup
+        using std::exp;
+#endif
+        _p = exp(result_type(1)) / (_alpha + exp(result_type(1)));
+    }
+    /// \endcond
+
+    exponential_distribution<RealType> _exp;
+    result_type _alpha;
+    result_type _beta;
+    // some data precomputed from the parameters
+    result_type _p;
+};
+
+
+} // namespace random
+
+using random::gamma_distribution;
+
+} // namespace boost
+
+#endif // BOOST_RANDOM_GAMMA_DISTRIBUTION_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/generate_canonical.hpp

@@ -0,0 +1,96 @@
+/* boost random/generate_canonical.hpp header file
+ *
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ *
+ */
+
+#ifndef BOOST_RANDOM_GENERATE_CANONICAL_HPP
+#define BOOST_RANDOM_GENERATE_CANONICAL_HPP
+
+#include <algorithm>
+#include <boost/assert.hpp>
+#include <boost/config/no_tr1/cmath.hpp>
+#include <boost/limits.hpp>
+#include <boost/type_traits/is_integral.hpp>
+#include <boost/mpl/bool.hpp>
+#include <boost/random/detail/signed_unsigned_tools.hpp>
+#include <boost/random/detail/generator_bits.hpp>
+
+namespace boost {
+namespace random {
+
+namespace detail {
+
+template<class RealType, std::size_t bits, class URNG>
+RealType generate_canonical_impl(URNG& g, boost::mpl::true_ /*is_integral*/)
+{
+    using std::pow;
+    typedef typename URNG::result_type base_result;
+    std::size_t digits = std::numeric_limits<RealType>::digits;
+    RealType R = RealType((g.max)()) - RealType((g.min)()) + 1;
+    RealType mult = R;
+    RealType limit =
+        pow(RealType(2),
+            RealType((std::min)(static_cast<std::size_t>(bits), digits)));
+    RealType S = RealType(detail::subtract<base_result>()(g(), (g.min)()));
+    while(mult < limit) {
+        RealType inc = RealType(detail::subtract<base_result>()(g(), (g.min)()));
+        S += inc * mult;
+        mult *= R;
+    }
+    return S / mult;
+}
+
+template<class RealType, std::size_t bits, class URNG>
+RealType generate_canonical_impl(URNG& g, boost::mpl::false_ /*is_integral*/)
+{
+    using std::pow;
+    using std::floor;
+    BOOST_ASSERT((g.min)() == 0);
+    BOOST_ASSERT((g.max)() == 1);
+    std::size_t digits = std::numeric_limits<RealType>::digits;
+    std::size_t engine_bits = detail::generator_bits<URNG>::value();
+    std::size_t b = (std::min)(bits, digits);
+    RealType R = pow(RealType(2), RealType(engine_bits));
+    RealType mult = R;
+    RealType limit = pow(RealType(2), RealType(b));
+    RealType S = RealType(g() - (g.min)());
+    while(mult < limit) {
+        RealType inc(floor((RealType(g()) - RealType((g.min)())) * R));
+        S += inc * mult;
+        mult *= R;
+    }
+    return S / mult;
+}
+
+}
+
+/**
+ * Returns a value uniformly distributed in the range [0, 1)
+ * with at least @c bits random bits.
+ */
+template<class RealType, std::size_t bits, class URNG>
+RealType generate_canonical(URNG& g)
+{
+    RealType result = detail::generate_canonical_impl<RealType, bits>(
+        g, boost::random::traits::is_integral<typename URNG::result_type>());
+    BOOST_ASSERT(result >= 0);
+    BOOST_ASSERT(result <= 1);
+    if(result == 1) {
+        result -= std::numeric_limits<RealType>::epsilon() / 2;
+        BOOST_ASSERT(result != 1);
+    }
+    return result;
+}
+
+} // namespace random
+} // namespace boost
+
+#endif // BOOST_RANDOM_GENERATE_CANONICAL_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/geometric_distribution.hpp

@@ -0,0 +1,267 @@
+/* boost random/geometric_distribution.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2001-02-18  moved to individual header files
+ */
+
+#ifndef BOOST_RANDOM_GEOMETRIC_DISTRIBUTION_HPP
+#define BOOST_RANDOM_GEOMETRIC_DISTRIBUTION_HPP
+
+#include <boost/config/no_tr1/cmath.hpp>          // std::log
+#include <iosfwd>
+#include <ios>
+#include <boost/assert.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/uniform_01.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * An instantiation of the class template @c geometric_distribution models
+ * a \random_distribution.  The distribution produces positive
+ * integers which are the number of bernoulli trials
+ * with probability @c p required to get one that fails.
+ *
+ * For the geometric distribution, \f$p(i) = p(1-p)^{i}\f$.
+ *
+ * @xmlwarning
+ * This distribution has been updated to match the C++ standard.
+ * Its behavior has changed from the original
+ * boost::geometric_distribution.  A backwards compatible
+ * wrapper is provided in namespace boost.
+ * @endxmlwarning
+ */
+template<class IntType = int, class RealType = double>
+class geometric_distribution
+{
+public:
+    typedef RealType input_type;
+    typedef IntType result_type;
+
+    class param_type
+    {
+    public:
+
+        typedef geometric_distribution distribution_type;
+
+        /** Constructs the parameters with p. */
+        explicit param_type(RealType p_arg = RealType(0.5))
+          : _p(p_arg)
+        {
+            BOOST_ASSERT(RealType(0) < _p && _p < RealType(1));
+        }
+
+        /** Returns the p parameter of the distribution. */
+        RealType p() const { return _p; }
+
+        /** Writes the parameters to a std::ostream. */
+        BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
+        {
+            os << parm._p;
+            return os;
+        }
+
+        /** Reads the parameters from a std::istream. */
+        BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
+        {
+            double p_in;
+            if(is >> p_in) {
+                if(p_in > RealType(0) && p_in < RealType(1)) {
+                    parm._p = p_in;
+                } else {
+                    is.setstate(std::ios_base::failbit);
+                }
+            }
+            return is;
+        }
+
+        /** Returns true if the two sets of parameters are equal. */
+        BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
+        { return lhs._p == rhs._p; }
+
+        /** Returns true if the two sets of parameters are different. */
+        BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+
+
+    private:
+        RealType _p;
+    };
+
+    /**
+     * Contructs a new geometric_distribution with the paramter @c p.
+     *
+     * Requires: 0 < p < 1
+     */
+    explicit geometric_distribution(const RealType& p_arg = RealType(0.5))
+      : _p(p_arg)
+    {
+        BOOST_ASSERT(RealType(0) < _p && _p < RealType(1));
+        init();
+    }
+
+    /** Constructs a new geometric_distribution from its parameters. */
+    explicit geometric_distribution(const param_type& parm)
+      : _p(parm.p())
+    {
+        init();
+    }
+
+    // compiler-generated copy ctor and assignment operator are fine
+
+    /** Returns: the distribution parameter @c p  */
+    RealType p() const { return _p; }
+
+    /** Returns the smallest value that the distribution can produce. */
+    IntType min BOOST_PREVENT_MACRO_SUBSTITUTION () const { return IntType(0); }
+
+    /** Returns the largest value that the distribution can produce. */
+    IntType max BOOST_PREVENT_MACRO_SUBSTITUTION () const
+    { return (std::numeric_limits<IntType>::max)(); }
+
+    /** Returns the parameters of the distribution. */
+    param_type param() const { return param_type(_p); }
+
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        _p = parm.p();
+        init();
+    }
+  
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { }
+
+    /**
+     * Returns a random variate distributed according to the
+     * geometric_distribution.
+     */
+    template<class Engine>
+    result_type operator()(Engine& eng) const
+    {
+        using std::log;
+        using std::floor;
+        RealType x = RealType(1) - boost::uniform_01<RealType>()(eng);
+        return IntType(floor(log(x) / _log_1mp));
+    }
+
+    /**
+     * Returns a random variate distributed according to the
+     * geometric distribution with parameters specified by param.
+     */
+    template<class Engine>
+    result_type operator()(Engine& eng, const param_type& parm) const
+    { return geometric_distribution(parm)(eng); }
+
+    /** Writes the distribution to a @c std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, geometric_distribution, gd)
+    {
+        os << gd._p;
+        return os;
+    }
+
+    /** Reads the distribution from a @c std::istream. */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, geometric_distribution, gd)
+    {
+        param_type parm;
+        if(is >> parm) {
+            gd.param(parm);
+        }
+        return is;
+    }
+
+    /**
+     * Returns true if the two distributions will produce identical
+     * sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(geometric_distribution, lhs, rhs)
+    { return lhs._p == rhs._p; }
+
+    /**
+     * Returns true if the two distributions may produce different
+     * sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(geometric_distribution)
+
+private:
+
+    /// \cond show_private
+
+    void init()
+    {
+        using std::log;
+        _log_1mp = log(1 - _p);
+    }
+
+    RealType _p;
+    RealType _log_1mp;
+
+    /// \endcond
+};
+
+} // namespace random
+
+/// \cond show_deprecated
+
+/**
+ * Provided for backwards compatibility.  This class is
+ * deprecated.  It provides the old behavior of geometric_distribution
+ * with \f$p(i) = (1-p) p^{i-1}\f$.
+ */
+template<class IntType = int, class RealType = double>
+class geometric_distribution
+{
+public:
+    typedef RealType input_type;
+    typedef IntType result_type;
+
+    explicit geometric_distribution(RealType p_arg = RealType(0.5))
+      : _impl(1 - p_arg) {}
+
+    RealType p() const { return 1 - _impl.p(); }
+
+    void reset() {}
+
+    template<class Engine>
+    IntType operator()(Engine& eng) const { return _impl(eng) + IntType(1); }
+
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, geometric_distribution, gd)
+    {
+        os << gd.p();
+        return os;
+    }
+
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, geometric_distribution, gd)
+    {
+        RealType val;
+        if(is >> val) {
+            typename impl_type::param_type impl_param(1 - val);
+            gd._impl.param(impl_param);
+        }
+        return is;
+    }
+
+private:
+    typedef random::geometric_distribution<IntType, RealType> impl_type;
+    impl_type _impl;
+};
+
+/// \endcond
+
+} // namespace boost
+
+#endif // BOOST_RANDOM_GEOMETRIC_DISTRIBUTION_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/hyperexponential_distribution.hpp

@@ -0,0 +1,883 @@
+/* boost random/hyperexponential_distribution.hpp header file
+ *
+ * Copyright Marco Guazzone 2014
+ * 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.
+ *
+ * Much of the code here taken by boost::math::hyperexponential_distribution.
+ * To this end, we would like to thank Paul Bristow and John Maddock for their
+ * valuable feedback.
+ *
+ * \author Marco Guazzone (marco.guazzone@gmail.com)
+ */
+
+#ifndef BOOST_RANDOM_HYPEREXPONENTIAL_DISTRIBUTION_HPP
+#define BOOST_RANDOM_HYPEREXPONENTIAL_DISTRIBUTION_HPP
+
+
+#include <boost/config.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/detail/vector_io.hpp>
+#include <boost/random/discrete_distribution.hpp>
+#include <boost/random/exponential_distribution.hpp>
+#include <boost/range/begin.hpp>
+#include <boost/range/end.hpp>
+#include <boost/range/size.hpp>
+#include <boost/type_traits/has_pre_increment.hpp>
+#include <cassert>
+#include <cmath>
+#include <cstddef>
+#include <iterator>
+#ifndef BOOST_NO_CXX11_HDR_INITIALIZER_LIST
+# include <initializer_list>
+#endif // BOOST_NO_CXX11_HDR_INITIALIZER_LIST
+#include <iostream>
+#include <limits>
+#include <numeric>
+#include <vector>
+
+
+namespace boost { namespace random {
+
+namespace hyperexp_detail {
+
+template <typename T>
+std::vector<T>& normalize(std::vector<T>& v)
+{
+    if (v.size() == 0)
+    {
+        return v;
+    }
+
+    const T sum = std::accumulate(v.begin(), v.end(), static_cast<T>(0));
+    T final_sum = 0;
+
+    const typename std::vector<T>::iterator end = --v.end();
+    for (typename std::vector<T>::iterator it = v.begin();
+         it != end;
+         ++it)
+    {
+        *it /= sum;
+        final_sum += *it;
+    }
+    *end = 1-final_sum; // avoids round off errors thus ensuring the probabilities really sum to 1
+
+    return v;
+}
+
+template <typename RealT>
+bool check_probabilities(std::vector<RealT> const& probabilities)
+{
+    const std::size_t n = probabilities.size();
+    RealT sum = 0;
+    for (std::size_t i = 0; i < n; ++i)
+    {
+        if (probabilities[i] < 0
+            || probabilities[i] > 1
+            || !(boost::math::isfinite)(probabilities[i]))
+        {
+            return false;
+        }
+        sum += probabilities[i];
+    }
+
+    //NOTE: the check below seems to fail on some architectures.
+    //      So we commented it.
+    //// - We try to keep phase probabilities correctly normalized in the distribution constructors
+    //// - However in practice we have to allow for a very slight divergence from a sum of exactly 1:
+    ////if (std::abs(sum-1) > (std::numeric_limits<RealT>::epsilon()*2))
+    //// This is from Knuth "The Art of Computer Programming: Vol.2, 3rd Ed", and can be used to
+    //// check is two numbers are approximately equal
+    //const RealT one = 1;
+    //const RealT tol = std::numeric_limits<RealT>::epsilon()*2.0;
+    //if (std::abs(sum-one) > (std::max(std::abs(sum), std::abs(one))*tol))
+    //{
+    //    return false;
+    //}
+
+    return true;
+}
+
+template <typename RealT>
+bool check_rates(std::vector<RealT> const& rates)
+{
+    const std::size_t n = rates.size();
+    for (std::size_t i = 0; i < n; ++i)
+    {
+        if (rates[i] <= 0
+            || !(boost::math::isfinite)(rates[i]))
+        {
+            return false;
+        }
+    }
+    return true;
+}
+
+template <typename RealT>
+bool check_params(std::vector<RealT> const& probabilities, std::vector<RealT> const& rates)
+{
+    if (probabilities.size() != rates.size())
+    {
+        return false;
+    }
+
+    return check_probabilities(probabilities)
+           && check_rates(rates);
+}
+
+} // Namespace hyperexp_detail
+
+
+/**
+ * The hyperexponential distribution is a real-valued continuous distribution
+ * with two parameters, the <em>phase probability vector</em> \c probs and the
+ * <em>rate vector</em> \c rates.
+ *
+ * A \f$k\f$-phase hyperexponential distribution is a mixture of \f$k\f$
+ * exponential distributions.
+ * For this reason, it is also referred to as <em>mixed exponential
+ * distribution</em> or <em>parallel \f$k\f$-phase exponential
+ * distribution</em>.
+ *
+ * A \f$k\f$-phase hyperexponential distribution is characterized by two
+ * parameters, namely a <em>phase probability vector</em> \f$\mathbf{\alpha}=(\alpha_1,\ldots,\alpha_k)\f$ and a <em>rate vector</em> \f$\mathbf{\lambda}=(\lambda_1,\ldots,\lambda_k)\f$.
+ *
+ * A \f$k\f$-phase hyperexponential distribution is frequently used in
+ * <em>queueing theory</em> to model the distribution of the superposition of
+ * \f$k\f$ independent events, like, for instance, the  service time distribution
+ * of a queueing station with \f$k\f$ servers in parallel where the \f$i\f$-th
+ * server is chosen with probability \f$\alpha_i\f$ and its service time
+ * distribution is an exponential distribution with rate \f$\lambda_i\f$
+ * (Allen,1990; Papadopolous et al.,1993; Trivedi,2002).
+ *
+ * For instance, CPUs service-time distribution in a computing system has often
+ * been observed to possess such a distribution (Rosin,1965).
+ * Also, the arrival of different types of customer to a single queueing station
+ * is often modeled as a hyperexponential distribution (Papadopolous et al.,1993).
+ * Similarly, if a product manufactured in several parallel assemply lines and
+ * the outputs are merged, the failure density of the overall product is likely
+ * to be hyperexponential (Trivedi,2002).
+ *
+ * Finally, since the hyperexponential distribution exhibits a high Coefficient
+ * of Variation (CoV), that is a CoV > 1, it is especially suited to fit
+ * empirical data with large CoV (Feitelson,2014; Wolski et al.,2013) and to
+ * approximate <em>long-tail probability distributions</em> (Feldmann et al.,1998).
+ *
+ * See (Boost,2014) for more information and examples.
+ *
+ * A \f$k\f$-phase hyperexponential distribution has a probability density
+ * function
+ * \f[
+ *  f(x) = \sum_{i=1}^k \alpha_i \lambda_i e^{-x\lambda_i}
+ * \f]
+ * where:
+ * - \f$k\f$ is the <em>number of phases</em> and also the size of the input
+ *   vector parameters,
+ * - \f$\mathbf{\alpha}=(\alpha_1,\ldots,\alpha_k)\f$ is the <em>phase probability
+ *   vector</em> parameter, and
+ * - \f$\mathbf{\lambda}=(\lambda_1,\ldots,\lambda_k)\f$ is the <em>rate vector</em>
+ *   parameter.
+ * .
+ *
+ * Given a \f$k\f$-phase hyperexponential distribution with phase probability
+ * vector \f$\mathbf{\alpha}\f$ and rate vector \f$\mathbf{\lambda}\f$, the
+ * random variate generation algorithm consists of the following steps (Tyszer,1999):
+ * -# Generate a random variable \f$U\f$ uniformly distribution on the interval \f$(0,1)\f$.
+ * -# Use \f$U\f$ to select the appropriate \f$\lambda_i\f$ (e.g., the
+ *  <em>alias method</em> can possibly be used for this step).
+ * -# Generate an exponentially distributed random variable \f$X\f$ with rate parameter \f$\lambda_i\f$.
+ * -# Return \f$X\f$.
+ * .
+ *
+ * References:
+ * -# A.O. Allen, <em>Probability, Statistics, and Queuing Theory with Computer Science Applications, Second Edition</em>, Academic Press, 1990.
+ * -# Boost C++ Libraries, <em>Boost.Math / Statistical Distributions: Hyperexponential Distribution</em>, Online: http://www.boost.org/doc/libs/release/libs/math/doc/html/dist.html , 2014.
+ * -# D.G. Feitelson, <em>Workload Modeling for Computer Systems Performance Evaluation</em>, Cambridge University Press, 2014
+ * -# A. Feldmann and W. Whitt, <em>Fitting mixtures of exponentials to long-tail distributions to analyze network performance models</em>, Performance Evaluation 31(3-4):245, doi:10.1016/S0166-5316(97)00003-5, 1998.
+ * -# H.T. Papadopolous, C. Heavey and J. Browne, <em>Queueing Theory in Manufacturing Systems Analysis and Design</em>, Chapman & Hall/CRC, 1993, p. 35.
+ * -# R.F. Rosin, <em>Determining a computing center environment</em>, Communications of the ACM 8(7):463-468, 1965.
+ * -# K.S. Trivedi, <em>Probability and Statistics with Reliability, Queueing, and Computer Science Applications</em>, John Wiley & Sons, Inc., 2002.
+ * -# J. Tyszer, <em>Object-Oriented Computer Simulation of Discrete-Event Systems</em>, Springer, 1999.
+ * -# Wikipedia, <em>Hyperexponential Distribution</em>, Online: http://en.wikipedia.org/wiki/Hyperexponential_distribution , 2014.
+ * -# Wolfram Mathematica, <em>Hyperexponential Distribution</em>, Online: http://reference.wolfram.com/language/ref/HyperexponentialDistribution.html , 2014.
+ * .
+ *
+ * \author Marco Guazzone (marco.guazzone@gmail.com)
+ */
+template<class RealT = double>
+class hyperexponential_distribution
+{
+    public: typedef RealT result_type;
+    public: typedef RealT input_type;
+
+
+    /**
+     * The parameters of a hyperexponential distribution.
+     *
+     * Stores the <em>phase probability vector</em> and the <em>rate vector</em>
+     * of the hyperexponential distribution.
+     *
+     * \author Marco Guazzone (marco.guazzone@gmail.com)
+     */
+    public: class param_type
+    {
+        public: typedef hyperexponential_distribution distribution_type;
+
+        /**
+         * Constructs a \c param_type with the default parameters
+         * of the distribution.
+         */
+        public: param_type()
+        : probs_(1, 1),
+          rates_(1, 1)
+        {
+        }
+
+        /**
+         * Constructs a \c param_type from the <em>phase probability vector</em>
+         * and <em>rate vector</em> parameters of the distribution.
+         *
+         * The <em>phase probability vector</em> parameter is given by the range
+         * defined by [\a prob_first, \a prob_last) iterator pair, and the
+         * <em>rate vector</em> parameter is given by the range defined by
+         * [\a rate_first, \a rate_last) iterator pair.
+         *
+         * \tparam ProbIterT Must meet the requirements of \c InputIterator concept (ISO,2014,sec. 24.2.3 [input.iterators]).
+         * \tparam RateIterT Must meet the requirements of \c InputIterator concept (ISO,2014,sec. 24.2.3 [input.iterators]).
+         *
+         * \param prob_first The iterator to the beginning of the range of non-negative real elements representing the phase probabilities; if elements don't sum to 1, they are normalized.
+         * \param prob_last The iterator to the ending of the range of non-negative real elements representing the phase probabilities; if elements don't sum to 1, they are normalized.
+         * \param rate_first The iterator to the beginning of the range of non-negative real elements representing the rates.
+         * \param rate_last The iterator to the ending of the range of non-negative real elements representing the rates.
+         *
+         * References:
+         * -# ISO, <em>ISO/IEC 14882-2014: Information technology - Programming languages - C++</em>, 2014
+         * .
+         */
+        public: template <typename ProbIterT, typename RateIterT>
+                param_type(ProbIterT prob_first, ProbIterT prob_last,
+                           RateIterT rate_first, RateIterT rate_last)
+        : probs_(prob_first, prob_last),
+          rates_(rate_first, rate_last)
+        {
+            hyperexp_detail::normalize(probs_);
+
+            assert( hyperexp_detail::check_params(probs_, rates_) );
+        }
+
+        /**
+         * Constructs a \c param_type from the <em>phase probability vector</em>
+         * and <em>rate vector</em> parameters of the distribution.
+         *
+         * The <em>phase probability vector</em> parameter is given by the range
+         * defined by \a prob_range, and the <em>rate vector</em> parameter is
+         * given by the range defined by \a rate_range.
+         *
+         * \tparam ProbRangeT Must meet the requirements of <a href="boost:/libs/range/doc/html/range/concepts.html">Range</a> concept.
+         * \tparam RateRangeT Must meet the requirements of <a href="boost:/libs/range/doc/html/range/concepts.html">Range</a> concept.
+         *
+         * \param prob_range The range of non-negative real elements representing the phase probabilities; if elements don't sum to 1, they are normalized.
+         * \param rate_range The range of positive real elements representing the rates.
+         *
+         * \note
+         *  The final \c disable_if parameter is an implementation detail that
+         *  differentiates between this two argument constructor and the
+         *  iterator-based two argument constructor described below.
+         */
+        //  We SFINAE this out of existance if either argument type is
+        //  incrementable as in that case the type is probably an iterator:
+        public: template <typename ProbRangeT, typename RateRangeT>
+                param_type(ProbRangeT const& prob_range,
+                           RateRangeT const& rate_range,
+                           typename boost::disable_if_c<boost::has_pre_increment<ProbRangeT>::value || boost::has_pre_increment<RateRangeT>::value>::type* = 0)
+        : probs_(boost::begin(prob_range), boost::end(prob_range)),
+          rates_(boost::begin(rate_range), boost::end(rate_range))
+        {
+            hyperexp_detail::normalize(probs_);
+
+            assert( hyperexp_detail::check_params(probs_, rates_) );
+        }
+
+        /**
+         * Constructs a \c param_type from the <em>rate vector</em> parameter of
+         * the distribution and with equal phase probabilities.
+         *
+         * The <em>rate vector</em> parameter is given by the range defined by
+         * [\a rate_first, \a rate_last) iterator pair, and the <em>phase
+         * probability vector</em> parameter is set to the equal phase
+         * probabilities (i.e., to a vector of the same length \f$k\f$ of the
+         * <em>rate vector</em> and with each element set to \f$1.0/k\f$).
+         *
+         * \tparam RateIterT Must meet the requirements of \c InputIterator concept (ISO,2014,sec. 24.2.3 [input.iterators]).
+         * \tparam RateIterT2 Must meet the requirements of \c InputIterator concept (ISO,2014,sec. 24.2.3 [input.iterators]).
+         *
+         * \param rate_first The iterator to the beginning of the range of non-negative real elements representing the rates.
+         * \param rate_last The iterator to the ending of the range of non-negative real elements representing the rates.
+         *
+         * \note
+         *  The final \c disable_if parameter is an implementation detail that
+         *  differentiates between this two argument constructor and the
+         *  range-based two argument constructor described above.
+         *
+         * References:
+         * -# ISO, <em>ISO/IEC 14882-2014: Information technology - Programming languages - C++</em>, 2014
+         * .
+         */
+        //  We SFINAE this out of existance if the argument type is
+        //  incrementable as in that case the type is probably an iterator.
+        public: template <typename RateIterT>
+                param_type(RateIterT rate_first, 
+                           RateIterT rate_last,  
+                           typename boost::enable_if_c<boost::has_pre_increment<RateIterT>::value>::type* = 0)
+        : probs_(std::distance(rate_first, rate_last), 1), // will be normalized below
+          rates_(rate_first, rate_last)
+        {
+            assert(probs_.size() == rates_.size());
+        }
+
+        /**
+         * Constructs a @c param_type from the "rates" parameters
+         * of the distribution and with equal phase probabilities.
+         *
+         * The <em>rate vector</em> parameter is given by the range defined by
+         * \a rate_range, and the <em>phase probability vector</em> parameter is
+         * set to the equal phase probabilities (i.e., to a vector of the same
+         * length \f$k\f$ of the <em>rate vector</em> and with each element set
+         * to \f$1.0/k\f$).
+         *
+         * \tparam RateRangeT Must meet the requirements of <a href="boost:/libs/range/doc/html/range/concepts.html">Range</a> concept.
+         *
+         * \param rate_range The range of positive real elements representing the rates.
+         */
+        public: template <typename RateRangeT>
+                param_type(RateRangeT const& rate_range)
+        : probs_(boost::size(rate_range), 1), // Will be normalized below
+          rates_(boost::begin(rate_range), boost::end(rate_range))
+        {
+            hyperexp_detail::normalize(probs_);
+
+            assert( hyperexp_detail::check_params(probs_, rates_) );
+        }
+
+#ifndef BOOST_NO_CXX11_HDR_INITIALIZER_LIST
+        /**
+         * Constructs a \c param_type from the <em>phase probability vector</em>
+         * and <em>rate vector</em> parameters of the distribution.
+         *
+         * The <em>phase probability vector</em> parameter is given by the
+         * <em>brace-init-list</em> (ISO,2014,sec. 8.5.4 [dcl.init.list])
+         * defined by \a l1, and the <em>rate vector</em> parameter is given by the
+         * <em>brace-init-list</em> (ISO,2014,sec. 8.5.4 [dcl.init.list])
+         * defined by \a l2.
+         *
+         * \param l1 The initializer list for inizializing the phase probability vector.
+         * \param l2 The initializer list for inizializing the rate vector.
+         *
+         * References:
+         * -# ISO, <em>ISO/IEC 14882-2014: Information technology - Programming languages - C++</em>, 2014
+         * .
+         */
+        public: param_type(std::initializer_list<RealT> l1, std::initializer_list<RealT> l2)
+        : probs_(l1.begin(), l1.end()),
+          rates_(l2.begin(), l2.end())
+        {
+            hyperexp_detail::normalize(probs_);
+
+            assert( hyperexp_detail::check_params(probs_, rates_) );
+        }
+
+        /**
+         * Constructs a \c param_type from the <em>rate vector</em> parameter
+         * of the distribution and with equal phase probabilities.
+         *
+         * The <em>rate vector</em> parameter is given by the
+         * <em>brace-init-list</em> (ISO,2014,sec. 8.5.4 [dcl.init.list])
+         * defined by \a l1, and the <em>phase probability vector</em> parameter is
+         * set to the equal phase probabilities (i.e., to a vector of the same
+         * length \f$k\f$ of the <em>rate vector</em> and with each element set
+         * to \f$1.0/k\f$).
+         *
+         * \param l1 The initializer list for inizializing the rate vector.
+         *
+         * References:
+         * -# ISO, <em>ISO/IEC 14882-2014: Information technology - Programming languages - C++</em>, 2014
+         * .
+         */
+        public: param_type(std::initializer_list<RealT> l1)
+        : probs_(std::distance(l1.begin(), l1.end()), 1), // Will be normalized below
+          rates_(l1.begin(), l1.end())
+        {
+            hyperexp_detail::normalize(probs_);
+
+            assert( hyperexp_detail::check_params(probs_, rates_) );
+        }
+#endif // BOOST_NO_CXX11_HDR_INITIALIZER_LIST
+
+        /**
+         * Gets the <em>phase probability vector</em> parameter of the distribtuion.
+         *
+         * \return The <em>phase probability vector</em> parameter of the distribution.
+         *
+         * \note
+         *  The returned probabilities are the normalized version of the ones
+         *  passed at construction time.
+         */
+        public: std::vector<RealT> probabilities() const
+        {
+            return probs_;
+        }
+
+        /**
+         * Gets the <em>rate vector</em> parameter of the distribtuion.
+         *
+         * \return The <em>rate vector</em> parameter of the distribution.
+         */
+        public: std::vector<RealT> rates() const
+        {
+            return rates_;
+        }
+
+        /** Writes a \c param_type to a \c std::ostream. */
+        public: BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, param)
+        {
+            detail::print_vector(os, param.probs_);
+            os << ' ';
+            detail::print_vector(os, param.rates_);
+
+            return os;
+        }
+
+        /** Reads a \c param_type from a \c std::istream. */
+        public: BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, param)
+        {
+            // NOTE: if \c std::ios_base::exceptions is set, the code below may
+            //       throw in case of a I/O failure.
+            //       To prevent leaving the state of \c param inconsistent:
+            //       - if an exception is thrown, the state of \c param is left
+            //         unchanged (i.e., is the same as the one at the beginning
+            //         of the function's execution), and
+            //       - the state of \c param only after reading the whole input.
+
+            std::vector<RealT> probs;
+            std::vector<RealT> rates;
+
+            // Reads probability and rate vectors
+            detail::read_vector(is, probs);
+            if (!is)
+            {
+                return is;
+            }
+            is >> std::ws;
+            detail::read_vector(is, rates);
+            if (!is)
+            {
+                return is;
+            }
+
+            // Update the state of the param_type object
+            if (probs.size() > 0)
+            {
+                param.probs_.swap(probs);
+                probs.clear();
+            }
+            if (rates.size() > 0)
+            {
+                param.rates_.swap(rates);
+                rates.clear();
+            }
+
+            bool fail = false;
+
+            // Adjust vector sizes (if needed)
+            if (param.probs_.size() != param.rates_.size()
+                || param.probs_.size() == 0)
+            {
+                fail = true;
+
+                const std::size_t np = param.probs_.size();
+                const std::size_t nr = param.rates_.size();
+
+                if (np > nr)
+                {
+                    param.rates_.resize(np, 1);
+                }
+                else if (nr > np)
+                {
+                    param.probs_.resize(nr, 1);
+                }
+                else
+                {
+                    param.probs_.resize(1, 1);
+                    param.rates_.resize(1, 1);
+                }
+            }
+
+            // Normalize probabilities
+            // NOTE: this cannot be done earlier since the probability vector
+            //       can be changed due to size conformance
+            hyperexp_detail::normalize(param.probs_);
+
+            // Set the error state in the underlying stream in case of invalid input
+            if (fail)
+            {
+                // This throws an exception if ios_base::exception(failbit) is enabled
+                is.setstate(std::ios_base::failbit);
+            }
+
+            //post: vector size conformance
+            assert(param.probs_.size() == param.rates_.size());
+
+            return is;
+        }
+
+        /** Returns true if the two sets of parameters are the same. */
+        public: BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
+        {
+            return lhs.probs_ == rhs.probs_
+                   && lhs.rates_ == rhs.rates_;
+        }
+        
+        /** Returns true if the two sets of parameters are the different. */
+        public: BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+
+
+        private: std::vector<RealT> probs_; ///< The <em>phase probability vector</em> parameter of the distribution
+        private: std::vector<RealT> rates_; ///< The <em>rate vector</em> parameter of the distribution
+    }; // param_type
+
+
+    /**
+     * Constructs a 1-phase \c hyperexponential_distribution (i.e., an
+     * exponential distribution) with rate 1.
+     */
+    public: hyperexponential_distribution()
+    : dd_(std::vector<RealT>(1, 1)),
+      rates_(1, 1)
+    {
+        // empty
+    }
+
+    /**
+     * Constructs a \c hyperexponential_distribution from the <em>phase
+     * probability vector</em> and <em>rate vector</em> parameters of the
+     * distribution.
+     *
+     * The <em>phase probability vector</em> parameter is given by the range
+     * defined by [\a prob_first, \a prob_last) iterator pair, and the
+     * <em>rate vector</em> parameter is given by the range defined by
+     * [\a rate_first, \a rate_last) iterator pair.
+     *
+     * \tparam ProbIterT Must meet the requirements of \c InputIterator concept (ISO,2014,sec. 24.2.3 [input.iterators]).
+     * \tparam RateIterT Must meet the requirements of \c InputIterator concept (ISO,2014,sec. 24.2.3 [input.iterators]).
+     *
+     * \param prob_first The iterator to the beginning of the range of non-negative real elements representing the phase probabilities; if elements don't sum to 1, they are normalized.
+     * \param prob_last The iterator to the ending of the range of non-negative real elements representing the phase probabilities; if elements don't sum to 1, they are normalized.
+     * \param rate_first The iterator to the beginning of the range of non-negative real elements representing the rates.
+     * \param rate_last The iterator to the ending of the range of non-negative real elements representing the rates.
+     *
+     * References:
+     * -# ISO, <em>ISO/IEC 14882-2014: Information technology - Programming languages - C++</em>, 2014
+     * .
+     */
+    public: template <typename ProbIterT, typename RateIterT>
+            hyperexponential_distribution(ProbIterT prob_first, ProbIterT prob_last,
+                                          RateIterT rate_first, RateIterT rate_last)
+    : dd_(prob_first, prob_last),
+      rates_(rate_first, rate_last)
+    {
+        assert( hyperexp_detail::check_params(dd_.probabilities(), rates_) );
+    }
+
+    /**
+     * Constructs a \c hyperexponential_distribution from the <em>phase
+     * probability vector</em> and <em>rate vector</em> parameters of the
+     * distribution.
+     *
+     * The <em>phase probability vector</em> parameter is given by the range
+     * defined by \a prob_range, and the <em>rate vector</em> parameter is
+     * given by the range defined by \a rate_range.
+     *
+     * \tparam ProbRangeT Must meet the requirements of <a href="boost:/libs/range/doc/html/range/concepts.html">Range</a> concept.
+     * \tparam RateRangeT Must meet the requirements of <a href="boost:/libs/range/doc/html/range/concepts.html">Range</a> concept.
+     *
+     * \param prob_range The range of non-negative real elements representing the phase probabilities; if elements don't sum to 1, they are normalized.
+     * \param rate_range The range of positive real elements representing the rates.
+     *
+     * \note
+     *  The final \c disable_if parameter is an implementation detail that
+     *  differentiates between this two argument constructor and the
+     *  iterator-based two argument constructor described below.
+     */
+    //  We SFINAE this out of existance if either argument type is
+    //  incrementable as in that case the type is probably an iterator:
+    public: template <typename ProbRangeT, typename RateRangeT>
+            hyperexponential_distribution(ProbRangeT const& prob_range,
+                                          RateRangeT const& rate_range,
+                                          typename boost::disable_if_c<boost::has_pre_increment<ProbRangeT>::value || boost::has_pre_increment<RateRangeT>::value>::type* = 0)
+    : dd_(prob_range),
+      rates_(boost::begin(rate_range), boost::end(rate_range))
+    {
+        assert( hyperexp_detail::check_params(dd_.probabilities(), rates_) );
+    }
+
+    /**
+     * Constructs a \c hyperexponential_distribution from the <em>rate
+     * vector</em> parameter of the distribution and with equal phase
+     * probabilities.
+     *
+     * The <em>rate vector</em> parameter is given by the range defined by
+     * [\a rate_first, \a rate_last) iterator pair, and the <em>phase
+     * probability vector</em> parameter is set to the equal phase
+     * probabilities (i.e., to a vector of the same length \f$k\f$ of the
+     * <em>rate vector</em> and with each element set to \f$1.0/k\f$).
+     *
+     * \tparam RateIterT Must meet the requirements of \c InputIterator concept (ISO,2014,sec. 24.2.3 [input.iterators]).
+     * \tparam RateIterT2 Must meet the requirements of \c InputIterator concept (ISO,2014,sec. 24.2.3 [input.iterators]).
+     *
+     * \param rate_first The iterator to the beginning of the range of non-negative real elements representing the rates.
+     * \param rate_last The iterator to the ending of the range of non-negative real elements representing the rates.
+     *
+     * \note
+     *  The final \c disable_if parameter is an implementation detail that
+     *  differentiates between this two argument constructor and the
+     *  range-based two argument constructor described above.
+     *
+     * References:
+     * -# ISO, <em>ISO/IEC 14882-2014: Information technology - Programming languages - C++</em>, 2014
+     * .
+     */
+    //  We SFINAE this out of existance if the argument type is
+    //  incrementable as in that case the type is probably an iterator.
+    public: template <typename RateIterT>
+            hyperexponential_distribution(RateIterT rate_first,
+                                          RateIterT rate_last,
+                                          typename boost::enable_if_c<boost::has_pre_increment<RateIterT>::value>::type* = 0)
+    : dd_(std::vector<RealT>(std::distance(rate_first, rate_last), 1)),
+      rates_(rate_first, rate_last)
+    {
+        assert( hyperexp_detail::check_params(dd_.probabilities(), rates_) );
+    }
+
+    /**
+     * Constructs a @c param_type from the "rates" parameters
+     * of the distribution and with equal phase probabilities.
+     *
+     * The <em>rate vector</em> parameter is given by the range defined by
+     * \a rate_range, and the <em>phase probability vector</em> parameter is
+     * set to the equal phase probabilities (i.e., to a vector of the same
+     * length \f$k\f$ of the <em>rate vector</em> and with each element set
+     * to \f$1.0/k\f$).
+     *
+     * \tparam RateRangeT Must meet the requirements of <a href="boost:/libs/range/doc/html/range/concepts.html">Range</a> concept.
+     *
+     * \param rate_range The range of positive real elements representing the rates.
+     */
+    public: template <typename RateRangeT>
+            hyperexponential_distribution(RateRangeT const& rate_range)
+    : dd_(std::vector<RealT>(boost::size(rate_range), 1)),
+      rates_(boost::begin(rate_range), boost::end(rate_range))
+    {
+        assert( hyperexp_detail::check_params(dd_.probabilities(), rates_) );
+    }
+
+    /**
+     * Constructs a \c hyperexponential_distribution from its parameters.
+     *
+     * \param param The parameters of the distribution.
+     */
+    public: explicit hyperexponential_distribution(param_type const& param)
+    : dd_(param.probabilities()),
+      rates_(param.rates())
+    {
+        assert( hyperexp_detail::check_params(dd_.probabilities(), rates_) );
+    }
+
+#ifndef BOOST_NO_CXX11_HDR_INITIALIZER_LIST
+    /**
+     * Constructs a \c hyperexponential_distribution from the <em>phase
+     * probability vector</em> and <em>rate vector</em> parameters of the
+     * distribution.
+     *
+     * The <em>phase probability vector</em> parameter is given by the
+     * <em>brace-init-list</em> (ISO,2014,sec. 8.5.4 [dcl.init.list])
+     * defined by \a l1, and the <em>rate vector</em> parameter is given by the
+     * <em>brace-init-list</em> (ISO,2014,sec. 8.5.4 [dcl.init.list])
+     * defined by \a l2.
+     *
+     * \param l1 The initializer list for inizializing the phase probability vector.
+     * \param l2 The initializer list for inizializing the rate vector.
+     *
+     * References:
+     * -# ISO, <em>ISO/IEC 14882-2014: Information technology - Programming languages - C++</em>, 2014
+     * .
+     */
+    public: hyperexponential_distribution(std::initializer_list<RealT> const& l1, std::initializer_list<RealT> const& l2)
+    : dd_(l1.begin(), l1.end()),
+      rates_(l2.begin(), l2.end())
+    {
+        assert( hyperexp_detail::check_params(dd_.probabilities(), rates_) );
+    }
+
+    /**
+     * Constructs a \c hyperexponential_distribution from the <em>rate
+     * vector</em> parameter of the distribution and with equal phase
+     * probabilities.
+     *
+     * The <em>rate vector</em> parameter is given by the
+     * <em>brace-init-list</em> (ISO,2014,sec. 8.5.4 [dcl.init.list])
+     * defined by \a l1, and the <em>phase probability vector</em> parameter is
+     * set to the equal phase probabilities (i.e., to a vector of the same
+     * length \f$k\f$ of the <em>rate vector</em> and with each element set
+     * to \f$1.0/k\f$).
+     *
+     * \param l1 The initializer list for inizializing the rate vector.
+     *
+     * References:
+     * -# ISO, <em>ISO/IEC 14882-2014: Information technology - Programming languages - C++</em>, 2014
+     * .
+     */
+    public: hyperexponential_distribution(std::initializer_list<RealT> const& l1)
+    : dd_(std::vector<RealT>(std::distance(l1.begin(), l1.end()), 1)),
+      rates_(l1.begin(), l1.end())
+    {
+        assert( hyperexp_detail::check_params(dd_.probabilities(), rates_) );
+    }
+#endif
+
+    /**
+     * Gets a random variate distributed according to the
+     * hyperexponential distribution.
+     *
+     * \tparam URNG Must meet the requirements of \uniform_random_number_generator.
+     *
+     * \param urng A uniform random number generator object.
+     *
+     * \return A random variate distributed according to the hyperexponential distribution.
+     */
+    public: template<class URNG>\
+            RealT operator()(URNG& urng) const
+    {
+        const int i = dd_(urng);
+
+        return boost::random::exponential_distribution<RealT>(rates_[i])(urng);
+    }
+
+    /**
+     * Gets a random variate distributed according to the hyperexponential
+     * distribution with parameters specified by \c param.
+     *
+     * \tparam URNG Must meet the requirements of \uniform_random_number_generator.
+     *
+     * \param urng A uniform random number generator object.
+     * \param param A distribution parameter object.
+     *
+     * \return A random variate distributed according to the hyperexponential distribution.
+     *  distribution with parameters specified by \c param.
+     */
+    public: template<class URNG>
+            RealT operator()(URNG& urng, const param_type& param) const
+    {
+        return hyperexponential_distribution(param)(urng);
+    }
+
+    /** Returns the number of phases of the distribution. */
+    public: std::size_t num_phases() const
+    {
+        return rates_.size();
+    }
+
+    /** Returns the <em>phase probability vector</em> parameter of the distribution. */
+    public: std::vector<RealT> probabilities() const
+    {
+        return dd_.probabilities();
+    }
+
+    /** Returns the <em>rate vector</em> parameter of the distribution. */
+    public: std::vector<RealT> rates() const
+    {
+        return rates_;
+    }
+
+    /** Returns the smallest value that the distribution can produce. */
+    public: RealT min BOOST_PREVENT_MACRO_SUBSTITUTION () const
+    {
+        return 0;
+    }
+
+    /** Returns the largest value that the distribution can produce. */
+    public: RealT max BOOST_PREVENT_MACRO_SUBSTITUTION () const
+    {
+        return std::numeric_limits<RealT>::infinity();
+    }
+
+    /** Returns the parameters of the distribution. */
+    public: param_type param() const
+    {
+        std::vector<RealT> probs = dd_.probabilities();
+
+        return param_type(probs.begin(), probs.end(), rates_.begin(), rates_.end());
+    }
+
+    /** Sets the parameters of the distribution. */
+    public: void param(param_type const& param)
+    {
+        dd_.param(typename boost::random::discrete_distribution<int,RealT>::param_type(param.probabilities()));
+        rates_ = param.rates();
+    }
+
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    public: void reset()
+    {
+        // empty
+    }
+
+    /** Writes an @c hyperexponential_distribution to a @c std::ostream. */
+    public: BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, hyperexponential_distribution, hd)
+    {
+        os << hd.param();
+        return os;
+    }
+
+    /** Reads an @c hyperexponential_distribution from a @c std::istream. */
+    public: BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, hyperexponential_distribution, hd)
+    {
+        param_type param;
+        if(is >> param)
+        {
+            hd.param(param);
+        }
+        return is;
+    }
+
+    /**
+     * Returns true if the two instances of @c hyperexponential_distribution will
+     * return identical sequences of values given equal generators.
+     */
+    public: BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(hyperexponential_distribution, lhs, rhs)
+    {
+        return lhs.dd_ == rhs.dd_
+               && lhs.rates_ == rhs.rates_;
+    }
+    
+    /**
+     * Returns true if the two instances of @c hyperexponential_distribution will
+     * return different sequences of values given equal generators.
+     */
+    public: BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(hyperexponential_distribution)
+
+
+    private: boost::random::discrete_distribution<int,RealT> dd_; ///< The \c discrete_distribution used to sample the phase probability and choose the rate
+    private: std::vector<RealT> rates_; ///< The <em>rate vector</em> parameter of the distribution
+}; // hyperexponential_distribution
+
+}} // namespace boost::random
+
+
+#endif // BOOST_RANDOM_HYPEREXPONENTIAL_DISTRIBUTION_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/independent_bits.hpp

