/* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */

/*

 Copyright (C) 2004 Ferdinando Ametrano

 Copyright (C) 2000, 2001, 2002, 2003 RiskMap srl

 Copyright (C) 2004 Walter Penschke

 This file is part of QuantLib, a free-software/open-source library

 for financial quantitative analysts and developers - http://quantlib.org/

 QuantLib is free software: you can redistribute it and/or modify it

 under the terms of the QuantLib license.  You should have received a

 copy of the license along with this program; if not, please email

 <quantlib-dev@lists.sf.net>. The license is also available online at

 <http://quantlib.org/license.shtml>.

 This program is distributed in the hope that it will be useful, but WITHOUT

 ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS

 FOR A PARTICULAR PURPOSE.  See the license for more details.

*/

/*! \file rngtraits.hpp

    \brief random-number generation policies

*/

#ifndef quantlib_rng_traits_hpp

#define quantlib_rng_traits_hpp

#include <ql/methods/montecarlo/pathgenerator.hpp>

#include <ql/math/randomnumbers/mt19937uniformrng.hpp>

#include <ql/math/randomnumbers/inversecumulativerng.hpp>

#include <ql/math/randomnumbers/randomsequencegenerator.hpp>

#include <ql/math/randomnumbers/sobolrsg.hpp>

#include <ql/math/randomnumbers/inversecumulativersg.hpp>

#include <ql/math/distributions/normaldistribution.hpp>

#include <ql/math/distributions/poissondistribution.hpp>

namespace QuantLib {

    // random number traits

    template <class URNG, class IC>

    struct GenericPseudoRandom {

        // typedefs

        typedef URNG urng_type;

        typedef InverseCumulativeRng<urng_type,IC> rng_type;

        typedef RandomSequenceGenerator<urng_type> ursg_type;

        typedef InverseCumulativeRsg<ursg_type,IC> rsg_type;

        // more traits

        enum { allowsErrorEstimate = 1 };

        // factory

        static rsg_type make_sequence_generator(Size dimension,

                                                BigNatural seed) {

            ursg_type g(dimension, seed);

            return (icInstance ? rsg_type(g, *icInstance) : rsg_type(g));

        }

        // data

        static ext::shared_ptr<IC> icInstance;

    };

    // static member initialization

    template<class URNG, class IC>

    ext::shared_ptr<IC> GenericPseudoRandom<URNG, IC>::icInstance;

    //! default traits for pseudo-random number generation

    /*! \test a sequence generator is generated and tested by comparing

              samples against known good values.

    */

    typedef GenericPseudoRandom<MersenneTwisterUniformRng,

                                InverseCumulativeNormal> PseudoRandom;

    //! traits for Poisson-distributed pseudo-random number generation

    /*! \test sequence generators are generated and tested by comparing

              samples against known good values.

    */

    typedef GenericPseudoRandom<MersenneTwisterUniformRng,

                                InverseCumulativePoisson> PoissonPseudoRandom;

    template <class URSG, class IC>

    struct GenericLowDiscrepancy {

        // typedefs

        typedef URSG ursg_type;

        typedef InverseCumulativeRsg<ursg_type,IC> rsg_type;

        // more traits

        enum { allowsErrorEstimate = 0 };

        // factory

        static rsg_type make_sequence_generator(Size dimension,

                                                BigNatural seed) {

            ursg_type g(dimension, seed);

            return (icInstance ? rsg_type(g, *icInstance) : rsg_type(g));

        }

        // data

        static ext::shared_ptr<IC> icInstance;

    };

    // static member initialization

    template<class URSG, class IC>

    ext::shared_ptr<IC> GenericLowDiscrepancy<URSG, IC>::icInstance;

    //! default traits for low-discrepancy sequence generation

    typedef GenericLowDiscrepancy<SobolRsg,

                                  InverseCumulativeNormal> LowDiscrepancy;

}

#endif