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

/*

 Copyright (C) 2003 Ferdinando Ametrano

 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.

*/

// ===========================================================================

// NOTE: The following copyright notice applies to the original code,

//

// Copyright (C) 2002 Peter Jäckel "Monte Carlo Methods in Finance".

// All rights reserved.

//

// Permission to use, copy, modify, and distribute this software is freely

// granted, provided that this notice is preserved.

// ===========================================================================

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

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

#include <ql/math/primenumbers.hpp>

namespace QuantLib {

    HaltonRsg::HaltonRsg(Size dimensionality,

                         unsigned long seed,

                         bool randomStart,

                         bool randomShift)

    : dimensionality_(dimensionality), sequence_(std::vector<Real>(dimensionality), 1.0),

      randomStart_(dimensionality, 0UL), randomShift_(dimensionality, 0.0) {

        QL_REQUIRE(dimensionality>0, 

                   "dimensionality must be greater than 0");

        if (randomStart || randomShift) {

            RandomSequenceGenerator<MersenneTwisterUniformRng>

                uniformRsg(dimensionality_, seed);

            if (randomStart)

                randomStart_ = uniformRsg.nextInt32Sequence();

            if (randomShift)

                randomShift_ = uniformRsg.nextSequence().value;

        }

    }

    const HaltonRsg::sample_type& HaltonRsg::nextSequence() const {

        ++sequenceCounter_;

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

            double h = 0.0;

            unsigned long b = PrimeNumbers::get(i);

            double f = 1.0;

            unsigned long k = sequenceCounter_+randomStart_[i];

            while (k != 0U) {

                f /= b;

                h += (k%b)*f;

                k /= b;

            }

            sequence_.value[i] = h+randomShift_[i];

            sequence_.value[i] -= long(sequence_.value[i]);

        }

        return sequence_;

    }

}