@@ -0,0 +1,271 @@
+/* boost random/independent_bits.hpp header file
+ *
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ *
+ */
+
+#ifndef BOOST_RANDOM_INDEPENDENT_BITS_HPP
+#define BOOST_RANDOM_INDEPENDENT_BITS_HPP
+
+#include <istream>
+#include <iosfwd>
+#include <boost/assert.hpp>
+#include <boost/limits.hpp>
+#include <boost/config.hpp>
+#include <boost/cstdint.hpp>
+#include <boost/integer/integer_mask.hpp>
+#include <boost/random/traits.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/integer_log2.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/detail/seed.hpp>
+#include <boost/random/detail/seed_impl.hpp>
+#include <boost/random/detail/signed_unsigned_tools.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * An instantiation of class template @c independent_bits_engine
+ * model a \pseudo_random_number_generator.  It generates random
+ * numbers distributed between [0, 2^w) by combining one or
+ * more invocations of the base engine.
+ *
+ * Requires: 0 < w <= std::numeric_limits<UIntType>::digits
+ */
+template<class Engine, std::size_t w, class UIntType>
+class independent_bits_engine
+{
+public:
+    typedef Engine base_type;
+    typedef UIntType result_type;
+    typedef typename Engine::result_type base_result_type;
+
+    // Required by old Boost.Random concept
+    BOOST_STATIC_CONSTANT(bool, has_fixed_range = false);
+
+    /** Returns the smallest value that the generator can produce. */
+    static result_type min BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return 0; }
+    /** Returns the largest value that the generator can produce. */
+    static result_type max BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return max_imp(boost::is_integral<UIntType>()); }
+
+    /**
+     * Constructs an @c independent_bits_engine using the
+     * default constructor of the base generator.
+     */
+    independent_bits_engine() { }
+
+    /**
+     * Constructs an @c independent_bits_engine, using seed as
+     * the constructor argument for both base generators.
+     */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(independent_bits_engine,
+        base_result_type, seed_arg)
+    {
+        _base.seed(seed_arg);
+    }
+
+    /**
+     * Constructs an @c independent_bits_engine, using seq as
+     * the constructor argument for the base generator.
+     */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_CONSTRUCTOR(independent_bits_engine,
+        SeedSeq, seq)
+    { _base.seed(seq); }
+
+    /** Constructs an @c independent_bits_engine by copying @c base. */
+    independent_bits_engine(const base_type& base_arg) : _base(base_arg) {}
+
+    /**
+     * Contructs an @c independent_bits_engine with
+     * values from the range defined by the input iterators first
+     * and last.  first will be modified to point to the element
+     * after the last one used.
+     *
+     * Throws: @c std::invalid_argument if the input range is too small.
+     *
+     * Exception Safety: Basic
+     */
+    template<class It>
+    independent_bits_engine(It& first, It last) : _base(first, last) { }
+
+    /**
+     * Seeds an @c independent_bits_engine using the default
+     * seed of the base generator.
+     */
+    void seed() { _base.seed(); }
+
+    /**
+     * Seeds an @c independent_bits_engine, using @c seed as the
+     * seed for the base generator.
+     */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_SEED(independent_bits_engine,
+        base_result_type, seed_arg)
+    { _base.seed(seed_arg); }
+
+    /**
+     * Seeds an @c independent_bits_engine, using @c seq to
+     * seed the base generator.
+     */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_SEED(independent_bits_engine,
+        SeedSeq, seq)
+    { _base.seed(seq); }
+
+    /**
+     * Seeds an @c independent_bits_engine with
+     * values from the range defined by the input iterators first
+     * and last.  first will be modified to point to the element
+     * after the last one used.
+     *
+     * Throws: @c std::invalid_argument if the input range is too small.
+     *
+     * Exception Safety: Basic
+     */
+    template<class It> void seed(It& first, It last)
+    { _base.seed(first, last); }
+
+    /** Returns the next value of the generator. */
+    result_type operator()()
+    {
+        // While it may seem wasteful to recalculate this
+        // every time, both msvc and gcc can propagate
+        // constants, resolving this at compile time.
+        base_unsigned range =
+            detail::subtract<base_result_type>()((_base.max)(), (_base.min)());
+        std::size_t m =
+            (range == (std::numeric_limits<base_unsigned>::max)()) ?
+                std::numeric_limits<base_unsigned>::digits :
+                detail::integer_log2(range + 1);
+        std::size_t n = (w + m - 1) / m;
+        std::size_t w0, n0;
+        base_unsigned y0, y1;
+        base_unsigned y0_mask, y1_mask;
+        calc_params(n, range, w0, n0, y0, y1, y0_mask, y1_mask);
+        if(base_unsigned(range - y0 + 1) > y0 / n) {
+            // increment n and try again.
+            ++n;
+            calc_params(n, range, w0, n0, y0, y1, y0_mask, y1_mask);
+        }
+
+        BOOST_ASSERT(n0*w0 + (n - n0)*(w0 + 1) == w);
+
+        result_type S = 0;
+        for(std::size_t k = 0; k < n0; ++k) {
+            base_unsigned u;
+            do {
+                u = detail::subtract<base_result_type>()(_base(), (_base.min)());
+            } while(u > base_unsigned(y0 - 1));
+            S = (S << w0) + (u & y0_mask);
+        }
+        for(std::size_t k = 0; k < (n - n0); ++k) {
+            base_unsigned u;
+            do {
+                u = detail::subtract<base_result_type>()(_base(), (_base.min)());
+            } while(u > base_unsigned(y1 - 1));
+            S = (S << (w0 + 1)) + (u & y1_mask);
+        }
+        return S;
+    }
+  
+    /** Fills a range with random values */
+    template<class Iter>
+    void generate(Iter first, Iter last)
+    { detail::generate_from_int(*this, first, last); }
+
+    /** Advances the state of the generator by @c z. */
+    void discard(boost::uintmax_t z)
+    {
+        for(boost::uintmax_t i = 0; i < z; ++i) {
+            (*this)();
+        }
+    }
+
+    const base_type& base() const { return _base; }
+
+    /**
+     * Writes the textual representation if the generator to a @c std::ostream.
+     * The textual representation of the engine is the textual representation
+     * of the base engine.
+     */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, independent_bits_engine, r)
+    {
+        os << r._base;
+        return os;
+    }
+
+    /**
+     * Reads the state of an @c independent_bits_engine from a
+     * @c std::istream.
+     */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, independent_bits_engine, r)
+    {
+        is >> r._base;
+        return is;
+    }
+
+    /**
+     * Returns: true iff the two @c independent_bits_engines will
+     * produce the same sequence of values.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(independent_bits_engine, x, y)
+    { return x._base == y._base; }
+    /**
+     * Returns: true iff the two @c independent_bits_engines will
+     * produce different sequences of values.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(independent_bits_engine)
+
+private:
+
+    /// \cond show_private
+    typedef typename boost::random::traits::make_unsigned<base_result_type>::type base_unsigned;
+
+    static UIntType max_imp(const boost::true_type&)
+    {
+       return boost::low_bits_mask_t<w>::sig_bits;
+    }
+    static UIntType max_imp(const boost::false_type&)
+    {
+       // We have a multiprecision integer type:
+       BOOST_STATIC_ASSERT(std::numeric_limits<UIntType>::is_specialized);
+       return w < std::numeric_limits<UIntType>::digits ? UIntType((UIntType(1) << w) - 1) : UIntType((((UIntType(1) << (w - 1)) - 1) << 1) | 1u);
+    }
+
+    void calc_params(
+        std::size_t n, base_unsigned range,
+        std::size_t& w0, std::size_t& n0,
+        base_unsigned& y0, base_unsigned& y1,
+        base_unsigned& y0_mask, base_unsigned& y1_mask)
+    {
+        BOOST_ASSERT(w >= n);
+        w0 = w/n;
+        n0 = n - w % n;
+        y0_mask = (base_unsigned(2) << (w0 - 1)) - 1;
+        y1_mask = (y0_mask << 1) | 1;
+        y0 = (range + 1) & ~y0_mask;
+        y1 = (range + 1) & ~y1_mask;
+        BOOST_ASSERT(y0 != 0 || base_unsigned(range + 1) == 0);
+    }
+    /// \endcond
+
+    Engine _base;
+};
+
+#ifndef BOOST_NO_INCLASS_MEMBER_INITIALIZATION
+template<class Engine, std::size_t w, class UIntType>
+const bool independent_bits_engine<Engine, w, UIntType>::has_fixed_range;
+#endif
+
+} // namespace random
+} // namespace boost
+
+#endif // BOOST_RANDOM_INDEPENDENT_BITS_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/inversive_congruential.hpp

@@ -0,0 +1,267 @@
+/* boost random/inversive_congruential.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2001-02-18  moved to individual header files
+ */
+
+#ifndef BOOST_RANDOM_INVERSIVE_CONGRUENTIAL_HPP
+#define BOOST_RANDOM_INVERSIVE_CONGRUENTIAL_HPP
+
+#include <iosfwd>
+#include <stdexcept>
+#include <boost/assert.hpp>
+#include <boost/config.hpp>
+#include <boost/cstdint.hpp>
+#include <boost/integer/static_log2.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/const_mod.hpp>
+#include <boost/random/detail/seed.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/detail/seed_impl.hpp>
+
+#include <boost/random/detail/disable_warnings.hpp>
+
+namespace boost {
+namespace random {
+
+// Eichenauer and Lehn 1986
+/**
+ * Instantiations of class template @c inversive_congruential_engine model a
+ * \pseudo_random_number_generator. It uses the inversive congruential
+ * algorithm (ICG) described in
+ *
+ *  @blockquote
+ *  "Inversive pseudorandom number generators: concepts, results and links",
+ *  Peter Hellekalek, In: "Proceedings of the 1995 Winter Simulation
+ *  Conference", C. Alexopoulos, K. Kang, W.R. Lilegdon, and D. Goldsman
+ *  (editors), 1995, pp. 255-262. ftp://random.mat.sbg.ac.at/pub/data/wsc95.ps
+ *  @endblockquote
+ *
+ * The output sequence is defined by x(n+1) = (a*inv(x(n)) - b) (mod p),
+ * where x(0), a, b, and the prime number p are parameters of the generator.
+ * The expression inv(k) denotes the multiplicative inverse of k in the
+ * field of integer numbers modulo p, with inv(0) := 0.
+ *
+ * The template parameter IntType shall denote a signed integral type large
+ * enough to hold p; a, b, and p are the parameters of the generators. The
+ * template parameter val is the validation value checked by validation.
+ *
+ * @xmlnote
+ * The implementation currently uses the Euclidian Algorithm to compute
+ * the multiplicative inverse. Therefore, the inversive generators are about
+ * 10-20 times slower than the others (see section"performance"). However,
+ * the paper talks of only 3x slowdown, so the Euclidian Algorithm is probably
+ * not optimal for calculating the multiplicative inverse.
+ * @endxmlnote
+ */
+template<class IntType, IntType a, IntType b, IntType p>
+class inversive_congruential_engine
+{
+public:
+    typedef IntType result_type;
+    BOOST_STATIC_CONSTANT(bool, has_fixed_range = false);
+
+    BOOST_STATIC_CONSTANT(result_type, multiplier = a);
+    BOOST_STATIC_CONSTANT(result_type, increment = b);
+    BOOST_STATIC_CONSTANT(result_type, modulus = p);
+    BOOST_STATIC_CONSTANT(IntType, default_seed = 1);
+
+    static result_type min BOOST_PREVENT_MACRO_SUBSTITUTION () { return b == 0 ? 1 : 0; }
+    static result_type max BOOST_PREVENT_MACRO_SUBSTITUTION () { return p-1; }
+    
+    /**
+     * Constructs an @c inversive_congruential_engine, seeding it with
+     * the default seed.
+     */
+    inversive_congruential_engine() { seed(); }
+
+    /**
+     * Constructs an @c inversive_congruential_engine, seeding it with @c x0.
+     */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(inversive_congruential_engine,
+                                               IntType, x0)
+    { seed(x0); }
+    
+    /**
+     * Constructs an @c inversive_congruential_engine, seeding it with values
+     * produced by a call to @c seq.generate().
+     */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_CONSTRUCTOR(inversive_congruential_engine,
+                                             SeedSeq, seq)
+    { seed(seq); }
+    
+    /**
+     * Constructs an @c inversive_congruential_engine, seeds it
+     * with values taken from the itrator range [first, last),
+     * and adjusts first to point to the element after the last one
+     * used.  If there are not enough elements, throws @c std::invalid_argument.
+     *
+     * first and last must be input iterators.
+     */
+    template<class It> inversive_congruential_engine(It& first, It last)
+    { seed(first, last); }
+
+    /**
+     * Calls seed(default_seed)
+     */
+    void seed() { seed(default_seed); }
+  
+    /**
+     * If c mod m is zero and x0 mod m is zero, changes the current value of
+     * the generator to 1. Otherwise, changes it to x0 mod m. If c is zero,
+     * distinct seeds in the range [1,m) will leave the generator in distinct
+     * states. If c is not zero, the range is [0,m).
+     */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_SEED(inversive_congruential_engine, IntType, x0)
+    {
+        // wrap _x if it doesn't fit in the destination
+        if(modulus == 0) {
+            _value = x0;
+        } else {
+            _value = x0 % modulus;
+        }
+        // handle negative seeds
+        if(_value <= 0 && _value != 0) {
+            _value += modulus;
+        }
+        // adjust to the correct range
+        if(increment == 0 && _value == 0) {
+            _value = 1;
+        }
+        BOOST_ASSERT(_value >= (min)());
+        BOOST_ASSERT(_value <= (max)());
+    }
+
+    /**
+     * Seeds an @c inversive_congruential_engine using values from a SeedSeq.
+     */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_SEED(inversive_congruential_engine, SeedSeq, seq)
+    { seed(detail::seed_one_int<IntType, modulus>(seq)); }
+    
+    /**
+     * seeds an @c inversive_congruential_engine with values taken
+     * from the itrator range [first, last) and adjusts @c first to
+     * point to the element after the last one used.  If there are
+     * not enough elements, throws @c std::invalid_argument.
+     *
+     * @c first and @c last must be input iterators.
+     */
+    template<class It> void seed(It& first, It last)
+    { seed(detail::get_one_int<IntType, modulus>(first, last)); }
+
+    /** Returns the next output of the generator. */
+    IntType operator()()
+    {
+        typedef const_mod<IntType, p> do_mod;
+        _value = do_mod::mult_add(a, do_mod::invert(_value), b);
+        return _value;
+    }
+  
+    /** Fills a range with random values */
+    template<class Iter>
+    void generate(Iter first, Iter last)
+    { detail::generate_from_int(*this, first, last); }
+
+    /** Advances the state of the generator by @c z. */
+    void discard(boost::uintmax_t z)
+    {
+        for(boost::uintmax_t j = 0; j < z; ++j) {
+            (*this)();
+        }
+    }
+
+    /**
+     * Writes the textual representation of the generator to a @c std::ostream.
+     */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, inversive_congruential_engine, x)
+    {
+        os << x._value;
+        return os;
+    }
+
+    /**
+     * Reads the textual representation of the generator from a @c std::istream.
+     */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, inversive_congruential_engine, x)
+    {
+        is >> x._value;
+        return is;
+    }
+
+    /**
+     * Returns true if the two generators will produce identical
+     * sequences of outputs.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(inversive_congruential_engine, x, y)
+    { return x._value == y._value; }
+
+    /**
+     * Returns true if the two generators will produce different
+     * sequences of outputs.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(inversive_congruential_engine)
+
+private:
+    IntType _value;
+};
+
+#ifndef BOOST_NO_INCLASS_MEMBER_INITIALIZATION
+//  A definition is required even for integral static constants
+template<class IntType, IntType a, IntType b, IntType p>
+const bool inversive_congruential_engine<IntType, a, b, p>::has_fixed_range;
+template<class IntType, IntType a, IntType b, IntType p>
+const typename inversive_congruential_engine<IntType, a, b, p>::result_type inversive_congruential_engine<IntType, a, b, p>::multiplier;
+template<class IntType, IntType a, IntType b, IntType p>
+const typename inversive_congruential_engine<IntType, a, b, p>::result_type inversive_congruential_engine<IntType, a, b, p>::increment;
+template<class IntType, IntType a, IntType b, IntType p>
+const typename inversive_congruential_engine<IntType, a, b, p>::result_type inversive_congruential_engine<IntType, a, b, p>::modulus;
+template<class IntType, IntType a, IntType b, IntType p>
+const typename inversive_congruential_engine<IntType, a, b, p>::result_type inversive_congruential_engine<IntType, a, b, p>::default_seed;
+#endif
+
+/// \cond show_deprecated
+
+// provided for backwards compatibility
+template<class IntType, IntType a, IntType b, IntType p, IntType val = 0>
+class inversive_congruential : public inversive_congruential_engine<IntType, a, b, p>
+{
+    typedef inversive_congruential_engine<IntType, a, b, p> base_type;
+public:
+    inversive_congruential(IntType x0 = 1) : base_type(x0) {}
+    template<class It>
+    inversive_congruential(It& first, It last) : base_type(first, last) {}
+};
+
+/// \endcond
+
+/**
+ * The specialization hellekalek1995 was suggested in
+ *
+ *  @blockquote
+ *  "Inversive pseudorandom number generators: concepts, results and links",
+ *  Peter Hellekalek, In: "Proceedings of the 1995 Winter Simulation
+ *  Conference", C. Alexopoulos, K. Kang, W.R. Lilegdon, and D. Goldsman
+ *  (editors), 1995, pp. 255-262. ftp://random.mat.sbg.ac.at/pub/data/wsc95.ps
+ *  @endblockquote
+ */
+typedef inversive_congruential_engine<uint32_t, 9102, 2147483647-36884165,
+  2147483647> hellekalek1995;
+
+} // namespace random
+
+using random::hellekalek1995;
+
+} // namespace boost
+
+#include <boost/random/detail/enable_warnings.hpp>
+
+#endif // BOOST_RANDOM_INVERSIVE_CONGRUENTIAL_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/lagged_fibonacci.hpp

@@ -0,0 +1,537 @@
+/* boost random/lagged_fibonacci.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2013-10-14  fixed some warnings with Wshadow (mgaunard)
+ *  2001-02-18  moved to individual header files
+ */
+
+#ifndef BOOST_RANDOM_LAGGED_FIBONACCI_HPP
+#define BOOST_RANDOM_LAGGED_FIBONACCI_HPP
+
+#include <istream>
+#include <iosfwd>
+#include <algorithm>     // std::max
+#include <iterator>
+#include <boost/config/no_tr1/cmath.hpp>         // std::pow
+#include <boost/config.hpp>
+#include <boost/limits.hpp>
+#include <boost/cstdint.hpp>
+#include <boost/integer/integer_mask.hpp>
+#include <boost/random/linear_congruential.hpp>
+#include <boost/random/uniform_01.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/seed.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/detail/generator_seed_seq.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * Instantiations of class template \lagged_fibonacci_engine model a
+ * \pseudo_random_number_generator. It uses a lagged Fibonacci
+ * algorithm with two lags @c p and @c q:
+ * x(i) = x(i-p) + x(i-q) (mod 2<sup>w</sup>) with p > q.
+ */
+template<class UIntType, int w, unsigned int p, unsigned int q>
+class lagged_fibonacci_engine
+{
+public:
+    typedef UIntType result_type;
+    BOOST_STATIC_CONSTANT(bool, has_fixed_range = false);
+    BOOST_STATIC_CONSTANT(int, word_size = w);
+    BOOST_STATIC_CONSTANT(unsigned int, long_lag = p);
+    BOOST_STATIC_CONSTANT(unsigned int, short_lag = q);
+
+    BOOST_STATIC_CONSTANT(UIntType, default_seed = 331u);
+
+    /** Returns the smallest value that the generator can produce. */
+    static result_type min BOOST_PREVENT_MACRO_SUBSTITUTION () { return 0; }
+    /** Returns the largest value that the generator can produce. */
+    static result_type max BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return low_bits_mask_t<w>::sig_bits; }
+
+    /** Creates a new @c lagged_fibonacci_engine and calls @c seed(). */
+    lagged_fibonacci_engine() { seed(); }
+
+    /** Creates a new @c lagged_fibonacci_engine and calls @c seed(value). */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(lagged_fibonacci_engine,
+        UIntType, value)
+    { seed(value); }
+
+    /** Creates a new @c lagged_fibonacci_engine and calls @c seed(seq). */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_CONSTRUCTOR(lagged_fibonacci_engine,
+        SeedSeq, seq)
+    { seed(seq); }
+
+    /**
+     * Creates a new @c lagged_fibonacci_engine and calls @c seed(first, last).
+     */
+    template<class It> lagged_fibonacci_engine(It& first, It last)
+    { seed(first, last); }
+
+    // compiler-generated copy ctor and assignment operator are fine
+
+    /** Calls @c seed(default_seed). */
+    void seed() { seed(default_seed); }
+
+    /**
+     * Sets the state of the generator to values produced by
+     * a \minstd_rand0 generator.
+     */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_SEED(lagged_fibonacci_engine,
+        UIntType, value)
+    {
+        minstd_rand0 intgen(static_cast<boost::uint32_t>(value));
+        detail::generator_seed_seq<minstd_rand0> gen(intgen);
+        seed(gen);
+    }
+
+    /**
+     * Sets the state of the generator using values produced by seq.
+     */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_SEED(lagged_fibonacci_engine, SeedSeq, seq)
+    {
+        detail::seed_array_int<w>(seq, x);
+        i = long_lag;
+    }
+
+    /**
+     * Sets the state of the generator to values from the iterator
+     * range [first, last).  If there are not enough elements in the
+     * range [first, last) throws @c std::invalid_argument.
+     */
+    template<class It>
+    void seed(It& first, It last)
+    {
+        detail::fill_array_int<w>(first, last, x);
+        i = long_lag;
+    }
+
+    /** Returns the next value of the generator. */
+    result_type operator()()
+    {
+        if(i >= long_lag)
+            fill();
+        return x[i++];
+    }
+
+    /** Fills a range with random values */
+    template<class Iter>
+    void generate(Iter first, Iter last)
+    { detail::generate_from_int(*this, first, last); }
+
+    /** Advances the state of the generator by @c z. */
+    void discard(boost::uintmax_t z)
+    {
+        for(boost::uintmax_t j = 0; j < z; ++j) {
+            (*this)();
+        }
+    }
+
+    /**
+     * Writes the textual representation of the generator to a @c std::ostream.
+     */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, lagged_fibonacci_engine, f)
+    {
+        os << f.i;
+        for(unsigned int j = 0; j < f.long_lag; ++j)
+            os << ' ' << f.x[j];
+        return os;
+    }
+
+    /**
+     * Reads the textual representation of the generator from a @c std::istream.
+     */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, lagged_fibonacci_engine, f)
+    {
+        is >> f.i >> std::ws;
+        for(unsigned int j = 0; j < f.long_lag; ++j)
+            is >> f.x[j] >> std::ws;
+        return is;
+    }
+
+    /**
+     * Returns true if the two generators will produce identical
+     * sequences of outputs.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(lagged_fibonacci_engine, x_, y_)
+    { return x_.i == y_.i && std::equal(x_.x, x_.x+long_lag, y_.x); }
+
+    /**
+     * Returns true if the two generators will produce different
+     * sequences of outputs.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(lagged_fibonacci_engine)
+
+private:
+    /// \cond show_private
+    void fill();
+    /// \endcond
+
+    unsigned int i;
+    UIntType x[long_lag];
+};
+
+#ifndef BOOST_NO_INCLASS_MEMBER_INITIALIZATION
+//  A definition is required even for integral static constants
+template<class UIntType, int w, unsigned int p, unsigned int q>
+const bool lagged_fibonacci_engine<UIntType, w, p, q>::has_fixed_range;
+template<class UIntType, int w, unsigned int p, unsigned int q>
+const unsigned int lagged_fibonacci_engine<UIntType, w, p, q>::long_lag;
+template<class UIntType, int w, unsigned int p, unsigned int q>
+const unsigned int lagged_fibonacci_engine<UIntType, w, p, q>::short_lag;
+template<class UIntType, int w, unsigned int p, unsigned int q>
+const UIntType lagged_fibonacci_engine<UIntType, w, p, q>::default_seed;
+#endif
+
+/// \cond show_private
+
+template<class UIntType, int w, unsigned int p, unsigned int q>
+void lagged_fibonacci_engine<UIntType, w, p, q>::fill()
+{
+    // two loops to avoid costly modulo operations
+    {  // extra scope for MSVC brokenness w.r.t. for scope
+    for(unsigned int j = 0; j < short_lag; ++j)
+        x[j] = (x[j] + x[j+(long_lag-short_lag)]) & low_bits_mask_t<w>::sig_bits;
+    }
+    for(unsigned int j = short_lag; j < long_lag; ++j)
+        x[j] = (x[j] + x[j-short_lag]) & low_bits_mask_t<w>::sig_bits;
+    i = 0;
+}
+
+/// \endcond
+
+/// \cond show_deprecated
+
+// provided for backwards compatibility
+template<class UIntType, int w, unsigned int p, unsigned int q, UIntType v = 0>
+class lagged_fibonacci : public lagged_fibonacci_engine<UIntType, w, p, q>
+{
+    typedef lagged_fibonacci_engine<UIntType, w, p, q> base_type;
+public:
+    lagged_fibonacci() {}
+    BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(lagged_fibonacci, UIntType, val)
+    { this->seed(val); }
+    BOOST_RANDOM_DETAIL_SEED_SEQ_CONSTRUCTOR(lagged_fibonacci, SeedSeq, seq)
+    { this->seed(seq); }
+    template<class It>
+    lagged_fibonacci(It& first, It last) : base_type(first, last) {}
+};
+
+/// \endcond
+
+// lagged Fibonacci generator for the range [0..1)
+// contributed by Matthias Troyer
+// for p=55, q=24 originally by G. J. Mitchell and D. P. Moore 1958
+
+/**
+ * Instantiations of class template @c lagged_fibonacci_01 model a
+ * \pseudo_random_number_generator. It uses a lagged Fibonacci
+ * algorithm with two lags @c p and @c q, evaluated in floating-point
+ * arithmetic: x(i) = x(i-p) + x(i-q) (mod 1) with p > q. See
+ *
+ *  @blockquote
+ *  "Uniform random number generators for supercomputers", Richard Brent,
+ *  Proc. of Fifth Australian Supercomputer Conference, Melbourne,
+ *  Dec. 1992, pp. 704-706.
+ *  @endblockquote
+ *
+ * @xmlnote
+ * The quality of the generator crucially depends on the choice
+ * of the parameters. User code should employ one of the sensibly
+ * parameterized generators such as \lagged_fibonacci607 instead.
+ * @endxmlnote
+ *
+ * The generator requires considerable amounts of memory for the storage
+ * of its state array. For example, \lagged_fibonacci607 requires about
+ * 4856 bytes and \lagged_fibonacci44497 requires about 350 KBytes.
+ */
+template<class RealType, int w, unsigned int p, unsigned int q>
+class lagged_fibonacci_01_engine
+{
+public:
+    typedef RealType result_type;
+    BOOST_STATIC_CONSTANT(bool, has_fixed_range = false);
+    BOOST_STATIC_CONSTANT(int, word_size = w);
+    BOOST_STATIC_CONSTANT(unsigned int, long_lag = p);
+    BOOST_STATIC_CONSTANT(unsigned int, short_lag = q);
+
+    BOOST_STATIC_CONSTANT(boost::uint32_t, default_seed = 331u);
+
+    /** Constructs a @c lagged_fibonacci_01 generator and calls @c seed(). */
+    lagged_fibonacci_01_engine() { seed(); }
+    /** Constructs a @c lagged_fibonacci_01 generator and calls @c seed(value). */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(lagged_fibonacci_01_engine, uint32_t, value)
+    { seed(value); }
+    /** Constructs a @c lagged_fibonacci_01 generator and calls @c seed(gen). */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_CONSTRUCTOR(lagged_fibonacci_01_engine, SeedSeq, seq)
+    { seed(seq); }
+    template<class It> lagged_fibonacci_01_engine(It& first, It last)
+    { seed(first, last); }
+
+    // compiler-generated copy ctor and assignment operator are fine
+
+    /** Calls seed(default_seed). */
+    void seed() { seed(default_seed); }
+
+    /**
+     * Constructs a \minstd_rand0 generator with the constructor parameter
+     * value and calls seed with it. Distinct seeds in the range
+     * [1, 2147483647) will produce generators with different states. Other
+     * seeds will be equivalent to some seed within this range. See
+     * \linear_congruential_engine for details.
+     */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_SEED(lagged_fibonacci_01_engine, boost::uint32_t, value)
+    {
+        minstd_rand0 intgen(value);
+        detail::generator_seed_seq<minstd_rand0> gen(intgen);
+        seed(gen);
+    }
+
+    /**
+     * Seeds this @c lagged_fibonacci_01_engine using values produced by
+     * @c seq.generate.
+     */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_SEED(lagged_fibonacci_01_engine, SeedSeq, seq)
+    {
+        detail::seed_array_real<w>(seq, x);
+        i = long_lag;
+    }
+
+    /**
+     * Seeds this @c lagged_fibonacci_01_engine using values from the
+     * iterator range [first, last).  If there are not enough elements
+     * in the range, throws @c std::invalid_argument.
+     */
+    template<class It>
+    void seed(It& first, It last)
+    {
+        detail::fill_array_real<w>(first, last, x);
+        i = long_lag;
+    }
+
+    /** Returns the smallest value that the generator can produce. */
+    static result_type min BOOST_PREVENT_MACRO_SUBSTITUTION () { return result_type(0); }
+    /** Returns the upper bound of the generators outputs. */
+    static result_type max BOOST_PREVENT_MACRO_SUBSTITUTION () { return result_type(1); }
+
+    /** Returns the next value of the generator. */
+    result_type operator()()
+    {
+        if(i >= long_lag)
+            fill();
+        return x[i++];
+    }
+
+    /** Fills a range with random values */
+    template<class Iter>
+    void generate(Iter first, Iter last)
+    { return detail::generate_from_real(*this, first, last); }
+
+    /** Advances the state of the generator by @c z. */
+    void discard(boost::uintmax_t z)
+    {
+        for(boost::uintmax_t j = 0; j < z; ++j) {
+            (*this)();
+        }
+    }
+
+    /**
+     * Writes the textual representation of the generator to a @c std::ostream.
+     */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, lagged_fibonacci_01_engine, f)
+    {
+        // allow for Koenig lookup
+        using std::pow;
+        os << f.i;
+        std::ios_base::fmtflags oldflags = os.flags(os.dec | os.fixed | os.left);
+        for(unsigned int j = 0; j < f.long_lag; ++j)
+            os << ' ' << f.x[j] * f.modulus();
+        os.flags(oldflags);
+        return os;
+    }
+
+    /**
+     * Reads the textual representation of the generator from a @c std::istream.
+     */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, lagged_fibonacci_01_engine, f)
+    {
+        is >> f.i;
+        for(unsigned int j = 0; j < f.long_lag; ++j) {
+            typename lagged_fibonacci_01_engine::result_type value;
+            is >> std::ws >> value;
+            f.x[j] = value / f.modulus();
+        }
+        return is;
+    }
+
+    /**
+     * Returns true if the two generators will produce identical
+     * sequences of outputs.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(lagged_fibonacci_01_engine, x_, y_)
+    { return x_.i == y_.i && std::equal(x_.x, x_.x+long_lag, y_.x); }
+
+    /**
+     * Returns true if the two generators will produce different
+     * sequences of outputs.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(lagged_fibonacci_01_engine)
+
+private:
+    /// \cond show_private
+    void fill();
+    static RealType modulus()
+    {
+        using std::pow;
+        return pow(RealType(2), word_size);
+    }
+    /// \endcond
+    unsigned int i;
+    RealType x[long_lag];
+};
+
+#ifndef BOOST_NO_INCLASS_MEMBER_INITIALIZATION
+//  A definition is required even for integral static constants
+template<class RealType, int w, unsigned int p, unsigned int q>
+const bool lagged_fibonacci_01_engine<RealType, w, p, q>::has_fixed_range;
+template<class RealType, int w, unsigned int p, unsigned int q>
+const unsigned int lagged_fibonacci_01_engine<RealType, w, p, q>::long_lag;
+template<class RealType, int w, unsigned int p, unsigned int q>
+const unsigned int lagged_fibonacci_01_engine<RealType, w, p, q>::short_lag;
+template<class RealType, int w, unsigned int p, unsigned int q>
+const int lagged_fibonacci_01_engine<RealType,w,p,q>::word_size;
+template<class RealType, int w, unsigned int p, unsigned int q>
+const boost::uint32_t lagged_fibonacci_01_engine<RealType,w,p,q>::default_seed;
+#endif
+
+/// \cond show_private
+template<class RealType, int w, unsigned int p, unsigned int q>
+void lagged_fibonacci_01_engine<RealType, w, p, q>::fill()
+{
+    // two loops to avoid costly modulo operations
+    {  // extra scope for MSVC brokenness w.r.t. for scope
+    for(unsigned int j = 0; j < short_lag; ++j) {
+        RealType t = x[j] + x[j+(long_lag-short_lag)];
+        if(t >= RealType(1))
+            t -= RealType(1);
+        x[j] = t;
+    }
+    }
+    for(unsigned int j = short_lag; j < long_lag; ++j) {
+        RealType t = x[j] + x[j-short_lag];
+        if(t >= RealType(1))
+            t -= RealType(1);
+        x[j] = t;
+    }
+    i = 0;
+}
+/// \endcond
+
+/// \cond show_deprecated
+
+// provided for backwards compatibility
+template<class RealType, int w, unsigned int p, unsigned int q>
+class lagged_fibonacci_01 : public lagged_fibonacci_01_engine<RealType, w, p, q>
+{
+    typedef lagged_fibonacci_01_engine<RealType, w, p, q> base_type;
+public:
+    lagged_fibonacci_01() {}
+    BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(lagged_fibonacci_01, boost::uint32_t, val)
+    { this->seed(val); }
+    BOOST_RANDOM_DETAIL_SEED_SEQ_CONSTRUCTOR(lagged_fibonacci_01, SeedSeq, seq)
+    { this->seed(seq); }
+    template<class It>
+    lagged_fibonacci_01(It& first, It last) : base_type(first, last) {}
+};
+
+/// \endcond
+
+namespace detail {
+
+template<class Engine>
+struct generator_bits;
+
+template<class RealType, int w, unsigned int p, unsigned int q>
+struct generator_bits<lagged_fibonacci_01_engine<RealType, w, p, q> >
+{
+    static std::size_t value() { return w; }
+};
+
+template<class RealType, int w, unsigned int p, unsigned int q>
+struct generator_bits<lagged_fibonacci_01<RealType, w, p, q> >
+{
+    static std::size_t value() { return w; }
+};
+
+}
+
+#ifdef BOOST_RANDOM_DOXYGEN
+namespace detail {
+/**
+ * The specializations lagged_fibonacci607 ... lagged_fibonacci44497
+ * use well tested lags.
+ *
+ * See
+ *
+ *  @blockquote
+ *  "On the Periods of Generalized Fibonacci Recurrences", Richard P. Brent
+ *  Computer Sciences Laboratory Australian National University, December 1992
+ *  @endblockquote
+ *
+ * The lags used here can be found in
+ *
+ *  @blockquote
+ *  "Uniform random number generators for supercomputers", Richard Brent,
+ *  Proc. of Fifth Australian Supercomputer Conference, Melbourne,
+ *  Dec. 1992, pp. 704-706.
+ *  @endblockquote
+ */
+struct lagged_fibonacci_doc {};
+}
+#endif
+
+/** @copydoc boost::random::detail::lagged_fibonacci_doc */
+typedef lagged_fibonacci_01_engine<double, 48, 607, 273> lagged_fibonacci607;
+/** @copydoc boost::random::detail::lagged_fibonacci_doc */
+typedef lagged_fibonacci_01_engine<double, 48, 1279, 418> lagged_fibonacci1279;
+/** @copydoc boost::random::detail::lagged_fibonacci_doc */
+typedef lagged_fibonacci_01_engine<double, 48, 2281, 1252> lagged_fibonacci2281;
+/** @copydoc boost::random::detail::lagged_fibonacci_doc */
+typedef lagged_fibonacci_01_engine<double, 48, 3217, 576> lagged_fibonacci3217;
+/** @copydoc boost::random::detail::lagged_fibonacci_doc */
+typedef lagged_fibonacci_01_engine<double, 48, 4423, 2098> lagged_fibonacci4423;
+/** @copydoc boost::random::detail::lagged_fibonacci_doc */
+typedef lagged_fibonacci_01_engine<double, 48, 9689, 5502> lagged_fibonacci9689;
+/** @copydoc boost::random::detail::lagged_fibonacci_doc */
+typedef lagged_fibonacci_01_engine<double, 48, 19937, 9842> lagged_fibonacci19937;
+/** @copydoc boost::random::detail::lagged_fibonacci_doc */
+typedef lagged_fibonacci_01_engine<double, 48, 23209, 13470> lagged_fibonacci23209;
+/** @copydoc boost::random::detail::lagged_fibonacci_doc */
+typedef lagged_fibonacci_01_engine<double, 48, 44497, 21034> lagged_fibonacci44497;
+
+} // namespace random
+
+using random::lagged_fibonacci607;
+using random::lagged_fibonacci1279;
+using random::lagged_fibonacci2281;
+using random::lagged_fibonacci3217;
+using random::lagged_fibonacci4423;
+using random::lagged_fibonacci9689;
+using random::lagged_fibonacci19937;
+using random::lagged_fibonacci23209;
+using random::lagged_fibonacci44497;
+
+} // namespace boost
+
+#endif // BOOST_RANDOM_LAGGED_FIBONACCI_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/laplace_distribution.hpp

@@ -0,0 +1,175 @@
+/* boost random/laplace_distribution.hpp header file
+ *
+ * Copyright Steven Watanabe 2014
+ * 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.
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_LAPLACE_DISTRIBUTION_HPP
+#define BOOST_RANDOM_LAPLACE_DISTRIBUTION_HPP
+
+#include <cassert>
+#include <istream>
+#include <iosfwd>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/exponential_distribution.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * The laplace distribution is a real-valued distribution with
+ * two parameters, mean and beta.
+ *
+ * It has \f$\displaystyle p(x) = \frac{e^-{\frac{|x-\mu|}{\beta}}}{2\beta}\f$.
+ */
+template<class RealType = double>
+class laplace_distribution {
+public:
+    typedef RealType result_type;
+    typedef RealType input_type;
+
+    class param_type {
+    public:
+        typedef laplace_distribution distribution_type;
+
+        /**
+         * Constructs a @c param_type from the "mean" and "beta" parameters
+         * of the distribution.
+         */
+        explicit param_type(RealType mean_arg = RealType(0.0),
+                            RealType beta_arg = RealType(1.0))
+          : _mean(mean_arg), _beta(beta_arg)
+        {}
+
+        /** Returns the "mean" parameter of the distribtuion. */
+        RealType mean() const { return _mean; }
+        /** Returns the "beta" parameter of the distribution. */
+        RealType beta() const { return _beta; }
+
+        /** Writes a @c param_type to a @c std::ostream. */
+        BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
+        { os << parm._mean << ' ' << parm._beta; 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._beta; 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._beta == rhs._beta; }
+        
+        /** Returns true if the two sets of parameters are the different. */
+        BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+
+    private:
+        RealType _mean;
+        RealType _beta;
+    };
+
+    /**
+     * Constructs an @c laplace_distribution from its "mean" and "beta" parameters.
+     */
+    explicit laplace_distribution(RealType mean_arg = RealType(0.0),
+                               RealType beta_arg = RealType(1.0))
+      : _mean(mean_arg), _beta(beta_arg)
+    {}
+    /** Constructs an @c laplace_distribution from its parameters. */
+    explicit laplace_distribution(const param_type& parm)
+      : _mean(parm.mean()), _beta(parm.beta())
+    {}
+
+    /**
+     * Returns a random variate distributed according to the
+     * laplace distribution.
+     */
+    template<class URNG>
+    RealType operator()(URNG& urng) const
+    {
+        RealType exponential = exponential_distribution<RealType>()(urng);
+        if(uniform_01<RealType>()(urng) < 0.5)
+            exponential = -exponential;
+        return _mean + _beta * exponential;
+    }
+
+    /**
+     * Returns a random variate distributed accordint to the laplace
+     * distribution with parameters specified by @c param.
+     */
+    template<class URNG>
+    RealType operator()(URNG& urng, const param_type& parm) const
+    {
+        return laplace_distribution(parm)(urng);
+    }
+
+    /** Returns the "mean" parameter of the distribution. */
+    RealType mean() const { return _mean; }
+    /** Returns the "beta" parameter of the distribution. */
+    RealType beta() const { return _beta; }
+
+    /** Returns the smallest value that the distribution can produce. */
+    RealType min BOOST_PREVENT_MACRO_SUBSTITUTION () const
+    { return RealType(-std::numeric_limits<RealType>::infinity()); }
+    /** Returns the largest value that the distribution can produce. */
+    RealType max BOOST_PREVENT_MACRO_SUBSTITUTION () const
+    { return RealType(std::numeric_limits<RealType>::infinity()); }
+
+    /** Returns the parameters of the distribution. */
+    param_type param() const { return param_type(_mean, _beta); }
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        _mean = parm.mean();
+        _beta = parm.beta();
+    }
+
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { }
+
+    /** Writes an @c laplace_distribution to a @c std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, laplace_distribution, wd)
+    {
+        os << wd.param();
+        return os;
+    }
+
+    /** Reads an @c laplace_distribution from a @c std::istream. */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, laplace_distribution, wd)
+    {
+        param_type parm;
+        if(is >> parm) {
+            wd.param(parm);
+        }
+        return is;
+    }
+
+    /**
+     * Returns true if the two instances of @c laplace_distribution will
+     * return identical sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(laplace_distribution, lhs, rhs)
+    { return lhs._mean == rhs._mean && lhs._beta == rhs._beta; }
+    
+    /**
+     * Returns true if the two instances of @c laplace_distribution will
+     * return different sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(laplace_distribution)
+
+private:
+    RealType _mean;
+    RealType _beta;
+};
+
+} // namespace random
+} // namespace boost
+
+#endif // BOOST_RANDOM_LAPLACE_DISTRIBUTION_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/linear_congruential.hpp

