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

/*

 Copyright (C) 2004 Ferdinando Ametrano

 Copyright (C) 2004 Gianni Piolanti

 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

 <https://www.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 faurersg.hpp

    \brief Faure low-discrepancy sequence generator

*/

#ifndef quantlib_faure_ld_rsg_h

#define quantlib_faure_ld_rsg_h

#include <ql/math/matrix.hpp>

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

#include <vector>

namespace QuantLib {

    //! Faure low-discrepancy sequence generator

    /*! It is based on existing Fortran and C algorithms to calculate pascal

        matrix and gray transforms.

        -# E. Thiemard Economic generation of low-discrepancy sequences with

           a b-ary gray code.

        -# Algorithms 659, 647. http://www.netlib.org/toms/647,

           http://www.netlib.org/toms/659

        \test the correctness of the returned values is tested by

              reproducing known good values.

    */

    class FaureRsg {

      public:

        typedef Sample<std::vector<Real> > sample_type;

        FaureRsg(Size dimensionality);

        const std::vector<long int>& nextIntSequence() const {

            generateNextIntSequence();

            return integerSequence_;

        }

        const std::vector<long int>& lastIntSequence() const {

            return integerSequence_;

        }

        const sample_type& nextSequence() const {

            generateNextIntSequence();

            for (Size i=0; i<dimensionality_; i++)

                sequence_.value[i] = integerSequence_[i]/normalizationFactor_;

            return sequence_;

        }

        const sample_type& lastSequence() const { return sequence_; }

        Size dimension() const { return dimensionality_; }

      private:

        void generateNextIntSequence() const;

        Size dimensionality_;

        // mutable unsigned long sequenceCounter_;

        mutable sample_type sequence_;

        mutable std::vector<long int> integerSequence_;

        mutable std::vector<long int> bary_;

        mutable std::vector<std::vector<long int> > gray_;

        Size base_, mbit_;

        std::vector<std::vector<long int> > powBase_;

        std::vector<long int> addOne_;

        std::vector<std::vector<std::vector<long int> > > pascal3D;

        double normalizationFactor_;

    };

}

#endif