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

/*

 Copyright (C) 2009, 2011 Klaus Spanderen

 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.

*/

#include <algorithm>

#include <ql/stochasticprocess.hpp>

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

#include <ql/methods/finitedifferences/meshers/fdmsimpleprocess1dmesher.hpp>

namespace QuantLib {

    FdmSimpleProcess1dMesher::FdmSimpleProcess1dMesher(

        Size size,

        const ext::shared_ptr<StochasticProcess1D>& process,

        Time maturity, Size tAvgSteps, Real eps, Real mandatoryPoint)

        : Fdm1dMesher(size) {

        std::fill(locations_.begin(), locations_.end(), 0.0);    

        for (Size l=1; l<=tAvgSteps; ++l) {

            const Real t = (maturity*l)/tAvgSteps;

            const Real mp = (mandatoryPoint != Null<Real>()) ? mandatoryPoint

                                                             : process->x0();

            const Real qMin = std::min({

                    mp,

                    process->x0(),

                    process->evolve(0, process->x0(), t, 

                                    InverseCumulativeNormal()(eps))

                });

            const Real qMax = std::max({

                    mp,

                    process->x0(),

                    process->evolve(0, process->x0(), t,

                                    InverseCumulativeNormal()(1-eps))

                });

            const Real dp = (1-2*eps)/(size-1);

            Real p = eps;

            locations_[0] += qMin;

            for (Size i=1; i < size-1; ++i) {

                p += dp;

                locations_[i] += process->evolve(0, process->x0(), t, 

                                                 InverseCumulativeNormal()(p));

            }

            locations_.back() += qMax;

        }

        std::transform(locations_.begin(), locations_.end(), locations_.begin(),

                       [=](Real x) -> Real { return x / tAvgSteps; });

        for (Size i=0; i < size-1; ++i) {

            dminus_[i+1] = dplus_[i] = locations_[i+1] - locations_[i];

        }

        dplus_.back() = dminus_.front() = Null<Real>();        

    }

}