@@ -0,0 +1,466 @@
+/* boost random/linear_congruential.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2001-02-18  moved to individual header files
+ */
+
+#ifndef BOOST_RANDOM_LINEAR_CONGRUENTIAL_HPP
+#define BOOST_RANDOM_LINEAR_CONGRUENTIAL_HPP
+
+#include <iostream>
+#include <stdexcept>
+#include <boost/assert.hpp>
+#include <boost/config.hpp>
+#include <boost/cstdint.hpp>
+#include <boost/limits.hpp>
+#include <boost/static_assert.hpp>
+#include <boost/integer/static_log2.hpp>
+#include <boost/mpl/if.hpp>
+#include <boost/type_traits/is_arithmetic.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/const_mod.hpp>
+#include <boost/random/detail/seed.hpp>
+#include <boost/random/detail/seed_impl.hpp>
+#include <boost/detail/workaround.hpp>
+
+#include <boost/random/detail/disable_warnings.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * Instantiations of class template linear_congruential_engine model a
+ * \pseudo_random_number_generator. Linear congruential pseudo-random
+ * number generators are described in:
+ *
+ *  @blockquote
+ *  "Mathematical methods in large-scale computing units", D. H. Lehmer,
+ *  Proc. 2nd Symposium on Large-Scale Digital Calculating Machines,
+ *  Harvard University Press, 1951, pp. 141-146
+ *  @endblockquote
+ *
+ * Let x(n) denote the sequence of numbers returned by some pseudo-random
+ * number generator. Then for the linear congruential generator,
+ * x(n+1) := (a * x(n) + c) mod m. Parameters for the generator are
+ * x(0), a, c, m. The template parameter IntType shall denote an integral
+ * type. It must be large enough to hold values a, c, and m. The template
+ * parameters a and c must be smaller than m.
+ *
+ * Note: The quality of the generator crucially depends on the choice of
+ * the parameters. User code should use one of the sensibly parameterized
+ * generators such as minstd_rand instead.
+ */
+template<class IntType, IntType a, IntType c, IntType m>
+class linear_congruential_engine
+{
+public:
+    typedef IntType result_type;
+
+    // Required for old Boost.Random concept
+    BOOST_STATIC_CONSTANT(bool, has_fixed_range = false);
+
+    BOOST_STATIC_CONSTANT(IntType, multiplier = a);
+    BOOST_STATIC_CONSTANT(IntType, increment = c);
+    BOOST_STATIC_CONSTANT(IntType, modulus = m);
+    BOOST_STATIC_CONSTANT(IntType, default_seed = 1);
+    
+    BOOST_STATIC_ASSERT(std::numeric_limits<IntType>::is_integer);
+    BOOST_STATIC_ASSERT(m == 0 || a < m);
+    BOOST_STATIC_ASSERT(m == 0 || c < m);
+    
+    /**
+     * Constructs a @c linear_congruential_engine, using the default seed
+     */
+    linear_congruential_engine() { seed(); }
+
+    /**
+     * Constructs a @c linear_congruential_engine, seeding it with @c x0.
+     */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(linear_congruential_engine,
+                                               IntType, x0)
+    { seed(x0); }
+    
+    /**
+     * Constructs a @c linear_congruential_engine, seeding it with values
+     * produced by a call to @c seq.generate().
+     */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_CONSTRUCTOR(linear_congruential_engine,
+                                             SeedSeq, seq)
+    { seed(seq); }
+
+    /**
+     * Constructs a @c linear_congruential_engine  and seeds it
+     * with values taken from the itrator range [first, last)
+     * and adjusts first to point to the element after the last one
+     * used.  If there are not enough elements, throws @c std::invalid_argument.
+     *
+     * first and last must be input iterators.
+     */
+    template<class It>
+    linear_congruential_engine(It& first, It last)
+    {
+        seed(first, last);
+    }
+
+    // compiler-generated copy constructor and assignment operator are fine
+
+    /**
+     * Calls seed(default_seed)
+     */
+    void seed() { seed(default_seed); }
+
+    /**
+     * If c mod m is zero and x0 mod m is zero, changes the current value of
+     * the generator to 1. Otherwise, changes it to x0 mod m. If c is zero,
+     * distinct seeds in the range [1,m) will leave the generator in distinct
+     * states. If c is not zero, the range is [0,m).
+     */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_SEED(linear_congruential_engine, IntType, x0)
+    {
+        // wrap _x if it doesn't fit in the destination
+        if(modulus == 0) {
+            _x = x0;
+        } else {
+            _x = x0 % modulus;
+        }
+        // handle negative seeds
+        if(_x <= 0 && _x != 0) {
+            _x += modulus;
+        }
+        // adjust to the correct range
+        if(increment == 0 && _x == 0) {
+            _x = 1;
+        }
+        BOOST_ASSERT(_x >= (min)());
+        BOOST_ASSERT(_x <= (max)());
+    }
+
+    /**
+     * Seeds a @c linear_congruential_engine using values from a SeedSeq.
+     */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_SEED(linear_congruential_engine, SeedSeq, seq)
+    { seed(detail::seed_one_int<IntType, m>(seq)); }
+
+    /**
+     * seeds a @c linear_congruential_engine with values taken
+     * from the itrator range [first, last) and adjusts @c first to
+     * point to the element after the last one used.  If there are
+     * not enough elements, throws @c std::invalid_argument.
+     *
+     * @c first and @c last must be input iterators.
+     */
+    template<class It>
+    void seed(It& first, It last)
+    { seed(detail::get_one_int<IntType, m>(first, last)); }
+
+    /**
+     * Returns the smallest value that the @c linear_congruential_engine
+     * can produce.
+     */
+    static result_type min BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return c == 0 ? 1 : 0; }
+    /**
+     * Returns the largest value that the @c linear_congruential_engine
+     * can produce.
+     */
+    static result_type max BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return modulus-1; }
+
+    /** Returns the next value of the @c linear_congruential_engine. */
+    IntType operator()()
+    {
+        _x = const_mod<IntType, m>::mult_add(a, _x, c);
+        return _x;
+    }
+  
+    /** Fills a range with random values */
+    template<class Iter>
+    void generate(Iter first, Iter last)
+    { detail::generate_from_int(*this, first, last); }
+
+    /** Advances the state of the generator by @c z. */
+    void discard(boost::uintmax_t z)
+    {
+        typedef const_mod<IntType, m> mod_type;
+        IntType b_inv = mod_type::invert(a-1);
+        IntType b_gcd = mod_type::mult(a-1, b_inv);
+        if(b_gcd == 1) {
+            IntType a_z = mod_type::pow(a, z);
+            _x = mod_type::mult_add(a_z, _x, 
+                mod_type::mult(mod_type::mult(c, b_inv), a_z - 1));
+        } else {
+            // compute (a^z - 1)*c % (b_gcd * m) / (b / b_gcd) * inv(b / b_gcd)
+            // we're storing the intermediate result / b_gcd
+            IntType a_zm1_over_gcd = 0;
+            IntType a_km1_over_gcd = (a - 1) / b_gcd;
+            boost::uintmax_t exponent = z;
+            while(exponent != 0) {
+                if(exponent % 2 == 1) {
+                    a_zm1_over_gcd =
+                        mod_type::mult_add(
+                            b_gcd,
+                            mod_type::mult(a_zm1_over_gcd, a_km1_over_gcd),
+                            mod_type::add(a_zm1_over_gcd, a_km1_over_gcd));
+                }
+                a_km1_over_gcd = mod_type::mult_add(
+                    b_gcd,
+                    mod_type::mult(a_km1_over_gcd, a_km1_over_gcd),
+                    mod_type::add(a_km1_over_gcd, a_km1_over_gcd));
+                exponent /= 2;
+            }
+            
+            IntType a_z = mod_type::mult_add(b_gcd, a_zm1_over_gcd, 1);
+            IntType num = mod_type::mult(c, a_zm1_over_gcd);
+            b_inv = mod_type::invert((a-1)/b_gcd);
+            _x = mod_type::mult_add(a_z, _x, mod_type::mult(b_inv, num));
+        }
+    }
+
+    friend bool operator==(const linear_congruential_engine& x,
+                           const linear_congruential_engine& y)
+    { return x._x == y._x; }
+    friend bool operator!=(const linear_congruential_engine& x,
+                           const linear_congruential_engine& y)
+    { return !(x == y); }
+    
+#if !defined(BOOST_RANDOM_NO_STREAM_OPERATORS)
+    /** Writes a @c linear_congruential_engine to a @c std::ostream. */
+    template<class CharT, class Traits>
+    friend std::basic_ostream<CharT,Traits>&
+    operator<<(std::basic_ostream<CharT,Traits>& os,
+               const linear_congruential_engine& lcg)
+    {
+        return os << lcg._x;
+    }
+
+    /** Reads a @c linear_congruential_engine from a @c std::istream. */
+    template<class CharT, class Traits>
+    friend std::basic_istream<CharT,Traits>&
+    operator>>(std::basic_istream<CharT,Traits>& is,
+               linear_congruential_engine& lcg)
+    {
+        lcg.read(is);
+        return is;
+    }
+#endif
+
+private:
+
+    /// \cond show_private
+
+    template<class CharT, class Traits>
+    void read(std::basic_istream<CharT, Traits>& is) {
+        IntType x;
+        if(is >> x) {
+            if(x >= (min)() && x <= (max)()) {
+                _x = x;
+            } else {
+                is.setstate(std::ios_base::failbit);
+            }
+        }
+    }
+
+    /// \endcond
+
+    IntType _x;
+};
+
+#ifndef BOOST_NO_INCLASS_MEMBER_INITIALIZATION
+//  A definition is required even for integral static constants
+template<class IntType, IntType a, IntType c, IntType m>
+const bool linear_congruential_engine<IntType, a, c, m>::has_fixed_range;
+template<class IntType, IntType a, IntType c, IntType m>
+const IntType linear_congruential_engine<IntType,a,c,m>::multiplier;
+template<class IntType, IntType a, IntType c, IntType m>
+const IntType linear_congruential_engine<IntType,a,c,m>::increment;
+template<class IntType, IntType a, IntType c, IntType m>
+const IntType linear_congruential_engine<IntType,a,c,m>::modulus;
+template<class IntType, IntType a, IntType c, IntType m>
+const IntType linear_congruential_engine<IntType,a,c,m>::default_seed;
+#endif
+
+/// \cond show_deprecated
+
+// provided for backwards compatibility
+template<class IntType, IntType a, IntType c, IntType m, IntType val = 0>
+class linear_congruential : public linear_congruential_engine<IntType, a, c, m>
+{
+    typedef linear_congruential_engine<IntType, a, c, m> base_type;
+public:
+    linear_congruential(IntType x0 = 1) : base_type(x0) {}
+    template<class It>
+    linear_congruential(It& first, It last) : base_type(first, last) {}
+};
+
+/// \endcond
+
+/**
+ * The specialization \minstd_rand0 was originally suggested in
+ *
+ *  @blockquote
+ *  A pseudo-random number generator for the System/360, P.A. Lewis,
+ *  A.S. Goodman, J.M. Miller, IBM Systems Journal, Vol. 8, No. 2,
+ *  1969, pp. 136-146
+ *  @endblockquote
+ *
+ * It is examined more closely together with \minstd_rand in
+ *
+ *  @blockquote
+ *  "Random Number Generators: Good ones are hard to find",
+ *  Stephen K. Park and Keith W. Miller, Communications of
+ *  the ACM, Vol. 31, No. 10, October 1988, pp. 1192-1201 
+ *  @endblockquote
+ */
+typedef linear_congruential_engine<uint32_t, 16807, 0, 2147483647> minstd_rand0;
+
+/** The specialization \minstd_rand was suggested in
+ *
+ *  @blockquote
+ *  "Random Number Generators: Good ones are hard to find",
+ *  Stephen K. Park and Keith W. Miller, Communications of
+ *  the ACM, Vol. 31, No. 10, October 1988, pp. 1192-1201
+ *  @endblockquote
+ */
+typedef linear_congruential_engine<uint32_t, 48271, 0, 2147483647> minstd_rand;
+
+
+#if !defined(BOOST_NO_INT64_T) && !defined(BOOST_NO_INTEGRAL_INT64_T)
+/**
+ * Class @c rand48 models a \pseudo_random_number_generator. It uses
+ * the linear congruential algorithm with the parameters a = 0x5DEECE66D,
+ * c = 0xB, m = 2**48. It delivers identical results to the @c lrand48()
+ * function available on some systems (assuming lcong48 has not been called).
+ *
+ * It is only available on systems where @c uint64_t is provided as an
+ * integral type, so that for example static in-class constants and/or
+ * enum definitions with large @c uint64_t numbers work.
+ */
+class rand48 
+{
+public:
+    typedef boost::uint32_t result_type;
+
+    BOOST_STATIC_CONSTANT(bool, has_fixed_range = false);
+    /**
+     * Returns the smallest value that the generator can produce
+     */
+    static uint32_t min BOOST_PREVENT_MACRO_SUBSTITUTION () { return 0; }
+    /**
+     * Returns the largest value that the generator can produce
+     */
+    static uint32_t max BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return 0x7FFFFFFF; }
+  
+    /** Seeds the generator with the default seed. */
+    rand48() : lcf(cnv(static_cast<uint32_t>(1))) {}
+    /**
+     * Constructs a \rand48 generator with x(0) := (x0 << 16) | 0x330e.
+     */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(rand48, result_type, x0)
+    { seed(x0); }
+    /**
+     * Seeds the generator with values produced by @c seq.generate().
+     */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_CONSTRUCTOR(rand48, SeedSeq, seq)
+    { seed(seq); }
+    /**
+     * Seeds the generator using values from an iterator range,
+     * and updates first to point one past the last value consumed.
+     */
+    template<class It> rand48(It& first, It last) : lcf(first, last) { }
+
+    // compiler-generated copy ctor and assignment operator are fine
+
+    /** Seeds the generator with the default seed. */
+    void seed() { seed(static_cast<uint32_t>(1)); }
+    /**
+     * Changes the current value x(n) of the generator to (x0 << 16) | 0x330e.
+     */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_SEED(rand48, result_type, x0)
+    { lcf.seed(cnv(x0)); }
+    /**
+     * Seeds the generator using values from an iterator range,
+     * and updates first to point one past the last value consumed.
+     */
+    template<class It> void seed(It& first, It last) { lcf.seed(first,last); }
+    /**
+     * Seeds the generator with values produced by @c seq.generate().
+     */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_SEED(rand48, SeedSeq, seq)
+    { lcf.seed(seq); }
+
+    /**  Returns the next value of the generator. */
+    uint32_t operator()() { return static_cast<uint32_t>(lcf() >> 17); }
+    
+    /** Advances the state of the generator by @c z. */
+    void discard(boost::uintmax_t z) { lcf.discard(z); }
+  
+    /** Fills a range with random values */
+    template<class Iter>
+    void generate(Iter first, Iter last)
+    {
+        for(; first != last; ++first) {
+            *first = (*this)();
+        }
+    }
+
+#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
+    /**  Writes a @c rand48 to a @c std::ostream. */
+    template<class CharT,class Traits>
+    friend std::basic_ostream<CharT,Traits>&
+    operator<<(std::basic_ostream<CharT,Traits>& os, const rand48& r)
+    { os << r.lcf; return os; }
+
+    /** Reads a @c rand48 from a @c std::istream. */
+    template<class CharT,class Traits>
+    friend std::basic_istream<CharT,Traits>&
+    operator>>(std::basic_istream<CharT,Traits>& is, rand48& r)
+    { is >> r.lcf; return is; }
+#endif
+
+    /**
+     * Returns true if the two generators will produce identical
+     * sequences of values.
+     */
+    friend bool operator==(const rand48& x, const rand48& y)
+    { return x.lcf == y.lcf; }
+    /**
+     * Returns true if the two generators will produce different
+     * sequences of values.
+     */
+    friend bool operator!=(const rand48& x, const rand48& y)
+    { return !(x == y); }
+private:
+    /// \cond show_private
+    typedef random::linear_congruential_engine<uint64_t,
+        // xxxxULL is not portable
+        uint64_t(0xDEECE66DUL) | (uint64_t(0x5) << 32),
+        0xB, uint64_t(1)<<48> lcf_t;
+    lcf_t lcf;
+
+    static boost::uint64_t cnv(boost::uint32_t x)
+    { return (static_cast<uint64_t>(x) << 16) | 0x330e; }
+    /// \endcond
+};
+#endif /* !BOOST_NO_INT64_T && !BOOST_NO_INTEGRAL_INT64_T */
+
+} // namespace random
+
+using random::minstd_rand0;
+using random::minstd_rand;
+using random::rand48;
+
+} // namespace boost
+
+#include <boost/random/detail/enable_warnings.hpp>
+
+#endif // BOOST_RANDOM_LINEAR_CONGRUENTIAL_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/linear_feedback_shift.hpp

@@ -0,0 +1,217 @@
+/* boost random/linear_feedback_shift.hpp header file
+ *
+ * Copyright Jens Maurer 2002
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ *
+ */
+
+#ifndef BOOST_RANDOM_LINEAR_FEEDBACK_SHIFT_HPP
+#define BOOST_RANDOM_LINEAR_FEEDBACK_SHIFT_HPP
+
+#include <iosfwd>
+#include <stdexcept>
+#include <boost/config.hpp>
+#include <boost/cstdint.hpp>
+#include <boost/static_assert.hpp>
+#include <boost/integer/integer_mask.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/seed.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/detail/seed_impl.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * Instatiations of @c linear_feedback_shift model a
+ * \pseudo_random_number_generator.  It was originally
+ * proposed in
+ *
+ *  @blockquote
+ *  "Random numbers generated by linear recurrence modulo two.",
+ *  Tausworthe, R. C.(1965), Mathematics of Computation 19, 201-209.
+ *  @endblockquote
+ */
+template<class UIntType, int w, int k, int q, int s>
+class linear_feedback_shift_engine
+{
+public:
+    typedef UIntType result_type;
+    BOOST_STATIC_CONSTANT(bool, has_fixed_range = false);
+    BOOST_STATIC_CONSTANT(int, word_size = w);
+    BOOST_STATIC_CONSTANT(int, exponent1 = k);
+    BOOST_STATIC_CONSTANT(int, exponent2 = q);
+    BOOST_STATIC_CONSTANT(int, step_size = s);
+    BOOST_STATIC_CONSTANT(UIntType, default_seed = 341);
+
+    /** Returns the smallest value that the generator can produce. */
+    static result_type min BOOST_PREVENT_MACRO_SUBSTITUTION () { return 0; }
+    /** Returns the largest value that the generator can produce. */
+    static result_type max BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return wordmask(); }
+
+    BOOST_STATIC_ASSERT(w > 0);
+    BOOST_STATIC_ASSERT(q > 0);
+    BOOST_STATIC_ASSERT(k < w);
+    BOOST_STATIC_ASSERT(0 < 2*q && 2*q < k);
+    BOOST_STATIC_ASSERT(0 < s && s <= k-q);
+
+    /** Constructs a @c linear_feedback_shift_engine, using the default seed. */
+    linear_feedback_shift_engine() { seed(); }
+    
+    /** Constructs a @c linear_feedback_shift_engine, seeding it with s0. */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(linear_feedback_shift_engine,
+        UIntType, s0)
+    { seed(s0); }
+    
+    /** Constructs a @c linear_feedback_shift_engine, seeding it with seq. */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_CONSTRUCTOR(linear_feedback_shift_engine,
+        SeedSeq, seq)
+    { seed(seq); }
+    
+    /**
+     * Constructs a @c linear_feedback_shift_engine, seeding it with 
+     * values from the range [first, last).
+     */
+    template<class It> linear_feedback_shift_engine(It& first, It last)
+    { seed(first, last); }
+    
+    /** Seeds a @c linear_feedback_shift_engine with the default seed. */
+    void seed() {  seed(default_seed); }
+    
+    /** Seeds a @c linear_feedback_shift_engine with @c s0. */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_SEED(linear_feedback_shift_engine,
+        UIntType, s0)
+    {
+        value = s0 & wordmask();
+        if(value < (1 << (w-k))) {
+            value += 1 << (w-k);
+        }
+    }
+    
+    /**
+     * Seeds a @c linear_feedback_shift_engine with values
+     * produced by @c seq.generate().
+     */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_SEED(linear_feedback_shift_engine,
+        SeedSeq, seq)
+    { seed(detail::seed_one_int<UIntType, (UIntType(2) << (w - 1))>(seq)); }
+    
+    /**
+     * Seeds a @c linear_feedback_shift_engine with values
+     * from the range [first, last).
+     */
+    template<class It> void seed(It& first, It last)
+    {
+        seed(detail::get_one_int<UIntType, (UIntType(2) << (w - 1))>(first, last));
+    }
+
+    /** Returns the next value of the generator. */
+    result_type operator()()
+    {
+        const UIntType b = (((value << q) ^ value) & wordmask()) >> (k-s);
+        const UIntType mask = (wordmask() << (w-k)) & wordmask();
+        value = ((value & mask) << s) ^ b;
+        return value;
+    }
+  
+    /** Fills a range with random values */
+    template<class Iter>
+    void generate(Iter first, Iter last)
+    { detail::generate_from_int(*this, first, last); }
+
+    /** Advances the state of the generator by @c z. */
+    void discard(boost::uintmax_t z)
+    {
+        for(boost::uintmax_t j = 0; j < z; ++j) {
+            (*this)();
+        }
+    }
+    
+    /**
+     * Writes the textual representation of the generator to a @c std::ostream.
+     */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, linear_feedback_shift_engine, x)
+    {
+        os << x.value;
+        return os;
+    }
+    
+    /**
+     * Reads the textual representation of the generator from a @c std::istream.
+     */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, linear_feedback_shift_engine, x)
+    {
+        is >> x.value;
+        return is;
+    }
+
+    /**
+     * Returns true if the two generators will produce identical
+     * sequences of outputs.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(linear_feedback_shift_engine, x, y)
+    { return x.value == y.value; }
+    
+    /**
+     * Returns true if the two generators will produce different
+     * sequences of outputs.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(linear_feedback_shift_engine)
+
+private:
+    /// \cond show_private
+    static UIntType wordmask() { return boost::low_bits_mask_t<w>::sig_bits; }
+    /// \endcond
+    UIntType value;
+};
+
+#ifndef BOOST_NO_INCLASS_MEMBER_INITIALIZATION
+//  A definition is required even for integral static constants
+template<class UIntType, int w, int k, int q, int s>
+const bool linear_feedback_shift_engine<UIntType, w, k, q, s>::has_fixed_range;
+template<class UIntType, int w, int k, int q, int s>
+const int linear_feedback_shift_engine<UIntType, w, k, q, s>::word_size;
+template<class UIntType, int w, int k, int q, int s>
+const int linear_feedback_shift_engine<UIntType, w, k, q, s>::exponent1;
+template<class UIntType, int w, int k, int q, int s>
+const int linear_feedback_shift_engine<UIntType, w, k, q, s>::exponent2;
+template<class UIntType, int w, int k, int q, int s>
+const int linear_feedback_shift_engine<UIntType, w, k, q, s>::step_size;
+template<class UIntType, int w, int k, int q, int s>
+const UIntType linear_feedback_shift_engine<UIntType, w, k, q, s>::default_seed;
+#endif
+
+/// \cond show_deprecated
+
+/** Provided for backwards compatibility. */
+template<class UIntType, int w, int k, int q, int s, UIntType v = 0>
+class linear_feedback_shift :
+    public linear_feedback_shift_engine<UIntType, w, k, q, s>
+{
+    typedef linear_feedback_shift_engine<UIntType, w, k, q, s> base_type;
+public:
+    linear_feedback_shift() {}
+    BOOST_RANDOM_DETAIL_SEED_SEQ_CONSTRUCTOR(linear_feedback_shift,
+        SeedSeq, seq)
+    { seed(seq); }
+    BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(linear_feedback_shift,
+        UIntType, val)
+    { seed(val); }
+    template<class It>
+    linear_feedback_shift(It& first, It last) : base_type(first, last) {}
+};
+
+/// \endcond
+
+} // namespace random
+} // namespace boost
+
+#endif // BOOST_RANDOM_LINEAR_FEEDBACK_SHIFT_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/lognormal_distribution.hpp

@@ -0,0 +1,254 @@
+/* boost random/lognormal_distribution.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2001-02-18  moved to individual header files
+ */
+
+#ifndef BOOST_RANDOM_LOGNORMAL_DISTRIBUTION_HPP
+#define BOOST_RANDOM_LOGNORMAL_DISTRIBUTION_HPP
+
+#include <boost/config/no_tr1/cmath.hpp>      // std::exp, std::sqrt
+#include <cassert>
+#include <iosfwd>
+#include <istream>
+#include <boost/limits.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/normal_distribution.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * Instantiations of class template lognormal_distribution model a
+ * \random_distribution. Such a distribution produces random numbers
+ * with \f$\displaystyle p(x) = \frac{1}{x s \sqrt{2\pi}} e^{\frac{-\left(\log(x)-m\right)^2}{2s^2}}\f$
+ * for x > 0.
+ *
+ * @xmlwarning
+ * This distribution has been updated to match the C++ standard.
+ * Its behavior has changed from the original
+ * boost::lognormal_distribution.  A backwards compatible
+ * version is provided in namespace boost.
+ * @endxmlwarning
+ */
+template<class RealType = double>
+class lognormal_distribution
+{
+public:
+    typedef typename normal_distribution<RealType>::input_type input_type;
+    typedef RealType result_type;
+
+    class param_type
+    {
+    public:
+
+        typedef lognormal_distribution distribution_type;
+
+        /** Constructs the parameters of a lognormal_distribution. */
+        explicit param_type(RealType m_arg = RealType(0.0),
+                            RealType s_arg = RealType(1.0))
+          : _m(m_arg), _s(s_arg) {}
+
+        /** Returns the "m" parameter of the distribution. */
+        RealType m() const { return _m; }
+
+        /** Returns the "s" parameter of the distribution. */
+        RealType s() const { return _s; }
+
+        /** Writes the parameters to a std::ostream. */
+        BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
+        {
+            os << parm._m << " " << parm._s;
+            return os;
+        }
+
+        /** Reads the parameters from a std::istream. */
+        BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
+        {
+            is >> parm._m >> std::ws >> parm._s;
+            return is;
+        }
+
+        /** Returns true if the two sets of parameters are equal. */
+        BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
+        { return lhs._m == rhs._m && lhs._s == rhs._s; }
+
+        /** Returns true if the two sets of parameters are different. */
+        BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+
+    private:
+        RealType _m;
+        RealType _s;
+    };
+
+    /**
+     * Constructs a lognormal_distribution. @c m and @c s are the
+     * parameters of the distribution.
+     */
+    explicit lognormal_distribution(RealType m_arg = RealType(0.0),
+                                    RealType s_arg = RealType(1.0))
+      : _normal(m_arg, s_arg) {}
+
+    /**
+     * Constructs a lognormal_distribution from its parameters.
+     */
+    explicit lognormal_distribution(const param_type& parm)
+      : _normal(parm.m(), parm.s()) {}
+
+    // compiler-generated copy ctor and assignment operator are fine
+
+    /** Returns the m parameter of the distribution. */
+    RealType m() const { return _normal.mean(); }
+    /** Returns the s parameter of the distribution. */
+    RealType s() const { return _normal.sigma(); }
+
+    /** Returns the smallest value that the distribution can produce. */
+    RealType min BOOST_PREVENT_MACRO_SUBSTITUTION () const
+    { return RealType(0); }
+    /** 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(m(), s()); }
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        typedef normal_distribution<RealType> normal_type;
+        typename normal_type::param_type normal_param(parm.m(), parm.s());
+        _normal.param(normal_param);
+    }
+    
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { _normal.reset(); }
+
+    /**
+     * Returns a random variate distributed according to the
+     * lognormal distribution.
+     */
+    template<class Engine>
+    result_type operator()(Engine& eng)
+    {
+        using std::exp;
+        return exp(_normal(eng));
+    }
+
+    /**
+     * Returns a random variate distributed according to the
+     * lognormal distribution with parameters specified by param.
+     */
+    template<class Engine>
+    result_type operator()(Engine& eng, const param_type& parm)
+    { return lognormal_distribution(parm)(eng); }
+
+    /** Writes the distribution to a @c std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, lognormal_distribution, ld)
+    {
+        os << ld._normal;
+        return os;
+    }
+
+    /** Reads the distribution from a @c std::istream. */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, lognormal_distribution, ld)
+    {
+        is >> ld._normal;
+        return is;
+    }
+
+    /**
+     * Returns true if the two distributions will produce identical
+     * sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(lognormal_distribution, lhs, rhs)
+    { return lhs._normal == rhs._normal; }
+
+    /**
+     * Returns true if the two distributions may produce different
+     * sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(lognormal_distribution)
+
+private:
+    normal_distribution<result_type> _normal;
+};
+
+} // namespace random
+
+/// \cond show_deprecated
+
+/**
+ * Provided for backwards compatibility.  This class is
+ * deprecated.  It provides the old behavior of lognormal_distribution with
+ * \f$\displaystyle p(x) = \frac{1}{x \sigma_N \sqrt{2\pi}} e^{\frac{-\left(\log(x)-\mu_N\right)^2}{2\sigma_N^2}}\f$
+ * for x > 0, where \f$\displaystyle \mu_N = \log\left(\frac{\mu^2}{\sqrt{\sigma^2 + \mu^2}}\right)\f$ and
+ * \f$\displaystyle \sigma_N = \sqrt{\log\left(1 + \frac{\sigma^2}{\mu^2}\right)}\f$.
+ */
+template<class RealType = double>
+class lognormal_distribution
+{
+public:
+    typedef typename normal_distribution<RealType>::input_type input_type;
+    typedef RealType result_type;
+
+    lognormal_distribution(RealType mean_arg = RealType(1.0),
+                           RealType sigma_arg = RealType(1.0))
+      : _mean(mean_arg), _sigma(sigma_arg)
+    {
+        init();
+    }
+    RealType mean() const { return _mean; }
+    RealType sigma() const { return _sigma; }
+    void reset() { _normal.reset(); }
+    template<class Engine>
+    RealType operator()(Engine& eng)
+    {
+        using std::exp;
+        return exp(_normal(eng) * _nsigma + _nmean);
+    }
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, lognormal_distribution, ld)
+    {
+        os << ld._normal << " " << ld._mean << " " << ld._sigma;
+        return os;
+    }
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, lognormal_distribution, ld)
+    {
+        is >> ld._normal >> std::ws >> ld._mean >> std::ws >> ld._sigma;
+        ld.init();
+        return is;
+    }
+private:
+    /// \cond show_private
+    void init()
+    {
+        using std::log;
+        using std::sqrt;
+        _nmean = log(_mean*_mean/sqrt(_sigma*_sigma + _mean*_mean));
+        _nsigma = sqrt(log(_sigma*_sigma/_mean/_mean+result_type(1)));
+    }
+    RealType _mean;
+    RealType _sigma;
+    RealType _nmean;
+    RealType _nsigma;
+    normal_distribution<RealType> _normal;
+    /// \endcond
+};
+
+/// \endcond
+
+} // namespace boost
+
+#endif // BOOST_RANDOM_LOGNORMAL_DISTRIBUTION_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/mersenne_twister.hpp

