libfit1DCore.h

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// SPDX-License-Identifier: LGPL-3.0-or-later
/***********************************************************************************/
/*  Copyright 2011 WSL Institute for Snow and Avalanche Research    SLF-DAVOS      */
/***********************************************************************************/
/* This file is part of MeteoIO.
    MeteoIO is free software: you can redistribute it and/or modify
    it under the terms of the GNU Lesser General Public License as published by
    the Free Software Foundation, either version 3 of the License, or
    (at your option) any later version.
 
    MeteoIO 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
    GNU Lesser General Public License for more details.
 
    You should have received a copy of the GNU Lesser General Public License
    along with MeteoIO.  If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef LIBFIT1DCORE_H
#define LIBFIT1DCORE_H
 
#include <meteoio/IOExceptions.h>
#include <meteoio/dataClasses/Matrix.h>
 
#include <vector>
 
namespace mio {
 
//class to use as an interface
class FitModel {
        public:
                FitModel(const std::string& i_regname, const size_t& i_nParam, const size_t& i_min_nb_pts)
                               : Lambda(), X(), Y(), infoString(), regname(i_regname), nPts(0), nParam(i_nParam), min_nb_pts(i_min_nb_pts), fit_ready(false) {}
                virtual ~FitModel() {}
                virtual void setData(const std::vector<double>& in_X, const std::vector<double>& in_Y) = 0;
                void setGuess(const std::vector<double>& lambda_in);
                virtual void setLapseRate(const double& /*lapse_rate*/) {throw InvalidArgumentException("Lapse rates can only be forced for linear regressions!", AT);}
                virtual void setDegree(const size_t& /*degree*/) {throw InvalidArgumentException("Degree can only be set for polynomial regression!", AT);}
                virtual bool fit() = 0;
                virtual double f(const double& x) const = 0;
                double operator ()(const double& x) const { return f(x);}
                std::vector<double> getParams() const;
                std::string getName() const {return regname;}
                std::string getInfo() const {return infoString;}
                void setInfo(const std::string& info) {infoString=info;}
                FitModel& operator =(const FitModel& source);
                bool isReady() const {return fit_ready;}
                std::string toString() const;
        protected:
                virtual bool checkInputs();
 
                std::vector<double> Lambda; //parameters of the fit
                std::vector<double> X; //X of input data set to fit
                std::vector<double> Y; //Y of input data set to fit
                std::string infoString;
 
                const std::string regname; //model name
                size_t nPts; //number of data points
                size_t nParam; //number of parameters
                size_t min_nb_pts; //minimum number of data points
                bool fit_ready; //set to false if fit() must be called before using the fit
};
 
class FitLeastSquare : public FitModel {
        public:
                FitLeastSquare(const std::string& i_regname, const size_t& i_nParam, const size_t& i_min_nb_pts) : FitModel(i_regname, i_nParam, i_min_nb_pts) {}
                void setData(const std::vector<double>& in_X, const std::vector<double>& in_Y);
                bool fit();
                virtual double f(const double& x) const = 0;
 
        protected:
                virtual void setDefaultGuess(); //set defaults guess values. Called by setData
 
        private:
                void initLambda();
                void initDLambda(Matrix& dLambda) const;
                double getDelta(const double& var) const;
                double DDer(const double& x, const size_t& index);
                bool computeFit();
 
                static const double lambda_init; //initial default guess
                static const double delta_init_abs; //initial delta, absolute
                static const double delta_init_rel; //initial delta, relative
                static const double eps_conv; //convergence criteria
                static const unsigned int max_iter; //maximum number of iterations
};
 
} //end namespace
 
#endif