@@ -0,0 +1,682 @@
+/* boost random/mersenne_twister.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * Copyright Steven Watanabe 2010
+ * 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2013-10-14  fixed some warnings with Wshadow (mgaunard)
+ *  2001-02-18  moved to individual header files
+ */
+
+#ifndef BOOST_RANDOM_MERSENNE_TWISTER_HPP
+#define BOOST_RANDOM_MERSENNE_TWISTER_HPP
+
+#include <iosfwd>
+#include <istream>
+#include <stdexcept>
+#include <boost/config.hpp>
+#include <boost/cstdint.hpp>
+#include <boost/integer/integer_mask.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/ptr_helper.hpp>
+#include <boost/random/detail/seed.hpp>
+#include <boost/random/detail/seed_impl.hpp>
+#include <boost/random/detail/generator_seed_seq.hpp>
+#include <boost/random/detail/polynomial.hpp>
+
+#include <boost/random/detail/disable_warnings.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * Instantiations of class template mersenne_twister_engine model a
+ * \pseudo_random_number_generator. It uses the algorithm described in
+ *
+ *  @blockquote
+ *  "Mersenne Twister: A 623-dimensionally equidistributed uniform
+ *  pseudo-random number generator", Makoto Matsumoto and Takuji Nishimura,
+ *  ACM Transactions on Modeling and Computer Simulation: Special Issue on
+ *  Uniform Random Number Generation, Vol. 8, No. 1, January 1998, pp. 3-30.
+ *  @endblockquote
+ *
+ * @xmlnote
+ * The boost variant has been implemented from scratch and does not
+ * derive from or use mt19937.c provided on the above WWW site. However, it
+ * was verified that both produce identical output.
+ * @endxmlnote
+ *
+ * The seeding from an integer was changed in April 2005 to address a
+ * <a href="http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/MT2002/emt19937ar.html">weakness</a>.
+ *
+ * The quality of the generator crucially depends on the choice of the
+ * parameters.  User code should employ one of the sensibly parameterized
+ * generators such as \mt19937 instead.
+ *
+ * The generator requires considerable amounts of memory for the storage of
+ * its state array. For example, \mt11213b requires about 1408 bytes and
+ * \mt19937 requires about 2496 bytes.
+ */
+template<class UIntType,
+         std::size_t w, std::size_t n, std::size_t m, std::size_t r,
+         UIntType a, std::size_t u, UIntType d, std::size_t s,
+         UIntType b, std::size_t t,
+         UIntType c, std::size_t l, UIntType f>
+class mersenne_twister_engine
+{
+public:
+    typedef UIntType result_type;
+    BOOST_STATIC_CONSTANT(std::size_t, word_size = w);
+    BOOST_STATIC_CONSTANT(std::size_t, state_size = n);
+    BOOST_STATIC_CONSTANT(std::size_t, shift_size = m);
+    BOOST_STATIC_CONSTANT(std::size_t, mask_bits = r);
+    BOOST_STATIC_CONSTANT(UIntType, xor_mask = a);
+    BOOST_STATIC_CONSTANT(std::size_t, tempering_u = u);
+    BOOST_STATIC_CONSTANT(UIntType, tempering_d = d);
+    BOOST_STATIC_CONSTANT(std::size_t, tempering_s = s);
+    BOOST_STATIC_CONSTANT(UIntType, tempering_b = b);
+    BOOST_STATIC_CONSTANT(std::size_t, tempering_t = t);
+    BOOST_STATIC_CONSTANT(UIntType, tempering_c = c);
+    BOOST_STATIC_CONSTANT(std::size_t, tempering_l = l);
+    BOOST_STATIC_CONSTANT(UIntType, initialization_multiplier = f);
+    BOOST_STATIC_CONSTANT(UIntType, default_seed = 5489u);
+
+    // backwards compatibility
+    BOOST_STATIC_CONSTANT(UIntType, parameter_a = a);
+    BOOST_STATIC_CONSTANT(std::size_t, output_u = u);
+    BOOST_STATIC_CONSTANT(std::size_t, output_s = s);
+    BOOST_STATIC_CONSTANT(UIntType, output_b = b);
+    BOOST_STATIC_CONSTANT(std::size_t, output_t = t);
+    BOOST_STATIC_CONSTANT(UIntType, output_c = c);
+    BOOST_STATIC_CONSTANT(std::size_t, output_l = l);
+
+    // old Boost.Random concept requirements
+    BOOST_STATIC_CONSTANT(bool, has_fixed_range = false);
+
+
+    /**
+     * Constructs a @c mersenne_twister_engine and calls @c seed().
+     */
+    mersenne_twister_engine() { seed(); }
+
+    /**
+     * Constructs a @c mersenne_twister_engine and calls @c seed(value).
+     */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(mersenne_twister_engine,
+                                               UIntType, value)
+    { seed(value); }
+    template<class It> mersenne_twister_engine(It& first, It last)
+    { seed(first,last); }
+
+    /**
+     * Constructs a mersenne_twister_engine and calls @c seed(gen).
+     *
+     * @xmlnote
+     * The copy constructor will always be preferred over
+     * the templated constructor.
+     * @endxmlnote
+     */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_CONSTRUCTOR(mersenne_twister_engine,
+                                             SeedSeq, seq)
+    { seed(seq); }
+
+    // compiler-generated copy ctor and assignment operator are fine
+
+    /** Calls @c seed(default_seed). */
+    void seed() { seed(default_seed); }
+
+    /**
+     * Sets the state x(0) to v mod 2w. Then, iteratively,
+     * sets x(i) to
+     * (i + f * (x(i-1) xor (x(i-1) rshift w-2))) mod 2<sup>w</sup>
+     * for i = 1 .. n-1. x(n) is the first value to be returned by operator().
+     */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_SEED(mersenne_twister_engine, UIntType, value)
+    {
+        // New seeding algorithm from
+        // http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/MT2002/emt19937ar.html
+        // In the previous versions, MSBs of the seed affected only MSBs of the
+        // state x[].
+        const UIntType mask = (max)();
+        x[0] = value & mask;
+        for (i = 1; i < n; i++) {
+            // See Knuth "The Art of Computer Programming"
+            // Vol. 2, 3rd ed., page 106
+            x[i] = (f * (x[i-1] ^ (x[i-1] >> (w-2))) + i) & mask;
+        }
+
+        normalize_state();
+    }
+
+    /**
+     * Seeds a mersenne_twister_engine using values produced by seq.generate().
+     */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_SEED(mersenne_twister_engine, SeeqSeq, seq)
+    {
+        detail::seed_array_int<w>(seq, x);
+        i = n;
+
+        normalize_state();
+    }
+
+    /** Sets the state of the generator using values from an iterator range. */
+    template<class It>
+    void seed(It& first, It last)
+    {
+        detail::fill_array_int<w>(first, last, x);
+        i = n;
+
+        normalize_state();
+    }
+
+    /** Returns the smallest value that the generator can produce. */
+    static result_type min BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return 0; }
+    /** Returns the largest value that the generator can produce. */
+    static result_type max BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return boost::low_bits_mask_t<w>::sig_bits; }
+
+    /** Produces the next value of the generator. */
+    result_type operator()();
+
+    /** Fills a range with random values */
+    template<class Iter>
+    void generate(Iter first, Iter last)
+    { detail::generate_from_int(*this, first, last); }
+
+    /**
+     * Advances the state of the generator by @c z steps.  Equivalent to
+     *
+     * @code
+     * for(unsigned long long i = 0; i < z; ++i) {
+     *     gen();
+     * }
+     * @endcode
+     */
+    void discard(boost::uintmax_t z)
+    {
+#ifndef BOOST_RANDOM_MERSENNE_TWISTER_DISCARD_THRESHOLD
+#define BOOST_RANDOM_MERSENNE_TWISTER_DISCARD_THRESHOLD 10000000
+#endif
+        if(z > BOOST_RANDOM_MERSENNE_TWISTER_DISCARD_THRESHOLD) {
+            discard_many(z);
+        } else {
+            for(boost::uintmax_t j = 0; j < z; ++j) {
+                (*this)();
+            }
+        }
+    }
+
+#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
+    /** Writes a mersenne_twister_engine to a @c std::ostream */
+    template<class CharT, class Traits>
+    friend std::basic_ostream<CharT,Traits>&
+    operator<<(std::basic_ostream<CharT,Traits>& os,
+               const mersenne_twister_engine& mt)
+    {
+        mt.print(os);
+        return os;
+    }
+
+    /** Reads a mersenne_twister_engine from a @c std::istream */
+    template<class CharT, class Traits>
+    friend std::basic_istream<CharT,Traits>&
+    operator>>(std::basic_istream<CharT,Traits>& is,
+               mersenne_twister_engine& mt)
+    {
+        for(std::size_t j = 0; j < mt.state_size; ++j)
+            is >> mt.x[j] >> std::ws;
+        // MSVC (up to 7.1) and Borland (up to 5.64) don't handle the template
+        // value parameter "n" available from the class template scope, so use
+        // the static constant with the same value
+        mt.i = mt.state_size;
+        return is;
+    }
+#endif
+
+    /**
+     * Returns true if the two generators are in the same state,
+     * and will thus produce identical sequences.
+     */
+    friend bool operator==(const mersenne_twister_engine& x_,
+                           const mersenne_twister_engine& y_)
+    {
+        if(x_.i < y_.i) return x_.equal_imp(y_);
+        else return y_.equal_imp(x_);
+    }
+
+    /**
+     * Returns true if the two generators are in different states.
+     */
+    friend bool operator!=(const mersenne_twister_engine& x_,
+                           const mersenne_twister_engine& y_)
+    { return !(x_ == y_); }
+
+private:
+    /// \cond show_private
+
+    void twist();
+
+    /**
+     * Does the work of operator==.  This is in a member function
+     * for portability.  Some compilers, such as msvc 7.1 and
+     * Sun CC 5.10 can't access template parameters or static
+     * members of the class from inline friend functions.
+     *
+     * requires i <= other.i
+     */
+    bool equal_imp(const mersenne_twister_engine& other) const
+    {
+        UIntType back[n];
+        std::size_t offset = other.i - i;
+        for(std::size_t j = 0; j + offset < n; ++j)
+            if(x[j] != other.x[j+offset])
+                return false;
+        rewind(&back[n-1], offset);
+        for(std::size_t j = 0; j < offset; ++j)
+            if(back[j + n - offset] != other.x[j])
+                return false;
+        return true;
+    }
+
+    /**
+     * Does the work of operator<<.  This is in a member function
+     * for portability.
+     */
+    template<class CharT, class Traits>
+    void print(std::basic_ostream<CharT, Traits>& os) const
+    {
+        UIntType data[n];
+        for(std::size_t j = 0; j < i; ++j) {
+            data[j + n - i] = x[j];
+        }
+        if(i != n) {
+            rewind(&data[n - i - 1], n - i);
+        }
+        os << data[0];
+        for(std::size_t j = 1; j < n; ++j) {
+            os << ' ' << data[j];
+        }
+    }
+
+    /**
+     * Copies z elements of the state preceding x[0] into
+     * the array whose last element is last.
+     */
+    void rewind(UIntType* last, std::size_t z) const
+    {
+        const UIntType upper_mask = (~static_cast<UIntType>(0)) << r;
+        const UIntType lower_mask = ~upper_mask;
+        UIntType y0 = x[m-1] ^ x[n-1];
+        if(y0 & (static_cast<UIntType>(1) << (w-1))) {
+            y0 = ((y0 ^ a) << 1) | 1;
+        } else {
+            y0 = y0 << 1;
+        }
+        for(std::size_t sz = 0; sz < z; ++sz) {
+            UIntType y1 =
+                rewind_find(last, sz, m-1) ^ rewind_find(last, sz, n-1);
+            if(y1 & (static_cast<UIntType>(1) << (w-1))) {
+                y1 = ((y1 ^ a) << 1) | 1;
+            } else {
+                y1 = y1 << 1;
+            }
+            *(last - sz) = (y0 & upper_mask) | (y1 & lower_mask);
+            y0 = y1;
+        }
+    }
+
+    /**
+     * Converts an arbitrary array into a valid generator state.
+     * First we normalize x[0], so that it contains the same
+     * value we would get by running the generator forwards
+     * and then in reverse.  (The low order r bits are redundant).
+     * Then, if the state consists of all zeros, we set the
+     * high order bit of x[0] to 1.  This function only needs to
+     * be called by seed, since the state transform preserves
+     * this relationship.
+     */
+    void normalize_state()
+    {
+        const UIntType upper_mask = (~static_cast<UIntType>(0)) << r;
+        const UIntType lower_mask = ~upper_mask;
+        UIntType y0 = x[m-1] ^ x[n-1];
+        if(y0 & (static_cast<UIntType>(1) << (w-1))) {
+            y0 = ((y0 ^ a) << 1) | 1;
+        } else {
+            y0 = y0 << 1;
+        }
+        x[0] = (x[0] & upper_mask) | (y0 & lower_mask);
+
+        // fix up the state if it's all zeroes.
+        for(std::size_t j = 0; j < n; ++j) {
+            if(x[j] != 0) return;
+        }
+        x[0] = static_cast<UIntType>(1) << (w-1);
+    }
+
+    /**
+     * Given a pointer to the last element of the rewind array,
+     * and the current size of the rewind array, finds an element
+     * relative to the next available slot in the rewind array.
+     */
+    UIntType
+    rewind_find(UIntType* last, std::size_t size, std::size_t j) const
+    {
+        std::size_t index = (j + n - size + n - 1) % n;
+        if(index < n - size) {
+            return x[index];
+        } else {
+            return *(last - (n - 1 - index));
+        }
+    }
+
+    /**
+     * Optimized algorithm for large jumps.
+     *
+     * Hiroshi Haramoto, Makoto Matsumoto, and Pierre L'Ecuyer. 2008.
+     * A Fast Jump Ahead Algorithm for Linear Recurrences in a Polynomial
+     * Space. In Proceedings of the 5th international conference on
+     * Sequences and Their Applications (SETA '08).
+     * DOI=10.1007/978-3-540-85912-3_26
+     */
+    void discard_many(boost::uintmax_t z)
+    {
+        // Compute the minimal polynomial, phi(t)
+        // This depends only on the transition function,
+        // which is constant.  The characteristic
+        // polynomial is the same as the minimal
+        // polynomial for a maximum period generator
+        // (which should be all specializations of
+        // mersenne_twister.)  Even if it weren't,
+        // the characteristic polynomial is guaranteed
+        // to be a multiple of the minimal polynomial,
+        // which is good enough.
+        detail::polynomial phi = get_characteristic_polynomial();
+
+        // calculate g(t) = t^z % phi(t)
+        detail::polynomial g = mod_pow_x(z, phi);
+
+        // h(s_0, t) = \sum_{i=0}^{2k-1}o(s_i)t^{2k-i-1}
+        detail::polynomial h;
+        const std::size_t num_bits = w*n - r;
+        for(std::size_t j = 0; j < num_bits * 2; ++j) {
+            // Yes, we're advancing the generator state
+            // here, but it doesn't matter because
+            // we're going to overwrite it completely
+            // in reconstruct_state.
+            if(i >= n) twist();
+            h[2*num_bits - j - 1] = x[i++] & UIntType(1);
+        }
+        // g(t)h(s_0, t)
+        detail::polynomial gh = g * h;
+        detail::polynomial result;
+        for(std::size_t j = 0; j <= num_bits; ++j) {
+            result[j] = gh[2*num_bits - j - 1];
+        }
+        reconstruct_state(result);
+    }
+    static detail::polynomial get_characteristic_polynomial()
+    {
+        const std::size_t num_bits = w*n - r;
+        detail::polynomial helper;
+        helper[num_bits - 1] = 1;
+        mersenne_twister_engine tmp;
+        tmp.reconstruct_state(helper);
+        // Skip the first num_bits elements, since we
+        // already know what they are.
+        for(std::size_t j = 0; j < num_bits; ++j) {
+            if(tmp.i >= n) tmp.twist();
+            if(j == num_bits - 1)
+                assert((tmp.x[tmp.i] & 1) == 1);
+            else
+                assert((tmp.x[tmp.i] & 1) == 0);
+            ++tmp.i;
+        }
+        detail::polynomial phi;
+        phi[num_bits] = 1;
+        detail::polynomial next_bits = tmp.as_polynomial(num_bits);
+        for(std::size_t j = 0; j < num_bits; ++j) {
+            int val = next_bits[j] ^ phi[num_bits-j-1];
+            phi[num_bits-j-1] = val;
+            if(val) {
+                for(std::size_t k = j + 1; k < num_bits; ++k) {
+                    phi[num_bits-k-1] ^= next_bits[k-j-1];
+                }
+            }
+        }
+        return phi;
+    }
+    detail::polynomial as_polynomial(std::size_t size) {
+        detail::polynomial result;
+        for(std::size_t j = 0; j < size; ++j) {
+            if(i >= n) twist();
+            result[j] = x[i++] & UIntType(1);
+        }
+        return result;
+    }
+    void reconstruct_state(const detail::polynomial& p)
+    {
+        const UIntType upper_mask = (~static_cast<UIntType>(0)) << r;
+        const UIntType lower_mask = ~upper_mask;
+        const std::size_t num_bits = w*n - r;
+        for(std::size_t j = num_bits - n + 1; j <= num_bits; ++j)
+            x[j % n] = p[j];
+
+        UIntType y0 = 0;
+        for(std::size_t j = num_bits + 1; j >= n - 1; --j) {
+            UIntType y1 = x[j % n] ^ x[(j + m) % n];
+            if(p[j - n + 1])
+                y1 = (y1 ^ a) << UIntType(1) | UIntType(1);
+            else
+                y1 = y1 << UIntType(1);
+            x[(j + 1) % n] = (y0 & upper_mask) | (y1 & lower_mask);
+            y0 = y1;
+        }
+        i = 0;
+    }
+
+    /// \endcond
+
+    // state representation: next output is o(x(i))
+    //   x[0]  ... x[k] x[k+1] ... x[n-1]   represents
+    //  x(i-k) ... x(i) x(i+1) ... x(i-k+n-1)
+
+    UIntType x[n];
+    std::size_t i;
+};
+
+/// \cond show_private
+
+#ifndef BOOST_NO_INCLASS_MEMBER_INITIALIZATION
+//  A definition is required even for integral static constants
+#define BOOST_RANDOM_MT_DEFINE_CONSTANT(type, name)                         \
+template<class UIntType, std::size_t w, std::size_t n, std::size_t m,       \
+    std::size_t r, UIntType a, std::size_t u, UIntType d, std::size_t s,    \
+    UIntType b, std::size_t t, UIntType c, std::size_t l, UIntType f>       \
+const type mersenne_twister_engine<UIntType,w,n,m,r,a,u,d,s,b,t,c,l,f>::name
+BOOST_RANDOM_MT_DEFINE_CONSTANT(std::size_t, word_size);
+BOOST_RANDOM_MT_DEFINE_CONSTANT(std::size_t, state_size);
+BOOST_RANDOM_MT_DEFINE_CONSTANT(std::size_t, shift_size);
+BOOST_RANDOM_MT_DEFINE_CONSTANT(std::size_t, mask_bits);
+BOOST_RANDOM_MT_DEFINE_CONSTANT(UIntType, xor_mask);
+BOOST_RANDOM_MT_DEFINE_CONSTANT(std::size_t, tempering_u);
+BOOST_RANDOM_MT_DEFINE_CONSTANT(UIntType, tempering_d);
+BOOST_RANDOM_MT_DEFINE_CONSTANT(std::size_t, tempering_s);
+BOOST_RANDOM_MT_DEFINE_CONSTANT(UIntType, tempering_b);
+BOOST_RANDOM_MT_DEFINE_CONSTANT(std::size_t, tempering_t);
+BOOST_RANDOM_MT_DEFINE_CONSTANT(UIntType, tempering_c);
+BOOST_RANDOM_MT_DEFINE_CONSTANT(std::size_t, tempering_l);
+BOOST_RANDOM_MT_DEFINE_CONSTANT(UIntType, initialization_multiplier);
+BOOST_RANDOM_MT_DEFINE_CONSTANT(UIntType, default_seed);
+BOOST_RANDOM_MT_DEFINE_CONSTANT(UIntType, parameter_a);
+BOOST_RANDOM_MT_DEFINE_CONSTANT(std::size_t, output_u );
+BOOST_RANDOM_MT_DEFINE_CONSTANT(std::size_t, output_s);
+BOOST_RANDOM_MT_DEFINE_CONSTANT(UIntType, output_b);
+BOOST_RANDOM_MT_DEFINE_CONSTANT(std::size_t, output_t);
+BOOST_RANDOM_MT_DEFINE_CONSTANT(UIntType, output_c);
+BOOST_RANDOM_MT_DEFINE_CONSTANT(std::size_t, output_l);
+BOOST_RANDOM_MT_DEFINE_CONSTANT(bool, has_fixed_range);
+#undef BOOST_RANDOM_MT_DEFINE_CONSTANT
+#endif
+
+template<class UIntType,
+         std::size_t w, std::size_t n, std::size_t m, std::size_t r,
+         UIntType a, std::size_t u, UIntType d, std::size_t s,
+         UIntType b, std::size_t t,
+         UIntType c, std::size_t l, UIntType f>
+void
+mersenne_twister_engine<UIntType,w,n,m,r,a,u,d,s,b,t,c,l,f>::twist()
+{
+    const UIntType upper_mask = (~static_cast<UIntType>(0)) << r;
+    const UIntType lower_mask = ~upper_mask;
+
+    const std::size_t unroll_factor = 6;
+    const std::size_t unroll_extra1 = (n-m) % unroll_factor;
+    const std::size_t unroll_extra2 = (m-1) % unroll_factor;
+
+    // split loop to avoid costly modulo operations
+    {  // extra scope for MSVC brokenness w.r.t. for scope
+        for(std::size_t j = 0; j < n-m-unroll_extra1; j++) {
+            UIntType y = (x[j] & upper_mask) | (x[j+1] & lower_mask);
+            x[j] = x[j+m] ^ (y >> 1) ^ ((x[j+1]&1) * a);
+        }
+    }
+    {
+        for(std::size_t j = n-m-unroll_extra1; j < n-m; j++) {
+            UIntType y = (x[j] & upper_mask) | (x[j+1] & lower_mask);
+            x[j] = x[j+m] ^ (y >> 1) ^ ((x[j+1]&1) * a);
+        }
+    }
+    {
+        for(std::size_t j = n-m; j < n-1-unroll_extra2; j++) {
+            UIntType y = (x[j] & upper_mask) | (x[j+1] & lower_mask);
+            x[j] = x[j-(n-m)] ^ (y >> 1) ^ ((x[j+1]&1) * a);
+        }
+    }
+    {
+        for(std::size_t j = n-1-unroll_extra2; j < n-1; j++) {
+            UIntType y = (x[j] & upper_mask) | (x[j+1] & lower_mask);
+            x[j] = x[j-(n-m)] ^ (y >> 1) ^ ((x[j+1]&1) * a);
+        }
+    }
+    // last iteration
+    UIntType y = (x[n-1] & upper_mask) | (x[0] & lower_mask);
+    x[n-1] = x[m-1] ^ (y >> 1) ^ ((x[0]&1) * a);
+    i = 0;
+}
+/// \endcond
+
+template<class UIntType,
+         std::size_t w, std::size_t n, std::size_t m, std::size_t r,
+         UIntType a, std::size_t u, UIntType d, std::size_t s,
+         UIntType b, std::size_t t,
+         UIntType c, std::size_t l, UIntType f>
+inline typename
+mersenne_twister_engine<UIntType,w,n,m,r,a,u,d,s,b,t,c,l,f>::result_type
+mersenne_twister_engine<UIntType,w,n,m,r,a,u,d,s,b,t,c,l,f>::operator()()
+{
+    if(i == n)
+        twist();
+    // Step 4
+    UIntType z = x[i];
+    ++i;
+    z ^= ((z >> u) & d);
+    z ^= ((z << s) & b);
+    z ^= ((z << t) & c);
+    z ^= (z >> l);
+    return z;
+}
+
+/**
+ * The specializations \mt11213b and \mt19937 are from
+ *
+ *  @blockquote
+ *  "Mersenne Twister: A 623-dimensionally equidistributed
+ *  uniform pseudo-random number generator", Makoto Matsumoto
+ *  and Takuji Nishimura, ACM Transactions on Modeling and
+ *  Computer Simulation: Special Issue on Uniform Random Number
+ *  Generation, Vol. 8, No. 1, January 1998, pp. 3-30.
+ *  @endblockquote
+ */
+typedef mersenne_twister_engine<uint32_t,32,351,175,19,0xccab8ee7,
+    11,0xffffffff,7,0x31b6ab00,15,0xffe50000,17,1812433253> mt11213b;
+
+/**
+ * The specializations \mt11213b and \mt19937 are from
+ *
+ *  @blockquote
+ *  "Mersenne Twister: A 623-dimensionally equidistributed
+ *  uniform pseudo-random number generator", Makoto Matsumoto
+ *  and Takuji Nishimura, ACM Transactions on Modeling and
+ *  Computer Simulation: Special Issue on Uniform Random Number
+ *  Generation, Vol. 8, No. 1, January 1998, pp. 3-30.
+ *  @endblockquote
+ */
+typedef mersenne_twister_engine<uint32_t,32,624,397,31,0x9908b0df,
+    11,0xffffffff,7,0x9d2c5680,15,0xefc60000,18,1812433253> mt19937;
+
+#if !defined(BOOST_NO_INT64_T) && !defined(BOOST_NO_INTEGRAL_INT64_T)
+typedef mersenne_twister_engine<uint64_t,64,312,156,31,
+    UINT64_C(0xb5026f5aa96619e9),29,UINT64_C(0x5555555555555555),17,
+    UINT64_C(0x71d67fffeda60000),37,UINT64_C(0xfff7eee000000000),43,
+    UINT64_C(6364136223846793005)> mt19937_64;
+#endif
+
+/// \cond show_deprecated
+
+template<class UIntType,
+         int w, int n, int m, int r,
+         UIntType a, int u, std::size_t s,
+         UIntType b, int t,
+         UIntType c, int l, UIntType v>
+class mersenne_twister :
+    public mersenne_twister_engine<UIntType,
+        w, n, m, r, a, u, ~(UIntType)0, s, b, t, c, l, 1812433253>
+{
+    typedef mersenne_twister_engine<UIntType,
+        w, n, m, r, a, u, ~(UIntType)0, s, b, t, c, l, 1812433253> base_type;
+public:
+    mersenne_twister() {}
+    BOOST_RANDOM_DETAIL_GENERATOR_CONSTRUCTOR(mersenne_twister, Gen, gen)
+    { seed(gen); }
+    BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(mersenne_twister, UIntType, val)
+    { seed(val); }
+    template<class It>
+    mersenne_twister(It& first, It last) : base_type(first, last) {}
+    void seed() { base_type::seed(); }
+    BOOST_RANDOM_DETAIL_GENERATOR_SEED(mersenne_twister, Gen, gen)
+    {
+        detail::generator_seed_seq<Gen> seq(gen);
+        base_type::seed(seq);
+    }
+    BOOST_RANDOM_DETAIL_ARITHMETIC_SEED(mersenne_twister, UIntType, val)
+    { base_type::seed(val); }
+    template<class It>
+    void seed(It& first, It last) { base_type::seed(first, last); }
+};
+
+/// \endcond
+
+} // namespace random
+
+using random::mt11213b;
+using random::mt19937;
+using random::mt19937_64;
+
+} // namespace boost
+
+BOOST_RANDOM_PTR_HELPER_SPEC(boost::mt11213b)
+BOOST_RANDOM_PTR_HELPER_SPEC(boost::mt19937)
+BOOST_RANDOM_PTR_HELPER_SPEC(boost::mt19937_64)
+
+#include <boost/random/detail/enable_warnings.hpp>
+
+#endif // BOOST_RANDOM_MERSENNE_TWISTER_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/negative_binomial_distribution.hpp

@@ -0,0 +1,220 @@
+/* boost random/negative_binomial_distribution.hpp header file
+ *
+ * Copyright Steven Watanabe 2010
+ * 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.
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_NEGATIVE_BINOMIAL_DISTRIBUTION_HPP_INCLUDED
+#define BOOST_RANDOM_NEGATIVE_BINOMIAL_DISTRIBUTION_HPP_INCLUDED
+
+#include <iosfwd>
+
+#include <boost/limits.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/gamma_distribution.hpp>
+#include <boost/random/poisson_distribution.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * The negative binomial distribution is an integer valued
+ * distribution with two parameters, @c k and @c p.  The
+ * distribution produces non-negative values.
+ *
+ * The distribution function is
+ * \f$\displaystyle P(i) = {k+i-1\choose i}p^k(1-p)^i\f$.
+ *
+ * This implementation uses a gamma-poisson mixture.
+ */
+template<class IntType = int, class RealType = double>
+class negative_binomial_distribution {
+public:
+    typedef IntType result_type;
+    typedef RealType input_type;
+
+    class param_type {
+    public:
+        typedef negative_binomial_distribution distribution_type;
+        /**
+         * Construct a param_type object.  @c k and @c p
+         * are the parameters of the distribution.
+         *
+         * Requires: k >=0 && 0 <= p <= 1
+         */
+        explicit param_type(IntType k_arg = 1, RealType p_arg = RealType (0.5))
+          : _k(k_arg), _p(p_arg)
+        {}
+        /** Returns the @c k parameter of the distribution. */
+        IntType k() const { return _k; }
+        /** Returns the @c p parameter of the distribution. */
+        RealType p() const { return _p; }
+#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
+        /** Writes the parameters of the distribution to a @c std::ostream. */
+        template<class CharT, class Traits>
+        friend std::basic_ostream<CharT,Traits>&
+        operator<<(std::basic_ostream<CharT,Traits>& os,
+                   const param_type& parm)
+        {
+            os << parm._p << " " << parm._k;
+            return os;
+        }
+    
+        /** Reads the parameters of the distribution from a @c std::istream. */
+        template<class CharT, class Traits>
+        friend std::basic_istream<CharT,Traits>&
+        operator>>(std::basic_istream<CharT,Traits>& is, param_type& parm)
+        {
+            is >> parm._p >> std::ws >> parm._k;
+            return is;
+        }
+#endif
+        /** Returns true if the parameters have the same values. */
+        friend bool operator==(const param_type& lhs, const param_type& rhs)
+        {
+            return lhs._k == rhs._k && lhs._p == rhs._p;
+        }
+        /** Returns true if the parameters have different values. */
+        friend bool operator!=(const param_type& lhs, const param_type& rhs)
+        {
+            return !(lhs == rhs);
+        }
+    private:
+        IntType _k;
+        RealType _p;
+    };
+    
+    /**
+     * Construct a @c negative_binomial_distribution object. @c k and @c p
+     * are the parameters of the distribution.
+     *
+     * Requires: k >=0 && 0 <= p <= 1
+     */
+    explicit negative_binomial_distribution(IntType k_arg = 1,
+                                            RealType p_arg = RealType(0.5))
+      : _k(k_arg), _p(p_arg)
+    {}
+    
+    /**
+     * Construct an @c negative_binomial_distribution object from the
+     * parameters.
+     */
+    explicit negative_binomial_distribution(const param_type& parm)
+      : _k(parm.k()), _p(parm.p())
+    {}
+    
+    /**
+     * Returns a random variate distributed according to the
+     * negative binomial distribution.
+     */
+    template<class URNG>
+    IntType operator()(URNG& urng) const
+    {
+        gamma_distribution<RealType> gamma(_k, (1-_p)/_p);
+        poisson_distribution<IntType, RealType> poisson(gamma(urng));
+        return poisson(urng);
+    }
+    
+    /**
+     * Returns a random variate distributed according to the negative
+     * binomial distribution with parameters specified by @c param.
+     */
+    template<class URNG>
+    IntType operator()(URNG& urng, const param_type& parm) const
+    {
+        return negative_binomial_distribution(parm)(urng);
+    }
+
+    /** Returns the @c k parameter of the distribution. */
+    IntType k() const { return _k; }
+    /** Returns the @c p parameter of the distribution. */
+    RealType p() const { return _p; }
+
+    /** Returns the smallest value that the distribution can produce. */
+    IntType min BOOST_PREVENT_MACRO_SUBSTITUTION() const { return 0; }
+    /** Returns the largest value that the distribution can produce. */
+    IntType max BOOST_PREVENT_MACRO_SUBSTITUTION() const
+    { return (std::numeric_limits<IntType>::max)(); }
+
+    /** Returns the parameters of the distribution. */
+    param_type param() const { return param_type(_k, _p); }
+    /** Sets parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        _k = parm.k();
+        _p = parm.p();
+    }
+
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { }
+
+#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
+    /** Writes the parameters of the distribution to a @c std::ostream. */
+    template<class CharT, class Traits>
+    friend std::basic_ostream<CharT,Traits>&
+    operator<<(std::basic_ostream<CharT,Traits>& os,
+               const negative_binomial_distribution& bd)
+    {
+        os << bd.param();
+        return os;
+    }
+    
+    /** Reads the parameters of the distribution from a @c std::istream. */
+    template<class CharT, class Traits>
+    friend std::basic_istream<CharT,Traits>&
+    operator>>(std::basic_istream<CharT,Traits>& is,
+               negative_binomial_distribution& bd)
+    {
+        bd.read(is);
+        return is;
+    }
+#endif
+
+    /** Returns true if the two distributions will produce the same
+        sequence of values, given equal generators. */
+    friend bool operator==(const negative_binomial_distribution& lhs,
+                           const negative_binomial_distribution& rhs)
+    {
+        return lhs._k == rhs._k && lhs._p == rhs._p;
+    }
+    /** Returns true if the two distributions could produce different
+        sequences of values, given equal generators. */
+    friend bool operator!=(const negative_binomial_distribution& lhs,
+                           const negative_binomial_distribution& rhs)
+    {
+        return !(lhs == rhs);
+    }
+
+private:
+
+    /// @cond \show_private
+
+    template<class CharT, class Traits>
+    void read(std::basic_istream<CharT, Traits>& is) {
+        param_type parm;
+        if(is >> parm) {
+            param(parm);
+        }
+    }
+
+    // parameters
+    IntType _k;
+    RealType _p;
+
+    /// @endcond
+};
+
+}
+
+}
+
+#endif

depends/x86_64-pc-linux-gnu/include/boost/random/non_central_chi_squared_distribution.hpp

@@ -0,0 +1,221 @@
+/* boost random/non_central_chi_squared_distribution.hpp header file
+ *
+ * Copyright Thijs van den Berg 2014
+ * 
+ * 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.
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_NON_CENTRAL_CHI_SQUARED_DISTRIBUTION_HPP
+#define BOOST_RANDOM_NON_CENTRAL_CHI_SQUARED_DISTRIBUTION_HPP
+
+#include <boost/config/no_tr1/cmath.hpp>
+#include <iosfwd>
+#include <istream>
+#include <boost/limits.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include <boost/random/normal_distribution.hpp>
+#include <boost/random/chi_squared_distribution.hpp>
+#include <boost/random/poisson_distribution.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * The noncentral chi-squared distribution is a real valued distribution with
+ * two parameter, @c k and @c lambda.  The distribution produces values > 0.
+ *
+ * This is the distribution of the sum of squares of k Normal distributed
+ * variates each with variance one and \f$\lambda\f$ the sum of squares of the
+ * normal means.
+ *
+ * The distribution function is
+ * \f$\displaystyle P(x) = \frac{1}{2} e^{-(x+\lambda)/2} \left( \frac{x}{\lambda} \right)^{k/4-1/2} I_{k/2-1}( \sqrt{\lambda x} )\f$.
+ *  where  \f$\displaystyle I_\nu(z)\f$ is a modified Bessel function of the
+ * first kind.
+ *
+ * The algorithm is taken from
+ *
+ *  @blockquote
+ *  "Monte Carlo Methods in Financial Engineering", Paul Glasserman,
+ *  2003, XIII, 596 p, Stochastic Modelling and Applied Probability, Vol. 53,
+ *  ISBN 978-0-387-21617-1, p 124, Fig. 3.5.
+ *  @endblockquote
+ */
+template <typename RealType = double>
+class non_central_chi_squared_distribution {
+public:
+    typedef RealType result_type;
+    typedef RealType input_type;
+    
+    class param_type {
+    public:
+        typedef non_central_chi_squared_distribution distribution_type;
+        
+        /**
+         * Constructs the parameters of a non_central_chi_squared_distribution.
+         * @c k and @c lambda are the parameter of the distribution.
+         *
+         * Requires: k > 0 && lambda > 0
+         */
+        explicit
+        param_type(RealType k_arg = RealType(1), RealType lambda_arg = RealType(1))
+        : _k(k_arg), _lambda(lambda_arg)
+        {
+            BOOST_ASSERT(k_arg > RealType(0));
+            BOOST_ASSERT(lambda_arg > RealType(0));
+        }
+        
+        /** Returns the @c k parameter of the distribution */
+        RealType k() const { return _k; }
+        
+        /** Returns the @c lambda parameter of the distribution */
+        RealType lambda() const { return _lambda; }
+
+        /** Writes the parameters of the distribution to a @c std::ostream. */
+        BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
+        {
+            os << parm._k << ' ' << parm._lambda;
+            return os;
+        }
+        
+        /** Reads the parameters of the distribution from a @c std::istream. */
+        BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
+        {
+            is >> parm._k >> std::ws >> parm._lambda;
+            return is;
+        }
+
+        /** Returns true if the parameters have the same values. */
+        BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
+        { return lhs._k == rhs._k && lhs._lambda == rhs._lambda; }
+        
+        /** Returns true if the parameters have different values. */
+        BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+        
+    private:
+        RealType _k;
+        RealType _lambda;
+    };
+
+    /**
+     * Construct a @c non_central_chi_squared_distribution object. @c k and
+     * @c lambda are the parameter of the distribution.
+     *
+     * Requires: k > 0 && lambda > 0
+     */
+    explicit
+    non_central_chi_squared_distribution(RealType k_arg = RealType(1), RealType lambda_arg = RealType(1))
+      : _param(k_arg, lambda_arg)
+    {
+        BOOST_ASSERT(k_arg > RealType(0));
+        BOOST_ASSERT(lambda_arg > RealType(0));
+    }
+
+    /**
+     * Construct a @c non_central_chi_squared_distribution object from the parameter.
+     */
+    explicit
+    non_central_chi_squared_distribution(const param_type& parm)
+      : _param( parm )
+    { }
+    
+    /**
+     * Returns a random variate distributed according to the
+     * non central chi squared distribution specified by @c param.
+     */
+    template<typename URNG>
+    RealType operator()(URNG& eng, const param_type& parm) const
+    { return non_central_chi_squared_distribution(parm)(eng); }
+    
+    /**
+     * Returns a random variate distributed according to the
+     * non central chi squared distribution.
+     */
+    template<typename URNG> 
+    RealType operator()(URNG& eng) 
+    {
+        using std::sqrt;
+        if (_param.k() > 1) {
+            boost::random::normal_distribution<RealType> n_dist;
+            boost::random::chi_squared_distribution<RealType> c_dist(_param.k() - RealType(1));
+            RealType _z = n_dist(eng);
+            RealType _x = c_dist(eng);
+            RealType term1 = _z + sqrt(_param.lambda());
+            return term1*term1 + _x;
+        }
+        else {
+            boost::random::poisson_distribution<> p_dist(_param.lambda()/RealType(2));
+            boost::random::poisson_distribution<>::result_type _p = p_dist(eng);
+            boost::random::chi_squared_distribution<RealType> c_dist(_param.k() + RealType(2)*_p);
+            return c_dist(eng);
+        }
+    }
+
+    /** Returns the @c k parameter of the distribution. */
+    RealType k() const { return _param.k(); }
+    
+    /** Returns the @c lambda parameter of the distribution. */
+    RealType lambda() const { return _param.lambda(); }
+    
+    /** Returns the parameters of the distribution. */
+    param_type param() const { return _param; }
+    
+    /** Sets parameters of the distribution. */
+    void param(const param_type& parm) { _param = parm; }
+    
+    /** Resets the distribution, so that subsequent uses does not depend on values already produced by it.*/
+    void reset() {}
+    
+    /** Returns the smallest value that the distribution can produce. */
+    RealType min BOOST_PREVENT_MACRO_SUBSTITUTION() const
+    { return RealType(0); }
+    
+    /** Returns the largest value that the distribution can produce. */
+    RealType max BOOST_PREVENT_MACRO_SUBSTITUTION() const
+    { return (std::numeric_limits<RealType>::infinity)(); }
+
+    /** Writes the parameters of the distribution to a @c std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, non_central_chi_squared_distribution, dist)
+    {
+        os << dist.param();
+        return os;
+    }
+    
+    /** reads the parameters of the distribution from a @c std::istream. */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, non_central_chi_squared_distribution, dist)
+    {
+        param_type parm;
+        if(is >> parm) {
+            dist.param(parm);
+        }
+        return is;
+    }
+
+    /** Returns true if two distributions have the same parameters and produce 
+        the same sequence of random numbers given equal generators.*/
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(non_central_chi_squared_distribution, lhs, rhs)
+    { return lhs.param() == rhs.param(); }
+    
+    /** Returns true if two distributions have different parameters and/or can produce 
+       different sequences of random numbers given equal generators.*/
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(non_central_chi_squared_distribution)
+    
+private:
+
+    /// @cond show_private
+    param_type  _param;
+    /// @endcond
+};
+
+} // namespace random
+} // namespace boost
+
+#endif

depends/x86_64-pc-linux-gnu/include/boost/random/normal_distribution.hpp

@@ -0,0 +1,374 @@
+/* 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.
+ *
+ * $Id$
+ *
+ * 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/detail/int_float_pair.hpp>
+#include <boost/random/uniform_01.hpp>
+#include <boost/random/exponential_distribution.hpp>
+
+namespace boost {
+namespace random {
+
+namespace detail {
+
+// tables for the ziggurat algorithm
+template<class RealType>
+struct normal_table {
+    static const RealType table_x[129];
+    static const RealType table_y[129];
+};
+
+template<class RealType>
+const RealType normal_table<RealType>::table_x[129] = {
+    3.7130862467403632609, 3.4426198558966521214, 3.2230849845786185446, 3.0832288582142137009,
+    2.9786962526450169606, 2.8943440070186706210, 2.8231253505459664379, 2.7611693723841538514,
+    2.7061135731187223371, 2.6564064112581924999, 2.6109722484286132035, 2.5690336259216391328,
+    2.5300096723854666170, 2.4934545220919507609, 2.4590181774083500943, 2.4264206455302115930,
+    2.3954342780074673425, 2.3658713701139875435, 2.3375752413355307354, 2.3104136836950021558,
+    2.2842740596736568056, 2.2590595738653295251, 2.2346863955870569803, 2.2110814088747278106,
+    2.1881804320720206093, 2.1659267937448407377, 2.1442701823562613518, 2.1231657086697899595,
+    2.1025731351849988838, 2.0824562379877246441, 2.0627822745039633575, 2.0435215366506694976,
+    2.0246469733729338782, 2.0061338699589668403, 1.9879595741230607243, 1.9701032608497132242,
+    1.9525457295488889058, 1.9352692282919002011, 1.9182573008597320303, 1.9014946531003176140,
+    1.8849670357028692380, 1.8686611409895420085, 1.8525645117230870617, 1.8366654602533840447,
+    1.8209529965910050740, 1.8054167642140487420, 1.7900469825946189862, 1.7748343955807692457,
+    1.7597702248942318749, 1.7448461281083765085, 1.7300541605582435350, 1.7153867407081165482,
+    1.7008366185643009437, 1.6863968467734863258, 1.6720607540918522072, 1.6578219209482075462,
+    1.6436741568569826489, 1.6296114794646783962, 1.6156280950371329644, 1.6017183802152770587,
+    1.5878768648844007019, 1.5740982160167497219, 1.5603772223598406870, 1.5467087798535034608,
+    1.5330878776675560787, 1.5195095847593707806, 1.5059690368565502602, 1.4924614237746154081,
+    1.4789819769830978546, 1.4655259573357946276, 1.4520886428822164926, 1.4386653166774613138,
+    1.4252512545068615734, 1.4118417124397602509, 1.3984319141236063517, 1.3850170377251486449,
+    1.3715922024197322698, 1.3581524543224228739, 1.3446927517457130432, 1.3312079496576765017,
+    1.3176927832013429910, 1.3041418501204215390, 1.2905495919178731508, 1.2769102735516997175,
+    1.2632179614460282310, 1.2494664995643337480, 1.2356494832544811749, 1.2217602305309625678,
+    1.2077917504067576028, 1.1937367078237721994, 1.1795873846544607035, 1.1653356361550469083,
+    1.1509728421389760651, 1.1364898520030755352, 1.1218769225722540661, 1.1071236475235353980,
+    1.0922188768965537614, 1.0771506248819376573, 1.0619059636836193998, 1.0464709007525802629,
+    1.0308302360564555907, 1.0149673952392994716, 0.99886423348064351303, 0.98250080350276038481,
+    0.96585507938813059489, 0.94890262549791195381, 0.93161619660135381056, 0.91396525100880177644,
+    0.89591535256623852894, 0.87742742909771569142, 0.85845684317805086354, 0.83895221428120745572,
+    0.81885390668331772331, 0.79809206062627480454, 0.77658398787614838598, 0.75423066443451007146,
+    0.73091191062188128150, 0.70647961131360803456, 0.68074791864590421664, 0.65347863871504238702,
+    0.62435859730908822111, 0.59296294244197797913, 0.55869217837551797140, 0.52065603872514491759,
+    0.47743783725378787681, 0.42654798630330512490, 0.36287143102841830424, 0.27232086470466385065,
+    0
+};
+
+template<class RealType>
+const RealType normal_table<RealType>::table_y[129] = {
+    0, 0.0026696290839025035092, 0.0055489952208164705392, 0.0086244844129304709682,
+    0.011839478657982313715, 0.015167298010672042468, 0.018592102737165812650, 0.022103304616111592615,
+    0.025693291936149616572, 0.029356317440253829618, 0.033087886146505155566, 0.036884388786968774128,
+    0.040742868074790604632, 0.044660862200872429800, 0.048636295860284051878, 0.052667401903503169793,
+    0.056752663481538584188, 0.060890770348566375972, 0.065080585213631873753, 0.069321117394180252601,
+    0.073611501884754893389, 0.077950982514654714188, 0.082338898242957408243, 0.086774671895542968998,
+    0.091257800827634710201, 0.09578784912257815216, 0.10036444102954554013, 0.10498725541035453978,
+    0.10965602101581776100, 0.11437051244988827452, 0.11913054670871858767, 0.12393598020398174246,
+    0.12878670619710396109, 0.13368265258464764118, 0.13862377998585103702, 0.14361008009193299469,
+    0.14864157424369696566, 0.15371831220958657066, 0.15884037114093507813, 0.16400785468492774791,
+    0.16922089223892475176, 0.17447963833240232295, 0.17978427212496211424, 0.18513499701071343216,
+    0.19053204032091372112, 0.19597565311811041399, 0.20146611007620324118, 0.20700370944187380064,
+    0.21258877307373610060, 0.21822164655637059599, 0.22390269938713388747, 0.22963232523430270355,
+    0.23541094226572765600, 0.24123899354775131610, 0.24711694751469673582, 0.25304529850976585934,
+    0.25902456739871074263, 0.26505530225816194029, 0.27113807914102527343, 0.27727350292189771153,
+    0.28346220822601251779, 0.28970486044581049771, 0.29600215684985583659, 0.30235482778947976274,
+    0.30876363800925192282, 0.31522938806815752222, 0.32175291587920862031, 0.32833509837615239609,
+    0.33497685331697116147, 0.34167914123501368412, 0.34844296754987246935, 0.35526938485154714435,
+    0.36215949537303321162, 0.36911445366827513952, 0.37613546951445442947, 0.38322381105988364587,
+    0.39038080824138948916, 0.39760785649804255208, 0.40490642081148835099, 0.41227804010702462062,
+    0.41972433205403823467, 0.42724699830956239880, 0.43484783025466189638, 0.44252871528024661483,
+    0.45029164368692696086, 0.45813871627287196483, 0.46607215269457097924, 0.47409430069824960453,
+    0.48220764633483869062, 0.49041482528932163741, 0.49871863547658432422, 0.50712205108130458951,
+    0.51562823824987205196, 0.52424057267899279809, 0.53296265938998758838, 0.54179835503172412311,
+    0.55075179312105527738, 0.55982741271069481791, 0.56902999107472161225, 0.57836468112670231279,
+    0.58783705444182052571, 0.59745315095181228217, 0.60721953663260488551, 0.61714337082656248870,
+    0.62723248525781456578, 0.63749547734314487428, 0.64794182111855080873, 0.65858200005865368016,
+    0.66942766735770616891, 0.68049184100641433355, 0.69178914344603585279, 0.70333609902581741633,
+    0.71515150742047704368, 0.72725691835450587793, 0.73967724368333814856, 0.75244155918570380145,
+    0.76558417390923599480, 0.77914608594170316563, 0.79317701178385921053, 0.80773829469612111340,
+    0.82290721139526200050, 0.83878360531064722379, 0.85550060788506428418, 0.87324304892685358879,
+    0.89228165080230272301, 0.91304364799203805999, 0.93628268170837107547, 0.96359969315576759960,
+    1
+};
+
+
+template<class RealType = double>
+struct unit_normal_distribution
+{
+    template<class Engine>
+    RealType operator()(Engine& eng) {
+        const double * const table_x = normal_table<double>::table_x;
+        const double * const table_y = normal_table<double>::table_y;
+        for(;;) {
+            std::pair<RealType, int> vals = generate_int_float_pair<RealType, 8>(eng);
+            int i = vals.second;
+            int sign = (i & 1) * 2 - 1;
+            i = i >> 1;
+            RealType x = vals.first * RealType(table_x[i]);
+            if(x < table_x[i + 1]) return x * sign;
+            if(i == 0) return generate_tail(eng) * sign;
+
+            RealType y01 = uniform_01<RealType>()(eng);
+            RealType y = RealType(table_y[i]) + y01 * RealType(table_y[i + 1] - table_y[i]);
+
+            // These store the value y - bound, or something proportional to that difference:
+            RealType y_above_ubound, y_above_lbound;
+
+            // There are three cases to consider:
+            // - convex regions (where x[i] > x[j] >= 1)
+            // - concave regions (where 1 <= x[i] < x[j])
+            // - region containing the inflection point (where x[i] > 1 > x[j])
+            // For convex (concave), exp^(-x^2/2) is bounded below (above) by the tangent at
+            // (x[i],y[i]) and is bounded above (below) by the diagonal line from (x[i+1],y[i+1]) to
+            // (x[i],y[i]).
+            //
+            // *If* the inflection point region satisfies slope(x[i+1]) < slope(diagonal), then we
+            // can treat the inflection region as a convex region: this condition is necessary and
+            // sufficient to ensure that the curve lies entirely below the diagonal (that, in turn,
+            // also implies that it will be above the tangent at x[i]).
+            //
+            // For the current table size (128), this is satisfied: slope(x[i+1]) = -0.60653 <
+            // slope(diag) = -0.60649, and so we have only two cases below instead of three.
+
+            if (table_x[i] >= 1) { // convex (incl. inflection)
+                y_above_ubound = RealType(table_x[i] - table_x[i+1]) * y01 - (RealType(table_x[i]) - x);
+                y_above_lbound = y - (RealType(table_y[i]) + (RealType(table_x[i]) - x) * RealType(table_y[i]) * RealType(table_x[i]));
+            }
+            else { // concave
+                y_above_lbound = RealType(table_x[i] - table_x[i+1]) * y01 - (RealType(table_x[i]) - x);
+                y_above_ubound = y - (RealType(table_y[i]) + (RealType(table_x[i]) - x) * RealType(table_y[i]) * RealType(table_x[i]));
+            }
+
+            if (y_above_ubound < 0 // if above the upper bound reject immediately
+                    &&
+                    (
+                     y_above_lbound < 0 // If below the lower bound accept immediately
+                     ||
+                     y < f(x) // Otherwise it's between the bounds and we need a full check
+                    )
+               ) {
+                return x * sign;
+            }
+        }
+    }
+    static RealType f(RealType x) {
+        using std::exp;
+        return exp(-(x*x/2));
+    }
+    // Generate from the tail using rejection sampling from the exponential(x_1) distribution,
+    // shifted by x_1.  This looks a little different from the usual rejection sampling because it
+    // transforms the condition by taking the log of both sides, thus avoiding the costly exp() call
+    // on the RHS, then takes advantage of the fact that -log(unif01) is simply generating an
+    // exponential (by inverse cdf sampling) by replacing the log(unif01) on the LHS with a
+    // exponential(1) draw, y.
+    template<class Engine>
+    RealType generate_tail(Engine& eng) {
+        const RealType tail_start = RealType(normal_table<double>::table_x[1]);
+        boost::random::exponential_distribution<RealType> exp_x(tail_start);
+        boost::random::exponential_distribution<RealType> exp_y;
+        for(;;) {
+            RealType x = exp_x(eng);
+            RealType y = exp_y(eng);
+            // If we were doing non-transformed rejection sampling, this condition would be:
+            // if (unif01 < exp(-.5*x*x)) return x + tail_start;
+            if(2*y > x*x) return x + tail_start;
+        }
+    }
+};
+
+} // namespace detail
+
+
+/**
+ * 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.
+ *
+ * The implementation uses the "ziggurat" algorithm, as described in
+ *
+ *  @blockquote
+ *  "The Ziggurat Method for Generating Random Variables",
+ *  George Marsaglia and Wai Wan Tsang, Journal of Statistical Software,
+ *  Volume 5, Number 8 (2000), 1-7.
+ *  @endblockquote
+ */
+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)
+    {
+        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())
+    {}
+
+    /**  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();
+    }
+
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { }
+
+    /**  Returns a normal variate. */
+    template<class Engine>
+    result_type operator()(Engine& eng)
+    {
+        detail::unit_normal_distribution<RealType> impl;
+        return impl(eng) * _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;
+        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;
+        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;
+    }
+
+    /**
+     * 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;
+
+};
+
+} // namespace random
+
+using random::normal_distribution;
+
+} // namespace boost
+
+#endif // BOOST_RANDOM_NORMAL_DISTRIBUTION_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/piecewise_constant_distribution.hpp

@@ -0,0 +1,466 @@
+/* boost random/piecewise_constant_distribution.hpp header file
+ *
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_PIECEWISE_CONSTANT_DISTRIBUTION_HPP_INCLUDED
+#define BOOST_RANDOM_PIECEWISE_CONSTANT_DISTRIBUTION_HPP_INCLUDED
+
+#include <vector>
+#include <numeric>
+#include <boost/assert.hpp>
+#include <boost/random/uniform_real.hpp>
+#include <boost/random/discrete_distribution.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/detail/vector_io.hpp>
+
+#ifndef BOOST_NO_CXX11_HDR_INITIALIZER_LIST
+#include <initializer_list>
+#endif
+
+#include <boost/range/begin.hpp>
+#include <boost/range/end.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * The class @c piecewise_constant_distribution models a \random_distribution.
+ */
+template<class RealType = double, class WeightType = double>
+class piecewise_constant_distribution {
+public:
+    typedef std::size_t input_type;
+    typedef RealType result_type;
+
+    class param_type {
+    public:
+
+        typedef piecewise_constant_distribution distribution_type;
+
+        /**
+         * Constructs a @c param_type object, representing a distribution
+         * that produces values uniformly distributed in the range [0, 1).
+         */
+        param_type()
+        {
+            _weights.push_back(WeightType(1));
+            _intervals.push_back(RealType(0));
+            _intervals.push_back(RealType(1));
+        }
+        /**
+         * Constructs a @c param_type object from two iterator ranges
+         * containing the interval boundaries and the interval weights.
+         * If there are less than two boundaries, then this is equivalent to
+         * the default constructor and creates a single interval, [0, 1).
+         *
+         * The values of the interval boundaries must be strictly
+         * increasing, and the number of weights must be one less than
+         * the number of interval boundaries.  If there are extra
+         * weights, they are ignored.
+         */
+        template<class IntervalIter, class WeightIter>
+        param_type(IntervalIter intervals_first, IntervalIter intervals_last,
+                   WeightIter weight_first)
+          : _intervals(intervals_first, intervals_last)
+        {
+            if(_intervals.size() < 2) {
+                _intervals.clear();
+                _intervals.push_back(RealType(0));
+                _intervals.push_back(RealType(1));
+                _weights.push_back(WeightType(1));
+            } else {
+                _weights.reserve(_intervals.size() - 1);
+                for(std::size_t i = 0; i < _intervals.size() - 1; ++i) {
+                    _weights.push_back(*weight_first++);
+                }
+            }
+        }
+#ifndef BOOST_NO_CXX11_HDR_INITIALIZER_LIST
+        /**
+         * Constructs a @c param_type object from an
+         * initializer_list containing the interval boundaries
+         * and a unary function specifying the weights.  Each
+         * weight is determined by calling the function at the
+         * midpoint of the corresponding interval.
+         *
+         * If the initializer_list contains less than two elements,
+         * this is equivalent to the default constructor and the
+         * distribution will produce values uniformly distributed
+         * in the range [0, 1).
+         */
+        template<class T, class F>
+        param_type(const std::initializer_list<T>& il, F f)
+          : _intervals(il.begin(), il.end())
+        {
+            if(_intervals.size() < 2) {
+                _intervals.clear();
+                _intervals.push_back(RealType(0));
+                _intervals.push_back(RealType(1));
+                _weights.push_back(WeightType(1));
+            } else {
+                _weights.reserve(_intervals.size() - 1);
+                for(std::size_t i = 0; i < _intervals.size() - 1; ++i) {
+                    RealType midpoint = (_intervals[i] + _intervals[i + 1]) / 2;
+                    _weights.push_back(f(midpoint));
+                }
+            }
+        }
+#endif
+        /**
+         * Constructs a @c param_type object from Boost.Range
+         * ranges holding the interval boundaries and the weights.  If
+         * there are less than two interval boundaries, this is equivalent
+         * to the default constructor and the distribution will produce
+         * values uniformly distributed in the range [0, 1).  The
+         * number of weights must be one less than the number of
+         * interval boundaries.
+         */
+        template<class IntervalRange, class WeightRange>
+        param_type(const IntervalRange& intervals_arg,
+                   const WeightRange& weights_arg)
+          : _intervals(boost::begin(intervals_arg), boost::end(intervals_arg)),
+            _weights(boost::begin(weights_arg), boost::end(weights_arg))
+        {
+            if(_intervals.size() < 2) {
+                _intervals.clear();
+                _intervals.push_back(RealType(0));
+                _intervals.push_back(RealType(1));
+                _weights.push_back(WeightType(1));
+            }
+        }
+
+        /**
+         * Constructs the parameters for a distribution that approximates a
+         * function.  The range of the distribution is [xmin, xmax).  This
+         * range is divided into nw equally sized intervals and the weights
+         * are found by calling the unary function f on the midpoints of the
+         * intervals.
+         */
+        template<class F>
+        param_type(std::size_t nw, RealType xmin, RealType xmax, F f)
+        {
+            std::size_t n = (nw == 0) ? 1 : nw;
+            double delta = (xmax - xmin) / n;
+            BOOST_ASSERT(delta > 0);
+            for(std::size_t k = 0; k < n; ++k) {
+                _weights.push_back(f(xmin + k*delta + delta/2));
+                _intervals.push_back(xmin + k*delta);
+            }
+            _intervals.push_back(xmax);
+        }
+
+        /**  Returns a vector containing the interval boundaries. */
+        std::vector<RealType> intervals() const { return _intervals; }
+
+        /**
+         * Returns a vector containing the probability densities
+         * over all the intervals of the distribution.
+         */
+        std::vector<RealType> densities() const
+        {
+            RealType sum = std::accumulate(_weights.begin(), _weights.end(),
+                                             static_cast<RealType>(0));
+            std::vector<RealType> result;
+            result.reserve(_weights.size());
+            for(std::size_t i = 0; i < _weights.size(); ++i) {
+                RealType width = _intervals[i + 1] - _intervals[i];
+                result.push_back(_weights[i] / (sum * width));
+            }
+            return result;
+        }
+
+        /** Writes the parameters to a @c std::ostream. */
+        BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
+        {
+            detail::print_vector(os, parm._intervals);
+            detail::print_vector(os, parm._weights);
+            return os;
+        }
+        
+        /** Reads the parameters from a @c std::istream. */
+        BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
+        {
+            std::vector<RealType> new_intervals;
+            std::vector<WeightType> new_weights;
+            detail::read_vector(is, new_intervals);
+            detail::read_vector(is, new_weights);
+            if(is) {
+                parm._intervals.swap(new_intervals);
+                parm._weights.swap(new_weights);
+            }
+            return is;
+        }
+
+        /** Returns true if the two sets of parameters are the same. */
+        BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
+        {
+            return lhs._intervals == rhs._intervals
+                && lhs._weights == rhs._weights;
+        }
+        /** Returns true if the two sets of parameters are different. */
+        BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+
+    private:
+
+        friend class piecewise_constant_distribution;
+
+        std::vector<RealType> _intervals;
+        std::vector<WeightType> _weights;
+    };
+
+    /**
+     * Creates a new @c piecewise_constant_distribution with
+     * a single interval, [0, 1).
+     */
+    piecewise_constant_distribution()
+    {
+        _intervals.push_back(RealType(0));
+        _intervals.push_back(RealType(1));
+    }
+    /**
+     * Constructs a piecewise_constant_distribution from two iterator ranges
+     * containing the interval boundaries and the interval weights.
+     * If there are less than two boundaries, then this is equivalent to
+     * the default constructor and creates a single interval, [0, 1).
+     *
+     * The values of the interval boundaries must be strictly
+     * increasing, and the number of weights must be one less than
+     * the number of interval boundaries.  If there are extra
+     * weights, they are ignored.
+     *
+     * For example,
+     *
+     * @code
+     * double intervals[] = { 0.0, 1.0, 4.0 };
+     * double weights[] = { 1.0, 1.0 };
+     * piecewise_constant_distribution<> dist(
+     *     &intervals[0], &intervals[0] + 3, &weights[0]);
+     * @endcode
+     *
+     * The distribution has a 50% chance of producing a
+     * value between 0 and 1 and a 50% chance of producing
+     * a value between 1 and 4.
+     */
+    template<class IntervalIter, class WeightIter>
+    piecewise_constant_distribution(IntervalIter first_interval,
+                                    IntervalIter last_interval,
+                                    WeightIter first_weight)
+      : _intervals(first_interval, last_interval)
+    {
+        if(_intervals.size() < 2) {
+            _intervals.clear();
+            _intervals.push_back(RealType(0));
+            _intervals.push_back(RealType(1));
+        } else {
+            std::vector<WeightType> actual_weights;
+            actual_weights.reserve(_intervals.size() - 1);
+            for(std::size_t i = 0; i < _intervals.size() - 1; ++i) {
+                actual_weights.push_back(*first_weight++);
+            }
+            typedef discrete_distribution<std::size_t, WeightType> bins_type;
+            typename bins_type::param_type bins_param(actual_weights);
+            _bins.param(bins_param);
+        }
+    }
+#ifndef BOOST_NO_CXX11_HDR_INITIALIZER_LIST
+    /**
+     * Constructs a piecewise_constant_distribution from an
+     * initializer_list containing the interval boundaries
+     * and a unary function specifying the weights.  Each
+     * weight is determined by calling the function at the
+     * midpoint of the corresponding interval.
+     *
+     * If the initializer_list contains less than two elements,
+     * this is equivalent to the default constructor and the
+     * distribution will produce values uniformly distributed
+     * in the range [0, 1).
+     */
+    template<class T, class F>
+    piecewise_constant_distribution(std::initializer_list<T> il, F f)
+      : _intervals(il.begin(), il.end())
+    {
+        if(_intervals.size() < 2) {
+            _intervals.clear();
+            _intervals.push_back(RealType(0));
+            _intervals.push_back(RealType(1));
+        } else {
+            std::vector<WeightType> actual_weights;
+            actual_weights.reserve(_intervals.size() - 1);
+            for(std::size_t i = 0; i < _intervals.size() - 1; ++i) {
+                RealType midpoint = (_intervals[i] + _intervals[i + 1]) / 2;
+                actual_weights.push_back(f(midpoint));
+            }
+            typedef discrete_distribution<std::size_t, WeightType> bins_type;
+            typename bins_type::param_type bins_param(actual_weights);
+            _bins.param(bins_param);
+        }
+    }
+#endif
+    /**
+     * Constructs a piecewise_constant_distribution from Boost.Range
+     * ranges holding the interval boundaries and the weights.  If
+     * there are less than two interval boundaries, this is equivalent
+     * to the default constructor and the distribution will produce
+     * values uniformly distributed in the range [0, 1).  The
+     * number of weights must be one less than the number of
+     * interval boundaries.
+     */
+    template<class IntervalsRange, class WeightsRange>
+    piecewise_constant_distribution(const IntervalsRange& intervals_arg,
+                                    const WeightsRange& weights_arg)
+      : _bins(weights_arg),
+        _intervals(boost::begin(intervals_arg), boost::end(intervals_arg))
+    {
+        if(_intervals.size() < 2) {
+            _intervals.clear();
+            _intervals.push_back(RealType(0));
+            _intervals.push_back(RealType(1));
+        }
+    }
+    /**
+     * Constructs a piecewise_constant_distribution that approximates a
+     * function.  The range of the distribution is [xmin, xmax).  This
+     * range is divided into nw equally sized intervals and the weights
+     * are found by calling the unary function f on the midpoints of the
+     * intervals.
+     */
+    template<class F>
+    piecewise_constant_distribution(std::size_t nw,
+                                    RealType xmin,
+                                    RealType xmax,
+                                    F f)
+      : _bins(nw, xmin, xmax, f)
+    {
+        if(nw == 0) { nw = 1; }
+        RealType delta = (xmax - xmin) / nw;
+        _intervals.reserve(nw + 1);
+        for(std::size_t i = 0; i < nw; ++i) {
+            _intervals.push_back(xmin + i * delta);
+        }
+        _intervals.push_back(xmax);
+    }
+    /**
+     * Constructs a piecewise_constant_distribution from its parameters.
+     */
+    explicit piecewise_constant_distribution(const param_type& parm)
+      : _bins(parm._weights),
+        _intervals(parm._intervals)
+    {
+    }
+
+    /**
+     * Returns a value distributed according to the parameters of the
+     * piecewist_constant_distribution.
+     */
+    template<class URNG>
+    RealType operator()(URNG& urng) const
+    {
+        std::size_t i = _bins(urng);
+        return uniform_real<RealType>(_intervals[i], _intervals[i+1])(urng);
+    }
+    
+    /**
+     * Returns a value distributed according to the parameters
+     * specified by param.
+     */
+    template<class URNG>
+    RealType operator()(URNG& urng, const param_type& parm) const
+    {
+        return piecewise_constant_distribution(parm)(urng);
+    }
+    
+    /** Returns the smallest value that the distribution can produce. */
+    result_type min BOOST_PREVENT_MACRO_SUBSTITUTION () const
+    { return _intervals.front(); }
+    /** Returns the largest value that the distribution can produce. */
+    result_type max BOOST_PREVENT_MACRO_SUBSTITUTION () const
+    { return _intervals.back(); }
+
+    /**
+     * Returns a vector containing the probability density
+     * over each interval.
+     */
+    std::vector<RealType> densities() const
+    {
+        std::vector<RealType> result(_bins.probabilities());
+        for(std::size_t i = 0; i < result.size(); ++i) {
+            result[i] /= (_intervals[i+1] - _intervals[i]);
+        }
+        return(result);
+    }
+    /**  Returns a vector containing the interval boundaries. */
+    std::vector<RealType> intervals() const { return _intervals; }
+
+    /** Returns the parameters of the distribution. */
+    param_type param() const
+    {
+        return param_type(_intervals, _bins.probabilities());
+    }
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        std::vector<RealType> new_intervals(parm._intervals);
+        typedef discrete_distribution<std::size_t, WeightType> bins_type;
+        typename bins_type::param_type bins_param(parm._weights);
+        _bins.param(bins_param);
+        _intervals.swap(new_intervals);
+    }
+    
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { _bins.reset(); }
+
+    /** Writes a distribution to a @c std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(
+        os, piecewise_constant_distribution, pcd)
+    {
+        os << pcd.param();
+        return os;
+    }
+
+    /** Reads a distribution from a @c std::istream */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(
+        is, piecewise_constant_distribution, pcd)
+    {
+        param_type parm;
+        if(is >> parm) {
+            pcd.param(parm);
+        }
+        return is;
+    }
+
+    /**
+     * Returns true if the two distributions will return the
+     * same sequence of values, when passed equal generators.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(
+        piecewise_constant_distribution, lhs,  rhs)
+    {
+        return lhs._bins == rhs._bins && lhs._intervals == rhs._intervals;
+    }
+    /**
+     * Returns true if the two distributions may return different
+     * sequences of values, when passed equal generators.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(piecewise_constant_distribution)
+
+private:
+    discrete_distribution<std::size_t, WeightType> _bins;
+    std::vector<RealType> _intervals;
+};
+
+}
+}
+
+#endif

depends/x86_64-pc-linux-gnu/include/boost/random/piecewise_linear_distribution.hpp

@@ -0,0 +1,531 @@
+/* boost random/piecewise_linear_distribution.hpp header file
+ *
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_PIECEWISE_LINEAR_DISTRIBUTION_HPP_INCLUDED
+#define BOOST_RANDOM_PIECEWISE_LINEAR_DISTRIBUTION_HPP_INCLUDED
+
+#include <vector>
+#include <algorithm>
+#include <cmath>
+#include <cstdlib>
+#include <boost/assert.hpp>
+#include <boost/random/uniform_real.hpp>
+#include <boost/random/discrete_distribution.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/detail/vector_io.hpp>
+
+#ifndef BOOST_NO_CXX11_HDR_INITIALIZER_LIST
+#include <initializer_list>
+#endif
+
+#include <boost/range/begin.hpp>
+#include <boost/range/end.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * The class @c piecewise_linear_distribution models a \random_distribution.
+ */
+template<class RealType = double>
+class piecewise_linear_distribution {
+public:
+    typedef std::size_t input_type;
+    typedef RealType result_type;
+
+    class param_type {
+    public:
+
+        typedef piecewise_linear_distribution distribution_type;
+
+        /**
+         * Constructs a @c param_type object, representing a distribution
+         * that produces values uniformly distributed in the range [0, 1).
+         */
+        param_type()
+        {
+            _weights.push_back(RealType(1));
+            _weights.push_back(RealType(1));
+            _intervals.push_back(RealType(0));
+            _intervals.push_back(RealType(1));
+        }
+        /**
+         * Constructs a @c param_type object from two iterator ranges
+         * containing the interval boundaries and weights at the boundaries.
+         * If there are fewer than two boundaries, then this is equivalent to
+         * the default constructor and the distribution will produce values
+         * uniformly distributed in the range [0, 1).
+         *
+         * The values of the interval boundaries must be strictly
+         * increasing, and the number of weights must be the same as
+         * the number of interval boundaries.  If there are extra
+         * weights, they are ignored.
+         */
+        template<class IntervalIter, class WeightIter>
+        param_type(IntervalIter intervals_first, IntervalIter intervals_last,
+                   WeightIter weight_first)
+          : _intervals(intervals_first, intervals_last)
+        {
+            if(_intervals.size() < 2) {
+                _intervals.clear();
+                _weights.push_back(RealType(1));
+                _weights.push_back(RealType(1));
+                _intervals.push_back(RealType(0));
+                _intervals.push_back(RealType(1));
+            } else {
+                _weights.reserve(_intervals.size());
+                for(std::size_t i = 0; i < _intervals.size(); ++i) {
+                    _weights.push_back(*weight_first++);
+                }
+            }
+        }
+#ifndef BOOST_NO_CXX11_HDR_INITIALIZER_LIST
+        /**
+         * Constructs a @c param_type object from an initializer_list
+         * containing the interval boundaries and a unary function
+         * specifying the weights at the boundaries.  Each weight is
+         * determined by calling the function at the corresponding point.
+         *
+         * If the initializer_list contains fewer than two elements,
+         * this is equivalent to the default constructor and the
+         * distribution will produce values uniformly distributed
+         * in the range [0, 1).
+         */
+        template<class T, class F>
+        param_type(const std::initializer_list<T>& il, F f)
+          : _intervals(il.begin(), il.end())
+        {
+            if(_intervals.size() < 2) {
+                _intervals.clear();
+                _weights.push_back(RealType(1));
+                _weights.push_back(RealType(1));
+                _intervals.push_back(RealType(0));
+                _intervals.push_back(RealType(1));
+            } else {
+                _weights.reserve(_intervals.size());
+                for(typename std::vector<RealType>::const_iterator
+                    iter = _intervals.begin(), end = _intervals.end();
+                    iter != end; ++iter)
+                {
+                    _weights.push_back(f(*iter));
+                }
+            }
+        }
+#endif
+        /**
+         * Constructs a @c param_type object from Boost.Range ranges holding
+         * the interval boundaries and the weights at the boundaries.  If
+         * there are fewer than two interval boundaries, this is equivalent
+         * to the default constructor and the distribution will produce
+         * values uniformly distributed in the range [0, 1).  The
+         * number of weights must be equal to the number of
+         * interval boundaries.
+         */
+        template<class IntervalRange, class WeightRange>
+        param_type(const IntervalRange& intervals_arg,
+                   const WeightRange& weights_arg)
+          : _intervals(boost::begin(intervals_arg), boost::end(intervals_arg)),
+            _weights(boost::begin(weights_arg), boost::end(weights_arg))
+        {
+            if(_intervals.size() < 2) {
+                _weights.clear();
+                _weights.push_back(RealType(1));
+                _weights.push_back(RealType(1));
+                _intervals.clear();
+                _intervals.push_back(RealType(0));
+                _intervals.push_back(RealType(1));
+            }
+        }
+
+        /**
+         * Constructs the parameters for a distribution that approximates a
+         * function.  The range of the distribution is [xmin, xmax).  This
+         * range is divided into nw equally sized intervals and the weights
+         * are found by calling the unary function f on the boundaries of the
+         * intervals.
+         */
+        template<class F>
+        param_type(std::size_t nw, RealType xmin, RealType xmax, F f)
+        {
+            std::size_t n = (nw == 0) ? 1 : nw;
+            double delta = (xmax - xmin) / n;
+            BOOST_ASSERT(delta > 0);
+            for(std::size_t k = 0; k < n; ++k) {
+                _weights.push_back(f(xmin + k*delta));
+                _intervals.push_back(xmin + k*delta);
+            }
+            _weights.push_back(f(xmax));
+            _intervals.push_back(xmax);
+        }
+
+        /**  Returns a vector containing the interval boundaries. */
+        std::vector<RealType> intervals() const { return _intervals; }
+
+        /**
+         * Returns a vector containing the probability densities
+         * at all the interval boundaries.
+         */
+        std::vector<RealType> densities() const
+        {
+            RealType sum = static_cast<RealType>(0);
+            for(std::size_t i = 0; i < _intervals.size() - 1; ++i) {
+                RealType width = _intervals[i + 1] - _intervals[i];
+                sum += (_weights[i] + _weights[i + 1]) * width / 2;
+            }
+            std::vector<RealType> result;
+            result.reserve(_weights.size());
+            for(typename std::vector<RealType>::const_iterator
+                iter = _weights.begin(), end = _weights.end();
+                iter != end; ++iter)
+            {
+                result.push_back(*iter / sum);
+            }
+            return result;
+        }
+
+        /** Writes the parameters to a @c std::ostream. */
+        BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
+        {
+            detail::print_vector(os, parm._intervals);
+            detail::print_vector(os, parm._weights);
+            return os;
+        }
+        
+        /** Reads the parameters from a @c std::istream. */
+        BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
+        {
+            std::vector<RealType> new_intervals;
+            std::vector<RealType> new_weights;
+            detail::read_vector(is, new_intervals);
+            detail::read_vector(is, new_weights);
+            if(is) {
+                parm._intervals.swap(new_intervals);
+                parm._weights.swap(new_weights);
+            }
+            return is;
+        }
+
+        /** Returns true if the two sets of parameters are the same. */
+        BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
+        {
+            return lhs._intervals == rhs._intervals
+                && lhs._weights == rhs._weights;
+        }
+        /** Returns true if the two sets of parameters are different. */
+        BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+
+    private:
+        friend class piecewise_linear_distribution;
+
+        std::vector<RealType> _intervals;
+        std::vector<RealType> _weights;
+    };
+
+    /**
+     * Creates a new @c piecewise_linear_distribution that
+     * produces values uniformly distributed in the range [0, 1).
+     */
+    piecewise_linear_distribution()
+    {
+        default_init();
+    }
+    /**
+     * Constructs a piecewise_linear_distribution from two iterator ranges
+     * containing the interval boundaries and the weights at the boundaries.
+     * If there are fewer than two boundaries, then this is equivalent to
+     * the default constructor and creates a distribution that
+     * produces values uniformly distributed in the range [0, 1).
+     *
+     * The values of the interval boundaries must be strictly
+     * increasing, and the number of weights must be equal to
+     * the number of interval boundaries.  If there are extra
+     * weights, they are ignored.
+     *
+     * For example,
+     *
+     * @code
+     * double intervals[] = { 0.0, 1.0, 2.0 };
+     * double weights[] = { 0.0, 1.0, 0.0 };
+     * piecewise_constant_distribution<> dist(
+     *     &intervals[0], &intervals[0] + 3, &weights[0]);
+     * @endcode
+     *
+     * produces a triangle distribution.
+     */
+    template<class IntervalIter, class WeightIter>
+    piecewise_linear_distribution(IntervalIter first_interval,
+                                  IntervalIter last_interval,
+                                  WeightIter first_weight)
+      : _intervals(first_interval, last_interval)
+    {
+        if(_intervals.size() < 2) {
+            default_init();
+        } else {
+            _weights.reserve(_intervals.size());
+            for(std::size_t i = 0; i < _intervals.size(); ++i) {
+                _weights.push_back(*first_weight++);
+            }
+            init();
+        }
+    }
+#ifndef BOOST_NO_CXX11_HDR_INITIALIZER_LIST
+    /**
+     * Constructs a piecewise_linear_distribution from an
+     * initializer_list containing the interval boundaries
+     * and a unary function specifying the weights.  Each
+     * weight is determined by calling the function at the
+     * corresponding interval boundary.
+     *
+     * If the initializer_list contains fewer than two elements,
+     * this is equivalent to the default constructor and the
+     * distribution will produce values uniformly distributed
+     * in the range [0, 1).
+     */
+    template<class T, class F>
+    piecewise_linear_distribution(std::initializer_list<T> il, F f)
+      : _intervals(il.begin(), il.end())
+    {
+        if(_intervals.size() < 2) {
+            default_init();
+        } else {
+            _weights.reserve(_intervals.size());
+            for(typename std::vector<RealType>::const_iterator
+                iter = _intervals.begin(), end = _intervals.end();
+                iter != end; ++iter)
+            {
+                _weights.push_back(f(*iter));
+            }
+            init();
+        }
+    }
+#endif
+    /**
+     * Constructs a piecewise_linear_distribution from Boost.Range
+     * ranges holding the interval boundaries and the weights.  If
+     * there are fewer than two interval boundaries, this is equivalent
+     * to the default constructor and the distribution will produce
+     * values uniformly distributed in the range [0, 1).  The
+     * number of weights must be equal to the number of
+     * interval boundaries.
+     */
+    template<class IntervalsRange, class WeightsRange>
+    piecewise_linear_distribution(const IntervalsRange& intervals_arg,
+                                  const WeightsRange& weights_arg)
+      : _intervals(boost::begin(intervals_arg), boost::end(intervals_arg)),
+        _weights(boost::begin(weights_arg), boost::end(weights_arg))
+    {
+        if(_intervals.size() < 2) {
+            default_init();
+        } else {
+            init();
+        }
+    }
+    /**
+     * Constructs a piecewise_linear_distribution that approximates a
+     * function.  The range of the distribution is [xmin, xmax).  This
+     * range is divided into nw equally sized intervals and the weights
+     * are found by calling the unary function f on the interval boundaries.
+     */
+    template<class F>
+    piecewise_linear_distribution(std::size_t nw,
+                                  RealType xmin,
+                                  RealType xmax,
+                                  F f)
+    {
+        if(nw == 0) { nw = 1; }
+        RealType delta = (xmax - xmin) / nw;
+        _intervals.reserve(nw + 1);
+        for(std::size_t i = 0; i < nw; ++i) {
+            RealType x = xmin + i * delta;
+            _intervals.push_back(x);
+            _weights.push_back(f(x));
+        }
+        _intervals.push_back(xmax);
+        _weights.push_back(f(xmax));
+        init();
+    }
+    /**
+     * Constructs a piecewise_linear_distribution from its parameters.
+     */
+    explicit piecewise_linear_distribution(const param_type& parm)
+      : _intervals(parm._intervals),
+        _weights(parm._weights)
+    {
+        init();
+    }
+
+    /**
+     * Returns a value distributed according to the parameters of the
+     * piecewise_linear_distribution.
+     */
+    template<class URNG>
+    RealType operator()(URNG& urng) const
+    {
+        std::size_t i = _bins(urng);
+        bool is_in_rectangle = (i % 2 == 0);
+        i = i / 2;
+        uniform_real<RealType> dist(_intervals[i], _intervals[i+1]);
+        if(is_in_rectangle) {
+            return dist(urng);
+        } else if(_weights[i] < _weights[i+1]) {
+            return (std::max)(dist(urng), dist(urng));
+        } else {
+            return (std::min)(dist(urng), dist(urng));
+        }
+    }
+    
+    /**
+     * Returns a value distributed according to the parameters
+     * specified by param.
+     */
+    template<class URNG>
+    RealType operator()(URNG& urng, const param_type& parm) const
+    {
+        return piecewise_linear_distribution(parm)(urng);
+    }
+    
+    /** Returns the smallest value that the distribution can produce. */
+    result_type min BOOST_PREVENT_MACRO_SUBSTITUTION () const
+    { return _intervals.front(); }
+    /** Returns the largest value that the distribution can produce. */
+    result_type max BOOST_PREVENT_MACRO_SUBSTITUTION () const
+    { return _intervals.back(); }
+
+    /**
+     * Returns a vector containing the probability densities
+     * at the interval boundaries.
+     */
+    std::vector<RealType> densities() const
+    {
+        RealType sum = static_cast<RealType>(0);
+        for(std::size_t i = 0; i < _intervals.size() - 1; ++i) {
+            RealType width = _intervals[i + 1] - _intervals[i];
+            sum += (_weights[i] + _weights[i + 1]) * width / 2;
+        }
+        std::vector<RealType> result;
+        result.reserve(_weights.size());
+        for(typename std::vector<RealType>::const_iterator
+            iter = _weights.begin(), end = _weights.end();
+            iter != end; ++iter)
+        {
+            result.push_back(*iter / sum);
+        }
+        return result;
+    }
+    /**  Returns a vector containing the interval boundaries. */
+    std::vector<RealType> intervals() const { return _intervals; }
+
+    /** Returns the parameters of the distribution. */
+    param_type param() const
+    {
+        return param_type(_intervals, _weights);
+    }
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        std::vector<RealType> new_intervals(parm._intervals);
+        std::vector<RealType> new_weights(parm._weights);
+        init(new_intervals, new_weights);
+        _intervals.swap(new_intervals);
+        _weights.swap(new_weights);
+    }
+    
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { _bins.reset(); }
+
+    /** Writes a distribution to a @c std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(
+        os, piecewise_linear_distribution, pld)
+    {
+        os << pld.param();
+        return os;
+    }
+
+    /** Reads a distribution from a @c std::istream */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(
+        is, piecewise_linear_distribution, pld)
+    {
+        param_type parm;
+        if(is >> parm) {
+            pld.param(parm);
+        }
+        return is;
+    }
+
+    /**
+     * Returns true if the two distributions will return the
+     * same sequence of values, when passed equal generators.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(
+        piecewise_linear_distribution, lhs,  rhs)
+    {
+        return lhs._intervals == rhs._intervals && lhs._weights == rhs._weights;
+    }
+    /**
+     * Returns true if the two distributions may return different
+     * sequences of values, when passed equal generators.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(piecewise_linear_distribution)
+
+private:
+
+    /// @cond \show_private
+
+    void init(const std::vector<RealType>& intervals_arg,
+              const std::vector<RealType>& weights_arg)
+    {
+        using std::abs;
+        std::vector<RealType> bin_weights;
+        bin_weights.reserve((intervals_arg.size() - 1) * 2);
+        for(std::size_t i = 0; i < intervals_arg.size() - 1; ++i) {
+            RealType width = intervals_arg[i + 1] - intervals_arg[i];
+            RealType w1 = weights_arg[i];
+            RealType w2 = weights_arg[i + 1];
+            bin_weights.push_back((std::min)(w1, w2) * width);
+            bin_weights.push_back(abs(w1 - w2) * width / 2);
+        }
+        typedef discrete_distribution<std::size_t, RealType> bins_type;
+        typename bins_type::param_type bins_param(bin_weights);
+        _bins.param(bins_param);
+    }
+
+    void init()
+    {
+        init(_intervals, _weights);
+    }
+
+    void default_init()
+    {
+        _intervals.clear();
+        _intervals.push_back(RealType(0));
+        _intervals.push_back(RealType(1));
+        _weights.clear();
+        _weights.push_back(RealType(1));
+        _weights.push_back(RealType(1));
+        init();
+    }
+
+    discrete_distribution<std::size_t, RealType> _bins;
+    std::vector<RealType> _intervals;
+    std::vector<RealType> _weights;
+
+    /// @endcond
+};
+
+}
+}
+
+#endif

depends/x86_64-pc-linux-gnu/include/boost/random/poisson_distribution.hpp

@@ -0,0 +1,360 @@
+/* boost random/poisson_distribution.hpp header file
+ *
+ * Copyright Jens Maurer 2002
+ * Copyright Steven Watanabe 2010
+ * 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.
+ *
+ * $Id$
+ *
+ */
+
+#ifndef BOOST_RANDOM_POISSON_DISTRIBUTION_HPP
+#define BOOST_RANDOM_POISSON_DISTRIBUTION_HPP
+
+#include <boost/config/no_tr1/cmath.hpp>
+#include <cstdlib>
+#include <iosfwd>
+#include <boost/assert.hpp>
+#include <boost/limits.hpp>
+#include <boost/random/uniform_01.hpp>
+#include <boost/random/detail/config.hpp>
+
+#include <boost/random/detail/disable_warnings.hpp>
+
+namespace boost {
+namespace random {
+
+namespace detail {
+
+template<class RealType>
+struct poisson_table {
+    static RealType value[10];
+};
+
+template<class RealType>
+RealType poisson_table<RealType>::value[10] = {
+    0.0,
+    0.0,
+    0.69314718055994529,
+    1.7917594692280550,
+    3.1780538303479458,
+    4.7874917427820458,
+    6.5792512120101012,
+    8.5251613610654147,
+    10.604602902745251,
+    12.801827480081469
+};
+
+}
+
+/**
+ * An instantiation of the class template @c poisson_distribution is a
+ * model of \random_distribution.  The poisson distribution has
+ * \f$p(i) = \frac{e^{-\lambda}\lambda^i}{i!}\f$
+ *
+ * This implementation is based on the PTRD algorithm described
+ * 
+ *  @blockquote
+ *  "The transformed rejection method for generating Poisson random variables",
+ *  Wolfgang Hormann, Insurance: Mathematics and Economics
+ *  Volume 12, Issue 1, February 1993, Pages 39-45
+ *  @endblockquote
+ */
+template<class IntType = int, class RealType = double>
+class poisson_distribution {
+public:
+    typedef IntType result_type;
+    typedef RealType input_type;
+
+    class param_type {
+    public:
+        typedef poisson_distribution distribution_type;
+        /**
+         * Construct a param_type object with the parameter "mean"
+         *
+         * Requires: mean > 0
+         */
+        explicit param_type(RealType mean_arg = RealType(1))
+          : _mean(mean_arg)
+        {
+            BOOST_ASSERT(_mean > 0);
+        }
+        /* Returns the "mean" parameter of the distribution. */
+        RealType mean() const { return _mean; }
+#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
+        /** Writes the parameters of the distribution to a @c std::ostream. */
+        template<class CharT, class Traits>
+        friend std::basic_ostream<CharT, Traits>&
+        operator<<(std::basic_ostream<CharT, Traits>& os,
+                   const param_type& parm)
+        {
+            os << parm._mean;
+            return os;
+        }
+
+        /** Reads the parameters of the distribution from a @c std::istream. */
+        template<class CharT, class Traits>
+        friend std::basic_istream<CharT, Traits>&
+        operator>>(std::basic_istream<CharT, Traits>& is, param_type& parm)
+        {
+            is >> parm._mean;
+            return is;
+        }
+#endif
+        /** Returns true if the parameters have the same values. */
+        friend bool operator==(const param_type& lhs, const param_type& rhs)
+        {
+            return lhs._mean == rhs._mean;
+        }
+        /** Returns true if the parameters have different values. */
+        friend bool operator!=(const param_type& lhs, const param_type& rhs)
+        {
+            return !(lhs == rhs);
+        }
+    private:
+        RealType _mean;
+    };
+    
+    /**
+     * Constructs a @c poisson_distribution with the parameter @c mean.
+     *
+     * Requires: mean > 0
+     */
+    explicit poisson_distribution(RealType mean_arg = RealType(1))
+      : _mean(mean_arg)
+    {
+        BOOST_ASSERT(_mean > 0);
+        init();
+    }
+    
+    /**
+     * Construct an @c poisson_distribution object from the
+     * parameters.
+     */
+    explicit poisson_distribution(const param_type& parm)
+      : _mean(parm.mean())
+    {
+        init();
+    }
+    
+    /**
+     * Returns a random variate distributed according to the
+     * poisson distribution.
+     */
+    template<class URNG>
+    IntType operator()(URNG& urng) const
+    {
+        if(use_inversion()) {
+            return invert(urng);
+        } else {
+            return generate(urng);
+        }
+    }
+
+    /**
+     * Returns a random variate distributed according to the
+     * poisson distribution with parameters specified by param.
+     */
+    template<class URNG>
+    IntType operator()(URNG& urng, const param_type& parm) const
+    {
+        return poisson_distribution(parm)(urng);
+    }
+
+    /** Returns the "mean" parameter of the distribution. */
+    RealType mean() const { return _mean; }
+    
+    /** Returns the smallest value that the distribution can produce. */
+    IntType min BOOST_PREVENT_MACRO_SUBSTITUTION() const { return 0; }
+    /** Returns the largest value that the distribution can produce. */
+    IntType max BOOST_PREVENT_MACRO_SUBSTITUTION() const
+    { return (std::numeric_limits<IntType>::max)(); }
+
+    /** Returns the parameters of the distribution. */
+    param_type param() const { return param_type(_mean); }
+    /** Sets parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        _mean = parm.mean();
+        init();
+    }
+
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { }
+
+#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
+    /** Writes the parameters of the distribution to a @c std::ostream. */
+    template<class CharT, class Traits>
+    friend std::basic_ostream<CharT,Traits>&
+    operator<<(std::basic_ostream<CharT,Traits>& os,
+               const poisson_distribution& pd)
+    {
+        os << pd.param();
+        return os;
+    }
+    
+    /** Reads the parameters of the distribution from a @c std::istream. */
+    template<class CharT, class Traits>
+    friend std::basic_istream<CharT,Traits>&
+    operator>>(std::basic_istream<CharT,Traits>& is, poisson_distribution& pd)
+    {
+        pd.read(is);
+        return is;
+    }
+#endif
+    
+    /** Returns true if the two distributions will produce the same
+        sequence of values, given equal generators. */
+    friend bool operator==(const poisson_distribution& lhs,
+                           const poisson_distribution& rhs)
+    {
+        return lhs._mean == rhs._mean;
+    }
+    /** Returns true if the two distributions could produce different
+        sequences of values, given equal generators. */
+    friend bool operator!=(const poisson_distribution& lhs,
+                           const poisson_distribution& rhs)
+    {
+        return !(lhs == rhs);
+    }
+
+private:
+
+    /// @cond show_private
+
+    template<class CharT, class Traits>
+    void read(std::basic_istream<CharT, Traits>& is) {
+        param_type parm;
+        if(is >> parm) {
+            param(parm);
+        }
+    }
+
+    bool use_inversion() const
+    {
+        return _mean < 10;
+    }
+
+    static RealType log_factorial(IntType k)
+    {
+        BOOST_ASSERT(k >= 0);
+        BOOST_ASSERT(k < 10);
+        return detail::poisson_table<RealType>::value[k];
+    }
+
+    void init()
+    {
+        using std::sqrt;
+        using std::exp;
+
+        if(use_inversion()) {
+            _exp_mean = exp(-_mean);
+        } else {
+            _ptrd.smu = sqrt(_mean);
+            _ptrd.b = 0.931 + 2.53 * _ptrd.smu;
+            _ptrd.a = -0.059 + 0.02483 * _ptrd.b;
+            _ptrd.inv_alpha = 1.1239 + 1.1328 / (_ptrd.b - 3.4);
+            _ptrd.v_r = 0.9277 - 3.6224 / (_ptrd.b - 2);
+        }
+    }
+    
+    template<class URNG>
+    IntType generate(URNG& urng) const
+    {
+        using std::floor;
+        using std::abs;
+        using std::log;
+
+        while(true) {
+            RealType u;
+            RealType v = uniform_01<RealType>()(urng);
+            if(v <= 0.86 * _ptrd.v_r) {
+                u = v / _ptrd.v_r - 0.43;
+                return static_cast<IntType>(floor(
+                    (2*_ptrd.a/(0.5-abs(u)) + _ptrd.b)*u + _mean + 0.445));
+            }
+
+            if(v >= _ptrd.v_r) {
+                u = uniform_01<RealType>()(urng) - 0.5;
+            } else {
+                u = v/_ptrd.v_r - 0.93;
+                u = ((u < 0)? -0.5 : 0.5) - u;
+                v = uniform_01<RealType>()(urng) * _ptrd.v_r;
+            }
+
+            RealType us = 0.5 - abs(u);
+            if(us < 0.013 && v > us) {
+                continue;
+            }
+
+            RealType k = floor((2*_ptrd.a/us + _ptrd.b)*u+_mean+0.445);
+            v = v*_ptrd.inv_alpha/(_ptrd.a/(us*us) + _ptrd.b);
+
+            RealType log_sqrt_2pi = 0.91893853320467267;
+
+            if(k >= 10) {
+                if(log(v*_ptrd.smu) <= (k + 0.5)*log(_mean/k)
+                               - _mean
+                               - log_sqrt_2pi
+                               + k
+                               - (1/12. - (1/360. - 1/(1260.*k*k))/(k*k))/k) {
+                    return static_cast<IntType>(k);
+                }
+            } else if(k >= 0) {
+                if(log(v) <= k*log(_mean)
+                           - _mean
+                           - log_factorial(static_cast<IntType>(k))) {
+                    return static_cast<IntType>(k);
+                }
+            }
+        }
+    }
+
+    template<class URNG>
+    IntType invert(URNG& urng) const
+    {
+        RealType p = _exp_mean;
+        IntType x = 0;
+        RealType u = uniform_01<RealType>()(urng);
+        while(u > p) {
+            u = u - p;
+            ++x;
+            p = _mean * p / x;
+        }
+        return x;
+    }
+
+    RealType _mean;
+
+    union {
+        // for ptrd
+        struct {
+            RealType v_r;
+            RealType a;
+            RealType b;
+            RealType smu;
+            RealType inv_alpha;
+        } _ptrd;
+        // for inversion
+        RealType _exp_mean;
+    };
+
+    /// @endcond
+};
+
+} // namespace random
+
+using random::poisson_distribution;
+
+} // namespace boost
+
+#include <boost/random/detail/enable_warnings.hpp>
+
+#endif // BOOST_RANDOM_POISSON_DISTRIBUTION_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/random_device.hpp

@@ -0,0 +1,143 @@
+/* boost random/random_device.hpp header file
+ *
+ * Copyright Jens Maurer 2000
+ * 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)
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2000-02-18  Portability fixes (thanks to Beman Dawes)
+ */
+
+//  See http://www.boost.org/libs/random for documentation.
+
+
+#ifndef BOOST_RANDOM_RANDOM_DEVICE_HPP
+#define BOOST_RANDOM_RANDOM_DEVICE_HPP
+
+#include <string>
+#include <boost/config.hpp>
+#include <boost/noncopyable.hpp>
+#include <boost/random/detail/auto_link.hpp>
+#include <boost/system/config.hpp> // force autolink to find Boost.System
+
+namespace boost {
+namespace random {
+
+/**
+ * Class \random_device models a \nondeterministic_random_number_generator.
+ * It uses one or more implementation-defined stochastic processes to
+ * generate a sequence of uniformly distributed non-deterministic random
+ * numbers. For those environments where a non-deterministic random number
+ * generator is not available, class random_device must not be implemented. See
+ *
+ *  @blockquote
+ *  "Randomness Recommendations for Security", D. Eastlake, S. Crocker,
+ *  J. Schiller, Network Working Group, RFC 1750, December 1994
+ *  @endblockquote
+ *
+ * for further discussions. 
+ *
+ * @xmlnote
+ * Some operating systems abstract the computer hardware enough
+ * to make it difficult to non-intrusively monitor stochastic processes.
+ * However, several do provide a special device for exactly this purpose.
+ * It seems to be impossible to emulate the functionality using Standard
+ * C++ only, so users should be aware that this class may not be available
+ * on all platforms.
+ * @endxmlnote
+ *
+ * <b>Implementation Note for Linux</b>
+ *
+ * On the Linux operating system, token is interpreted as a filesystem
+ * path. It is assumed that this path denotes an operating system
+ * pseudo-device which generates a stream of non-deterministic random
+ * numbers. The pseudo-device should never signal an error or end-of-file.
+ * Otherwise, @c std::ios_base::failure is thrown. By default,
+ * \random_device uses the /dev/urandom pseudo-device to retrieve
+ * the random numbers. Another option would be to specify the /dev/random
+ * pseudo-device, which blocks on reads if the entropy pool has no more
+ * random bits available.
+ *
+ * <b>Implementation Note for Windows</b>
+ *
+ * On the Windows operating system, token is interpreted as the name
+ * of a cryptographic service provider.  By default \random_device uses
+ * MS_DEF_PROV.
+ *
+ * <b>Performance</b>
+ *
+ * The test program <a href="\boost/libs/random/performance/nondet_random_speed.cpp">
+ * nondet_random_speed.cpp</a> measures the execution times of the
+ * random_device.hpp implementation of the above algorithms in a tight
+ * loop. The performance has been evaluated on an
+ * Intel(R) Core(TM) i7 CPU Q 840 \@ 1.87GHz, 1867 Mhz with
+ * Visual C++ 2010, Microsoft Windows 7 Professional and with gcc 4.4.5,
+ * Ubuntu Linux 2.6.35-25-generic.
+ *
+ * <table cols="2">
+ *   <tr><th>Platform</th><th>time per invocation [microseconds]</th></tr>
+ *   <tr><td> Windows </td><td>2.9</td></tr>
+ *   <tr><td> Linux </td><td>1.7</td></tr>
+ * </table>
+ *
+ * The measurement error is estimated at +/- 1 usec.
+ */
+class random_device : private noncopyable
+{
+public:
+    typedef unsigned int result_type;
+    BOOST_STATIC_CONSTANT(bool, has_fixed_range = false);
+
+    /** Returns the smallest value that the \random_device can produce. */
+    static result_type min BOOST_PREVENT_MACRO_SUBSTITUTION () { return 0; }
+    /** Returns the largest value that the \random_device can produce. */
+    static result_type max BOOST_PREVENT_MACRO_SUBSTITUTION () { return ~0u; }
+
+    /** Constructs a @c random_device, optionally using the default device. */
+    BOOST_RANDOM_DECL random_device();
+    /** 
+     * Constructs a @c random_device, optionally using the given token as an
+     * access specification (for example, a URL) to some implementation-defined
+     * service for monitoring a stochastic process. 
+     */
+    BOOST_RANDOM_DECL explicit random_device(const std::string& token);
+
+    BOOST_RANDOM_DECL ~random_device();
+
+    /**
+     * Returns: An entropy estimate for the random numbers returned by
+     * operator(), in the range min() to log2( max()+1). A deterministic
+     * random number generator (e.g. a pseudo-random number engine)
+     * has entropy 0.
+     *
+     * Throws: Nothing.
+     */
+    BOOST_RANDOM_DECL double entropy() const;
+    /** Returns a random value in the range [min, max]. */
+    BOOST_RANDOM_DECL unsigned int operator()();
+
+    /** Fills a range with random 32-bit values. */
+    template<class Iter>
+    void generate(Iter begin, Iter end)
+    {
+        for(; begin != end; ++begin) {
+            *begin = (*this)();
+        }
+    }
+
+private:
+    class impl;
+    impl * pimpl;
+};
+
+} // namespace random
+
+using random::random_device;
+
+} // namespace boost
+
+#endif /* BOOST_RANDOM_RANDOM_DEVICE_HPP */

depends/x86_64-pc-linux-gnu/include/boost/random/random_number_generator.hpp

@@ -0,0 +1,73 @@
+/* boost random/random_number_generator.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2001-02-18  moved to individual header files
+ */
+
+#ifndef BOOST_RANDOM_RANDOM_NUMBER_GENERATOR_HPP
+#define BOOST_RANDOM_RANDOM_NUMBER_GENERATOR_HPP
+
+#include <boost/assert.hpp>
+#include <boost/random/uniform_int_distribution.hpp>
+
+#include <boost/random/detail/disable_warnings.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * Instantiations of class template random_number_generator model a
+ * RandomNumberGenerator (std:25.2.11 [lib.alg.random.shuffle]). On
+ * each invocation, it returns a uniformly distributed integer in
+ * the range [0..n).
+ *
+ * The template parameter IntType shall denote some integer-like value type.
+ */
+template<class URNG, class IntType = long>
+class random_number_generator
+{
+public:
+    typedef URNG base_type;
+    typedef IntType argument_type;
+    typedef IntType result_type;
+    /**
+     * Constructs a random_number_generator functor with the given
+     * \uniform_random_number_generator as the underlying source of
+     * random numbers.
+     */
+    random_number_generator(base_type& rng) : _rng(rng) {}
+
+    // compiler-generated copy ctor is fine
+    // assignment is disallowed because there is a reference member
+
+    /**
+     * Returns a value in the range [0, n)
+     */
+    result_type operator()(argument_type n)
+    {
+        BOOST_ASSERT(n > 0);
+        return uniform_int_distribution<IntType>(0, n-1)(_rng);
+    }
+
+private:
+    base_type& _rng;
+};
+
+} // namespace random
+
+using random::random_number_generator;
+
+} // namespace boost
+
+#include <boost/random/detail/enable_warnings.hpp>
+
+#endif // BOOST_RANDOM_RANDOM_NUMBER_GENERATOR_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/ranlux.hpp

@@ -0,0 +1,99 @@
+/* boost random/ranlux.hpp header file
+ *
+ * Copyright Jens Maurer 2002
+ * 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2001-02-18  created
+ */
+
+#ifndef BOOST_RANDOM_RANLUX_HPP
+#define BOOST_RANDOM_RANLUX_HPP
+
+#include <boost/config.hpp>
+#include <boost/random/subtract_with_carry.hpp>
+#include <boost/random/discard_block.hpp>
+
+namespace boost {
+
+namespace random {
+
+namespace detail {
+/**
+ * The ranlux family of generators are described in
+ *
+ *  @blockquote
+ *  "A portable high-quality random number generator for lattice field theory
+ *  calculations", M. Luescher, Computer Physics Communications, 79 (1994)
+ *  pp 100-110. 
+ *  @endblockquote
+ *
+ * The levels are given in
+ * 
+ *  @blockquote
+ *  "RANLUX: A Fortran implementation of the high-quality
+ *  pseudorandom number generator of Luescher", F. James,
+ *  Computer Physics Communications 79 (1994) 111-114
+ *  @endblockquote
+ */
+class ranlux_documentation {};
+}
+
+typedef subtract_with_carry_engine<uint32_t, 24, 10, 24> ranlux_base;
+typedef subtract_with_carry_01_engine<float, 24, 10, 24> ranlux_base_01;
+typedef subtract_with_carry_01_engine<double, 48, 10, 24> ranlux64_base_01;
+
+
+/** @copydoc boost::random::detail::ranlux_documentation */
+typedef discard_block_engine<ranlux_base, 223, 24> ranlux3;
+/** @copydoc boost::random::detail::ranlux_documentation */
+typedef discard_block_engine<ranlux_base, 389, 24> ranlux4;
+
+/** @copydoc boost::random::detail::ranlux_documentation */
+typedef discard_block_engine<ranlux_base_01, 223, 24> ranlux3_01;
+/** @copydoc boost::random::detail::ranlux_documentation */
+typedef discard_block_engine<ranlux_base_01, 389, 24> ranlux4_01;
+
+/** @copydoc boost::random::detail::ranlux_documentation */
+typedef discard_block_engine<ranlux64_base_01, 223, 24> ranlux64_3_01;
+/** @copydoc boost::random::detail::ranlux_documentation */
+typedef discard_block_engine<ranlux64_base_01, 389, 24> ranlux64_4_01;
+
+#if !defined(BOOST_NO_INT64_T) && !defined(BOOST_NO_INTEGRAL_INT64_T)
+typedef subtract_with_carry_engine<uint64_t, 48, 10, 24> ranlux64_base;
+/** @copydoc boost::random::detail::ranlux_documentation */
+typedef discard_block_engine<ranlux64_base, 223, 24> ranlux64_3;
+/** @copydoc boost::random::detail::ranlux_documentation */
+typedef discard_block_engine<ranlux64_base, 389, 24> ranlux64_4;
+#endif /* !BOOST_NO_INT64_T && !BOOST_NO_INTEGRAL_INT64_T */
+
+
+typedef subtract_with_carry_engine<uint32_t, 24, 10, 24> ranlux24_base;
+typedef subtract_with_carry_engine<uint64_t, 48, 5, 12> ranlux48_base;
+
+typedef discard_block_engine<ranlux24_base, 223, 23> ranlux24;
+#if !defined(BOOST_NO_INT64_T) && !defined(BOOST_NO_INTEGRAL_INT64_T)
+typedef discard_block_engine<ranlux48_base, 389, 11> ranlux48;
+#endif
+}
+
+using random::ranlux3;
+using random::ranlux4;
+using random::ranlux3_01;
+using random::ranlux4_01;
+using random::ranlux64_3_01;
+using random::ranlux64_4_01;
+#if !defined(BOOST_NO_INT64_T) && !defined(BOOST_NO_INTEGRAL_INT64_T)
+using random::ranlux64_3;
+using random::ranlux64_4;
+#endif
+
+} // namespace boost
+
+#endif // BOOST_RANDOM_LINEAR_CONGRUENTIAL_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/seed_seq.hpp

@@ -0,0 +1,118 @@
+/* boost random/seed_seq.hpp header file
+ *
+ * Copyright Steven Watanabe 2010
+ * 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.
+ *
+ * $Id$
+ *
+ */
+
+#ifndef BOOST_RANDOM_SEED_SEQ_HPP
+#define BOOST_RANDOM_SEED_SEQ_HPP
+
+#include <boost/config.hpp>
+#include <boost/cstdint.hpp>
+#include <boost/range/begin.hpp>
+#include <boost/range/end.hpp>
+#include <cstddef>
+#include <vector>
+#include <algorithm>
+#include <iterator>
+
+#ifndef BOOST_NO_CXX11_HDR_INITIALIZER_LIST
+#include <initializer_list>
+#endif
+
+namespace boost {
+namespace random {
+
+/**
+ * The class @c seed_seq stores a sequence of 32-bit words
+ * for seeding a \pseudo_random_number_generator.  These
+ * words will be combined to fill the entire state of the
+ * generator.
+ */
+class seed_seq {
+public:
+    typedef boost::uint_least32_t result_type;
+
+    /** Initializes a seed_seq to hold an empty sequence. */
+    seed_seq() {}
+#ifndef BOOST_NO_CXX11_HDR_INITIALIZER_LIST
+    /** Initializes the sequence from an initializer_list. */
+    template<class T>
+    seed_seq(const std::initializer_list<T>& il) : v(il.begin(), il.end()) {}
+#endif
+    /** Initializes the sequence from an iterator range. */
+    template<class Iter>
+    seed_seq(Iter first, Iter last) : v(first, last) {}
+    /** Initializes the sequence from Boost.Range range. */
+    template<class Range>
+    explicit seed_seq(const Range& range)
+      : v(boost::begin(range), boost::end(range)) {}
+
+    /**
+     * Fills a range with 32-bit values based on the stored sequence.
+     *
+     * Requires: Iter must be a Random Access Iterator whose value type
+     * is an unsigned integral type at least 32 bits wide.
+     */
+    template<class Iter>
+    void generate(Iter first, Iter last) const
+    {
+        typedef typename std::iterator_traits<Iter>::value_type value_type;
+        std::fill(first, last, static_cast<value_type>(0x8b8b8b8bu));
+        std::size_t s = v.size();
+        std::size_t n = last - first;
+        std::size_t t =
+            (n >= 623) ? 11 :
+            (n >=  68) ?  7 :
+            (n >=  39) ?  5 :
+            (n >=   7) ?  3 :
+            (n - 1)/2;
+        std::size_t p = (n - t) / 2;
+        std::size_t q = p + t;
+        std::size_t m = (std::max)(s+1, n);
+        value_type mask = 0xffffffffu;
+        for(std::size_t k = 0; k < m; ++k) {
+            value_type r1 = static_cast<value_type>
+                (*(first + k%n) ^ *(first + (k+p)%n) ^ *(first + (k+n-1)%n));
+            r1 = r1 ^ (r1 >> 27);
+            r1 = (r1 * 1664525u) & mask;
+            value_type r2 = static_cast<value_type>(r1 +
+                ((k == 0) ? s :
+                 (k <= s) ? k % n + v[k - 1] :
+                 (k % n)));
+            *(first + (k+p)%n) = (*(first + (k+p)%n) + r1) & mask;
+            *(first + (k+q)%n) = (*(first + (k+q)%n) + r2) & mask;
+            *(first + k%n) = r2;
+        }
+        for(std::size_t k = m; k < m + n; ++k) {
+            value_type r3 = static_cast<value_type>
+                ((*(first + k%n) + *(first + (k+p)%n) + *(first + (k+n-1)%n))
+                & mask);
+            r3 = r3 ^ (r3 >> 27);
+            r3 = (r3 * 1566083941u) & mask;
+            value_type r4 = static_cast<value_type>(r3 - k%m);
+            *(first + (k+p)%n) ^= r3;
+            *(first + (k+q)%n) ^= r4;
+            *(first + k%n) = r4;
+        }
+    }
+    /** Returns the size of the sequence. */
+    std::size_t size() const { return v.size(); }
+    /** Writes the stored sequence to iter. */
+    template<class Iter>
+    void param(Iter out) { std::copy(v.begin(), v.end(), out); }
+private:
+    std::vector<result_type> v;
+};
+
+}
+}
+
+#endif

depends/x86_64-pc-linux-gnu/include/boost/random/shuffle_order.hpp

@@ -0,0 +1,269 @@
+/* boost random/shuffle_order.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * Copyright Steven Watanabe 2010
+ * 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.
+ *
+ * $Id$
+ *
+ */
+
+#ifndef BOOST_RANDOM_SHUFFLE_ORDER_HPP
+#define BOOST_RANDOM_SHUFFLE_ORDER_HPP
+
+#include <iostream>
+#include <algorithm>     // std::copy
+#include <cassert>
+#include <boost/config.hpp>
+#include <boost/limits.hpp>
+#include <boost/static_assert.hpp>
+#include <boost/cstdint.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/detail/seed.hpp>
+#include <boost/random/detail/signed_unsigned_tools.hpp>
+#include <boost/random/linear_congruential.hpp>
+
+#include <boost/random/detail/disable_warnings.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * Instatiations of class template @c shuffle_order_engine model a
+ * \pseudo_random_number_generator. It mixes the output
+ * of some (usually \linear_congruential_engine)
+ * \uniform_random_number_generator to get better statistical properties.
+ * The algorithm is described in
+ *
+ *  @blockquote
+ *  "Improving a poor random number generator", Carter Bays
+ *  and S.D. Durham, ACM Transactions on Mathematical Software,
+ *  Vol 2, No. 1, March 1976, pp. 59-64.
+ *  http://doi.acm.org/10.1145/355666.355670
+ *  @endblockquote
+ *
+ * The output of the base generator is buffered in an array of
+ * length k. Every output X(n) has a second role: It gives an
+ * index into the array where X(n+1) will be retrieved. Used
+ * array elements are replaced with fresh output from the base
+ * generator.
+ *
+ * Template parameters are the base generator and the array
+ * length k, which should be around 100.
+ */
+template<class UniformRandomNumberGenerator, std::size_t k>
+class shuffle_order_engine
+{
+public:
+    typedef UniformRandomNumberGenerator base_type;
+    typedef typename base_type::result_type result_type;
+
+    BOOST_STATIC_CONSTANT(bool, has_fixed_range = false);
+    BOOST_STATIC_CONSTANT(std::size_t, buffer_size = k);
+    BOOST_STATIC_CONSTANT(std::size_t, table_size = k);
+
+    BOOST_STATIC_ASSERT(std::numeric_limits<result_type>::is_integer);
+    BOOST_STATIC_ASSERT(k > 0);
+
+    /**
+     * Constructs a @c shuffle_order_engine by invoking the
+     * default constructor of the base generator.
+     *
+     * Complexity: Exactly k+1 invocations of the base generator.
+     */
+    shuffle_order_engine() : _rng() { init(); }
+    /**
+     * Constructs a @c shuffle_output_engine by invoking the one-argument
+     * constructor of the base generator with the parameter seed.
+     *
+     * Complexity: Exactly k+1 invocations of the base generator.
+     */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(shuffle_order_engine,
+                                               result_type, s)
+    { _rng.seed(s); init(); }
+    BOOST_RANDOM_DETAIL_SEED_SEQ_CONSTRUCTOR(shuffle_order_engine, SeedSeq, seq)
+    { _rng.seed(seq); init(); }
+    /**
+     * Constructs a @c shuffle_output_engine by using a copy
+     * of the provided generator.
+     *
+     * Precondition: The template argument UniformRandomNumberGenerator
+     * shall denote a CopyConstructible type.
+     *
+     * Complexity: Exactly k+1 invocations of the base generator.
+     */
+    explicit shuffle_order_engine(const base_type & rng) : _rng(rng) { init(); }
+
+#ifndef BOOST_NO_CXX11_RVALUE_REFERENCES
+    explicit shuffle_order_engine(base_type&& rng) : _rng(rng) { init(); }
+#endif
+
+    template<class It> shuffle_order_engine(It& first, It last)
+      : _rng(first, last) { init(); }
+    void seed() { _rng.seed(); init(); }
+    /**
+     * Invokes the one-argument seed method of the base generator
+     * with the parameter seed and re-initializes the internal buffer array.
+     *
+     * Complexity: Exactly k+1 invocations of the base generator.
+     */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_SEED(shuffle_order_engine,
+        result_type, seed_arg)
+    { _rng.seed(seed_arg); init(); }
+    /**
+     * Invokes the one-argument seed method of the base generator
+     * with the parameter seq and re-initializes the internal buffer array.
+     *
+     * Complexity: Exactly k+1 invocations of the base generator.
+     */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_SEED(shuffle_order_engine, SeedSeq, seq)
+    { _rng.seed(seq); init(); }
+    template<class It> void seed(It& first, It last)
+    { _rng.seed(first, last); init(); }
+
+    const base_type& base() const { return _rng; }
+
+    result_type operator()() {
+        // calculating the range every time may seem wasteful.  However, this
+        // makes the information locally available for the optimizer.
+        typedef typename boost::random::traits::make_unsigned<result_type>::type base_unsigned;
+        const base_unsigned brange =
+            detail::subtract<result_type>()((max)(), (min)());
+        const base_unsigned off =
+            detail::subtract<result_type>()(y, (min)());
+
+        base_unsigned j;
+        if(k == 1) {
+            j = 0;
+        } else if(brange < (std::numeric_limits<base_unsigned>::max)() / k) {
+            // try to do it in the native type if we know that it won't
+            // overflow
+            j = k * off / (brange + 1);
+        } else if(brange < (std::numeric_limits<uintmax_t>::max)() / k) {
+            // Otherwise try to use uint64_t
+            j = static_cast<base_unsigned>(
+                static_cast<uintmax_t>(off) * k /
+                (static_cast<uintmax_t>(brange) + 1));
+        } else {
+            boost::uintmax_t divisor =
+                static_cast<boost::uintmax_t>(brange) + 1;
+            j = static_cast<base_unsigned>(detail::muldiv(off, k, divisor));
+        }
+        // assert(0 <= j && j < k);
+        y = v[j];
+        v[j] = _rng();
+        return y;
+    }
+
+    /** Advances the generator by z steps. */
+    void discard(boost::uintmax_t z)
+    {
+        for(boost::uintmax_t j = 0; j < z; ++j) {
+            (*this)();
+        }
+    }
+
+    /** Fills a range with pseudo-random values. */
+    template<class Iter>
+    void generate(Iter first, Iter last)
+    { detail::generate_from_int(*this, first, last); }
+
+    /** Returns the smallest value that the generator can produce. */
+    static result_type min BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return (base_type::min)(); }
+    /** Returns the largest value that the generator can produce. */
+    static result_type max BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return (base_type::max)(); }
+
+    /** Writes a @c shuffle_order_engine to a @c std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, shuffle_order_engine, s)
+    {
+        os << s._rng;
+        for(std::size_t i = 0; i < k; ++i)
+            os << ' ' << s.v[i];
+        os << ' ' << s.y;
+        return os;
+    }
+
+    /** Reads a @c shuffle_order_engine from a @c std::istream. */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, shuffle_order_engine, s)
+    {
+        is >> s._rng;
+        for(std::size_t i = 0; i < k; ++i)
+            is >> std::ws >> s.v[i];
+        is >> std::ws >> s.y;
+        return is;
+    }
+
+    /** Returns true if the two generators will produce identical sequences. */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(shuffle_order_engine, x, y)
+    { return x._rng == y._rng && x.y == y.y && std::equal(x.v, x.v+k, y.v); }
+    /** Returns true if the two generators will produce different sequences. */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(shuffle_order_engine)
+
+private:
+
+    /// \cond show_private
+
+    void init()
+    {
+        // we cannot use std::generate, because it uses pass-by-value for _rng
+        for(result_type * p = v; p != v+k; ++p)
+            *p = _rng();
+        y = _rng();
+    }
+
+    /// \endcond
+
+    base_type _rng;
+    result_type v[k];
+    result_type y;
+};
+
+#ifndef BOOST_NO_INCLASS_MEMBER_INITIALIZATION
+//  A definition is required even for integral static constants
+template<class URNG, std::size_t k>
+const bool shuffle_order_engine<URNG, k>::has_fixed_range;
+template<class URNG, std::size_t k>
+const std::size_t shuffle_order_engine<URNG, k>::table_size;
+template<class URNG, std::size_t k>
+const std::size_t shuffle_order_engine<URNG, k>::buffer_size;
+#endif
+
+/**
+ * According to Harry Erwin (private e-mail), the specialization
+ * @c kreutzer1986 was suggested in:
+ *
+ * @blockquote
+ * "System Simulation: Programming Styles and Languages (International
+ * Computer Science Series)", Wolfgang Kreutzer, Addison-Wesley, December 1986.
+ * @endblockquote
+ */
+typedef shuffle_order_engine<
+    linear_congruential_engine<uint32_t, 1366, 150889, 714025>,
+    97> kreutzer1986;
+
+/**
+ * The specialization @c knuth_b is specified by the C++ standard.
+ * It is described in
+ *
+ * @blockquote
+ * "The Art of Computer Programming, Second Edition, Volume 2,
+ * Seminumerical Algorithms", Donald Knuth, Addison-Wesley, 1981.
+ * @endblockquote
+ */
+typedef shuffle_order_engine<minstd_rand0, 256> knuth_b;
+
+} // namespace random
+
+using random::kreutzer1986;
+
+} // namespace boost
+
+#include <boost/random/detail/enable_warnings.hpp>
+
+#endif // BOOST_RANDOM_SHUFFLE_OUTPUT_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/shuffle_output.hpp

@@ -0,0 +1,51 @@
+/* boost random/shuffle_output.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2001-02-18  moved to individual header files
+ */
+
+#ifndef BOOST_RANDOM_SHUFFLE_OUTPUT_HPP
+#define BOOST_RANDOM_SHUFFLE_OUTPUT_HPP
+
+#include <boost/random/shuffle_order.hpp>
+
+namespace boost {
+namespace random {
+
+/// \cond
+
+template<typename URNG, int k, 
+         typename URNG::result_type val = 0> 
+class shuffle_output : public shuffle_order_engine<URNG, k>
+{
+    typedef shuffle_order_engine<URNG, k> base_t;
+public:
+    typedef typename base_t::result_type result_type;
+    shuffle_output() {}
+    template<class T>
+    explicit shuffle_output(T& arg) : base_t(arg) {}
+    template<class T>
+    explicit shuffle_output(const T& arg) : base_t(arg) {}
+    template<class It>
+    shuffle_output(It& first, It last) : base_t(first, last) {}
+    result_type min BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return (this->base().min)(); }
+    result_type max BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return (this->base().max)(); }
+};
+
+/// \endcond
+
+}
+}
+
+#endif // BOOST_RANDOM_SHUFFLE_OUTPUT_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/student_t_distribution.hpp

@@ -0,0 +1,180 @@
+/* boost random/student_t_distribution.hpp header file
+ *
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_STUDENT_T_DISTRIBUTION_HPP
+#define BOOST_RANDOM_STUDENT_T_DISTRIBUTION_HPP
+
+#include <boost/config/no_tr1/cmath.hpp>
+#include <iosfwd>
+#include <boost/config.hpp>
+#include <boost/limits.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/chi_squared_distribution.hpp>
+#include <boost/random/normal_distribution.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * The Student t distribution is a real valued distribution with one
+ * parameter n, the number of degrees of freedom.
+ *
+ * It has \f$\displaystyle p(x) =
+ *   \frac{1}{\sqrt{n\pi}}
+ *   \frac{\Gamma((n+1)/2)}{\Gamma(n/2)}
+ *   \left(1+\frac{x^2}{n}\right)^{-(n+1)/2}
+ * \f$.
+ */
+template<class RealType = double>
+class student_t_distribution {
+public:
+    typedef RealType result_type;
+    typedef RealType input_type;
+
+    class param_type {
+    public:
+        typedef student_t_distribution distribution_type;
+
+        /**
+         * Constructs a @c param_type with "n" degrees of freedom.
+         *
+         * Requires: n > 0
+         */
+        explicit param_type(RealType n_arg = RealType(1.0))
+          : _n(n_arg)
+        {}
+
+        /** Returns the number of degrees of freedom of the distribution. */
+        RealType n() const { return _n; }
+
+        /** Writes a @c param_type to a @c std::ostream. */
+        BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
+        { os << parm._n; return os; }
+
+        /** Reads a @c param_type from a @c std::istream. */
+        BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
+        { is >> parm._n; return is; }
+
+        /** Returns true if the two sets of parameters are the same. */
+        BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
+        { return lhs._n == rhs._n; }
+        
+        /** Returns true if the two sets of parameters are the different. */
+        BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+
+    private:
+        RealType _n;
+    };
+
+    /**
+     * Constructs an @c student_t_distribution with "n" degrees of freedom.
+     *
+     * Requires: n > 0
+     */
+    explicit student_t_distribution(RealType n_arg = RealType(1.0))
+      : _normal(), _chi_squared(n_arg)
+    {}
+    /** Constructs an @c student_t_distribution from its parameters. */
+    explicit student_t_distribution(const param_type& parm)
+      : _normal(), _chi_squared(parm.n())
+    {}
+
+    /**
+     * Returns a random variate distributed according to the
+     * Student t distribution.
+     */
+    template<class URNG>
+    RealType operator()(URNG& urng)
+    {
+        using std::sqrt;
+        return _normal(urng) / sqrt(_chi_squared(urng) / n());
+    }
+
+    /**
+     * Returns a random variate distributed accordint to the Student
+     * t distribution with parameters specified by @c param.
+     */
+    template<class URNG>
+    RealType operator()(URNG& urng, const param_type& parm) const
+    {
+        return student_t_distribution(parm)(urng);
+    }
+
+    /** Returns the number of degrees of freedom. */
+    RealType n() const { return _chi_squared.n(); }
+
+    /** 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(n()); }
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        typedef chi_squared_distribution<RealType> chi_squared_type;
+        typename chi_squared_type::param_type chi_squared_param(parm.n());
+        _chi_squared.param(chi_squared_param);
+    }
+
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset()
+    {
+        _normal.reset();
+        _chi_squared.reset();
+    }
+
+    /** Writes a @c student_t_distribution to a @c std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, student_t_distribution, td)
+    {
+        os << td.param();
+        return os;
+    }
+
+    /** Reads a @c student_t_distribution from a @c std::istream. */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, student_t_distribution, td)
+    {
+        param_type parm;
+        if(is >> parm) {
+            td.param(parm);
+        }
+        return is;
+    }
+
+    /**
+     * Returns true if the two instances of @c student_t_distribution will
+     * return identical sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(student_t_distribution, lhs, rhs)
+    { return lhs._normal == rhs._normal && lhs._chi_squared == rhs._chi_squared; }
+    
+    /**
+     * Returns true if the two instances of @c student_t_distribution will
+     * return different sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(student_t_distribution)
+
+private:
+    normal_distribution<RealType> _normal;
+    chi_squared_distribution<RealType> _chi_squared;
+};
+
+} // namespace random
+} // namespace boost
+
+#endif // BOOST_RANDOM_STUDENT_T_DISTRIBUTION_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/subtract_with_carry.hpp

@@ -0,0 +1,613 @@
+/* boost random/subtract_with_carry.hpp header file
+ *
+ * Copyright Jens Maurer 2002
+ * 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2002-03-02  created
+ */
+
+#ifndef BOOST_RANDOM_SUBTRACT_WITH_CARRY_HPP
+#define BOOST_RANDOM_SUBTRACT_WITH_CARRY_HPP
+
+#include <boost/config/no_tr1/cmath.hpp>         // std::pow
+#include <iostream>
+#include <algorithm>     // std::equal
+#include <stdexcept>
+#include <boost/config.hpp>
+#include <boost/limits.hpp>
+#include <boost/cstdint.hpp>
+#include <boost/static_assert.hpp>
+#include <boost/integer/static_log2.hpp>
+#include <boost/integer/integer_mask.hpp>
+#include <boost/detail/workaround.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/seed.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/detail/seed_impl.hpp>
+#include <boost/random/detail/generator_seed_seq.hpp>
+#include <boost/random/linear_congruential.hpp>
+
+
+namespace boost {
+namespace random {
+
+namespace detail {
+   
+struct subtract_with_carry_discard
+{
+    template<class Engine>
+    static void apply(Engine& eng, boost::uintmax_t z)
+    {
+        typedef typename Engine::result_type IntType;
+        const std::size_t short_lag = Engine::short_lag;
+        const std::size_t long_lag = Engine::long_lag;
+        std::size_t k = eng.k;
+        IntType carry = eng.carry;
+        if(k != 0) {
+            // increment k until it becomes 0.
+            if(k < short_lag) {
+                std::size_t limit = (short_lag - k) < z?
+                    short_lag : (k + static_cast<std::size_t>(z));
+                for(std::size_t j = k; j < limit; ++j) {
+                    carry = eng.do_update(j, j + long_lag - short_lag, carry);
+                }
+            }
+            std::size_t limit = (long_lag - k) < z?
+                long_lag : (k + static_cast<std::size_t>(z));
+            std::size_t start = (k < short_lag ? short_lag : k);
+            for(std::size_t j = start; j < limit; ++j) {
+                carry = eng.do_update(j, j - short_lag, carry);
+            }
+        }
+
+        k = ((z % long_lag) + k) % long_lag;
+
+        if(k < z) {
+            // main loop: update full blocks from k = 0 to long_lag
+            for(std::size_t i = 0; i < (z - k) / long_lag; ++i) {
+                for(std::size_t j = 0; j < short_lag; ++j) {
+                    carry = eng.do_update(j, j + long_lag - short_lag, carry);
+                }
+                for(std::size_t j = short_lag; j < long_lag; ++j) {
+                    carry = eng.do_update(j, j - short_lag, carry);
+                }
+            }
+
+            // Update the last partial block
+            std::size_t limit = short_lag < k? short_lag : k; 
+            for(std::size_t j = 0; j < limit; ++j) {
+                carry = eng.do_update(j, j + long_lag - short_lag, carry);
+            }
+            for(std::size_t j = short_lag; j < k; ++j) {
+                carry = eng.do_update(j, j - short_lag, carry);
+            }
+        }
+        eng.carry = carry;
+        eng.k = k;
+    }
+};
+
+}
+
+/**
+ * Instantiations of @c subtract_with_carry_engine model a
+ * \pseudo_random_number_generator.  The algorithm is
+ * described in
+ *
+ *  @blockquote
+ *  "A New Class of Random Number Generators", George
+ *  Marsaglia and Arif Zaman, Annals of Applied Probability,
+ *  Volume 1, Number 3 (1991), 462-480.
+ *  @endblockquote
+ */
+template<class IntType, std::size_t w, std::size_t s, std::size_t r>
+class subtract_with_carry_engine
+{
+public:
+    typedef IntType result_type;
+    BOOST_STATIC_CONSTANT(std::size_t, word_size = w);
+    BOOST_STATIC_CONSTANT(std::size_t, long_lag = r);
+    BOOST_STATIC_CONSTANT(std::size_t, short_lag = s);
+    BOOST_STATIC_CONSTANT(uint32_t, default_seed = 19780503u);
+
+    // Required by the old Boost.Random concepts
+    BOOST_STATIC_CONSTANT(bool, has_fixed_range = false);
+    // Backwards compatibility
+    BOOST_STATIC_CONSTANT(result_type, modulus = (result_type(1) << w));
+    
+    BOOST_STATIC_ASSERT(std::numeric_limits<result_type>::is_integer);
+
+    /**
+     * Constructs a new @c subtract_with_carry_engine and seeds
+     * it with the default seed.
+     */
+    subtract_with_carry_engine() { seed(); }
+    /**
+     * Constructs a new @c subtract_with_carry_engine and seeds
+     * it with @c value.
+     */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(subtract_with_carry_engine,
+                                               IntType, value)
+    { seed(value); }
+    /**
+     * Constructs a new @c subtract_with_carry_engine and seeds
+     * it with values produced by @c seq.generate().
+     */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_CONSTRUCTOR(subtract_with_carry_engine,
+                                             SeedSeq, seq)
+    { seed(seq); }
+    /**
+     * Constructs a new @c subtract_with_carry_engine and seeds
+     * it with values from a range.  first is updated to point
+     * one past the last value consumed.  If there are not
+     * enough elements in the range to fill the entire state of
+     * the generator, throws @c std::invalid_argument.
+     */
+    template<class It> subtract_with_carry_engine(It& first, It last)
+    { seed(first,last); }
+
+    // compiler-generated copy ctor and assignment operator are fine
+
+    /** Seeds the generator with the default seed. */
+    void seed() { seed(default_seed); }
+    BOOST_RANDOM_DETAIL_ARITHMETIC_SEED(subtract_with_carry_engine,
+                                        IntType, value)
+    {
+        typedef linear_congruential_engine<uint32_t,40014,0,2147483563> gen_t;
+        gen_t intgen(static_cast<boost::uint32_t>(value == 0 ? default_seed : value));
+        detail::generator_seed_seq<gen_t> gen(intgen);
+        seed(gen);
+    }
+
+    /** Seeds the generator with values produced by @c seq.generate(). */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_SEED(subtract_with_carry, SeedSeq, seq)
+    {
+        detail::seed_array_int<w>(seq, x);
+        carry = (x[long_lag-1] == 0);
+        k = 0;
+    }
+
+    /**
+     * Seeds the generator with values from a range.  Updates @c first to
+     * point one past the last consumed value.  If the range does not
+     * contain enough elements to fill the entire state of the generator,
+     * throws @c std::invalid_argument.
+     */
+    template<class It>
+    void seed(It& first, It last)
+    {
+        detail::fill_array_int<w>(first, last, x);
+        carry = (x[long_lag-1] == 0);
+        k = 0;
+    }
+
+    /** Returns the smallest value that the generator can produce. */
+    static result_type min BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return 0; }
+    /** Returns the largest value that the generator can produce. */
+    static result_type max BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return boost::low_bits_mask_t<w>::sig_bits; }
+
+    /** Returns the next value of the generator. */
+    result_type operator()()
+    {
+        std::size_t short_index =
+            (k < short_lag)?
+                (k + long_lag - short_lag) :
+                (k - short_lag);
+        carry = do_update(k, short_index, carry);
+        IntType result = x[k];
+        ++k;
+        if(k >= long_lag)
+            k = 0;
+        return result;
+    }
+
+    /** Advances the state of the generator by @c z. */
+    void discard(boost::uintmax_t z)
+    {
+        detail::subtract_with_carry_discard::apply(*this, z);
+    }
+
+    /** Fills a range with random values. */
+    template<class It>
+    void generate(It first, It last)
+    { detail::generate_from_int(*this, first, last); }
+ 
+    /** Writes a @c subtract_with_carry_engine to a @c std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, subtract_with_carry_engine, f)
+    {
+        for(unsigned int j = 0; j < f.long_lag; ++j)
+            os << f.compute(j) << ' ';
+        os << f.carry;
+        return os;
+    }
+
+    /** Reads a @c subtract_with_carry_engine from a @c std::istream. */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, subtract_with_carry_engine, f)
+    {
+        for(unsigned int j = 0; j < f.long_lag; ++j)
+            is >> f.x[j] >> std::ws;
+        is >> f.carry;
+        f.k = 0;
+        return is;
+    }
+
+    /**
+     * Returns true if the two generators will produce identical
+     * sequences of values.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(subtract_with_carry_engine, x, y)
+    {
+        for(unsigned int j = 0; j < r; ++j)
+            if(x.compute(j) != y.compute(j))
+                return false;
+        return true;
+    }
+
+    /**
+     * Returns true if the two generators will produce different
+     * sequences of values.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(subtract_with_carry_engine)
+
+private:
+    /// \cond show_private
+    // returns x(i-r+index), where index is in 0..r-1
+    IntType compute(unsigned int index) const
+    {
+        return x[(k+index) % long_lag];
+    }
+
+    friend struct detail::subtract_with_carry_discard;
+
+    IntType do_update(std::size_t current, std::size_t short_index, IntType carry)
+    {
+        IntType delta;
+        IntType temp = x[current] + carry;
+        if (x[short_index] >= temp) {
+            // x(n) >= 0
+            delta =  x[short_index] - temp;
+            carry = 0;
+        } else {
+            // x(n) < 0
+            delta = modulus - temp + x[short_index];
+            carry = 1;
+        }
+        x[current] = delta;
+        return carry;
+    }
+    /// \endcond
+
+    // state representation; next output (state) is x(i)
+    //   x[0]  ... x[k] x[k+1] ... x[long_lag-1]     represents
+    //  x(i-k) ... x(i) x(i+1) ... x(i-k+long_lag-1)
+    // speed: base: 20-25 nsec
+    // ranlux_4: 230 nsec, ranlux_7: 430 nsec, ranlux_14: 810 nsec
+    // This state representation makes operator== and save/restore more
+    // difficult, because we've already computed "too much" and thus
+    // have to undo some steps to get at x(i-r) etc.
+
+    // state representation: next output (state) is x(i)
+    //   x[0]  ... x[k] x[k+1]          ... x[long_lag-1]     represents
+    //  x(i-k) ... x(i) x(i-long_lag+1) ... x(i-k-1)
+    // speed: base 28 nsec
+    // ranlux_4: 370 nsec, ranlux_7: 688 nsec, ranlux_14: 1343 nsec
+    IntType x[long_lag];
+    std::size_t k;
+    IntType carry;
+};
+
+#ifndef BOOST_NO_INCLASS_MEMBER_INITIALIZATION
+//  A definition is required even for integral static constants
+template<class IntType, std::size_t w, std::size_t s, std::size_t r>
+const bool subtract_with_carry_engine<IntType, w, s, r>::has_fixed_range;
+template<class IntType, std::size_t w, std::size_t s, std::size_t r>
+const IntType subtract_with_carry_engine<IntType, w, s, r>::modulus;
+template<class IntType, std::size_t w, std::size_t s, std::size_t r>
+const std::size_t subtract_with_carry_engine<IntType, w, s, r>::word_size;
+template<class IntType, std::size_t w, std::size_t s, std::size_t r>
+const std::size_t subtract_with_carry_engine<IntType, w, s, r>::long_lag;
+template<class IntType, std::size_t w, std::size_t s, std::size_t r>
+const std::size_t subtract_with_carry_engine<IntType, w, s, r>::short_lag;
+template<class IntType, std::size_t w, std::size_t s, std::size_t r>
+const uint32_t subtract_with_carry_engine<IntType, w, s, r>::default_seed;
+#endif
+
+
+// use a floating-point representation to produce values in [0..1)
+/**
+ * Instantiations of \subtract_with_carry_01_engine model a
+ * \pseudo_random_number_generator.  The algorithm is
+ * described in
+ *
+ *  @blockquote
+ *  "A New Class of Random Number Generators", George
+ *  Marsaglia and Arif Zaman, Annals of Applied Probability,
+ *  Volume 1, Number 3 (1991), 462-480.
+ *  @endblockquote
+ */
+template<class RealType, std::size_t w, std::size_t s, std::size_t r>
+class subtract_with_carry_01_engine
+{
+public:
+    typedef RealType result_type;
+    BOOST_STATIC_CONSTANT(bool, has_fixed_range = false);
+    BOOST_STATIC_CONSTANT(std::size_t, word_size = w);
+    BOOST_STATIC_CONSTANT(std::size_t, long_lag = r);
+    BOOST_STATIC_CONSTANT(std::size_t, short_lag = s);
+    BOOST_STATIC_CONSTANT(boost::uint32_t, default_seed = 19780503u);
+
+    BOOST_STATIC_ASSERT(!std::numeric_limits<result_type>::is_integer);
+
+    /** Creates a new \subtract_with_carry_01_engine using the default seed. */
+    subtract_with_carry_01_engine() { init_modulus(); seed(); }
+    /** Creates a new subtract_with_carry_01_engine and seeds it with value. */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(subtract_with_carry_01_engine,
+                                               boost::uint32_t, value)
+    { init_modulus(); seed(value); }
+    /**
+     * Creates a new \subtract_with_carry_01_engine and seeds with values
+     * produced by seq.generate().
+     */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_CONSTRUCTOR(subtract_with_carry_01_engine,
+                                             SeedSeq, seq)
+    { init_modulus(); seed(seq); }
+    /**
+     * Creates a new \subtract_with_carry_01_engine and seeds it with values
+     * from a range.  Advances first to point one past the last consumed
+     * value.  If the range does not contain enough elements to fill the
+     * entire state, throws @c std::invalid_argument.
+     */
+    template<class It> subtract_with_carry_01_engine(It& first, It last)
+    { init_modulus(); seed(first,last); }
+
+private:
+    /// \cond show_private
+    void init_modulus()
+    {
+#ifndef BOOST_NO_STDC_NAMESPACE
+        // allow for Koenig lookup
+        using std::pow;
+#endif
+        _modulus = pow(RealType(2), RealType(word_size));
+    }
+    /// \endcond
+
+public:
+    // compiler-generated copy ctor and assignment operator are fine
+
+    /** Seeds the generator with the default seed. */
+    void seed() { seed(default_seed); }
+
+    /** Seeds the generator with @c value. */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_SEED(subtract_with_carry_01_engine,
+                                        boost::uint32_t, value)
+    {
+        typedef linear_congruential_engine<uint32_t, 40014, 0, 2147483563> gen_t;
+        gen_t intgen(value == 0 ? default_seed : value);
+        detail::generator_seed_seq<gen_t> gen(intgen);
+        seed(gen);
+    }
+
+    /** Seeds the generator with values produced by @c seq.generate(). */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_SEED(subtract_with_carry_01_engine,
+                                      SeedSeq, seq)
+    {
+        detail::seed_array_real<w>(seq, x);
+        carry = (x[long_lag-1] ? result_type(0) : result_type(1 / _modulus));
+        k = 0;
+    }
+
+    /**
+     * Seeds the generator with values from a range.  Updates first to
+     * point one past the last consumed element.  If there are not
+     * enough elements in the range to fill the entire state, throws
+     * @c std::invalid_argument.
+     */
+    template<class It>
+    void seed(It& first, It last)
+    {
+        detail::fill_array_real<w>(first, last, x);
+        carry = (x[long_lag-1] ? result_type(0) : result_type(1 / _modulus));
+        k = 0;
+    }
+
+    /** Returns the smallest value that the generator can produce. */
+    static result_type min BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return result_type(0); }
+    /** Returns the largest value that the generator can produce. */
+    static result_type max BOOST_PREVENT_MACRO_SUBSTITUTION ()
+    { return result_type(1); }
+
+    /** Returns the next value of the generator. */
+    result_type operator()()
+    {
+        std::size_t short_index =
+            (k < short_lag) ?
+                (k + long_lag - short_lag) :
+                (k - short_lag);
+        carry = do_update(k, short_index, carry);
+        RealType result = x[k];
+        ++k;
+        if(k >= long_lag)
+            k = 0;
+        return result;
+    }
+
+    /** Advances the state of the generator by @c z. */
+    void discard(boost::uintmax_t z)
+    { detail::subtract_with_carry_discard::apply(*this, z); }
+
+    /** Fills a range with random values. */
+    template<class Iter>
+    void generate(Iter first, Iter last)
+    { detail::generate_from_real(*this, first, last); }
+
+    /** Writes a \subtract_with_carry_01_engine to a @c std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, subtract_with_carry_01_engine, f)
+    {
+        std::ios_base::fmtflags oldflags =
+            os.flags(os.dec | os.fixed | os.left); 
+        for(unsigned int j = 0; j < f.long_lag; ++j)
+            os << (f.compute(j) * f._modulus) << ' ';
+        os << (f.carry * f._modulus);
+        os.flags(oldflags);
+        return os;
+    }
+    
+    /** Reads a \subtract_with_carry_01_engine from a @c std::istream. */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, subtract_with_carry_01_engine, f)
+    {
+        RealType value;
+        for(unsigned int j = 0; j < long_lag; ++j) {
+            is >> value >> std::ws;
+            f.x[j] = value / f._modulus;
+        }
+        is >> value;
+        f.carry = value / f._modulus;
+        f.k = 0;
+        return is;
+    }
+
+    /** Returns true if the two generators will produce identical sequences. */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(subtract_with_carry_01_engine, x, y)
+    {
+        for(unsigned int j = 0; j < r; ++j)
+            if(x.compute(j) != y.compute(j))
+                return false;
+        return true;
+    }
+
+    /** Returns true if the two generators will produce different sequences. */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(subtract_with_carry_01_engine)
+
+private:
+    /// \cond show_private
+    RealType compute(unsigned int index) const
+    {
+        return x[(k+index) % long_lag];
+    }
+
+    friend struct detail::subtract_with_carry_discard;
+
+    RealType do_update(std::size_t current, std::size_t short_index, RealType carry)
+    {
+        RealType delta = x[short_index] - x[current] - carry;
+        if(delta < 0) {
+            delta += RealType(1);
+            carry = RealType(1)/_modulus;
+        } else {
+            carry = 0;
+        }
+        x[current] = delta;
+        return carry;
+    }
+    /// \endcond
+    std::size_t k;
+    RealType carry;
+    RealType x[long_lag];
+    RealType _modulus;
+};
+
+#ifndef BOOST_NO_INCLASS_MEMBER_INITIALIZATION
+//  A definition is required even for integral static constants
+template<class RealType, std::size_t w, std::size_t s, std::size_t r>
+const bool subtract_with_carry_01_engine<RealType, w, s, r>::has_fixed_range;
+template<class RealType, std::size_t w, std::size_t s, std::size_t r>
+const std::size_t subtract_with_carry_01_engine<RealType, w, s, r>::word_size;
+template<class RealType, std::size_t w, std::size_t s, std::size_t r>
+const std::size_t subtract_with_carry_01_engine<RealType, w, s, r>::long_lag;
+template<class RealType, std::size_t w, std::size_t s, std::size_t r>
+const std::size_t subtract_with_carry_01_engine<RealType, w, s, r>::short_lag;
+template<class RealType, std::size_t w, std::size_t s, std::size_t r>
+const uint32_t subtract_with_carry_01_engine<RealType, w, s, r>::default_seed;
+#endif
+
+
+/// \cond show_deprecated
+
+template<class IntType, IntType m, unsigned s, unsigned r, IntType v>
+class subtract_with_carry :
+    public subtract_with_carry_engine<IntType,
+        boost::static_log2<m>::value, s, r>
+{
+    typedef subtract_with_carry_engine<IntType,
+        boost::static_log2<m>::value, s, r> base_type;
+public:
+    subtract_with_carry() {}
+    BOOST_RANDOM_DETAIL_GENERATOR_CONSTRUCTOR(subtract_with_carry, Gen, gen)
+    { seed(gen); }
+    BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(subtract_with_carry,
+                                               IntType, val)
+    { seed(val); }
+    template<class It>
+    subtract_with_carry(It& first, It last) : base_type(first, last) {}
+    void seed() { base_type::seed(); }
+    BOOST_RANDOM_DETAIL_GENERATOR_SEED(subtract_with_carry, Gen, gen)
+    {
+        detail::generator_seed_seq<Gen> seq(gen);
+        base_type::seed(seq);
+    }
+    BOOST_RANDOM_DETAIL_ARITHMETIC_SEED(subtract_with_carry, IntType, val)
+    { base_type::seed(val); }
+    template<class It>
+    void seed(It& first, It last) { base_type::seed(first, last); }
+};
+
+template<class RealType, int w, unsigned s, unsigned r, int v = 0>
+class subtract_with_carry_01 :
+    public subtract_with_carry_01_engine<RealType, w, s, r>
+{
+    typedef subtract_with_carry_01_engine<RealType, w, s, r> base_type;
+public:
+    subtract_with_carry_01() {}
+    BOOST_RANDOM_DETAIL_GENERATOR_CONSTRUCTOR(subtract_with_carry_01, Gen, gen)
+    { seed(gen); }
+    BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(subtract_with_carry_01,
+                                               uint32_t, val)
+    { seed(val); }
+    template<class It>
+    subtract_with_carry_01(It& first, It last) : base_type(first, last) {}
+    void seed() { base_type::seed(); }
+    BOOST_RANDOM_DETAIL_GENERATOR_SEED(subtract_with_carry_01, Gen, gen)
+    {
+        detail::generator_seed_seq<Gen> seq(gen);
+        base_type::seed(seq);
+    }
+    BOOST_RANDOM_DETAIL_ARITHMETIC_SEED(subtract_with_carry_01, uint32_t, val)
+    { base_type::seed(val); }
+    template<class It>
+    void seed(It& first, It last) { base_type::seed(first, last); }
+};
+
+/// \endcond
+
+namespace detail {
+
+template<class Engine>
+struct generator_bits;
+
+template<class RealType, std::size_t w, std::size_t s, std::size_t r>
+struct generator_bits<subtract_with_carry_01_engine<RealType, w, s, r> > {
+    static std::size_t value() { return w; }
+};
+
+template<class RealType, int w, unsigned s, unsigned r, int v>
+struct generator_bits<subtract_with_carry_01<RealType, w, s, r, v> > {
+    static std::size_t value() { return w; }
+};
+
+}
+
+} // namespace random
+} // namespace boost
+
+#endif // BOOST_RANDOM_SUBTRACT_WITH_CARRY_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/taus88.hpp

@@ -0,0 +1,45 @@
+/* boost random/taus88.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * Copyright Steven Watanabe 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/libs/random for documentation.
+ *
+ * $Id$
+ *
+ */
+
+#ifndef BOOST_RANDOM_TAUS88_HPP
+#define BOOST_RANDOM_TAUS88_HPP
+
+#include <boost/random/linear_feedback_shift.hpp>
+#include <boost/random/xor_combine.hpp>
+
+namespace boost {
+namespace random {
+
+/** 
+ * The specialization taus88 was suggested in
+ *
+ *  @blockquote
+ *  "Maximally Equidistributed Combined Tausworthe Generators",
+ *  Pierre L'Ecuyer, Mathematics of Computation, Volume 65,
+ *  Number 213, January 1996, Pages 203-213
+ *  @endblockquote
+ */
+typedef xor_combine_engine<
+    xor_combine_engine<
+        linear_feedback_shift_engine<uint32_t, 32, 31, 13, 12>, 0,
+        linear_feedback_shift_engine<uint32_t, 32, 29, 2, 4>, 0>, 0,
+    linear_feedback_shift_engine<uint32_t, 32, 28, 3, 17>, 0> taus88;
+
+} // namespace random
+
+using random::taus88;
+
+} // namespace boost
+
+#endif // BOOST_RANDOM_TAUS88_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/traits.hpp

@@ -0,0 +1,107 @@
+/* boost random/traits.hpp header file
+ *
+ * Copyright John Maddock 2015
+ * 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.
+ *
+ * These traits classes serve two purposes: they are designed to mostly
+ * work out of the box for multiprecision types (ie number types that are
+ * C++ class types and not integers or floats from type-traits point of view),
+ * they are also a potential point of specialization for user-defined
+ * number types.
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_TRAITS_HPP
+#define BOOST_RANDOM_TRAITS_HPP
+
+#include <boost/type_traits/is_signed.hpp>
+#include <boost/type_traits/is_integral.hpp>
+#include <boost/type_traits/make_unsigned.hpp>
+#include <boost/mpl/bool.hpp>
+#include <limits>
+
+namespace boost {
+namespace random {
+namespace traits {
+   // \cond show_private
+   template <class T, bool intrinsic>
+   struct make_unsigned_imp
+   {
+      typedef typename boost::make_unsigned<T>::type type;
+   };
+   template <class T>
+   struct make_unsigned_imp<T, false>
+   {
+      BOOST_STATIC_ASSERT(std::numeric_limits<T>::is_specialized);
+      BOOST_STATIC_ASSERT(std::numeric_limits<T>::is_signed == false);
+      BOOST_STATIC_ASSERT(std::numeric_limits<T>::is_integer == true);
+      typedef T type;
+   };
+   // \endcond
+   /** \brief Converts the argument type T to an unsigned type.
+   *
+   * This trait has a single member `type` which is the unsigned type corresponding to T.
+   * Note that
+   * if T is signed, then member `type` *should define a type with one more bit precision than T*.  For built-in
+   * types this trait defaults to `boost::make_unsigned<T>::type`.  For user defined types it simply asserts that
+   * the argument type T is an unsigned integer (using std::numeric_limits).
+   * User defined specializations may be provided for other cases.
+   */
+   template <class T>
+   struct make_unsigned
+   // \cond show_private
+      : public make_unsigned_imp < T, boost::is_integral<T>::value > 
+      // \endcond
+   {};
+   // \cond show_private
+   template <class T, bool intrinsic>
+   struct make_unsigned_or_unbounded_imp
+   {
+      typedef typename boost::make_unsigned<T>::type type;
+   };
+   template <class T>
+   struct make_unsigned_or_unbounded_imp<T, false>
+   {
+      BOOST_STATIC_ASSERT(std::numeric_limits<T>::is_specialized);
+      BOOST_STATIC_ASSERT((std::numeric_limits<T>::is_signed == false) || (std::numeric_limits<T>::is_bounded == false));
+      BOOST_STATIC_ASSERT(std::numeric_limits<T>::is_integer == true);
+      typedef T type;
+   };
+   // \endcond
+   /** \brief Converts the argument type T to either an unsigned type or an unbounded integer type.
+   *
+   * This trait has a single member `type` which is either the unsigned type corresponding to T or an unbounded
+   * integer type.  This trait is used to generate types suitable for the calculation of a range: as a result
+   * if T is signed, then member `type` *should define a type with one more bit precision than T*.  For built-in
+   * types this trait defaults to `boost::make_unsigned<T>::type`.  For user defined types it simply asserts that
+   * the argument type T is either an unbounded integer, or an unsigned one (using std::numeric_limits).
+   * User defined specializations may be provided for other cases.
+   */
+   template <class T>
+   struct make_unsigned_or_unbounded
+      // \cond show_private
+      : public make_unsigned_or_unbounded_imp < T, boost::is_integral<T>::value > 
+      // \endcond
+   {};
+   /** \brief Traits class that indicates whether type T is an integer
+   */
+   template <class T>
+   struct is_integral
+      : public mpl::bool_<boost::is_integral<T>::value || (std::numeric_limits<T>::is_integer)>
+   {};
+   /** \brief Traits class that indicates whether type T is a signed integer
+   */
+   template <class T> struct is_signed
+      : public mpl::bool_ < boost::is_signed<T>::value || (std::numeric_limits<T>::is_specialized && std::numeric_limits<T>::is_integer && std::numeric_limits<T>::is_signed)>
+   {};
+
+}
+}
+}
+
+#endif

depends/x86_64-pc-linux-gnu/include/boost/random/triangle_distribution.hpp

@@ -0,0 +1,232 @@
+/* boost random/triangle_distribution.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2001-02-18  moved to individual header files
+ */
+
+#ifndef BOOST_RANDOM_TRIANGLE_DISTRIBUTION_HPP
+#define BOOST_RANDOM_TRIANGLE_DISTRIBUTION_HPP
+
+#include <boost/config/no_tr1/cmath.hpp>
+#include <iosfwd>
+#include <ios>
+#include <istream>
+#include <boost/assert.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/uniform_01.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * Instantiations of @c triangle_distribution model a \random_distribution.
+ * A @c triangle_distribution has three parameters, @c a, @c b, and @c c,
+ * which are the smallest, the most probable and the largest values of
+ * the distribution respectively.
+ */
+template<class RealType = double>
+class triangle_distribution
+{
+public:
+    typedef RealType input_type;
+    typedef RealType result_type;
+
+    class param_type
+    {
+    public:
+
+        typedef triangle_distribution distribution_type;
+
+        /** Constructs the parameters of a @c triangle_distribution. */
+        explicit param_type(RealType a_arg = RealType(0.0),
+                            RealType b_arg = RealType(0.5),
+                            RealType c_arg = RealType(1.0))
+          : _a(a_arg), _b(b_arg), _c(c_arg)
+        {
+            BOOST_ASSERT(_a <= _b && _b <= _c);
+        }
+
+        /** Returns the minimum value of the distribution. */
+        RealType a() const { return _a; }
+        /** Returns the mode of the distribution. */
+        RealType b() const { return _b; }
+        /** Returns the maximum value of the distribution. */
+        RealType c() const { return _c; }
+
+        /** Writes the parameters to a @c std::ostream. */
+        BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
+        {
+            os << parm._a << " " << parm._b << " " << parm._c;
+            return os;
+        }
+
+        /** Reads the parameters from a @c std::istream. */
+        BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
+        {
+            double a_in, b_in, c_in;
+            if(is >> a_in >> std::ws >> b_in >> std::ws >> c_in) {
+                if(a_in <= b_in && b_in <= c_in) {
+                    parm._a = a_in;
+                    parm._b = b_in;
+                    parm._c = c_in;
+                } else {
+                    is.setstate(std::ios_base::failbit);
+                }
+            }
+            return is;
+        }
+
+        /** Returns true if the two sets of parameters are equal. */
+        BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
+        { return lhs._a == rhs._a && lhs._b == rhs._b && lhs._c == rhs._c; }
+
+        /** Returns true if the two sets of parameters are different. */
+        BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+
+    private:
+        RealType _a;
+        RealType _b;
+        RealType _c;
+    };
+
+    /**
+     * Constructs a @c triangle_distribution with the parameters
+     * @c a, @c b, and @c c.
+     *
+     * Preconditions: a <= b <= c.
+     */
+    explicit triangle_distribution(RealType a_arg = RealType(0.0),
+                                   RealType b_arg = RealType(0.5),
+                                   RealType c_arg = RealType(1.0))
+      : _a(a_arg), _b(b_arg), _c(c_arg)
+    {
+        BOOST_ASSERT(_a <= _b && _b <= _c);
+        init();
+    }
+
+    /** Constructs a @c triangle_distribution from its parameters. */
+    explicit triangle_distribution(const param_type& parm)
+      : _a(parm.a()), _b(parm.b()), _c(parm.c())
+    {
+        init();
+    }
+
+    // compiler-generated copy ctor and assignment operator are fine
+
+    /** Returns the @c a parameter of the distribution */
+    result_type a() const { return _a; }
+    /** Returns the @c b parameter of the distribution */
+    result_type b() const { return _b; }
+    /** Returns the @c c parameter of the distribution */
+    result_type c() const { return _c; }
+
+    /** Returns the smallest value that the distribution can produce. */
+    RealType min BOOST_PREVENT_MACRO_SUBSTITUTION () const { return _a; }
+    /** Returns the largest value that the distribution can produce. */
+    RealType max BOOST_PREVENT_MACRO_SUBSTITUTION () const { return _c; }
+
+    /** Returns the parameters of the distribution. */
+    param_type param() const { return param_type(_a, _b, _c); }
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        _a = parm.a();
+        _b = parm.b();
+        _c = parm.c();
+        init();
+    }
+
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { }
+
+    /**
+     * Returns a random variate distributed according to the
+     * triangle distribution.
+     */
+    template<class Engine>
+    result_type operator()(Engine& eng)
+    {
+        using std::sqrt;
+        result_type u = uniform_01<result_type>()(eng);
+        if( u <= q1 )
+            return _a + p1*sqrt(u);
+        else
+        return _c - d3*sqrt(d2*u-d1);
+    }
+
+    /**
+     * Returns a random variate distributed according to the
+     * triangle distribution with parameters specified by param.
+     */
+    template<class Engine>
+    result_type operator()(Engine& eng, const param_type& parm)
+    { return triangle_distribution(parm)(eng); }
+
+    /** Writes the distribution to a @c std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, triangle_distribution, td)
+    {
+        os << td.param();
+        return os;
+    }
+
+    /** Reads the distribution from a @c std::istream. */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, triangle_distribution, td)
+    {
+        param_type parm;
+        if(is >> parm) {
+            td.param(parm);
+        }
+        return is;
+    }
+
+    /**
+     * Returns true if the two distributions will produce identical
+     * sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(triangle_distribution, lhs, rhs)
+    { return lhs._a == rhs._a && lhs._b == rhs._b && lhs._c == rhs._c; }
+
+    /**
+     * Returns true if the two distributions may produce different
+     * sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(triangle_distribution)
+
+private:
+    /// \cond show_private
+    void init()
+    {
+        using std::sqrt;
+        d1 = _b - _a;
+        d2 = _c - _a;
+        d3 = sqrt(_c - _b);
+        q1 = d1 / d2;
+        p1 = sqrt(d1 * d2);
+    }
+    /// \endcond
+
+    RealType _a, _b, _c;
+    RealType d1, d2, d3, q1, p1;
+};
+
+} // namespace random
+
+using random::triangle_distribution;
+
+} // namespace boost
+
+#endif // BOOST_RANDOM_TRIANGLE_DISTRIBUTION_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/uniform_01.hpp

@@ -0,0 +1,257 @@
+/* boost random/uniform_01.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2001-02-18  moved to individual header files
+ */
+
+#ifndef BOOST_RANDOM_UNIFORM_01_HPP
+#define BOOST_RANDOM_UNIFORM_01_HPP
+
+#include <iostream>
+#include <boost/config.hpp>
+#include <boost/limits.hpp>
+#include <boost/static_assert.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/ptr_helper.hpp>
+
+#include <boost/random/detail/disable_warnings.hpp>
+
+namespace boost {
+namespace random {
+
+#ifdef BOOST_RANDOM_DOXYGEN
+
+/**
+ * The distribution function uniform_01 models a \random_distribution.
+ * On each invocation, it returns a random floating-point value
+ * uniformly distributed in the range [0..1).
+ *
+ * The template parameter RealType shall denote a float-like value type
+ * with support for binary operators +, -, and /.
+ *
+ * Note: The current implementation is buggy, because it may not fill
+ * all of the mantissa with random bits. I'm unsure how to fill a
+ * (to-be-invented) @c boost::bigfloat class with random bits efficiently.
+ * It's probably time for a traits class.
+ */
+template<class RealType = double>
+class uniform_01
+{
+public:
+  typedef RealType input_type;
+  typedef RealType result_type;
+  result_type min BOOST_PREVENT_MACRO_SUBSTITUTION () const;
+  result_type max BOOST_PREVENT_MACRO_SUBSTITUTION () const;
+  void reset();
+
+  template<class Engine>
+  result_type operator()(Engine& eng);
+
+#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 new_uniform_01&)
+  {
+    return os;
+  }
+
+  template<class CharT, class Traits>
+  friend std::basic_istream<CharT,Traits>&
+  operator>>(std::basic_istream<CharT,Traits>& is, new_uniform_01&)
+  {
+    return is;
+  }
+#endif
+};
+
+#else
+
+namespace detail {
+
+template<class RealType>
+class new_uniform_01
+{
+public:
+  typedef RealType input_type;
+  typedef RealType result_type;
+  // compiler-generated copy ctor and copy assignment are fine
+  result_type min BOOST_PREVENT_MACRO_SUBSTITUTION () const { return result_type(0); }
+  result_type max BOOST_PREVENT_MACRO_SUBSTITUTION () const { return result_type(1); }
+  void reset() { }
+
+  template<class Engine>
+  result_type operator()(Engine& eng) {
+    for (;;) {
+      typedef typename Engine::result_type base_result;
+      result_type factor = result_type(1) /
+              (result_type(base_result((eng.max)()-(eng.min)())) +
+               result_type(std::numeric_limits<base_result>::is_integer ? 1 : 0));
+      result_type result = result_type(base_result(eng() - (eng.min)())) * factor;
+      if (result < result_type(1))
+        return result;
+    }
+  }
+
+#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 new_uniform_01&)
+  {
+    return os;
+  }
+
+  template<class CharT, class Traits>
+  friend std::basic_istream<CharT,Traits>&
+  operator>>(std::basic_istream<CharT,Traits>& is, new_uniform_01&)
+  {
+    return is;
+  }
+#endif
+};
+
+template<class UniformRandomNumberGenerator, class RealType>
+class backward_compatible_uniform_01
+{
+  typedef boost::random::detail::ptr_helper<UniformRandomNumberGenerator> traits;
+public:
+  typedef UniformRandomNumberGenerator base_type;
+  typedef RealType result_type;
+
+  BOOST_STATIC_CONSTANT(bool, has_fixed_range = false);
+
+#if !defined(BOOST_NO_LIMITS_COMPILE_TIME_CONSTANTS)
+  BOOST_STATIC_ASSERT(!std::numeric_limits<RealType>::is_integer);
+#endif
+
+  explicit backward_compatible_uniform_01(typename traits::rvalue_type rng)
+    : _rng(rng),
+      _factor(result_type(1) /
+              (result_type((base().max)()-(base().min)()) +
+               result_type(std::numeric_limits<base_result>::is_integer ? 1 : 0)))
+  {
+  }
+  // compiler-generated copy ctor and copy assignment are fine
+
+  result_type min BOOST_PREVENT_MACRO_SUBSTITUTION () const { return result_type(0); }
+  result_type max BOOST_PREVENT_MACRO_SUBSTITUTION () const { return result_type(1); }
+  typename traits::value_type& base() { return traits::ref(_rng); }
+  const typename traits::value_type& base() const { return traits::ref(_rng); }
+  void reset() { }
+
+  result_type operator()() {
+    for (;;) {
+      result_type result = result_type(base()() - (base().min)()) * _factor;
+      if (result < result_type(1))
+        return result;
+    }
+  }
+
+#if !defined(BOOST_NO_OPERATORS_IN_NAMESPACE) && !defined(BOOST_NO_MEMBER_TEMPLATE_FRIENDS)
+  template<class CharT, class Traits>
+  friend std::basic_ostream<CharT,Traits>&
+  operator<<(std::basic_ostream<CharT,Traits>& os, const backward_compatible_uniform_01& u)
+  {
+    os << u._rng;
+    return os;
+  }
+
+  template<class CharT, class Traits>
+  friend std::basic_istream<CharT,Traits>&
+  operator>>(std::basic_istream<CharT,Traits>& is, backward_compatible_uniform_01& u)
+  {
+    is >> u._rng;
+    return is;
+  }
+#endif
+
+private:
+  typedef typename traits::value_type::result_type base_result;
+  UniformRandomNumberGenerator _rng;
+  result_type _factor;
+};
+
+#ifndef BOOST_NO_INCLASS_MEMBER_INITIALIZATION
+//  A definition is required even for integral static constants
+template<class UniformRandomNumberGenerator, class RealType>
+const bool backward_compatible_uniform_01<UniformRandomNumberGenerator, RealType>::has_fixed_range;
+#endif
+
+template<class UniformRandomNumberGenerator, bool is_number = std::numeric_limits<UniformRandomNumberGenerator>::is_specialized>
+struct select_uniform_01
+{
+  template<class RealType>
+  struct apply
+  {
+    typedef backward_compatible_uniform_01<UniformRandomNumberGenerator, RealType> type;
+  };
+};
+
+template<class Num>
+struct select_uniform_01<Num, true>
+{
+  template<class RealType>
+  struct apply
+  {
+    typedef new_uniform_01<Num> type;
+  };
+};
+
+}
+
+// Because it is so commonly used: uniform distribution on the real [0..1)
+// range.  This allows for specializations to avoid a costly int -> float
+// conversion plus float multiplication
+template<class UniformRandomNumberGenerator = double, class RealType = double>
+class uniform_01
+  : public detail::select_uniform_01<UniformRandomNumberGenerator>::BOOST_NESTED_TEMPLATE apply<RealType>::type
+{
+  typedef typename detail::select_uniform_01<UniformRandomNumberGenerator>::BOOST_NESTED_TEMPLATE apply<RealType>::type impl_type;
+  typedef boost::random::detail::ptr_helper<UniformRandomNumberGenerator> traits;
+public:
+
+  uniform_01() {}
+
+  explicit uniform_01(typename traits::rvalue_type rng)
+    : impl_type(rng)
+  {
+  }
+
+#if !defined(BOOST_NO_OPERATORS_IN_NAMESPACE) && !defined(BOOST_NO_MEMBER_TEMPLATE_FRIENDS)
+  template<class CharT, class Traits>
+  friend std::basic_ostream<CharT,Traits>&
+  operator<<(std::basic_ostream<CharT,Traits>& os, const uniform_01& u)
+  {
+    os << static_cast<const impl_type&>(u);
+    return os;
+  }
+
+  template<class CharT, class Traits>
+  friend std::basic_istream<CharT,Traits>&
+  operator>>(std::basic_istream<CharT,Traits>& is, uniform_01& u)
+  {
+    is >> static_cast<impl_type&>(u);
+    return is;
+  }
+#endif
+};
+
+#endif
+
+} // namespace random
+
+using random::uniform_01;
+
+} // namespace boost
+
+#include <boost/random/detail/enable_warnings.hpp>
+
+#endif // BOOST_RANDOM_UNIFORM_01_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/uniform_int.hpp

@@ -0,0 +1,99 @@
+/* boost random/uniform_int.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2001-04-08  added min<max assertion (N. Becker)
+ *  2001-02-18  moved to individual header files
+ */
+
+#ifndef BOOST_RANDOM_UNIFORM_INT_HPP
+#define BOOST_RANDOM_UNIFORM_INT_HPP
+
+#include <boost/assert.hpp>
+#include <boost/random/uniform_int_distribution.hpp>
+
+namespace boost {
+
+/**
+ * The distribution function uniform_int models a \random_distribution.
+ * On each invocation, it returns a random integer value uniformly
+ * distributed in the set of integer numbers {min, min+1, min+2, ..., max}.
+ *
+ * The template parameter IntType shall denote an integer-like value type.
+ *
+ * This class is deprecated.  Please use @c uniform_int_distribution in
+ * new code.
+ */
+template<class IntType = int>
+class uniform_int : public random::uniform_int_distribution<IntType>
+{
+    typedef random::uniform_int_distribution<IntType> base_type;
+public:
+
+    class param_type : public base_type::param_type
+    {
+    public:
+        typedef uniform_int distribution_type;
+        /**
+         * Constructs the parameters of a uniform_int distribution.
+         *
+         * Requires: min <= max
+         */
+        explicit param_type(IntType min_arg = 0, IntType max_arg = 9)
+          : base_type::param_type(min_arg, max_arg)
+        {}
+    };
+
+    /**
+     * Constructs a uniform_int object. @c min and @c max are
+     * the parameters of the distribution.
+     *
+     * Requires: min <= max
+     */
+    explicit uniform_int(IntType min_arg = 0, IntType max_arg = 9)
+      : base_type(min_arg, max_arg)
+    {}
+
+    /** Constructs a uniform_int distribution from its parameters. */
+    explicit uniform_int(const param_type& parm)
+      : base_type(parm)
+    {}
+
+    /** Returns the parameters of the distribution */
+    param_type param() const { return param_type(this->a(), this->b()); }
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm) { this->base_type::param(parm); }
+
+    // Codergear seems to have trouble with a using declaration here
+
+    template<class Engine>
+    IntType operator()(Engine& eng) const
+    {
+        return static_cast<const base_type&>(*this)(eng);
+    }
+
+    template<class Engine>
+    IntType operator()(Engine& eng, const param_type& parm) const
+    {
+        return static_cast<const base_type&>(*this)(eng, parm);
+    }
+
+    template<class Engine>
+    IntType operator()(Engine& eng, IntType n) const
+    {
+        BOOST_ASSERT(n > 0);
+        return static_cast<const base_type&>(*this)(eng, param_type(0, n - 1));
+    }
+};
+
+} // namespace boost
+
+#endif // BOOST_RANDOM_UNIFORM_INT_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/uniform_int_distribution.hpp

@@ -0,0 +1,419 @@
+/* boost random/uniform_int_distribution.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2001-04-08  added min<max assertion (N. Becker)
+ *  2001-02-18  moved to individual header files
+ */
+
+#ifndef BOOST_RANDOM_UNIFORM_INT_DISTRIBUTION_HPP
+#define BOOST_RANDOM_UNIFORM_INT_DISTRIBUTION_HPP
+
+#include <iosfwd>
+#include <ios>
+#include <istream>
+#include <boost/config.hpp>
+#include <boost/limits.hpp>
+#include <boost/assert.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/detail/uniform_int_float.hpp>
+#include <boost/random/detail/signed_unsigned_tools.hpp>
+#include <boost/random/traits.hpp>
+#include <boost/mpl/bool.hpp>
+#ifdef BOOST_NO_CXX11_EXPLICIT_CONVERSION_OPERATORS
+#include <boost/mpl/if.hpp>
+#endif
+
+namespace boost {
+namespace random {
+namespace detail {
+    
+
+#ifdef BOOST_MSVC
+#pragma warning(push)
+// disable division by zero warning, since we can't
+// actually divide by zero.
+#pragma warning(disable:4723)
+#endif
+
+template<class Engine, class T>
+T generate_uniform_int(
+    Engine& eng, T min_value, T max_value,
+    boost::mpl::true_ /** is_integral<Engine::result_type> */)
+{
+    typedef T result_type;
+    typedef typename boost::random::traits::make_unsigned_or_unbounded<T>::type range_type;
+    typedef typename Engine::result_type base_result;
+    // ranges are always unsigned or unbounded
+    typedef typename boost::random::traits::make_unsigned_or_unbounded<base_result>::type base_unsigned;
+    const range_type range = random::detail::subtract<result_type>()(max_value, min_value);
+    const base_result bmin = (eng.min)();
+    const base_unsigned brange =
+      random::detail::subtract<base_result>()((eng.max)(), (eng.min)());
+
+    if(range == 0) {
+      return min_value;    
+    } else if(brange == range) {
+      // this will probably never happen in real life
+      // basically nothing to do; just take care we don't overflow / underflow
+      base_unsigned v = random::detail::subtract<base_result>()(eng(), bmin);
+      return random::detail::add<base_unsigned, result_type>()(v, min_value);
+    } else if(brange < range) {
+      // use rejection method to handle things like 0..3 --> 0..4
+      for(;;) {
+        // concatenate several invocations of the base RNG
+        // take extra care to avoid overflows
+
+        //  limit == floor((range+1)/(brange+1))
+        //  Therefore limit*(brange+1) <= range+1
+        range_type limit;
+        if(range == (std::numeric_limits<range_type>::max)()) {
+          limit = range/(range_type(brange)+1);
+          if(range % (range_type(brange)+1) == range_type(brange))
+            ++limit;
+        } else {
+          limit = (range+1)/(range_type(brange)+1);
+        }
+
+        // We consider "result" as expressed to base (brange+1):
+        // For every power of (brange+1), we determine a random factor
+        range_type result = range_type(0);
+        range_type mult = range_type(1);
+
+        // loop invariants:
+        //  result < mult
+        //  mult <= range
+        while(mult <= limit) {
+          // Postcondition: result <= range, thus no overflow
+          //
+          // limit*(brange+1)<=range+1                   def. of limit       (1)
+          // eng()-bmin<=brange                          eng() post.         (2)
+          // and mult<=limit.                            loop condition      (3)
+          // Therefore mult*(eng()-bmin+1)<=range+1      by (1),(2),(3)      (4)
+          // Therefore mult*(eng()-bmin)+mult<=range+1   rearranging (4)     (5)
+          // result<mult                                 loop invariant      (6)
+          // Therefore result+mult*(eng()-bmin)<range+1  by (5), (6)         (7)
+          //
+          // Postcondition: result < mult*(brange+1)
+          //
+          // result<mult                                 loop invariant      (1)
+          // eng()-bmin<=brange                          eng() post.         (2)
+          // Therefore result+mult*(eng()-bmin) <
+          //           mult+mult*(eng()-bmin)            by (1)              (3)
+          // Therefore result+(eng()-bmin)*mult <
+          //           mult+mult*brange                  by (2), (3)         (4)
+          // Therefore result+(eng()-bmin)*mult <
+          //           mult*(brange+1)                   by (4)
+          result += static_cast<range_type>(static_cast<range_type>(random::detail::subtract<base_result>()(eng(), bmin)) * mult);
+
+          // equivalent to (mult * (brange+1)) == range+1, but avoids overflow.
+          if(mult * range_type(brange) == range - mult + 1) {
+              // The destination range is an integer power of
+              // the generator's range.
+              return(result);
+          }
+
+          // Postcondition: mult <= range
+          // 
+          // limit*(brange+1)<=range+1                   def. of limit       (1)
+          // mult<=limit                                 loop condition      (2)
+          // Therefore mult*(brange+1)<=range+1          by (1), (2)         (3)
+          // mult*(brange+1)!=range+1                    preceding if        (4)
+          // Therefore mult*(brange+1)<range+1           by (3), (4)         (5)
+          // 
+          // Postcondition: result < mult
+          //
+          // See the second postcondition on the change to result. 
+          mult *= range_type(brange)+range_type(1);
+        }
+        // loop postcondition: range/mult < brange+1
+        //
+        // mult > limit                                  loop condition      (1)
+        // Suppose range/mult >= brange+1                Assumption          (2)
+        // range >= mult*(brange+1)                      by (2)              (3)
+        // range+1 > mult*(brange+1)                     by (3)              (4)
+        // range+1 > (limit+1)*(brange+1)                by (1), (4)         (5)
+        // (range+1)/(brange+1) > limit+1                by (5)              (6)
+        // limit < floor((range+1)/(brange+1))           by (6)              (7)
+        // limit==floor((range+1)/(brange+1))            def. of limit       (8)
+        // not (2)                                       reductio            (9)
+        //
+        // loop postcondition: (range/mult)*mult+(mult-1) >= range
+        //
+        // (range/mult)*mult + range%mult == range       identity            (1)
+        // range%mult < mult                             def. of %           (2)
+        // (range/mult)*mult+mult > range                by (1), (2)         (3)
+        // (range/mult)*mult+(mult-1) >= range           by (3)              (4)
+        //
+        // Note that the maximum value of result at this point is (mult-1),
+        // so after this final step, we generate numbers that can be
+        // at least as large as range.  We have to really careful to avoid
+        // overflow in this final addition and in the rejection.  Anything
+        // that overflows is larger than range and can thus be rejected.
+
+        // range/mult < brange+1  -> no endless loop
+        range_type result_increment =
+            generate_uniform_int(
+                eng,
+                static_cast<range_type>(0),
+                static_cast<range_type>(range/mult),
+                boost::mpl::true_());
+        if(std::numeric_limits<range_type>::is_bounded && ((std::numeric_limits<range_type>::max)() / mult < result_increment)) {
+          // The multiplcation would overflow.  Reject immediately.
+          continue;
+        }
+        result_increment *= mult;
+        // unsigned integers are guaranteed to wrap on overflow.
+        result += result_increment;
+        if(result < result_increment) {
+          // The addition overflowed.  Reject.
+          continue;
+        }
+        if(result > range) {
+          // Too big.  Reject.
+          continue;
+        }
+        return random::detail::add<range_type, result_type>()(result, min_value);
+      }
+    } else {                   // brange > range
+#ifdef BOOST_NO_CXX11_EXPLICIT_CONVERSION_OPERATORS
+      typedef typename mpl::if_c<
+         std::numeric_limits<range_type>::is_specialized && std::numeric_limits<base_unsigned>::is_specialized
+         && (std::numeric_limits<range_type>::digits >= std::numeric_limits<base_unsigned>::digits),
+         range_type, base_unsigned>::type mixed_range_type;
+#else
+      typedef base_unsigned mixed_range_type;
+#endif
+
+      mixed_range_type bucket_size;
+      // it's safe to add 1 to range, as long as we cast it first,
+      // because we know that it is less than brange.  However,
+      // we do need to be careful not to cause overflow by adding 1
+      // to brange.  We use mixed_range_type throughout for mixed
+      // arithmetic between base_unsigned and range_type - in the case
+      // that range_type has more bits than base_unsigned it is always
+      // safe to use range_type for this albeit it may be more effient
+      // to use base_unsigned.  The latter is a narrowing conversion though
+      // which may be disallowed if range_type is a multiprecision type
+      // and there are no explicit converison operators.
+
+      if(brange == (std::numeric_limits<base_unsigned>::max)()) {
+        bucket_size = static_cast<mixed_range_type>(brange) / (static_cast<mixed_range_type>(range)+1);
+        if(static_cast<mixed_range_type>(brange) % (static_cast<mixed_range_type>(range)+1) == static_cast<mixed_range_type>(range)) {
+          ++bucket_size;
+        }
+      } else {
+        bucket_size = static_cast<mixed_range_type>(brange + 1) / (static_cast<mixed_range_type>(range)+1);
+      }
+      for(;;) {
+        mixed_range_type result =
+          random::detail::subtract<base_result>()(eng(), bmin);
+        result /= bucket_size;
+        // result and range are non-negative, and result is possibly larger
+        // than range, so the cast is safe
+        if(result <= static_cast<mixed_range_type>(range))
+          return random::detail::add<mixed_range_type, result_type>()(result, min_value);
+      }
+    }
+}
+
+#ifdef BOOST_MSVC
+#pragma warning(pop)
+#endif
+
+template<class Engine, class T>
+inline T generate_uniform_int(
+    Engine& eng, T min_value, T max_value,
+    boost::mpl::false_ /** is_integral<Engine::result_type> */)
+{
+    uniform_int_float<Engine> wrapper(eng);
+    return generate_uniform_int(wrapper, min_value, max_value, boost::mpl::true_());
+}
+
+template<class Engine, class T>
+inline T generate_uniform_int(Engine& eng, T min_value, T max_value)
+{
+    typedef typename Engine::result_type base_result;
+    return generate_uniform_int(eng, min_value, max_value,
+        boost::random::traits::is_integral<base_result>());
+}
+
+}
+
+/**
+ * The class template uniform_int_distribution models a \random_distribution.
+ * On each invocation, it returns a random integer value uniformly
+ * distributed in the set of integers {min, min+1, min+2, ..., max}.
+ *
+ * The template parameter IntType shall denote an integer-like value type.
+ */
+template<class IntType = int>
+class uniform_int_distribution
+{
+public:
+    typedef IntType input_type;
+    typedef IntType result_type;
+
+    class param_type
+    {
+    public:
+
+        typedef uniform_int_distribution distribution_type;
+
+        /**
+         * Constructs the parameters of a uniform_int_distribution.
+         *
+         * Requires min <= max
+         */
+        explicit param_type(
+            IntType min_arg = 0,
+            IntType max_arg = (std::numeric_limits<IntType>::max)())
+          : _min(min_arg), _max(max_arg)
+        {
+            BOOST_ASSERT(_min <= _max);
+        }
+
+        /** Returns the minimum value of the distribution. */
+        IntType a() const { return _min; }
+        /** Returns the maximum value of the distribution. */
+        IntType b() const { return _max; }
+
+        /** Writes the parameters to a @c std::ostream. */
+        BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
+        {
+            os << parm._min << " " << parm._max;
+            return os;
+        }
+
+        /** Reads the parameters from a @c std::istream. */
+        BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
+        {
+            IntType min_in, max_in;
+            if(is >> min_in >> std::ws >> max_in) {
+                if(min_in <= max_in) {
+                    parm._min = min_in;
+                    parm._max = max_in;
+                } else {
+                    is.setstate(std::ios_base::failbit);
+                }
+            }
+            return is;
+        }
+
+        /** Returns true if the two sets of parameters are equal. */
+        BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
+        { return lhs._min == rhs._min && lhs._max == rhs._max; }
+
+        /** Returns true if the two sets of parameters are different. */
+        BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+
+    private:
+
+        IntType _min;
+        IntType _max;
+    };
+
+    /**
+     * Constructs a uniform_int_distribution. @c min and @c max are
+     * the parameters of the distribution.
+     *
+     * Requires: min <= max
+     */
+    explicit uniform_int_distribution(
+        IntType min_arg = 0,
+        IntType max_arg = (std::numeric_limits<IntType>::max)())
+      : _min(min_arg), _max(max_arg)
+    {
+        BOOST_ASSERT(min_arg <= max_arg);
+    }
+    /** Constructs a uniform_int_distribution from its parameters. */
+    explicit uniform_int_distribution(const param_type& parm)
+      : _min(parm.a()), _max(parm.b()) {}
+
+    /**  Returns the minimum value of the distribution */
+    IntType min BOOST_PREVENT_MACRO_SUBSTITUTION () const { return _min; }
+    /**  Returns the maximum value of the distribution */
+    IntType max BOOST_PREVENT_MACRO_SUBSTITUTION () const { return _max; }
+
+    /**  Returns the minimum value of the distribution */
+    IntType a() const { return _min; }
+    /**  Returns the maximum value of the distribution */
+    IntType b() const { return _max; }
+
+    /** Returns the parameters of the distribution. */
+    param_type param() const { return param_type(_min, _max); }
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        _min = parm.a();
+        _max = parm.b();
+    }
+
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { }
+
+    /** Returns an integer uniformly distributed in the range [min, max]. */
+    template<class Engine>
+    result_type operator()(Engine& eng) const
+    { return detail::generate_uniform_int(eng, _min, _max); }
+
+    /**
+     * Returns an integer uniformly distributed in the range
+     * [param.a(), param.b()].
+     */
+    template<class Engine>
+    result_type operator()(Engine& eng, const param_type& parm) const
+    { return detail::generate_uniform_int(eng, parm.a(), parm.b()); }
+
+    /** Writes the distribution to a @c std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, uniform_int_distribution, ud)
+    {
+        os << ud.param();
+        return os;
+    }
+
+    /** Reads the distribution from a @c std::istream. */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, uniform_int_distribution, ud)
+    {
+        param_type parm;
+        if(is >> parm) {
+            ud.param(parm);
+        }
+        return is;
+    }
+
+    /**
+     * Returns true if the two distributions will produce identical sequences
+     * of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(uniform_int_distribution, lhs, rhs)
+    { return lhs._min == rhs._min && lhs._max == rhs._max; }
+    
+    /**
+     * Returns true if the two distributions may produce different sequences
+     * of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(uniform_int_distribution)
+
+private:
+    IntType _min;
+    IntType _max;
+};
+
+} // namespace random
+} // namespace boost
+
+#endif // BOOST_RANDOM_UNIFORM_INT_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/uniform_on_sphere.hpp

@@ -0,0 +1,284 @@
+/* boost random/uniform_on_sphere.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2001-02-18  moved to individual header files
+ */
+
+#ifndef BOOST_RANDOM_UNIFORM_ON_SPHERE_HPP
+#define BOOST_RANDOM_UNIFORM_ON_SPHERE_HPP
+
+#include <vector>
+#include <algorithm>     // std::transform
+#include <functional>    // std::bind2nd, std::divides
+#include <boost/assert.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/normal_distribution.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * Instantiations of class template uniform_on_sphere model a
+ * \random_distribution. Such a distribution produces random
+ * numbers uniformly distributed on the unit sphere of arbitrary
+ * dimension @c dim. The @c Cont template parameter must be a STL-like
+ * container type with begin and end operations returning non-const
+ * ForwardIterators of type @c Cont::iterator. 
+ */
+template<class RealType = double, class Cont = std::vector<RealType> >
+class uniform_on_sphere
+{
+public:
+    typedef RealType input_type;
+    typedef Cont result_type;
+
+    class param_type
+    {
+    public:
+
+        typedef uniform_on_sphere distribution_type;
+
+        /**
+         * Constructs the parameters of a uniform_on_sphere
+         * distribution, given the dimension of the sphere.
+         */
+        explicit param_type(int dim_arg = 2) : _dim(dim_arg)
+        {
+            BOOST_ASSERT(_dim >= 0);
+        }
+
+        /** Returns the dimension of the sphere. */
+        int dim() const { return _dim; }
+
+        /** Writes the parameters to a @c std::ostream. */
+        BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
+        {
+            os << parm._dim;
+            return os;
+        }
+
+        /** Reads the parameters from a @c std::istream. */
+        BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
+        {
+            is >> parm._dim;
+            return is;
+        }
+
+        /** Returns true if the two sets of parameters are equal. */
+        BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
+        { return lhs._dim == rhs._dim; }
+
+        /** Returns true if the two sets of parameters are different. */
+        BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+
+    private:
+        int _dim;
+    };
+
+    /**
+     * Constructs a @c uniform_on_sphere distribution.
+     * @c dim is the dimension of the sphere.
+     *
+     * Requires: dim >= 0
+     */
+    explicit uniform_on_sphere(int dim_arg = 2)
+      : _container(dim_arg), _dim(dim_arg) { }
+
+    /**
+     * Constructs a @c uniform_on_sphere distribution from its parameters.
+     */
+    explicit uniform_on_sphere(const param_type& parm)
+      : _container(parm.dim()), _dim(parm.dim()) { }
+
+    // compiler-generated copy ctor and assignment operator are fine
+
+    /** Returns the dimension of the sphere. */
+    int dim() const { return _dim; }
+
+    /** Returns the parameters of the distribution. */
+    param_type param() const { return param_type(_dim); }
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        _dim = parm.dim();
+        _container.resize(_dim);
+    }
+
+    /**
+     * Returns the smallest value that the distribution can produce.
+     * Note that this is required to approximate the standard library's
+     * requirements.  The behavior is defined according to lexicographical
+     * comparison so that for a container type of std::vector,
+     * dist.min() <= x <= dist.max() where x is any value produced
+     * by the distribution.
+     */
+    result_type min BOOST_PREVENT_MACRO_SUBSTITUTION () const
+    {
+        result_type result(_dim);
+        if(_dim != 0) {
+            result.front() = RealType(-1.0);
+        }
+        return result;
+    }
+    /**
+     * Returns the largest value that the distribution can produce.
+     * Note that this is required to approximate the standard library's
+     * requirements.  The behavior is defined according to lexicographical
+     * comparison so that for a container type of std::vector,
+     * dist.min() <= x <= dist.max() where x is any value produced
+     * by the distribution.
+     */
+    result_type max BOOST_PREVENT_MACRO_SUBSTITUTION () const
+    {
+        result_type result(_dim);
+        if(_dim != 0) {
+            result.front() = RealType(1.0);
+        }
+        return result;
+    }
+
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() {}
+
+    /**
+     * Returns a point uniformly distributed over the surface of
+     * a sphere of dimension dim().
+     */
+    template<class Engine>
+    const result_type & operator()(Engine& eng)
+    {
+        using std::sqrt;
+        switch(_dim)
+        {
+        case 0: break;
+        case 1:
+            {
+                if(uniform_01<RealType>()(eng) < 0.5) {
+                    *_container.begin() = -1;
+                } else {
+                    *_container.begin() = 1;
+                }
+                break;
+            }
+        case 2:
+            {
+                uniform_01<RealType> uniform;
+                RealType sqsum;
+                RealType x, y;
+                do {
+                    x = uniform(eng) * 2 - 1;
+                    y = uniform(eng) * 2 - 1;
+                    sqsum = x*x + y*y;
+                } while(sqsum == 0 || sqsum > 1);
+                RealType mult = 1/sqrt(sqsum);
+                typename Cont::iterator iter = _container.begin();
+                *iter = x * mult;
+                iter++;
+                *iter = y * mult;
+                break;
+            }
+        case 3:
+            {
+                uniform_01<RealType> uniform;
+                RealType sqsum;
+                RealType x, y;
+                do {
+                    x = uniform(eng) * 2 - 1;
+                    y = uniform(eng) * 2 - 1;
+                    sqsum = x*x + y*y;
+                } while(sqsum > 1);
+                RealType mult = 2 * sqrt(1 - sqsum);
+                typename Cont::iterator iter = _container.begin();
+                *iter = x * mult;
+                ++iter;
+                *iter = y * mult;
+                ++iter;
+                *iter = 2 * sqsum - 1;
+                break;
+            }
+        default:
+            {
+                detail::unit_normal_distribution<RealType> normal;
+                RealType sqsum;
+                do {
+                    sqsum = 0;
+                    for(typename Cont::iterator it = _container.begin();
+                        it != _container.end();
+                        ++it) {
+                        RealType val = normal(eng);
+                        *it = val;
+                        sqsum += val * val;
+                    }
+                } while(sqsum == 0);
+                // for all i: result[i] /= sqrt(sqsum)
+                std::transform(_container.begin(), _container.end(), _container.begin(),
+                               std::bind2nd(std::multiplies<RealType>(), 1/sqrt(sqsum)));
+            }
+        }
+        return _container;
+    }
+
+    /**
+     * Returns a point uniformly distributed over the surface of
+     * a sphere of dimension param.dim().
+     */
+    template<class Engine>
+    result_type operator()(Engine& eng, const param_type& parm) const
+    {
+        return uniform_on_sphere(parm)(eng);
+    }
+
+    /** Writes the distribution to a @c std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, uniform_on_sphere, sd)
+    {
+        os << sd._dim;
+        return os;
+    }
+
+    /** Reads the distribution from a @c std::istream. */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, uniform_on_sphere, sd)
+    {
+        is >> sd._dim;
+        sd._container.resize(sd._dim);
+        return is;
+    }
+
+    /**
+     * Returns true if the two distributions will produce identical
+     * sequences of values, given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(uniform_on_sphere, lhs, rhs)
+    { return lhs._dim == rhs._dim; }
+
+    /**
+     * Returns true if the two distributions may produce different
+     * sequences of values, given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(uniform_on_sphere)
+
+private:
+    result_type _container;
+    int _dim;
+};
+
+} // namespace random
+
+using random::uniform_on_sphere;
+
+} // namespace boost
+
+#endif // BOOST_RANDOM_UNIFORM_ON_SPHERE_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/uniform_real.hpp

@@ -0,0 +1,82 @@
+/* boost random/uniform_real.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2001-04-08  added min<max assertion (N. Becker)
+ *  2001-02-18  moved to individual header files
+ */
+
+#ifndef BOOST_RANDOM_UNIFORM_REAL_HPP
+#define BOOST_RANDOM_UNIFORM_REAL_HPP
+
+#include <boost/assert.hpp>
+#include <boost/config.hpp>
+#include <boost/limits.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+
+namespace boost {
+
+/**
+ * The distribution function uniform_real models a random distribution.
+ * On each invocation, it returns a random floating-point value uniformly
+ * distributed in the range [min..max).
+ *
+ * This class is deprecated.  Please use @c uniform_real_distribution in
+ * new code.
+ */
+template<class RealType = double>
+class uniform_real : public random::uniform_real_distribution<RealType>
+{
+    typedef random::uniform_real_distribution<RealType> base_type;
+public:
+
+    class param_type : public base_type::param_type
+    {
+    public:
+        typedef uniform_real distribution_type;
+        /**
+         * Constructs the parameters of a uniform_real distribution.
+         *
+         * Requires: min <= max
+         */
+        explicit param_type(RealType min_arg = RealType(0.0),
+                            RealType max_arg = RealType(1.0))
+          : base_type::param_type(min_arg, max_arg)
+        {}
+    };
+
+    /**
+     * Constructs a uniform_real object. @c min and @c max are the
+     * parameters of the distribution.
+     *
+     * Requires: min <= max
+     */
+    explicit uniform_real(RealType min_arg = RealType(0.0),
+                          RealType max_arg = RealType(1.0))
+      : base_type(min_arg, max_arg)
+    {
+        BOOST_ASSERT(min_arg < max_arg);
+    }
+
+    /** Constructs a uniform_real distribution from its parameters. */
+    explicit uniform_real(const param_type& parm)
+      : base_type(parm)
+    {}
+
+    /** Returns the parameters of the distribution */
+    param_type param() const { return param_type(this->a(), this->b()); }
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm) { this->base_type::param(parm); }
+};
+
+} // namespace boost
+
+#endif // BOOST_RANDOM_UNIFORM_REAL_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/uniform_real_distribution.hpp

@@ -0,0 +1,241 @@
+/* boost random/uniform_real_distribution.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ *
+ */
+
+#ifndef BOOST_RANDOM_UNIFORM_REAL_DISTRIBUTION_HPP
+#define BOOST_RANDOM_UNIFORM_REAL_DISTRIBUTION_HPP
+
+#include <iosfwd>
+#include <ios>
+#include <istream>
+#include <boost/assert.hpp>
+#include <boost/config.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/detail/signed_unsigned_tools.hpp>
+#include <boost/type_traits/is_integral.hpp>
+#include <boost/mpl/bool.hpp>
+
+namespace boost {
+namespace random {
+namespace detail {
+
+template<class Engine, class T>
+T generate_uniform_real(
+    Engine& eng, T min_value, T max_value,
+    boost::mpl::false_  /** is_integral<Engine::result_type> */)
+{
+    for(;;) {
+        typedef T result_type;
+        result_type numerator = static_cast<T>(eng() - (eng.min)());
+        result_type divisor = static_cast<T>((eng.max)() - (eng.min)());
+        BOOST_ASSERT(divisor > 0);
+        BOOST_ASSERT(numerator >= 0 && numerator <= divisor);
+        T result = numerator / divisor * (max_value - min_value) + min_value;
+        if(result < max_value) return result;
+    }
+}
+
+template<class Engine, class T>
+T generate_uniform_real(
+    Engine& eng, T min_value, T max_value,
+    boost::mpl::true_  /** is_integral<Engine::result_type> */)
+{
+    for(;;) {
+        typedef T result_type;
+        typedef typename Engine::result_type base_result;
+        result_type numerator = static_cast<T>(subtract<base_result>()(eng(), (eng.min)()));
+        result_type divisor = static_cast<T>(subtract<base_result>()((eng.max)(), (eng.min)())) + 1;
+        BOOST_ASSERT(divisor > 0);
+        BOOST_ASSERT(numerator >= 0 && numerator <= divisor);
+        T result = numerator / divisor * (max_value - min_value) + min_value;
+        if(result < max_value) return result;
+    }
+}
+
+template<class Engine, class T>
+inline T generate_uniform_real(Engine& eng, T min_value, T max_value)
+{
+    if(max_value / 2 - min_value / 2 > (std::numeric_limits<T>::max)() / 2)
+        return 2 * generate_uniform_real(eng, T(min_value / 2), T(max_value / 2));
+    typedef typename Engine::result_type base_result;
+    return generate_uniform_real(eng, min_value, max_value,
+        boost::is_integral<base_result>());
+}
+
+}
+
+/**
+ * The class template uniform_real_distribution models a \random_distribution.
+ * On each invocation, it returns a random floating-point value uniformly
+ * distributed in the range [min..max).
+ */
+template<class RealType = double>
+class uniform_real_distribution
+{
+public:
+    typedef RealType input_type;
+    typedef RealType result_type;
+
+    class param_type
+    {
+    public:
+
+        typedef uniform_real_distribution distribution_type;
+
+        /**
+         * Constructs the parameters of a uniform_real_distribution.
+         *
+         * Requires min <= max
+         */
+        explicit param_type(RealType min_arg = RealType(0.0),
+                            RealType max_arg = RealType(1.0))
+          : _min(min_arg), _max(max_arg)
+        {
+            BOOST_ASSERT(_min < _max);
+        }
+
+        /** Returns the minimum value of the distribution. */
+        RealType a() const { return _min; }
+        /** Returns the maximum value of the distribution. */
+        RealType b() const { return _max; }
+
+        /** Writes the parameters to a @c std::ostream. */
+        BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
+        {
+            os << parm._min << " " << parm._max;
+            return os;
+        }
+
+        /** Reads the parameters from a @c std::istream. */
+        BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
+        {
+            RealType min_in, max_in;
+            if(is >> min_in >> std::ws >> max_in) {
+                if(min_in <= max_in) {
+                    parm._min = min_in;
+                    parm._max = max_in;
+                } else {
+                    is.setstate(std::ios_base::failbit);
+                }
+            }
+            return is;
+        }
+
+        /** Returns true if the two sets of parameters are equal. */
+        BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
+        { return lhs._min == rhs._min && lhs._max == rhs._max; }
+
+        /** Returns true if the two sets of parameters are different. */
+        BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+
+    private:
+
+        RealType _min;
+        RealType _max;
+    };
+
+    /**
+     * Constructs a uniform_real_distribution. @c min and @c max are
+     * the parameters of the distribution.
+     *
+     * Requires: min <= max
+     */
+    explicit uniform_real_distribution(
+        RealType min_arg = RealType(0.0),
+        RealType max_arg = RealType(1.0))
+      : _min(min_arg), _max(max_arg)
+    {
+        BOOST_ASSERT(min_arg < max_arg);
+    }
+    /** Constructs a uniform_real_distribution from its parameters. */
+    explicit uniform_real_distribution(const param_type& parm)
+      : _min(parm.a()), _max(parm.b()) {}
+
+    /**  Returns the minimum value of the distribution */
+    RealType min BOOST_PREVENT_MACRO_SUBSTITUTION () const { return _min; }
+    /**  Returns the maximum value of the distribution */
+    RealType max BOOST_PREVENT_MACRO_SUBSTITUTION () const { return _max; }
+
+    /**  Returns the minimum value of the distribution */
+    RealType a() const { return _min; }
+    /**  Returns the maximum value of the distribution */
+    RealType b() const { return _max; }
+
+    /** Returns the parameters of the distribution. */
+    param_type param() const { return param_type(_min, _max); }
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        _min = parm.a();
+        _max = parm.b();
+    }
+
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { }
+
+    /** Returns a value uniformly distributed in the range [min, max). */
+    template<class Engine>
+    result_type operator()(Engine& eng) const
+    { return detail::generate_uniform_real(eng, _min, _max); }
+
+    /**
+     * Returns a value uniformly distributed in the range
+     * [param.a(), param.b()).
+     */
+    template<class Engine>
+    result_type operator()(Engine& eng, const param_type& parm) const
+    { return detail::generate_uniform_real(eng, parm.a(), parm.b()); }
+
+    /** Writes the distribution to a @c std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, uniform_real_distribution, ud)
+    {
+        os << ud.param();
+        return os;
+    }
+
+    /** Reads the distribution from a @c std::istream. */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, uniform_real_distribution, ud)
+    {
+        param_type parm;
+        if(is >> parm) {
+            ud.param(parm);
+        }
+        return is;
+    }
+
+    /**
+     * Returns true if the two distributions will produce identical sequences
+     * of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(uniform_real_distribution, lhs, rhs)
+    { return lhs._min == rhs._min && lhs._max == rhs._max; }
+    
+    /**
+     * Returns true if the two distributions may produce different sequences
+     * of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(uniform_real_distribution)
+
+private:
+    RealType _min;
+    RealType _max;
+};
+
+} // namespace random
+} // namespace boost
+
+#endif // BOOST_RANDOM_UNIFORM_INT_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/uniform_smallint.hpp

@@ -0,0 +1,307 @@
+/* boost random/uniform_smallint.hpp header file
+ *
+ * Copyright Jens Maurer 2000-2001
+ * 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.
+ *
+ * $Id$
+ *
+ * Revision history
+ *  2001-04-08  added min<max assertion (N. Becker)
+ *  2001-02-18  moved to individual header files
+ */
+
+#ifndef BOOST_RANDOM_UNIFORM_SMALLINT_HPP
+#define BOOST_RANDOM_UNIFORM_SMALLINT_HPP
+
+#include <istream>
+#include <iosfwd>
+#include <boost/assert.hpp>
+#include <boost/config.hpp>
+#include <boost/limits.hpp>
+#include <boost/type_traits/is_integral.hpp>
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/detail/signed_unsigned_tools.hpp>
+#include <boost/random/uniform_01.hpp>
+#include <boost/detail/workaround.hpp>
+#include <boost/mpl/bool.hpp>
+
+#ifdef BOOST_NO_CXX11_EXPLICIT_CONVERSION_OPERATORS
+#include <boost/mpl/if.hpp>
+#endif
+
+namespace boost {
+namespace random {
+
+// uniform integer distribution on a small range [min, max]
+
+/**
+ * The distribution function uniform_smallint models a \random_distribution.
+ * On each invocation, it returns a random integer value uniformly distributed
+ * in the set of integer numbers {min, min+1, min+2, ..., max}. It assumes
+ * that the desired range (max-min+1) is small compared to the range of the
+ * underlying source of random numbers and thus makes no attempt to limit
+ * quantization errors.
+ *
+ * Let \f$r_{\mathtt{out}} = (\mbox{max}-\mbox{min}+1)\f$ the desired range of
+ * integer numbers, and
+ * let \f$r_{\mathtt{base}}\f$ be the range of the underlying source of random
+ * numbers. Then, for the uniform distribution, the theoretical probability
+ * for any number i in the range \f$r_{\mathtt{out}}\f$ will be
+ * \f$\displaystyle p_{\mathtt{out}}(i) = \frac{1}{r_{\mathtt{out}}}\f$.
+ * Likewise, assume a uniform distribution on \f$r_{\mathtt{base}}\f$ for
+ * the underlying source of random numbers, i.e.
+ * \f$\displaystyle p_{\mathtt{base}}(i) = \frac{1}{r_{\mathtt{base}}}\f$.
+ * Let \f$p_{\mathtt{out\_s}}(i)\f$ denote the random
+ * distribution generated by @c uniform_smallint. Then the sum over all
+ * i in \f$r_{\mathtt{out}}\f$ of
+ * \f$\displaystyle
+ * \left(\frac{p_{\mathtt{out\_s}}(i)}{p_{\mathtt{out}}(i)} - 1\right)^2\f$
+ * shall not exceed
+ * \f$\displaystyle \frac{r_{\mathtt{out}}}{r_{\mathtt{base}}^2}
+ * (r_{\mathtt{base}} \mbox{ mod } r_{\mathtt{out}})
+ * (r_{\mathtt{out}} - r_{\mathtt{base}} \mbox{ mod } r_{\mathtt{out}})\f$.
+ *
+ * The template parameter IntType shall denote an integer-like value type.
+ *
+ * @xmlnote
+ * The property above is the square sum of the relative differences
+ * in probabilities between the desired uniform distribution
+ * \f$p_{\mathtt{out}}(i)\f$ and the generated distribution
+ * \f$p_{\mathtt{out\_s}}(i)\f$.
+ * The property can be fulfilled with the calculation
+ * \f$(\mbox{base\_rng} \mbox{ mod } r_{\mathtt{out}})\f$, as follows:
+ * Let \f$r = r_{\mathtt{base}} \mbox{ mod } r_{\mathtt{out}}\f$.
+ * The base distribution on \f$r_{\mathtt{base}}\f$ is folded onto the
+ * range \f$r_{\mathtt{out}}\f$. The numbers i < r have assigned
+ * \f$\displaystyle
+ * \left\lfloor\frac{r_{\mathtt{base}}}{r_{\mathtt{out}}}\right\rfloor+1\f$
+ * numbers of the base distribution, the rest has only \f$\displaystyle
+ * \left\lfloor\frac{r_{\mathtt{base}}}{r_{\mathtt{out}}}\right\rfloor\f$.
+ * Therefore,
+ * \f$\displaystyle p_{\mathtt{out\_s}}(i) =
+ * \left(\left\lfloor\frac{r_{\mathtt{base}}}
+ * {r_{\mathtt{out}}}\right\rfloor+1\right) /
+ * r_{\mathtt{base}}\f$ for i < r and \f$\displaystyle p_{\mathtt{out\_s}}(i) =
+ * \left\lfloor\frac{r_{\mathtt{base}}}
+ * {r_{\mathtt{out}}}\right\rfloor/r_{\mathtt{base}}\f$ otherwise.
+ * Substituting this in the
+ * above sum formula leads to the desired result.
+ * @endxmlnote
+ *
+ * Note: The upper bound for
+ * \f$(r_{\mathtt{base}} \mbox{ mod } r_{\mathtt{out}})
+ * (r_{\mathtt{out}} - r_{\mathtt{base}} \mbox{ mod } r_{\mathtt{out}})\f$ is
+ * \f$\displaystyle \frac{r_{\mathtt{out}}^2}{4}\f$.  Regarding the upper bound
+ * for the square sum of the relative quantization error of
+ * \f$\displaystyle \frac{r_\mathtt{out}^3}{4r_{\mathtt{base}}^2}\f$, it
+ * seems wise to either choose \f$r_{\mathtt{base}}\f$ so that
+ * \f$r_{\mathtt{base}} > 10r_{\mathtt{out}}^2\f$ or ensure that
+ * \f$r_{\mathtt{base}}\f$ is
+ * divisible by \f$r_{\mathtt{out}}\f$.
+ */
+template<class IntType = int>
+class uniform_smallint
+{
+public:
+    typedef IntType input_type;
+    typedef IntType result_type;
+
+    class param_type
+    {
+    public:
+
+        typedef uniform_smallint distribution_type;
+
+        /** constructs the parameters of a @c uniform_smallint distribution. */
+        param_type(IntType min_arg = 0, IntType max_arg = 9)
+          : _min(min_arg), _max(max_arg)
+        {
+            BOOST_ASSERT(_min <= _max);
+        }
+
+        /** Returns the minimum value. */
+        IntType a() const { return _min; }
+        /** Returns the maximum value. */
+        IntType b() const { return _max; }
+        
+
+        /** Writes the parameters to a @c std::ostream. */
+        BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
+        {
+            os << parm._min << " " << parm._max;
+            return os;
+        }
+    
+        /** Reads the parameters from a @c std::istream. */
+        BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
+        {
+            is >> parm._min >> std::ws >> parm._max;
+            return is;
+        }
+
+        /** Returns true if the two sets of parameters are equal. */
+        BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
+        { return lhs._min == rhs._min && lhs._max == rhs._max; }
+
+        /** Returns true if the two sets of parameters are different. */
+        BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+
+    private:
+        IntType _min;
+        IntType _max;
+    };
+
+    /**
+     * Constructs a @c uniform_smallint. @c min and @c max are the
+     * lower and upper bounds of the output range, respectively.
+     */
+    explicit uniform_smallint(IntType min_arg = 0, IntType max_arg = 9)
+      : _min(min_arg), _max(max_arg) {}
+
+    /**
+     * Constructs a @c uniform_smallint from its parameters.
+     */
+    explicit uniform_smallint(const param_type& parm)
+      : _min(parm.a()), _max(parm.b()) {}
+
+    /** Returns the minimum value of the distribution. */
+    result_type a() const { return _min; }
+    /** Returns the maximum value of the distribution. */
+    result_type b() const { return _max; }
+    /** Returns the minimum value of the distribution. */
+    result_type min BOOST_PREVENT_MACRO_SUBSTITUTION () const { return _min; }
+    /** Returns the maximum value of the distribution. */
+    result_type max BOOST_PREVENT_MACRO_SUBSTITUTION () const { return _max; }
+
+    /** Returns the parameters of the distribution. */
+    param_type param() const { return param_type(_min, _max); }
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        _min = parm.a();
+        _max = parm.b();
+    }
+
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { }
+
+    /** Returns a value uniformly distributed in the range [min(), max()]. */
+    template<class Engine>
+    result_type operator()(Engine& eng) const
+    {
+        typedef typename Engine::result_type base_result;
+        return generate(eng, boost::random::traits::is_integral<base_result>());
+    }
+
+    /** Returns a value uniformly distributed in the range [param.a(), param.b()]. */
+    template<class Engine>
+    result_type operator()(Engine& eng, const param_type& parm) const
+    { return uniform_smallint(parm)(eng); }
+
+    /** Writes the distribution to a @c std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, uniform_smallint, ud)
+    {
+        os << ud._min << " " << ud._max;
+        return os;
+    }
+    
+    /** Reads the distribution from a @c std::istream. */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, uniform_smallint, ud)
+    {
+        is >> ud._min >> std::ws >> ud._max;
+        return is;
+    }
+
+    /**
+     * Returns true if the two distributions will produce identical
+     * sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(uniform_smallint, lhs, rhs)
+    { return lhs._min == rhs._min && lhs._max == rhs._max; }
+    
+    /**
+     * Returns true if the two distributions may produce different
+     * sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(uniform_smallint)
+
+private:
+    
+    // \cond show_private
+    template<class Engine>
+    result_type generate(Engine& eng, boost::mpl::true_) const
+    {
+        // equivalent to (eng() - eng.min()) % (_max - _min + 1) + _min,
+        // but guarantees no overflow.
+        typedef typename Engine::result_type base_result;
+        typedef typename boost::random::traits::make_unsigned<base_result>::type base_unsigned;
+        typedef typename boost::random::traits::make_unsigned_or_unbounded<result_type>::type range_type;
+#ifdef BOOST_NO_CXX11_EXPLICIT_CONVERSION_OPERATORS
+        typedef typename mpl::if_c<
+           std::numeric_limits<range_type>::is_specialized && std::numeric_limits<base_unsigned>::is_specialized
+           && (std::numeric_limits<range_type>::digits >= std::numeric_limits<base_unsigned>::digits),
+           range_type, base_unsigned>::type mixed_range_type;
+#else
+        typedef base_unsigned mixed_range_type;
+#endif
+        range_type range = random::detail::subtract<result_type>()(_max, _min);
+        base_unsigned base_range =
+            random::detail::subtract<base_result>()((eng.max)(), (eng.min)());
+        base_unsigned val =
+            random::detail::subtract<base_result>()(eng(), (eng.min)());
+        if(range >= base_range) {
+            return boost::random::detail::add<range_type, result_type>()(
+                static_cast<range_type>(val), _min);
+        } else {
+            // This involves mixed arithmetic between the base generators range
+            // type, and the result_type's range type.  mixed_range_type is
+            // normally the same as base_unsigned which is the most efficient
+            // option, but requires a narrowing explcit cast if result_type
+            // is a multiprecision type.  If no such casts are available then use
+            // multiprecision arithmetic throughout instead.
+            mixed_range_type modulus = static_cast<mixed_range_type>(range)+1;
+            return boost::random::detail::add<range_type, result_type>()(
+                static_cast<mixed_range_type>(val) % modulus, _min);
+        }
+    }
+    
+    template<class Engine>
+    result_type generate(Engine& eng, boost::mpl::false_) const
+    {
+        typedef typename Engine::result_type base_result;
+        typedef typename boost::random::traits::make_unsigned<result_type>::type range_type;
+        range_type range = random::detail::subtract<result_type>()(_max, _min);
+        base_result val = boost::uniform_01<base_result>()(eng);
+        // what is the worst that can possibly happen here?
+        // base_result may not be able to represent all the values in [0, range]
+        // exactly.  If this happens, it will cause round off error and we
+        // won't be able to produce all the values in the range.  We don't
+        // care about this because the user has already told us not to by
+        // using uniform_smallint.  However, we do need to be careful
+        // to clamp the result, or floating point rounding can produce
+        // an out of range result.
+        range_type offset = static_cast<range_type>(val * (static_cast<base_result>(range) + 1));
+        if(offset > range) return _max;
+        return boost::random::detail::add<range_type, result_type>()(offset , _min);
+    }
+    // \endcond
+
+    result_type _min;
+    result_type _max;
+};
+
+} // namespace random
+
+using random::uniform_smallint;
+
+} // namespace boost
+
+#endif // BOOST_RANDOM_UNIFORM_SMALLINT_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/variate_generator.hpp

@@ -0,0 +1,122 @@
+/* boost random/variate_generator.hpp header file
+ *
+ * Copyright Jens Maurer 2002
+ * Copyright Steven Watanabe 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.
+ *
+ * $Id$
+ *
+ */
+
+#ifndef BOOST_RANDOM_RANDOM_GENERATOR_HPP
+#define BOOST_RANDOM_RANDOM_GENERATOR_HPP
+
+#include <boost/random/detail/ptr_helper.hpp>
+
+#include <boost/random/detail/disable_warnings.hpp>
+
+namespace boost {
+
+/// \cond hide_private_members
+
+namespace random {
+
+///\endcond
+
+/**
+ * A random variate generator is used to join a random number
+ * generator together with a random number distribution.
+ * Boost.Random provides a vast choice of \generators as well
+ * as \distributions.
+ *
+ * The argument for the template parameter Engine shall be of
+ * the form U, U&, or U*, where U models a
+ * \uniform_random_number_generator.  Then, the member
+ * engine_value_type names U (not the pointer or reference to U).
+ *
+ * Specializations of @c variate_generator satisfy the
+ * requirements of CopyConstructible. They also satisfy the
+ * requirements of Assignable unless the template parameter
+ * Engine is of the form U&.
+ *
+ * The complexity of all functions specified in this section
+ * is constant. No function described in this section except
+ * the constructor throws an exception.
+ */
+template<class Engine, class Distribution>
+class variate_generator
+{
+private:
+    typedef boost::random::detail::ptr_helper<Engine> helper_type;
+public:
+    typedef typename helper_type::value_type engine_value_type;
+    typedef Engine engine_type;
+    typedef Distribution distribution_type;
+    typedef typename Distribution::result_type result_type;
+
+    /**
+     * Constructs a @c variate_generator object with the associated
+     * \uniform_random_number_generator eng and the associated
+     * \random_distribution d.
+     *
+     * Throws: If and what the copy constructor of Engine or
+     * Distribution throws.
+     */
+    variate_generator(Engine e, Distribution d)
+      : _eng(e), _dist(d) { }
+
+    /** Returns: distribution()(engine()) */
+    result_type operator()() { return _dist(engine()); }
+    /**
+     * Returns: distribution()(engine(), value).
+     */
+    template<class T>
+    result_type operator()(const T& value) { return _dist(engine(), value); }
+
+    /**
+     * Returns: A reference to the associated uniform random number generator.
+     */
+    engine_value_type& engine() { return helper_type::ref(_eng); }
+    /**
+     * Returns: A reference to the associated uniform random number generator.
+     */
+    const engine_value_type& engine() const { return helper_type::ref(_eng); }
+
+    /** Returns: A reference to the associated \random_distribution. */
+    distribution_type& distribution() { return _dist; }
+    /**
+     * Returns: A reference to the associated random distribution.
+     */
+    const distribution_type& distribution() const { return _dist; }
+
+    /**
+     * Precondition: distribution().min() is well-formed
+     *
+     * Returns: distribution().min()
+     */
+    result_type min BOOST_PREVENT_MACRO_SUBSTITUTION () const { return (distribution().min)(); }
+    /**
+     * Precondition: distribution().max() is well-formed
+     *
+     * Returns: distribution().max()
+     */
+    result_type max BOOST_PREVENT_MACRO_SUBSTITUTION () const { return (distribution().max)(); }
+
+private:
+    Engine _eng;
+    distribution_type _dist;
+};
+
+} // namespace random
+
+using random::variate_generator;
+
+} // namespace boost
+
+#include <boost/random/detail/enable_warnings.hpp>
+
+#endif // BOOST_RANDOM_RANDOM_GENERATOR_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/weibull_distribution.hpp

@@ -0,0 +1,177 @@
+/* boost random/weibull_distribution.hpp header file
+ *
+ * Copyright Steven Watanabe 2010
+ * 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.
+ *
+ * $Id$
+ */
+
+#ifndef BOOST_RANDOM_WEIBULL_DISTRIBUTION_HPP
+#define BOOST_RANDOM_WEIBULL_DISTRIBUTION_HPP
+
+#include <boost/config/no_tr1/cmath.hpp>
+#include <iosfwd>
+#include <istream>
+#include <boost/config.hpp>
+#include <boost/limits.hpp>
+#include <boost/random/detail/operators.hpp>
+#include <boost/random/uniform_01.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * The Weibull distribution is a real valued distribution with two
+ * parameters a and b, producing values >= 0.
+ *
+ * It has \f$\displaystyle p(x) = \frac{a}{b}\left(\frac{x}{b}\right)^{a-1}e^{-\left(\frac{x}{b}\right)^a}\f$.
+ */
+template<class RealType = double>
+class weibull_distribution {
+public:
+    typedef RealType result_type;
+    typedef RealType input_type;
+
+    class param_type {
+    public:
+        typedef weibull_distribution distribution_type;
+
+        /**
+         * Constructs a @c param_type from the "a" and "b" parameters
+         * of the distribution.
+         *
+         * Requires: a > 0 && b > 0
+         */
+        explicit param_type(RealType a_arg = 1.0, RealType b_arg = 1.0)
+          : _a(a_arg), _b(b_arg)
+        {}
+
+        /** Returns the "a" parameter of the distribtuion. */
+        RealType a() const { return _a; }
+        /** Returns the "b" parameter of the distribution. */
+        RealType b() const { return _b; }
+
+        /** Writes a @c param_type to a @c std::ostream. */
+        BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
+        { os << parm._a << ' ' << parm._b; return os; }
+
+        /** Reads a @c param_type from a @c std::istream. */
+        BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
+        { is >> parm._a >> std::ws >> parm._b; return is; }
+
+        /** Returns true if the two sets of parameters are the same. */
+        BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
+        { return lhs._a == rhs._a && lhs._b == rhs._b; }
+        
+        /** Returns true if the two sets of parameters are the different. */
+        BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
+
+    private:
+        RealType _a;
+        RealType _b;
+    };
+
+    /**
+     * Constructs a @c weibull_distribution from its "a" and "b" parameters.
+     *
+     * Requires: a > 0 && b > 0
+     */
+    explicit weibull_distribution(RealType a_arg = 1.0, RealType b_arg = 1.0)
+      : _a(a_arg), _b(b_arg)
+    {}
+    /** Constructs a @c weibull_distribution from its parameters. */
+    explicit weibull_distribution(const param_type& parm)
+      : _a(parm.a()), _b(parm.b())
+    {}
+
+    /**
+     * Returns a random variate distributed according to the
+     * @c weibull_distribution.
+     */
+    template<class URNG>
+    RealType operator()(URNG& urng) const
+    {
+        using std::pow;
+        using std::log;
+        return _b*pow(-log(1 - uniform_01<RealType>()(urng)), 1/_a);
+    }
+
+    /**
+     * Returns a random variate distributed accordint to the Weibull
+     * distribution with parameters specified by @c param.
+     */
+    template<class URNG>
+    RealType operator()(URNG& urng, const param_type& parm) const
+    {
+        return weibull_distribution(parm)(urng);
+    }
+
+    /** Returns the "a" parameter of the distribution. */
+    RealType a() const { return _a; }
+    /** Returns the "b" parameter of the distribution. */
+    RealType b() const { return _b; }
+
+    /** Returns the smallest value that the distribution can produce. */
+    RealType min BOOST_PREVENT_MACRO_SUBSTITUTION () const { return 0; }
+    /** 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(_a, _b); }
+    /** Sets the parameters of the distribution. */
+    void param(const param_type& parm)
+    {
+        _a = parm.a();
+        _b = parm.b();
+    }
+
+    /**
+     * Effects: Subsequent uses of the distribution do not depend
+     * on values produced by any engine prior to invoking reset.
+     */
+    void reset() { }
+
+    /** Writes a @c weibull_distribution to a @c std::ostream. */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, weibull_distribution, wd)
+    {
+        os << wd.param();
+        return os;
+    }
+
+    /** Reads a @c weibull_distribution from a @c std::istream. */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, weibull_distribution, wd)
+    {
+        param_type parm;
+        if(is >> parm) {
+            wd.param(parm);
+        }
+        return is;
+    }
+
+    /**
+     * Returns true if the two instances of @c weibull_distribution will
+     * return identical sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(weibull_distribution, lhs, rhs)
+    { return lhs._a == rhs._a && lhs._b == rhs._b; }
+    
+    /**
+     * Returns true if the two instances of @c weibull_distribution will
+     * return different sequences of values given equal generators.
+     */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(weibull_distribution)
+
+private:
+    RealType _a;
+    RealType _b;
+};
+
+} // namespace random
+} // namespace boost
+
+#endif // BOOST_RANDOM_WEIBULL_DISTRIBUTION_HPP

depends/x86_64-pc-linux-gnu/include/boost/random/xor_combine.hpp

@@ -0,0 +1,208 @@
+/* boost random/xor_combine.hpp header file
+ *
+ * Copyright Jens Maurer 2002
+ * 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.
+ *
+ * $Id$
+ *
+ */
+
+#ifndef BOOST_RANDOM_XOR_COMBINE_HPP
+#define BOOST_RANDOM_XOR_COMBINE_HPP
+
+#include <istream>
+#include <iosfwd>
+#include <cassert>
+#include <algorithm> // for std::min and std::max
+#include <boost/config.hpp>
+#include <boost/limits.hpp>
+#include <boost/cstdint.hpp>     // uint32_t
+#include <boost/random/detail/config.hpp>
+#include <boost/random/detail/seed.hpp>
+#include <boost/random/detail/seed_impl.hpp>
+#include <boost/random/detail/operators.hpp>
+
+namespace boost {
+namespace random {
+
+/**
+ * Instantiations of @c xor_combine_engine model a
+ * \pseudo_random_number_generator.  To produce its output it
+ * invokes each of the base generators, shifts their results
+ * and xors them together.
+ */
+template<class URNG1, int s1, class URNG2, int s2>
+class xor_combine_engine
+{
+public:
+    typedef URNG1 base1_type;
+    typedef URNG2 base2_type;
+    typedef typename base1_type::result_type result_type;
+
+    BOOST_STATIC_CONSTANT(bool, has_fixed_range = false);
+    BOOST_STATIC_CONSTANT(int, shift1 = s1);
+    BOOST_STATIC_CONSTANT(int, shift2 = s2);
+
+    /**
+     * Constructors a @c xor_combine_engine by default constructing
+     * both base generators.
+     */
+    xor_combine_engine() : _rng1(), _rng2() { }
+
+    /** Constructs a @c xor_combine by copying two base generators. */
+    xor_combine_engine(const base1_type & rng1, const base2_type & rng2)
+      : _rng1(rng1), _rng2(rng2) { }
+
+    /**
+     * Constructs a @c xor_combine_engine, seeding both base generators
+     * with @c v.
+     *
+     * @xmlwarning
+     * The exact algorithm used by this function may change in the future.
+     * @endxmlwarning
+     */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_CONSTRUCTOR(xor_combine_engine,
+        result_type, v)
+    { seed(v); }
+
+    /**
+     * Constructs a @c xor_combine_engine, seeding both base generators
+     * with values produced by @c seq.
+     */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_CONSTRUCTOR(xor_combine_engine,
+        SeedSeq, seq)
+    { seed(seq); }
+
+    /**
+     * Constructs a @c xor_combine_engine, seeding both base generators
+     * with values from the iterator range [first, last) and changes
+     * first to point to the element after the last one used.  If there
+     * are not enough elements in the range to seed both generators,
+     * throws @c std::invalid_argument.
+     */
+    template<class It> xor_combine_engine(It& first, It last)
+      : _rng1(first, last), _rng2( /* advanced by other call */ first, last) { }
+
+    /** Calls @c seed() for both base generators. */
+    void seed() { _rng1.seed(); _rng2.seed(); }
+
+    /** @c seeds both base generators with @c v. */
+    BOOST_RANDOM_DETAIL_ARITHMETIC_SEED(xor_combine_engine, result_type, v)
+    { _rng1.seed(v); _rng2.seed(v); }
+
+    /** @c seeds both base generators with values produced by @c seq. */
+    BOOST_RANDOM_DETAIL_SEED_SEQ_SEED(xor_combine_engine, SeedSeq, seq)
+    { _rng1.seed(seq); _rng2.seed(seq); }
+
+    /**
+     * seeds both base generators with values from the iterator
+     * range [first, last) and changes first to point to the element
+     * after the last one used.  If there are not enough elements in
+     * the range to seed both generators, throws @c std::invalid_argument.
+     */
+    template<class It> void seed(It& first, It last)
+    {
+        _rng1.seed(first, last);
+        _rng2.seed(first, last);
+    }
+
+    /** Returns the first base generator. */
+    const base1_type& base1() const { return _rng1; }
+
+    /** Returns the second base generator. */
+    const base2_type& base2() const { return _rng2; }
+
+    /** Returns the next value of the generator. */
+    result_type operator()()
+    {
+        return (_rng1() << s1) ^ (_rng2() << s2);
+    }
+  
+    /** Fills a range with random values */
+    template<class Iter>
+    void generate(Iter first, Iter last)
+    { detail::generate_from_int(*this, first, last); }
+
+    /** Advances the state of the generator by @c z. */
+    void discard(boost::uintmax_t z)
+    {
+        _rng1.discard(z);
+        _rng2.discard(z);
+    }
+
+    /** Returns the smallest value that the generator can produce. */
+    static result_type min BOOST_PREVENT_MACRO_SUBSTITUTION () { return (std::min)((URNG1::min)(), (URNG2::min)()); }
+    /** Returns the largest value that the generator can produce. */
+    static result_type max BOOST_PREVENT_MACRO_SUBSTITUTION () { return (std::max)((URNG1::min)(), (URNG2::max)()); }
+
+    /**
+     * Writes the textual representation of the generator to a @c std::ostream.
+     */
+    BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, xor_combine_engine, s)
+    {
+        os << s._rng1 << ' ' << s._rng2;
+        return os;
+    }
+    
+    /**
+     * Reads the textual representation of the generator from a @c std::istream.
+     */
+    BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, xor_combine_engine, s)
+    {
+        is >> s._rng1 >> std::ws >> s._rng2;
+        return is;
+    }
+    
+    /** Returns true if the two generators will produce identical sequences. */
+    BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(xor_combine_engine, x, y)
+    { return x._rng1 == y._rng1 && x._rng2 == y._rng2; }
+    
+    /** Returns true if the two generators will produce different sequences. */
+    BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(xor_combine_engine)
+
+private:
+    base1_type _rng1;
+    base2_type _rng2;
+};
+
+#ifndef BOOST_NO_INCLASS_MEMBER_INITIALIZATION
+//  A definition is required even for integral static constants
+template<class URNG1, int s1, class URNG2, int s2>
+const bool xor_combine_engine<URNG1, s1, URNG2, s2>::has_fixed_range;
+template<class URNG1, int s1, class URNG2, int s2>
+const int xor_combine_engine<URNG1, s1, URNG2, s2>::shift1;
+template<class URNG1, int s1, class URNG2, int s2>
+const int xor_combine_engine<URNG1, s1, URNG2, s2>::shift2;
+#endif
+
+/// \cond show_private
+
+/** Provided for backwards compatibility. */
+template<class URNG1, int s1, class URNG2, int s2,
+    typename URNG1::result_type v = 0>
+class xor_combine : public xor_combine_engine<URNG1, s1, URNG2, s2>
+{
+    typedef xor_combine_engine<URNG1, s1, URNG2, s2> base_type;
+public:
+    typedef typename base_type::result_type result_type;
+    xor_combine() {}
+    xor_combine(result_type val) : base_type(val) {}
+    template<class It>
+    xor_combine(It& first, It last) : base_type(first, last) {}
+    xor_combine(const URNG1 & rng1, const URNG2 & rng2)
+      : base_type(rng1, rng2) { }
+
+    result_type min BOOST_PREVENT_MACRO_SUBSTITUTION () const { return (std::min)((this->base1().min)(), (this->base2().min)()); }
+    result_type max BOOST_PREVENT_MACRO_SUBSTITUTION () const { return (std::max)((this->base1().min)(), (this->base2().max)()); }
+};
+
+/// \endcond
+
+} // namespace random
+} // namespace boost
+
+#endif // BOOST_RANDOM_XOR_COMBINE_HPP